M12 DRUG INTERACTION 
STUDIES   
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
This draft guidance, when finalized, will represent the current thinking of the Food and Drug 
Administration (FDA or Agency) on this topic.  It does not establish any rights for any person and is not 
binding on FDA or the public.  You can use an alternative approach if it satisfies the requirements of the 
applicable statutes and regulations.  To discuss an alternative approach, contact the FDA staff responsible 
for this guidance as listed on the title page.  The draft guidance has been left in the original International 
Council for Harmonisation format.  The final guidance will be reformatted and edited to conform with 
FDAs good guidance practice regulation and style. 
 
 
 
 
 
 
 
 
 
 
For questions regarding this draft document, contact (CDER) Kellie Reynolds, 
Kellie.Reynolds@fda.hhs.gov. 
 
 
 
 
   
 
 
 
 
 
FOREWORD 
 
 
 
The International Council for Harmonisation of Technical Requirements for Pharmaceuticals for 
Human Use (ICH) has the mission of achieving greater regulatory harmonization worldwide to 
ensure that safe, effective, and high-quality medicines are developed, registered, and maintained 
in the most resource-efficient manner.  By harmonizing the regulatory expectations in regions 
around the world, ICH guidelines have substantially reduced duplicative clinical studies, 
prevented unnecessary animal studies, standardized safety reporting and marketing application 
submissions, and contributed to many other improvements in the quality of global drug 
development and manufacturing and the products available to patients.  
 
 
 
ICH is a consensus-driven process that involves technical experts from regulatory authorities and 
industry parties in detailed technical and science-based harmonization work that results in the 
development of ICH guidelines.  The commitment to consistent adoption of these consensus-
based guidelines by regulators around the globe is critical to realizing the benefits of safe, 
effective, and high-quality medicines for patients as well as for industry.  As a Founding 
Regulatory Member of ICH, the Food and Drug Administration (FDA) plays a major role in the 
development of each of the ICH guidelines, which FDA then adopts and issues as guidance to 
industry.   
     
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5  INTERNATIONAL COUNCIL  FOR HARMONISATION OF TECHNICAL 
6  REQUIREMENTS FOR PHARMACEUTICALS FOR HUMAN  USE 
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9  ICH HARMONISED GUIDELINE 
 
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12  DRUG INTERACTION STUDIES 
M12 
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16  Draft version 
17  Endorsed on 24 May 2022 
 
18  Currently under public consultation 
 
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25  At Step 2 of the ICH Process, a consensus draft text or guideline, agreed by the appropriate 
26  ICH Expert Working Group, is transmitted by the ICH Assembly to the regulatory authorities 
27  of the ICH regions for internal and external consultation, according to national or regional 
28  procedures. 
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29  M12 
30  Document History 
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Code  History  Date 
M12  Endorsement by the Members of the ICH  24 May 2022 
Assembly under Step 2 and release for public 
consultation. 
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58  Legal notice: This document is protected by copyright and may, with the exception of the ICH logo, be 
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70  this copyright holder. 
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71  ICH HARMONISED GUIDELINE 
72  DRUG INTERACTION STUDIES 
M12 
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74  ICH Consensus Guideline 
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76  Table of Contents 
 
77  1.  INTRODUCTION ................................................................................................................... 6 
78  1.1 Objective .................................................................................................................................... 6 
79  1.2 Background ................................................................................................................................ 6 
80  1.3 Scope .......................................................................................................................................... 6 
81  1.4 General Principles ....................................................................................................................... 7 
82  2.  IN VITRO EVALUATION .................................................................................................... 8 
83  2.1 Evaluation of Metabolism-Mediated Interactions ....................................................................... 8 
84  2.1.1 Drug as a Substrate of Metabolizing Enzymes ................................................................. 8 
85  2.1.2 Drug as an Inhibitor of CYP Enzymes ............................................................................. 9 
86  2.1.3 Drug as an Inhibitor of UGTs ........................................................................................ 11 
87  2.1.4 Drug as an Inducer of CYP Enzymes ............................................................................. 11 
88  2.2 Evaluation of Transporter-Mediated Interactions .................................................................... 14 
89  2.2.1 Drug as a Substrate of Transporters .............................................................................. 14 
90  2.2.2 Drug as an Inhibitor of Transporters ............................................................................. 16 
91  2.2.3 Drug as an Inducer of Transporters .............................................................................. 17 
92  2.3 DDI Potential of Metabolites.................................................................................................... 17 
93  2.3.1 Metabolite as a Substrate ............................................................................................... 17 
94  2.3.2 Metabolite as an Inhibitor ............................................................................................. 18 
95  2.3.3 Metabolite as an Inducer ............................................................................................... 18 
96  3.  CLINICAL EVALUATION ................................................................................................. 19 
97  3.1 Types of Clinical DDI Studies (Terminology) ......................................................................... 19 
98  3.1.1 Standalone and Nested DDI Studies .............................................................................. 19 
99  3.1.2 DDI Studies with Index Perpetrators and Index Substrates ............................................ 19 
100  3.1.3 DDI Studies with Expected Concomitant Drugs ............................................................ 20 
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101  3.1.4 Cocktail Approach ......................................................................................................... 20 
102  3.2 Study Planning and Considerations for Clinical DDI Studies .................................................. 20 
103  3.2.1 Study Design .................................................................................................................. 21 
104  3.2.2 Specific Considerations for Nested DDI Studies ............................................................ 24 
105  3.2.3 Considerations for CYP-Mediated Interactions ............................................................. 25 
106  3.2.4 Considerations for Evaluation of UGT-Mediated Interactions ...................................... 27 
107  3.2.5 Considerations for Evaluation of Transporter-Mediated Interactions .......................... 28 
108  3.2.6 Cocktail Studies-Considerations for CYP or Transporter Cocktail Studies .................. 30 
109  4. OTHER TOPICS ..................................................................................................................... 31 
110  4.1 Pharmacogenetics ..................................................................................................................... 31 
111  4.2 Therapeutic Protein DDIs ......................................................................................................... 32 
112  4.2.1 Proinflammatory Cytokine-Related Mechanism ............................................................. 32 
113  4.2.2 Antibody-Drug Conjugates ............................................................................................ 33 
114  5. REPORTING AND INTERPRETING CLINICAL DDI STUDY RESULTS .................... 33 
115  5.1 Pharmacokinetic Data Analysis ................................................................................................ 34 
116  5.1.1 Non-Compartmental Analysis (NCA) ............................................................................. 34 
117  5.1.2 Population PK Analysis ................................................................................................. 34 
118  5.2 Reporting DDI Results ............................................................................................................. 34 
119  5.3. Interpreting DDI Study Results ............................................................................................... 34 
120  5.3.1 Investigational Drug as a Victim of DDIs: Determination of No-Effect Boundaries .... 34 
121  5.3.2 Investigational Drug as a Perpetrator of DDIs: Classification System ......................... 35 
122  5.3.3 Extrapolating Study Results ........................................................................................... 36 
123  6. RISK ASSESSMENT AND MANAGEMENT ...................................................................... 37 
124  7. APPENDICES .......................................................................................................................... 38 
125  7.1 In Vitro Evaluation of Metabolism-Based DDIs ...................................................................... 38 
126  7.1.1 In Vitro Systems ............................................................................................................. 38 
127  7.1.2 Investigational Drug as an Enzyme Substrate: Reaction Phenotyping .......................... 40 
128  7.1.3 Investigational Drug as an Enzyme Inhibitor ................................................................ 41 
129  7.1.4 Investigational Drug as an Enzyme Inducer .................................................................. 42 
130  7.2 In Vitro Evaluation Of Transporter-Based DDIs ..................................................................... 44 
131  7.2.1 In Vitro Systems ............................................................................................................. 44 
132  7.2.2 Investigational Drug as a Transporter Substrate .......................................................... 46 
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133  7.2.3 Investigational Drug as a Transporter Inhibitor ............................................................ 47 
134  7.3. Predictive Modeling ................................................................................................................ 47 
135  7.3.1 Using Mechanistic Static Models for DDI Predictions .................................................. 48 
136  7.3.2 Using PBPK Models to Predict Enzyme or Transporter-Based DDIs ........................... 50 
137  7.4. List of Drugs that can be used in In Vitro Studies .................................................................. 53 
138  7.4.1 CYPs Enzymes ................................................................................................................ 53 
139  7.4.2 UGTs .............................................................................................................................. 55 
140  7.4.3 Transporters ................................................................................................................... 56 
141  7.5 List of Drugs that can be used in Clinical Studies ................................................................... 57 
142  7.5.1 CYPs Enzymes ................................................................................................................ 57 
143  7.5.2 UGTs .............................................................................................................................. 60 
144  7.5.3 Transporters ................................................................................................................... 61 
145  8. REFERENCES ......................................................................................................................... 64 
146 146 
147 147 
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148  1.  INTRODUCTION 
 
149  1.1 Objective 
150  This guideline provides  recommendation to  promote a consistent  approach in designing, 
151  conducting, and interpreting enzyme- or transporter-mediated in vitro and clinical drug-drug 
152  interaction (DDI) studies during the development of a therapeutic product.  A consistent 
153  approach will reduce uncertainty for pharmaceutical industry to meet the requirement of multiple 
154  regulatory agencies and lead to more efficient utilization of resources. 
 
155  1.2 Background 
156  In clinical practice, patients are often prescribed more than one drug which can result in a DDI. 
157  Some patients, in particular fragile older patients or patients with serious or multiple health issues, 
158  can be prescribed a large number of different drugs (i.e., polypharmacy). The occurrence of DDIs 
159  is a common clinical problem that can increase the risk of adverse events, sometimes leading to 
160  hospital  admissions.  Alternatively,  some  DDIs  can  reduce  treatment  efficacy.  Hence,  it  is 
161  important to consider an investigational drugs potential to interact with other drugs. 
 
162  Regional  guidelines  for  investigations  of  DDIs  have  been  available  for  decades  and  have 
163  undergone several updates as scientific progress has been made. In general, the proposed approach 
164  to the investigation of interaction potential of investigational new drugs has been similar between 
165  regions, but despite harmonization initiatives, some differences have remained. This ICH guideline 
166  aims to harmonize recommendations for in vitro and clinical evaluation of DDIs. 
 
167  This guideline provides general recommendations on how to evaluate the DDI potential of an 
168  investigational drug. It is recognized that the DDI evaluation is generally tailored based on the 
169  specific drug, intended patient population, and therapeutic context. Alternative approaches can be 
170  used if they satisfy the requirements of the applicable statutes and regulations. The focus of the 
171  guideline is the development of new drugs, but if new scientific information regarding the potential 
172  for DDIs is obtained after drug approval, additional DDI evaluation should be considered. 
 
173  1.3 Scope 
174  The scope of the guideline is limited to pharmacokinetic interactions, with a focus on enzyme- and 
175  transporter-mediated interactions. These aspects in general apply to the development of small 
176  chemical molecules. DDI evaluation of biologics is only covered briefly, with focus on monoclonal 
177  antibodies and antibody-drug conjugates. Guidance is provided on how to investigate interactions 
178  mediated by inhibition or induction of enzymes or transporters, both in vitro and in vivo, and on 
179  how to translate the results to appropriate treatment recommendations. The guideline also includes 
180  recommendations on how to address metabolite-mediated interactions. The use of model-based 
181  data evaluation and DDI predictions are also covered. 
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182  Other types of pharmacokinetic interactions, e.g., regarding impact on absorption (e.g., gastric pH 
183  change, gastric motility change, formation of chelation or complexation, etc.), food effects, or 
184  protein binding displacement, are not part of this document and may be covered by regional 
185  guidelines. Similarly, DDIs that are a result of pharmacodynamic interactions are beyond the scope 
186  of this guideline. 
 
187  1.4 General Principles 
188  The potential for an investigational drug to cause DDIs should be investigated in a stepwise manner 
189  during drug development. The potential for a new drug to cause pharmacokinetic interactions both 
190  as a victim (effect of other drugs on the investigational drug) and as a perpetrator (effect of the 
191  investigational drug on concomitant drugs) should be evaluated. All aspects mentioned below are 
192  further expanded and discussed later in the document. 
 
193  Evaluating the  potential  of  an  investigational  drug as  a  victim  of  a  metabolic  enzyme-  or 
194  transporter-mediated DDI involves identification of the principal routes of the drugs elimination. 
195  For drugs that are not eliminated predominantly unchanged in urine or that are not biologics 
196  eliminated  through  unspecific  catabolism,  the  keystone  of  the  identification  of  principal 
197  elimination routes is a well performed clinical mass balance study. In some instances, e.g., if a 
198  large part of the dose is found as unchanged drug in feces, an absolute bioavailability study can 
199  also be a useful complement to aid interpretation. Using data from the mass balance study, the 
200  quantitative contributions of the different elimination pathways should be estimated based on the 
201  amount  of  dose  excreted  as  primary  and  secondary metabolites  along  specific  routes.  For 
202  quantitatively important elimination pathways, in vitro and clinical studies should be used to 
203  identify the main enzymes or transporter proteins involved in these pathways. The ability to predict 
204  interactions affecting the investigational drug is dependent on the identification of these proteins. 
 
205  Evaluating the DDI potential of an investigational drug as a perpetrator, involves characterizing 
206  the effect of the drug on enzymes and transporters. This evaluation often starts with in vitro 
207  experiments to elucidate potential DDI mechanisms. Identification of DDI risks should then be 
208  followed by clinical DDI studies based on mechanistic knowledge, and the results should be 
209  translated  to  appropriate  clinical  management  recommendations  for  drugs  as  a  victim  and 
210  perpetrator of DDIs. 
 
211  The results of DDI evaluations inform the protocols for clinical studies in patients regarding the 
212  use of concomitant drugs. Information about the interaction potential should be gained as early in 
213  drug development as practically possible to assure safety and avoid unnecessary restrictions of 
214  concomitant medications and/or exclusion of patients who require the concomitant medications in 
215  clinical studies, typically phase 2/3 studies. The timing of the different non-clinical and clinical 
216  studies is dependent on the context and type of product; some general recommendations are given 
217  below. Predictive modeling (see Section 7.3) can also assist evaluation of the DDI potential. 
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218    In vitro data on the investigational drug as a substrate of metabolic enzymes generally 
219  should be obtained before starting phase 1 (first-in-human) to evaluate metabolic stability 
220  and identify the potential main metabolic pathway(s) and enzyme(s) that metabolize the 
221  investigational drug (reaction phenotyping  studies). If in vitro studies suggest the 
222  possibility of clinically significant interaction with inhibitors or inducers of a metabolic 
223  enzyme, it is preferable that dedicated clinical DDI studies be conducted prior to studies in 
224  patients. Until studies are conducted, a conservative strategy, such as excluding patients on 
225  certain concomitant drugs that are inhibitors or inducers, may be needed. 
226    The results of the mass balance study should generally be available before starting phase 
227  3. Based on results of the mass balance study and in vitro studies, clinical studies with 
228  strong index enzyme inhibitors and inducers should be considered to confirm and quantify 
229  the main metabolism pathways and define the risk for clinically significant DDIs. 
230    ADME (absorption, distribution, metabolism, and excretion) properties determine whether 
231  in vitro data of the investigational drug as a substrate for transport proteins should be 
232  collected. If a drug has limited absorption or is expected to undergo significant active 
233  hepatic uptake, biliary excretion or active renal secretion as unchanged drug, the relevant 
234  transporters should be identified in vitro before initiating clinical studies in patients to 
235  avoid protocol restrictions. 
236    In vitro data on the effects of the investigational drug as a perpetrator on the major 
237  cytochrome P450 (CYP) enzymes and transporters should generally be available before 
238  administering the drug to patients. 
239    The pharmacokinetic DDI potential of metabolites with significant plasma exposure or 
240  pharmacological activity should be considered similarly as for the parent drug, but these 
241  investigations can generally be completed later in development when more knowledge 
242  about the exposure and activity of metabolites is available. 
 
243  2.  IN VITRO EVALUATION 
 
244  2.1 Evaluation of Metabolism-Mediated Interactions 
245  In vitro studies are important first steps to identify risks for a drug to be a victim or perpetrator for 
246  DDIs through inhibition or induction of drug metabolizing enzymes. 
 
247  2.1.1 Drug as a Substrate of Metabolizing Enzymes 
248  Typically, an in vitro screening to identify the main enzymes responsible for the metabolism of a 
249  new drug is performed early in drug development. If the mass-balance study suggests metabolism 
250  as an important elimination mechanism for the drug, enzymes involved in metabolic pathways 
251  which based on the mass-balance study are estimated to contribute to  25% of drug elimination 
252  should normally be identified. This applies to CYP enzymes as well as non-CYP enzymes. 
253  If oxidative metabolism is important, the identification of catalyzing enzymes usually starts by 
254  determining whether the investigational drug is an in vitro substrate for the most common CYP 
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255  enzymes involved in drug metabolism:  CYP1A2, CYP2B6, CYP2C8, CYP2C9, CYP2C19, 
256  CYP2D6, and CYP3A using in vitro phenotyping experiments. If the drug is not found to undergo 
257  significant metabolism by these major CYP enzymes, other enzymes can be investigated. These 
258  additional enzymes can include, but are not limited to: 
259    Other CYP enzymes, including CYP2A6, CYP2E1 CYP2J2, and CYP4F2 Other phase 1 
260  enzymes, including alcohol/aldehyde dehydrogenase (ADH/ALDH), aldehyde oxidase 
261  (AO),  carboxylesterase  (CES),  flavin  monooxygenase  (FMO),  monoamine  oxidase 
262  (MAO), and xanthine oxidase (XO). 
263    Phase  2  enzymes:  The  most  frequently  evaluated,  Uridine  5-diphospho- 
264  glucuronosyltransferase (UDP-glucuronosyl transferases (UGTs)), are responsible for 
265  glucuronide conjugation of drugs and metabolites. A phenotyping study is recommended 
266  for an investigational drug if it is mainly eliminated by direct glucuronidation.  The 
267  following UGTs play a role in metabolism of certain drugs: UGT1A1, 1A3, 1A4, 1A6, 
268  1A9, 1A10, 2B4, 2B7, 2B10, 2B15, and 2B17 (1). 
269    Other phase 2 enzymes, including glutathione S-transferases (GSTs), N-acetyltransferases 
270  (NATs), sulfotransferases (SULTs). 
 
271  Details on the experimental setup for in vitro studies to identify enzymes catalyzing the main 
272  elimination pathways are given in Sections 7.1.1 and 7.1.2. 
273  When the candidate enzymes have been identified in vitro, the main metabolic pathways (25% 
274  of total elimination) generally require additional clinical characterization to determine and quantify 
275  the risk of interaction  with the investigational  drug as  a victim. This is normally done by 
276  performing clinical DDI studies using a strong index inhibitor of the enzyme. For some enzymes, 
277  pharmacogenetic studies can substitute for clinical DDI studies (refer to Section 4.1). A clinical 
278  study  with  a  strong  inducer  is  also  generally  conducted,  since  inducers  often  up-regulate 
279  expression of multiple enzymes and transporters (except CYP2D6, which is generally considered 
280  not inducible by drugs). 
 
281  2.1.2 Drug as an Inhibitor of CYP Enzymes 
282  An investigational drugs potential to inhibit CYP1A2, CYP2B6, CYP2C8, CYP2C9, CYP2C19, 
283  CYP2D6, and CYP3A in both a reversible manner (i.e., as reversible inhibitor) and time-dependent 
284  manner (i.e., as time-dependent inhibitor (TDI)) should be evaluated. Investigation of potential 
285  inhibition of UGT enzymes is further discussed in Section 2.1.3. For details on the experimental 
286  setup for these experiments, refer to Sections 7.1.1 and 7.1.3. 
 
287  2.1.2.1 Reversible Inhibition 
288  In the reversible inhibition experiments, a Ki  (inhibition constant) is usually  determined 
289  experimentally or estimated based on half-maximal inhibitory concentration (IC50) (refer to 
290  Section 7.1.3). If the initial experiments testing a sufficiently  high concentration of the 
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291  investigational drug already indicate that the Ki will be markedly higher than the cutoffs given (see 
292  below), the risk for clinical inhibition can normally be excluded without further data. 
293  The risk for reversible enzyme inhibition can be excluded based on in vitro data (basic method) 
294  if 
 
K > 50 x C (i.e., 
295 295  i,u  max,u  ) 
CCmmmmmm,uu   
Kii,uu  < 0.02
296  K is the unbound inhibition constant. 
i,u 
297  C is the average unbound C at the highest recommended dose at steady state. 
max,u  max 
 
298  Considering uncertainties in protein binding measurements for highly bound drugs, i.e., >99% 
299  protein binding, fu,p (fraction unbound in plasma) should be set at 0.01 (i.e. 1%). It is understood 
300  that there have been advances in methodologies to measure fu,p for highly protein bound drugs, 
301  and this  is an area of active research. Hence, in some situations, the measured fu,p can be used if 
302  the accuracy and precision of measurement is demonstrated. Such a demonstration should include 
303  full validation data of the protein binding assay including bioanalytical method with appropriate 
304  positive controls (i.e., drugs with high binding to relevant plasma proteins). Demonstration of 
305  reproducible  findings  with  different  assays  (e.g.,  ultrafiltration,  equilibrium  dialysis, 
306  ultracentrifugation)  increases  the  reliability  of  the  fu,p  measurement  and  is  preferred.  This 
307  consideration for fu,p applies in other contexts where basic method, mechanistic static, and dynamic 
308  models (often referred as physiologically based pharmacokinetic (PBPK) modeling) can be used 
309  to interpret the in vitro results of enzyme and transporter inhibition/induction experiments. 
310  For orally administered drugs that are inhibitors of CYP3A, the risk of intestinal CYP3A inhibition 
311  can be excluded if 
 
 
312 312    (i.e.,  ) 
mmmmmmiimmuumm cccciicciiccmmcc dddddddd  DDdddddd250 mmmm 
ii
KK  >  0.1   250 mmmm  KKii  < 10
313  If risk for clinical inhibition cannot be excluded using this basic method, mechanistic static and/or 
314  PBPK models can be used to interpret the in vitro experiment results (refer to Section 7.3). If in 
315  vitro data and modeling do not exclude the risk for clinical inhibition, a clinical DDI study with a 
316  sensitive index substrate should be conducted. 
317  If a clinical study using a substrate for an enzyme that was inhibited in vitro by an investigational 
318  drug with a low Ki shows lack of inhibition, then the risk for clinical inhibition can be excluded 
319  for other enzymes having a larger Ki. Such an inference should be made only for the enzymes that 
320  are expressed at the same site and for which the inhibition potencies are determined in the same 
321  experiment (rank order approach) (2, 3). Of note, an orally administered drug can inhibit intestinal 
322  metabolic enzymes (e.g., CYP3A) in addition to hepatic enzymes. In such situations, the risk for 
323  inhibition of CYP3A in the gastrointestinal (GI) tract should be considered even if systemic 
324  inhibition of CYP3A can be excluded using the rank order approach based on a negative clinical 
325  study on another CYP enzyme. In the presence of inhibitory metabolites of an investigational drug, 
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326  their contribution should also be considered when using rank order approach to determine if 
327  clinical studies should be conducted. 
 
328 3 2.1.2.2 Time-Dependent Inhibition 
2
If an in vitro assay (described in Section 7.1.3) indicates an increased enzyme inhibition potential 
8 
with drug pre-incubation, the following equation can be used as the basic method to evaluate the 
329 3
risk for TDI (4-6). The risk for in vivo inhibition can be excluded based on in vitro data if 
2
9 
330 3 (kkddoodd+kkdddddd) 
3 kkdddddd  < 1.25 
0 
331 3
3
1 
 
332 3
3
2 
333 3
3
3 
334 334  where 
(kkiiccmmccii  5  CCmmmmmm,uu) 
335 335 
=  (KKII,uu + 5  CCmmmmmm,uu) 
ddoodd 
kk
336  k is the apparent first-order inactivation rate constant of the affected enzyme. 
obs 
337  k is the apparent first-order degradation rate constant of the affected enzyme (refer to Table 5) (7-10). 
deg 
338  K is the unbound inhibitor concentration causing half-maximal inactivation. 
I,u 
339  k is the maximal inactivation rate constant. 
inact 
340  C is the maximal unbound plasma concentration of the inhibitor drug at steady state. f should be set 
max,u  u,p 
341  to 1% if experimentally determined to be < 1% (also refer to Section 2.1.2.1). 
342  Note: C and K should be expressed in the same unit (e.g., in a molar concentration unit). 
max,u  I,u 
 
343  If the above ratio is  1.25, mechanistic static and/or PBPK models can be used to interpret the in 
344  vitro experiment results (refer to Section 7.3). If in vitro data and modeling do not exclude the risk 
345  for clinical inhibition, a clinical DDI study with a sensitive index substrate should be conducted. 
346  The rank order approach, mentioned above for reversible inhibitors, does not apply to TDIs. 
 
347  2.1.3 Drug as an Inhibitor of UGTs 
348  It is recognized that a drug which is not a substrate of an enzyme can still be an inhibitor. However, 
349  considering  the  generally  limited  magnitude  of  UGT inhibition-mediated  DDIs,  a  routine 
350  evaluation of investigational drugs to inhibit UGTs may not be warranted. If direct glucuronidation 
351  is one of the major elimination pathways of an investigational drug, it is recommended to study in 
352  vitro whether the drug can inhibit UGTs including UGT1A1 and UGT2B7. The evaluation is 
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353  usually performed using recombinant UGTs or human liver microsome (HLM) with relatively 
354  selective substrates (refer to Table 8, Section 7.4.2.1 for an illustrative list of substrates). When an 
355  investigational  drug  is  to  be  used  with  another  drug  that  is  mainly  metabolized  by  direct 
356  glucuronidation, it is recommended to evaluate the in vitro potential inhibitory effect of the 
357  investigational drug on the UGT isoform(s) responsible for the elimination of the other drug. 
 
358  2.1.4 Drug as an Inducer of CYP Enzymes 
359  An investigational drugs potential to induce enzymes via activation of nuclear receptors pregnane 
360  X receptor (PXR), constitutive androstane receptor (CAR), aryl hydrocarbon receptor (AhR), and 
361  if relevant other drug regulation pathways, should be evaluated. For technical advice on the 
362  experiments, refer to Section 7.1.4. 
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363  To assess the DDI liability of a drug as an inducer, studies should be performed in human 
364  hepatocytes from at least 3 individual donors and the extent of enzyme induction should be 
365  measured at mRNA level. The enzymes CYP3A4, CYP2B6 and CYP1A2 should always be 
366  included  as  markers  of  induction  mediated  via  PXR/CAR  (CYP3A4,  CYP2B6)  and  AhR 
367  (CYP1A2). Induction of other enzymes via these pathways can be studied in vitro but sometimes 
368  it is challenging to obtain satisfactory sensitivity to get a conclusive result. For CYP2C19, the 
369  mRNA responses to inducers are often limited (11, 12), and thus the activity should be measured 
370  using a probe substrate to evaluate the CYP2C19 induction potential of the investigational drug. 
371  If the in vivo induction potential of CYP3A4 enzymes by an investigational drug can be excluded 
372  based on in vitro results, evaluating the induction potential of a drug on CYP2C enzymes is not 
373  necessary because both CYP3A4 and CYP2C enzymes are induced via activation of the PXR, and 
374  CYP2Cs are generally less inducible compared to CYP3A4. 
375  If the investigational drug induces CYP3A4 in vitro, and the results suggest that a clinical study 
376  should be conducted, the potential of the investigational drug to induce CYP2Cs should be 
377  evaluated in vitro and/or in vivo. Alternatively, a negative clinical study with a sensitive CYP3A 
378  substrate can be used to rule out the induction potential of an investigational drug on CYP2C 
379  enzymes if the potential of CYP3A inhibition by the drug and its metabolite(s) can be excluded 
380  via in vitro and/or in vivo evaluation. 
381  As described below, there are several methods that can be used to interpret mRNA data from in 
382  vitro induction experiments and to assess the in vivo potential of a drug to induce enzymes. It is 
383  recommended to first use the basic qualitative method (mRNA fold-change). If the basic method 
384  indicates induction potential, the evaluation can continue using more quantitative approaches (e.g., 
385  correlation methods) provided it is possible to study a wide range of concentrations of the 
386  investigational drug to determine induction parameters (e.g., Emax  and EC50). For the more 
387  quantitative approaches, one well-performing, qualified batch of hepatocytes is sufficient. The 
388  basic method only uses in vitro data from the investigational drug, whereas correlation methods 
389  compare the induction response of the drug to that of multiple established clinical inducers of the 
390  enzyme of interest. 
391  In addition, mechanistic static or PBPK models can potentially be used (refer to Section 7.3). If a 
392  risk for induction cannot be excluded based on in vitro data and modeling, clinical studies with 
393  sensitive substrates of the enzymes of interest should be conducted. 
 
394  2.1.4.1 Basic mRNA Fold-Change Method 
395  The induction results should be evaluated separately for each donor. The levels of mRNA should 
396  be compared to the control (vehicle) incubations, and a fold-change over the vehicle control should 
397  be calculated. In vivo induction potential cannot be excluded if the drug in hepatocytes from at 
398  least one donor meets the following criteria, and further evaluation of the induction potential 
399  should be conducted: 
  13   
400    increases mRNA expression of a CYP enzyme in a concentration-dependent manner; and 
401    the fold-change of CYP mRNA expression is  2-fold at 15 Cmax,u (fu,p  = 0.01, if 
402  experimentally determined to be < 1%; also refer to Section 2.1.2.1). 
 
403  In addition, the induction potential cannot be ruled out for an investigational drug that increases 
404  CYP enzyme mRNA less than 2-fold of the vehicle control but more than 20% of the response of 
405  the positive control. Further evaluation is recommended when there is an inconclusive finding, 
406  e.g., conducting in vitro testing with hepatocyte from another donor that has 6-fold mRNA 
407  increase of the CYP enzyme by a positive control. 
 
408  To calculate the percent of the response to the positive control, the following equation should be 
409  used: 
 
   
410 410 
(mmmmmmmm ooddccdd iiccccccddmmdddd ddoo iiddddii ddccuudd iiccddmmiidddd ccddccccdd  1) 
% ddoo ppddddiiiiiippdd ccddcciiccddcc =   100 
(mmmmmmmm ooddccdd iiccccccddmmdddd ddoo ppddddiiiiiippdd ccddcciiccddcc  1) 
  411  2.1.4.2 Correlation Methods 
412  Correlation methods compare the induction effect of the investigational drug to that of established 
413  clinical inducers of the enzyme of interest (13-15). The magnitude of a clinical induction effect 
414  (e.g., area under the curve (AUC) ratio of sensitive substrate in the presence and absence of 
415  inducers) of an investigational drug is predicted based on a calibration curve of relative induction 
416  scores (RIS, see equation below) or Cmax,u/EC50 versus the in vivo induction effect for a set of 
417  known inducers of the same enzyme (also refer to Section 7.1.4). If the predicted AUC ratio > 0.8, 
418  the analysis can be used to exclude the risk for in vivo induction. 
 
420 
 
EEmmmmmm   CCmmmmmm,uu 
419    mmIIRR = 
EECC50 + CCmmmmmm,uu 
421  EC50 is the concentration causing half the maximal effect. 
422  Emax is the maximum induction effect. 
423  Cmax,u  is the unbound maximum plasma concentration of a drug at steady state, and fu,p  is 0.01, if 
424  experimentally determined to be < 1%. 
425  Sometimes, Emax or EC50 cannot be estimated due to an incomplete in vitro induction profile (e.g., 
426  limited by solubility or cytotoxicity of tested drug). An alternative correlation approach can be 
427  used if the method is validated (16). 
428  2.1.4.3 Basic Kinetic Model 
429  Mechanistic models have been proposed to predict the sum of different interaction processes 
430  (reversible inhibition, TDI, induction) systemically as well as in the GI tract (17). This approach 
431  is further discussed in Section 7.3. 
  14   
432  A limited version of this approach is described as below (18, 19). If R > 0.8, the analysis can be 
433  used to exclude the risk for in vivo induction. 
434 
435 
    1 
  mm =   (EEmmmmmm  10  CCmmmmmm,uu) 
436  1 + dd   
50 mmmmmm,uu
(EECC  + 10  CC ) 
437  R is predicted AUC ratio of a sensitive enzyme substrate with and without an inducer 
438  C is the unbound maximum plasma concentration in plasma, and f is 0.01, if experimentally 
max,u  u,p 
439  determined to be < 1%. 
440  d - scaling factor (20). If the scaling factor has not been determined in a calibrated hepatocyte batch (see 
441  Section 7.1.4), d=1 should be used. 
 
442  If the above methods indicate that the investigational drug has the potential to induce metabolizing 
443  enzymes (using specific cutoff values mentioned above or developed by individual laboratories 
444  for these methods), the enzyme induction potential of the investigational drug should be further 
445  investigated  by  conducting  a  clinical  DDI study with  a  sensitive  index  substrate  or  using 
446  mechanistic models (refer to Sections 7.3). 
 
447  2.1.4.4 Additional Considerations Related to Induction 
448  In vitro induction studies can also detect enzyme down-regulation. However, research in this area 
449  is presently very limited, and the mechanisms behind these effects are unclear  (11).  If 
450  concentration-dependent  down-regulation  is  observed  in  vitro  and  is  not  attributable  to 
451  cytotoxicity, additional in vitro or clinical studies can be considered to understand the potential 
452  clinical consequences. 
 
453  2.2 Evaluation of Transporter-Mediated Interactions 
 
454  2.2.1 Drug as a Substrate of Transporters 
455  P-glycoprotein  (P-gp)  and  breast  cancer  resistance  protein  (BCRP)  are  efflux  transporters 
456  expressed in the GI tract and can affect oral bioavailability of drugs. Thus, the possibility of being 
457  a substrate of P-gp and/or BCRP is often evaluated in vitro for investigational drugs given orally. 
458  Because P-gp and BCRP are also expressed in the liver and kidneys, in vitro study should be 
459  considered for a drug if biliary excretion or active renal secretion is likely to be a major elimination 
460  pathway of the drug. In addition, if the pharmacological target of the drug is in the brain, evaluating 
461  the drug as a substrate of P-gp and BCRP can help determine whether the drug penetrates into the 
462  brain (21). 
463  Organic anion transporting polypeptide (OATP)1B1 and OATP1B3 are important hepatic uptake 
464  transporters  that  often  mediate  transport  of  compounds  containing  anionic  group  under 
465  physiological pH of systemic circulation. Examination of whether an investigational drug is a 
  15   
466  substrate for OATP1B1 and 1B3 should be considered if hepatic metabolism or biliary excretion 
467  accounts for 25% of elimination of a drug or if the pharmacological target of a drug is in the liver. 
468  Organic anion transporter (OAT)1, OAT3, and Organic cation transporter (OCT)2 are renal uptake 
469  transporters. Multidrug and toxin extrusion protein (MATE)1 and MATE2-K are renal efflux 
470  transporters. These transporters are often involved in active renal secretion of drugs. In vitro 
471  studies to evaluate a drug as substrate of these transporters should be considered if a drug has renal 
472  toxicity or the drug clearance by renal active secretion is 25% of its systemic clearance. Assuming 
473  there is no reabsorption (e.g., passive reabsorption is equal to passive secretion and there is no 
474  active reabsorption), active secretion can be calculated as (CLr  (fu,p  GFR)), where GFR is 
475  glomerular filtration rate and CLr is renal clearance. If pharmacokinetic data following intravenous 
476  administration are not available, systemic clearance can be derived by multiplying apparent total 
477  clearance by estimated bioavailability. 
478  Besides the above-mentioned transporters, the importance of in vitro evaluation of a drug as 
479  substrate of additional transporters can be decided on a case-by-case basis. For example, multidrug 
480  resistance-associated protein (MRP)2 is also an efflux transporter in similar locations as P-gp and 
481  BCRP;  OATP2B1  is  an  uptake transporter present  in  the  intestines  and is  responsible for 
482  absorption of certain drugs; and OCT1 is a hepatic transporter mediating the uptake of some drugs 
483  into the liver. The decision to evaluate additional transporters can take into consideration the site 
484  of action, passive permeability, and knowledge about absorption and elimination pathways of a 
485  drug. 
 
486  2.2.1.1 Data Analysis and Interpretation 
487  When examining the possibility that an investigational drug is a substrate of transporters, in vitro 
488  studies should be performed using experimental systems with the transporter activity confirmed 
489  using probe substrates and inhibitors (refer to Tables 10 and 11, Section 7.4.3 for some examples). 
490  Further details about considerations when performing in vitro studies are described in Sections 
491  7.2.1 and 7.2.2. 
492  For uptake studies, if there is significant uptake of a tested drug in transporter-expressed cells 
493  relative to the vehicle control-transfected cells (e.g., 2-fold than controls) and the uptake in 
494  transporter-expressed cells can be inhibited by more than 50% by a known inhibitor of the 
495  transporter, the tested drug can be considered a substrate of the transporter examined. 
496  For bidirectional efflux studies, if there is significant directional transport of a tested drug in 
497  transporter-expressed cells relative to un-transfected or parental cells (e.g., net efflux ratio 2) or 
498  Caco-2 cells (e.g., efflux ratio 2), and the efflux ratio can be inhibited by more than 50% by a 
499  known inhibitor of the transporter, the tested drug can be considered as a substrate of the 
500  transporter examined. 
  16   
501  A cutoff other than 2 or a specific relative ratio to positive controls can be used if prior experience 
502  with the cell system used justifies these alternative methods. Sponsors can also propose criteria for 
503  vesicle assays based on prior experience and internal data. 
504  If in vitro studies indicate that a drug is a substrate of a transporter, clinical studies should be 
505  considered. Refer to Section 3.2.5.1 for more details. 
 
506  2.2.2 Drug as an Inhibitor of Transporters 
507  Studies should be conducted to evaluate whether an investigational drug is an inhibitor of P-gp, 
508  BCRP, OATP1B1, OATP1B3, OAT1, OAT3, OCT2, MATE1 and MATE2-K. Sponsors can 
509  consider evaluating the inhibition potential of a drug on other transporters such as BSEP (bile salt 
510  export pump, a hepatic efflux transporter responsible for excretion of bile acids and involved in 
511  bile acid homeostasis), MRP2, OCT1, and OATP2B1 on a case by case basis. In vitro studies 
512  should be performed using an experimental system whose transport activity is confirmed using 
513  probe substrates and inhibitors (see Section 7.4.3 for more details). Considerations about how in 
514  vitro studies should be conducted are described in Sections 7.2.1 and 7.2.3. 
 
515  The risk for transporter inhibition by an investigational drug in humans can be excluded based on 
516  in vitro data using the following basic methods (22-24) . The contribution of drug metabolites to 
517  transporter inhibition should also be considered (see Section 2.3.2). 
 
518  Table 1: Recommended ratio and cut-off value for drug as inhibitor of transporters 
 
Ki or IC50 > 0.1  (Dose/250 mL) (i.e., 
P-gp or BCRP 
(Dose/250 mL)/Ki or IC < 10) for orally administered drugs 
50 
OATP1B1 or OATP1B3  Ki or IC50 > 10  Cmax, inlet,u (i.e., Cmax,inlet,u /Ki or IC50 < 0.1) 
OAT1 or OAT3  Ki or IC50 > 10  Cmax,u (i.e., Cmax,u/ Ki or IC50 < 0.1) 
OCT2  Ki or IC50 > 10  Cmax,u (i.e., Cmax,u/ Ki or IC50 < 0.1) 
MATE1/MATE2-K  Ki or IC50 > 50  Cmax,u (i.e., Cmax,u/ Ki or IC50 < 0.02) 
519  C is unbound maximal plasma concentration of an inhibitor at steady state after therapeutic dose. 
max,u 
520  C is estimated unbound maximum plasma concentration of an inhibitor at liver inlet. 
max,inlet,u 
521  The f should be set to 1% if experimentally determined to be < 1% (also refer to Section 2.1.2.1). 
u,p 
 
522  The recommended ratio and cut-off value for P-gp or BCRP is for orally administered drugs. If 
523  the investigational drug is administered parenterally or if it is a metabolite formed post-absorption 
524  that inhibits P-gp or BCRP, Ki or IC50 > 50  Cmax,u (i.e., Cmax,u/ Ki or IC50 < 0.02) can be used. 
525  The cut-off values in Table 1 were determined based on in vitro-to-in vivo extrapolation analyses. 
526  Since the majority of the in vitro inhibitory potency data in those analyses were IC50, both IC50 
527  and Ki values can be used when applying the basic methods above. However, if the potential for 
528  an interaction is studied further with modeling approaches, Ki should be determined and used. It 
529  is recommended to use substrate concentrations less than Km for in vitro transporter inhibition 
  17   
530  experiments. Assuming competitive inhibition, the Ki  of an inhibitor approaches IC50  when 
531  substrate concentration is much less than Km. 
532  The cut-off values described above are based on limited published data. Other cut-off values can 
533  be proposed if justified based on in vitro to in vivo extrapolation and a calibration of the specific 
534  in vitro systems with known inhibitors and non-inhibitors of these transporter systems. 
535  If the above analysis indicates that a drug inhibits a transporter, a clinical study should be 
536  considered based on whether the likely concomitant medications used in the indicated patient 
537  populations are known substrates of the inhibited transporter and the safety profiles of those 
538  substrates. Alternatively, the inhibition potential of a drug can be evaluated using mechanistic 
539  static models, PBPK modeling, or endogenous biomarkers. These approaches should be supported 
540  by submission of evidence supporting validity of the methods. 
 
541  2.2.3 Drug as an Inducer of Transporters 
542  Currently, in vitro methods to evaluate transporter induction are not well established.  If an 
543  investigational drug has been observed to be an inducer of CYP enzymes via activation of nuclear 
544  receptors such as PXR or CAR, it is likely that transporters regulated through these receptors will 
545  be induced, such as P-gp. Refer to Section 3.2.5 which describes conducting clinical DDI studies 
546  mediated by transporters for more considerations. 
 
547  2.3 DDI Potential of Metabolites 
548  The assessment of DDI liability of an investigational drugs metabolites often starts with in vitro 
549  experiments and generally uses the same strategies as those for parent drugs. As described below, 
550  evaluation  of  the  DDI  potential  of  metabolites  with  significant  plasma  exposure  or 
551  pharmacological activities should be considered. 
 
552  2.3.1 Metabolite as a Substrate 
553  The risk of DDIs through altered formation or elimination of a metabolite should be investigated 
554  if available data indicate that change in metabolite exposure can result in clinically meaningful 
555  alteration of efficacy or safety of a drug (target as well as off-target effects). The enzymes 
556  responsible for formation and elimination of a metabolite should be identified in vitro if the 
557  metabolite contributes to an in vivo target effect to a similar or greater extent than the parent drug. 
558  The contribution to efficacy should be estimated by taking into account unbound metabolite and 
559  parent drug exposures (e.g., AUC expressed in molar units) in humans, pharmacological potency 
560  (e.g., receptor binding affinity, enzyme inhibitory potency), and if available, data related to target 
561  tissue distribution. If the plasma protein binding of the parent drug and the metabolite is high, it is 
562  preferred to determine their protein binding in the same study to reduce inter-study variability. In 
563  addition, if a metabolite is suspected to cause significant adverse effects based on available 
564  nonclinical or clinical information, major enzymes involved in the formation and elimination of 
565  that metabolite should be identified if possible. Similar to metabolic phenotyping for parent drugs, 
  18   
566  the characterization of enzymes involved in metabolite formation and metabolism should also start 
567  with major CYP enzymes and can examine other enzymes when appropriate. 
568  The general principles described above can also be applied to characterization of a metabolite as a 
569  substrate of major transporters, with consideration  of the relevance of  transporter-mediated 
570  distribution or elimination in the disposition of a metabolite. 
571  Whether a sponsor should conduct a clinical DDI study with an inhibitor or inducer of an enzyme 
572  or a transporter depends on the estimated fraction of formation or elimination of a metabolite 
573  mediated by an enzyme or transporter, how much the metabolite contributes to the clinical effect, 
574  the exposure-response relationship of the metabolite if known, and likely concomitant medications 
575  that affect the enzyme or transporter. 
 
576  2.3.2 Metabolite as an Inhibitor 
577  If in vitro assessments suggest that the parent drug inhibits major CYP enzymes and transporters 
578  and clinical DDI studies are planned, in vitro assessments of metabolites as enzyme or transporter 
579  inhibitors may not be needed because the inhibition potential of metabolites would be implicitly 
580  reflected in a clinical DDI study along with the parent drug, unless clinically relevant exposures 
581  of the metabolite cannot be adequately represented in the clinical DDI study (i.e., the study 
582  duration does not allow the metabolite to accumulate). It is noted that in vitro assessments of 
583  metabolites can become useful in interpreting the results of DDI studies. 
584  If in vitro assessments suggest that the parent drug alone does not inhibit major CYP 
585  enzymes/transporters or is not expected to inhibit enzymes/transporters clinically, DDI liability 
586  due to metabolites as inhibitors can still exist. As a pragmatic rule, it is recommended to investigate 
587  the CYP enzyme and transporter inhibitory potential of metabolites that have AUCmetabolite  25% 
588  of AUCparent  and also account for at least 10% of drug-related material in circulation (i.e., 
589  considered as major metabolite often determined based on radioactivity data). 
590  Based on the results of in vitro DDI assessments of a metabolite, the determination of whether to 
591  conduct a clinical DDI study follows the same approaches as those for the parent drug, except that 
592  some metabolites could be irrelevant for the evaluation of intestinal CYP or transporter inhibition. 
593  If basic methods suggest that the metabolite(s) could have in vivo DDI liability, and a mechanistic 
594  static or PBPK model is then used to evaluate the DDI risk of a drug, metabolite(s) should be 
595  incorporated in those models. 
 
596  2.3.3 Metabolite as an Inducer 
597  While metabolites can induce CYP enzymes, the in vitro evaluation of the parent drug as a 
598  potential inducer could also reflect induction by metabolites because metabolites can be generated 
599  during incubation of the parent drug with hepatocytes. However, when the drug is a prodrug or a 
600    metabolite is mainly formed extra-hepatically, in vitro evaluation of a metabolites induction 
601      potential on CYP enzymes is recommended if the metabolite is a major metabolite and has 
  19   
602    AUCmetabolite/AUCparent  25%. Based on the results of in vitro assessments of the metabolite, the 
603    determination of whether to conduct a clinical DDI study follows the same approach as for the  604   
parent drug. 
 
605  3.  CLINICAL EVALUATION 
 
606  3.1 Types of Clinical DDI Studies (Terminology) 
607    There are different study types that can be conducted to determine the presence or absence of a 608   
clinical DDI and the magnitude of the DDI if one exists. The study types described in this section 609   are 
not mutually exclusive. The specific goal of a study should be considered when determining 610    the 
type of study to conduct. 
 
611    Regulatory decision-making generally relies upon prospective studies specifically designed to 
612    evaluate the potential for DDIs. Retrospective evaluation of drug concentrations from studies not 
613    designed to evaluate DDIs rarely includes sufficient accuracy and precision to provide an adequate 
614    assessment. DDIs identified or ruled out using a retrospective analysis may need to be confirmed 
615    using a prospective evaluation. 
 
616    In some situations, predictive modeling approaches (mechanistic static or PBPK) can be used to 617   
translate in vitro results to the clinical setting, without a clinical DDI study. The scenarios and best 618   
practice considerations are described in Section 7.3. 
 
619  3.1.1 Standalone and Nested DDI Studies 
620    A stand-alone DDI study is a clinical study with the primary objective of determining the presence 
621    or absence of a clinical DDI and the magnitude of the DDI. Alternatively, DDIs can be evaluated 
622    as part of larger studies in patients (e.g., phase 2/3) for which DDI evaluation is not the primary 
623    objective, if the DDI evaluation is prospectively planned and appropriately designed. As such, the 
624    DDI evaluation is nested within a larger study (refer to Section 3.2.2 for more details). 
 
625  3.1.2 DDI Studies with Index Perpetrators and Index Substrates 
626    Perpetrators (inhibitors or inducers) and substrates (victims) with well-understood and predictable 
627    pharmacokinetic and DDI properties with regard to level of inhibition, induction, or metabolic 628   
pathway are known as index drugs. The most common purpose of studies conducted with these 629   
drugs is to estimate the greatest magnitude of interaction for the studied pathway. For drugs that 630    are 
evaluated  as  victims  of  a  DDI,  the  greatest  magnitude  of  interaction  generally results  from 631   
concomitant  administration  of  a  strong  index  inhibitor  or  inducer  of  the  drug's  metabolic 632   
pathway(s). For drugs evaluated as perpetrators of DDIs, the greatest magnitude of interaction  633   
generally results from concomitant administration of the drug with a sensitive index substrate. 
 
634  A distinctive feature of index studies is that the results usually can be extrapolated to other drug 
635  combinations. Thus, after conducting a study with an index inhibitor, one can assume that other 
  20   
636    inhibitors of equal strength for that metabolic pathway will generally have a similar DDI effect 637   
size. Additionally, if one concludes that the change in drug exposure following a concomitant 638   
strong index inhibitor is not clinically relevant, the same can be concluded for all other inhibitors 639   for 
that particular metabolic pathway without additional studies. Results from DDI studies with 640    index 
perpetrators  or  substrates  are  also  used  to  help  design  DDI  studies  with  commonly  used  641   
concomitant medications in the investigational drugs target population. 
 
642  A list of index drugs (either as substrates, inhibitors, or inducers) is presented in Section 7.5.1. 
 
643    Index substrates or perpetrators have not been identified for transporters and several metabolic 644   
pathways (e.g., CYP2B6, UGTs). The lack of index substrates or perpetrators is mainly due to  645   
selectivity  issues.  However,  information  similar  to  that  provided  by  studies  with  index 646   
perpetrators  or  substrates  (i.e.,  the  likelihood  of  a  DDI  due  to  a  specific  pathway)  is  often 647   
important. Although index substrates and perpetrators have not been identified, Sections 7.5.2 and 648   
7.5.3 list drugs that can be useful for DDI studies because they provide informative results and  649   
explain the limitations of the drugs. However, extrapolation of results of these studies can be more 650   
difficult than extrapolation of results from studies with index drugs. 
 
651  3.1.3 DDI Studies with Expected Concomitant Drugs 
652    It can be informative to conduct studies that investigate DDIs between the investigated drug and 
653    drugs likely to be administered to the target population. These studies can also be considered when 
654    a drug is used as an add-on to other therapies or as part of a fixed dose combination. When choosing 
655    drugs to evaluate in these studies, sponsors should consider the mechanistic understanding of the 
656    potential for DDIs and the relative frequency of co-administration. Results of studies with index 
657    drugs can help determine what additional studies should be conducted. 
 
658    Because of a general lack of index substrates or perpetrators for transporter-mediated pathways 659   
and  several  metabolic  pathways  (UGTs;  CYP2B6),  the  choice  of  transporter  substrates  or  660   
perpetrators for DDI evaluation is often based on the likelihood of co-administration. 
 
661  Although these studies are often informative to patients and medical professionals, the results 
662  could be difficult to extrapolate to other drugs. 
 
663  3.1.4 Cocktail Approach 
664    A cocktail study includes the simultaneous administration of substrates of multiple enzymes and/or 
665    transporters to study subjects. A cocktail approach can simultaneously evaluate a drugs inhibition 
666    or induction potential for multiple enzymes and transporters if the study is properly designed and 
667    conducted (refer to Section 3.2.6 for additional details). 
 
668  3.2 Study Planning and Considerations for Clinical DDI Studies 
669  The objective of most DDI studies is to determine the ratio of a measure of substrate drug exposure 
  21   
670    (e.g., AUC ratio) in the presence and absence of a perpetrator drug. The following considerations 
671    are important when designing prospective clinical DDI studies to unambiguously determine this 
672    ratio. 
 
673  3.2.1 Study Design 
 
674      3.2.1.1 Study Population and Number of Subjects 
675    Most clinical DDI studies can be conducted using healthy subjects, under the assumption that 
676    findings in healthy subjects translate to findings in the intended patient population. However, 
677    safety considerations can prevent the use of healthy subjects in studies of certain drugs. For some 
678    drugs,  use  of  the  intended  patient  population  in  DDI studies  can  allow  for  evaluation  of 
679    pharmacodynamic endpoints that cannot  be studied in healthy subjects, in addition to PK 680   
endpoints. 
 
681  The number of subjects included in a DDI study should be sufficient to provide a reliable estimate 
682  of the magnitude and variability of the interaction. 
 
683      3.2.1.2 Dose 
684    For studies intended to identify the interaction of greatest magnitude, the doses of the perpetrator 
685    drug used in DDI studies should maximize the possibility of identifying a DDI. Thus, the 686   
maximum dose and the shortest dosing interval of the perpetrator under the intended conditions 687    of 
use should generally be evaluated. 
 
688    If the victim drug has dose-proportional pharmacokinetics, sponsors can study any dose in the 
689    range where exposure to the drug increases in a dose-proportional manner. If the victim drug has 
690    dose-dependent pharmacokinetics, the therapeutic dose most likely to demonstrate a DDI should 
691    be used. When there are safety concerns, lower doses of the victim drug can be used. 
 
692    For studies with anticipated concomitant drugs when a clinically significant DDI is anticipated, it 
693    can be informative to build a dose adjustment of the victim drug into the study to allow 694   
identification of doses that can be administered together in clinical practice. In such a scenario, a 695   
clinically relevant dose of the perpetrator should be used. 
 
696      3.2.1.3 Single or Multiple Doses 
697    The perpetrator drug is often administered in a multiple dose regimen in DDI studies. However, 
698    sponsors can evaluate single-dose administration of a perpetrator if the interaction potential is only 
699    relevant during absorption (e.g., inhibition of intestinal P-gp or BCRP). 
 
700    In addition, DDI studies can evaluate single-dose administration of a perpetrator if the exposure 
701    of perpetrator following a single dose is representative of exposure at steady-state and if the 
702    perpetrator is not a potential inducer or time-dependent inhibitor. When studied with a substrate 
703      with a long half-life, it may be necessary to administer a perpetrator multiple times to cover the 
  22   
704    full time-course of the substrate exposure. The duration of the treatment with the perpetrator 
705    should be long enough to cover at least 90% of the plasma concentration-time curve of the victim. 
706    However, if the victim has a very long terminal half-life that does not allow dosing with the 
707    perpetrator to cover the full AUC, population PK analysis or PBPK analysis can be used to 
708    estimate the full interaction effect on the exposure of the victim. 
 
709    If a metabolite of the perpetrator has demonstrated time-dependent inhibition of the enzyme being 
710    evaluated in the DDI study, the duration of the treatment with the parent drug should be sufficient 
711    for steady state of the metabolite to be reached. 
 
712    Inducers should be administered as multiple doses to ensure the maximal induction of a specific 713   
pathway. It may take about 2 weeks of daily drug administration to achieve the maximum level of 714   
induction  in  a specific  pathway.  Shorter treatment  duration  of  perpetrators  can  be used  with 715   
appropriate  justification.  When  there  are  multiple  mechanisms  of  interactions  for  a  specific 716   
perpetrator, single-dose administration can be appropriate in certain situations (e.g., evaluation of 717   
rifampin as an inhibitor of OATP1B1), while multiple-dose administration can be appropriate in 718   
other situations (e.g., evaluation of rifampin as a CYP3A inducer). 
 
719    If the substrate does not demonstrate time-dependent pharmacokinetics, the substrate can be 
720    administered as single doses, and the observed magnitude increase in exposure can be extrapolated 
721    to  steady-state  conditions.  If  the  substrate  demonstrates  time-dependent  pharmacokinetics, 
722    multiple-dose administration of the substrate and a perpetrator should be evaluated. 
 
723      3.2.1.4 Formulations and Route of Administration 
724    The route of administration of the investigational drug evaluated in DDI studies should generally 
725    be the one planned for routine clinical use. When multiple routes of administration are developed 
726    for clinical use, the route of drug administration for DDI studies should be selected based on the 
727    expected mechanisms of the DDIs and the similarity of the concentration-time profiles for the 
728    parent drug and metabolites after different routes of administration. 
 
729    Formulation-related differences in DDIs may also occur. There are several examples of excipients 
730    resulting in altered DDIs (25, 26). The possibility of formulation differences in interaction 731   
potential should be considered when extrapolating interaction results between formulations (27, 732  28). 
In general, DDI potential can be extrapolated between formulations by comparing their rate 733    and 
extent of absorption. 
 
734      3.2.1.5 Parallel Versus Crossover Studies 
735    Crossover studies (one-sequence or randomized) are preferred over parallel study designs in order 
736    to reduce variability. Duration of the washout period should be based on the pharmacokinetics of 
737    the substrate and the perpetrator, the anticipated impact on the substrates half-life, and the 
738      duration necessary for enzyme activity to return to baseline or for potential pharmacodynamic 
  23   
739    effects to return to pre-treatment levels (if pharmacodynamic effects are also assessed). In some 740   
situations, additional crossover periods can be informative (e.g., to evaluate the time it takes for 741   
enzyme activity to return to normal following removal of an inducer or time-dependent inhibitor, 742   to 
evaluate  two  drugs  that  may  affect  each  other  (each  drug  alone  and  in  combination),  or  to 743   
evaluate the effects of acute and chronic treatment of a drug). 
 
744    Parallel, two-arm studies can be appropriate when a crossover study design is not feasible, such as 
745    when one of the drugs has a long half-life. Typically, parallel-design studies call for larger sample 
746    sizes than crossover studies and subjects should be matched for intrinsic factors likely to affect 747   
pharmacokinetics. 
 
748      3.2.1.6 Timing of Drug Administration 
749    In most DDI studies, the perpetrator and victim drugs can be administered at the same time. 
750    However, the timing of administration of the perpetrator is critical if it is both an inhibitor and an 
751    inducer. For example, rifampin is an inducer of multiple enzymes and transporters, and also an 752   
inhibitor of transporters (e.g., OATP1B and P-gp). If rifampin, after a pre-treatment period, is co- 753   
administered with a drug that is a substrate of an inducible enzyme and also OATP1B1 and/or P- 754   gp, 
the observed exposure change of the victim reflects the net effect and underestimates the effects 755    of 
other inducers that do not inhibit OATP1B1 and/or P-gp. To determine the impact of induction, 756     
staggered administration of rifampin with the victim (e.g., separated by 24 hours) is recommended. 
 
757    If a large part of an interaction occurs during absorption or first pass, staggered dosing schedules 
758    can be studied (clinical study or PBPK) to understand whether such a method is a viable mitigation 
759    strategy for the DDI. 
 
760    When evaluating the interaction between drugs that require different food conditions for optimal 
761    absorption, the timing of drug administration should be adjusted to maximize the potential to detect 
762    an  interaction  (i.e.,  index  studies)  and/or  to  reflect  the  clinically relevant  conditions  (i.e., 
763    concomitant use studies). 
 
764      3.2.1.7 Co-Medications and Other Extrinsic Factors Affecting DDIs 
765    To reduce variability in the magnitude of DDIs, use of the following should be excluded to the 766   
extent possible during DDI studies: other medications, dietary/nutritional supplements, tobacco, 767   
alcohol,  foods,  and  fruit  juices  that  may  affect  the  expression  or  function  of  enzymes  and 768   
transporters. The exclusion should begin for a sufficient time before subjects enter the study and 769   
continue for the duration of the study. 
 
770      3.2.1.8 Sample and Data Collection 
771    PK sampling times should be sufficient to characterize the AUC0-inf (for single-dose studies) or the 
772    AUC0-tau (for multiple-dose studies) and Cmax of the substrate drug administered alone and under 
773      conditions of the anticipated interaction. Data on additional pharmacokinetic parameters should 
  24   
774    be collected based on the pharmacokinetic or pharmacological relevance for the proposed 775   
indication (e.g., the minimum concentration (Cmin), partial AUC). The sampling times for single- 776   
dose studies should be planned so that the mean difference between the AUC0-t and the AUC0-inf 777    is 
less than 20 percent. Samples collected should contain the moieties needed to interpret study 778  results; 
in  most  cases,  the  moiety  needed  to  interpret  results  will  be  the  parent  drug.  Metabolite  779   
concentrations should be determined if they provide information about the effect of a DDI on 780   
safety or efficacy, or if the data inform the mechanism of the drug interaction. 
 
781      3.2.1.9 Pharmacodynamic Endpoints 
782    When in vitro data provide a plausible DDI mechanism that cannot be evaluated with systemic 783   
drug exposure, collection and analysis of pharmacodynamic data can be informative. One possible 784   
scenario where this could occur is when transporter inhibition alters access of the drug to specific 785   
organs or tissues. In such scenarios, clinical consequences, such as altered efficacy or increased 786   
toxicity  resulting  from  altered  tissue  distribution  of  a  substrate  drug,  can  be  measured  as 787   
pharmacodynamic endpoints, and in vitro evidence of a drugs interaction potential can support 788   data 
interpretation. 
 
789  3.2.2 Specific Considerations for Nested DDI Studies 
790    Nested DDI studies are clinical DDI investigations that are part of other studies (e.g., phase 2/3) 
791    in which the assessment of DDI is not the primary objective. However, these trials are designed 792   
prospectively to investigate DDIs as an exploratory or secondary objective. Nested DDI studies 793    are 
usually used to evaluate the drug as a victim of concomitant drugs and sometimes can also be 794    used 
to  assess  the  drug  as  a  perpetrator.  The  results  of  such  analyses  can  be  informative,  and 795   
sometimes  conclusive,  when  the  clinical  studies  are  adequately designed  to  detect  significant 796   
changes in drug exposure due to DDIs. An advantage of nested DDI studies is the fact that they 797    are 
conducted in a patient population and may more closely represent the anticipated clinical 798  setting. 
However, nested DDI studies can also be challenging because they call for careful attention 799    to study 
design and data collection. In some cases, PBPK modeling can assist the design of nested 800    DDI 
studies (refer to Section 7.3.2). If large interactions are anticipated that would result in 801  clinically 
unacceptable  risks  to  subjects,  including  increased  toxicity  or  decreased  efficacy, 802    sponsors 
should consider whether another approach to DDI evaluation is more appropriate (29). 
 
803    A nested DDI study can evaluate the effect of concomitant drugs that are used for the full duration 
804    of the clinical trial or those that are added in response to the patients condition during the trial. 805   
Concomitant  drugs  to  be  evaluated  should  be  prespecified.  The  drugs  are  typically  selected 806   
because  there  is  a  mechanistic  reason  to  anticipate  an  interaction.  Relevance  in  the  patient 807   
population is also a consideration. The study design can specify individual drugs or a grouping, 808   
based on mechanism (e.g., strong CYP3A inhibitors) (30). However, if a grouping is evaluated it 809    is 
important to consider the potential for differences in the effect of different drugs in the group 810    and 
the effect of the potential variability on data analysis and translation of the findings. 
  25   
811    Simulations can be used to determine the appropriate number of PK samples and to assist in the 812   
selection of sampling times. A power analysis can also be performed to estimate the minimum 813  effect 
size that is likely to be detected with acceptable precision in a study using a given number 814  of patients 
on a concomitant drug. 
 
815    Collection  of  the  following  data  is  critical  to  ensure  interpretable  results:  timing  of  drug 
816    administration (investigational drug and concomitant drug), drug dose, timing relative to food 
817    (when relevant), other concomitant drugs, and PK sampling date and time (actual, not scheduled). 
818    It is also important to document the start date of the concomitant drug relative to when an 
819    interaction will be observed, particularly when the concomitant drug is an inducer or time- 
820    dependent inhibitor. 
 
821    Nested DDI studies are typically evaluated using population PK analysis, which should be 822   
performed  according  to  well-established  scientific  practice  using  a  model  that  is  validated  in 823   
relation  to  its  purposes.  The  population  PK  analysis  plan  for  the  DDI  assessment  should  be 824   
established prior to conduct of the study.  In general, the standard analysis approach is a binary  825   
evaluation that includes the concomitant drug as a static categorical covariate. Sponsors should 826   
consider whether their selected analysis methods will provide the desired level of precision in DDI 827   
evaluation. Regardless of analysis method, all assumptions should be stated. 
 
828    In some instances, unplanned analyses of potential DDIs in phase 2/3 trials are conducted to 
829    explain clinical study results, such as safety or efficacy issues in a group of patients, or to screen 
830    for potential DDIs not anticipated at the time the trials were designed. If the data collected meet 831   
the criteria described above, it can be possible to draw conclusions about the presence or absence 832   of 
an interaction. In situations where the data do not permit an accurate assessment of a DDI, a 833   
confirmatory evaluation of the DDI should be conducted. 
 
834  3.2.3 Considerations for CYP-Mediated Interactions 
 
835      3.2.3.1 The Investigational Drug as a Substrate for CYP Enzymes 
836    When evaluating the investigational drug as a substrate, the first clinical DDI studies should, in 837   
general,  determine  the  effects  of  a  strong  index  inhibitor  and  a  strong  index  inducer  on  the 838   
investigational drug. Moderate index inhibitors or inducers can be used if strong index inhibitors 839    or 
inducers are not available for a particular enzyme. Some of these inhibitors and inducers can 840    also 
affect other metabolism and/or transporter pathways; thus, when selecting index inhibitors 841    and 
inducers  for  prospective  DDI  studies,  all  metabolic  and  transport  pathways  of  the 842   
investigational drug should be considered. Studies with other strong inhibitors and inducers of 843  CYP 
enzymes  can  also  be  appropriate,  considering  the  criteria  listed  in  Section  7.5.1.  If  the 844   
investigational drug is a substrate for multiple enzymes and/or transporters, measuring metabolites 845   
can, in some cases, help with the interpretation of study results and interacting mechanisms. 
  26   
846    If a DDI study with a strong index inhibitor or inducer indicates no DDI is present, additional 
847    clinical studies with other inhibitors or inducers of the same enzyme are not needed. However, as 
848    a negative DDI study may reveal that the enzyme proposed to be the major metabolizing enzyme 
849    based on in vitro data is not contributing to the elimination of the drug, this may instead indicate 
850    that further clinical investigations with strong inhibitors of alternative candidate enzymes should 
851    be conducted. 
 
852    If a DDI study with strong index inhibitors or inducers indicates that there is a clinically relevant 
853    interaction, evaluating the impact of moderate inhibitors or inducers can be useful to gain a full 854   
understanding of the investigational drugs DDI potential. The evaluated moderate inhibitors and 855   
inducers may be anticipated concomitant medications in the intended patient population. The effect 856  of 
the additional inhibitors and inducers can be evaluated in a clinical interaction study, or, in some 857   
cases,  modeling  approaches  can  provide  additional  information  (refer  to  Section  7.3).  If  it  is 858   
anticipated that co-administration with strong inducers or inhibitors should be avoided, a DDI 859   
study with a moderate inducer or inhibitor may be preferable as the initial study. 
 
860    If the investigational drug is subject to significant metabolism by a genetically polymorphic 
861    enzyme for which a well-defined poor metabolizer phenotype exists that results in non-functional 
862    enzyme activity, a comparison of the pharmacokinetic parameters of the drug in individuals with 
863    the poor metabolizer phenotype versus those with a normal metabolizer phenotype can substitute 
864    for an interaction study for that particular pathway (refer to Section 4.1). 
 
865      3.2.3.2 The Investigational Drug as an Inhibitor or an Inducer of CYP Enzymes 
866    When studying an investigational drug as a potential inhibitor or inducer of a CYP enzyme, the 867   
index substrate selected for the initial clinical studies should be sensitive to changes in activity or 868   
amount of the CYP enzyme being evaluated (refer to Section 7.5.1). Because some substrates are 869   
not specific for one CYP enzyme and sometimes are also substrates of transporters, the most 870   
appropriate substrate should be selected considering the inhibitor/inducer characteristics of the  871   
investigational drug, based on available in vitro and clinical data. Other CYP enzyme substrates 872    can 
also be appropriate. If the substrate drug is metabolized by more than one enzyme, measuring 873   
metabolites sometimes can help with interpretation of study results. 
 
874    If the initial study with the most sensitive index substrates is negative, studies with less sensitive 
875    substrates of the enzyme are not needed. If an initial study determines that an investigational drug 
876    either inhibits or induces the metabolism of sensitive index substrates, further studies using other 
877    substrates (e.g., relevant co-medications) can be useful. The magnitude of the effect of the 
878    investigational drug on the sensitive index substrate and the potential for concomitant use with 879   
other drugs that are substrates of the same enzyme should be considered. 
 
880  If the investigational drug is both an inducer and an inhibitor of an enzyme, the net effect of the 
881  drug on enzyme function may be time dependent. The timing of pharmacokinetic endpoints should 
  27   
882    permit an understanding of the changes in effects over time, when relevant (31). To achieve this 
883    understanding, the pharmacokinetics of the victim drug should be evaluated at early and late time 
884    points during the administration of the investigational drug in the test period. The effect of 
885    reversible inhibition may be more pronounced in the beginning of the treatment and the induction 
886    may be most pronounced after ending the treatment. 
 
887  3.2.4 Considerations for Evaluation of UGT-Mediated Interactions 
 
888      3.2.4.1 Investigational Drug as a Substrate of UGTs 
889    Based on limited literature evidence, the magnitude of DDI mediated through inhibition of UGTs 
890    (reflected by AUC ratio of a substrate in the presence of an inhibitor compared to no inhibitor) 891   
rarely exceeds 3-fold and is often around 2-fold or less (32). For an investigational drug that is 892   
mainly eliminated by direct glucuronidation, clinical DDI studies with UGT inhibitors should be 893   
conducted on a case-by-case basis, considering the safety profile of the drug and the likelihood of 894    its 
concomitant use with inhibitors of that UGT isoform (refer to Table 16, Section 7.5.2 for some 895   
examples  of  UGT  inhibitors).  Some  UGT  substrates  are  also  substrates  of  other  enzymes  or 896   
transporters, and the interaction with a UGT inhibitor may involve other mechanisms when the 897  UGT 
inhibitor also affects those enzymes or transporters. Thus, it may be valuable to also measure 898    the 
glucuronide  conjugate  concentrations  in  addition  to  the  UGT  substrate  itself.  The  change  of  899   
glucuronide  metabolite  relative  to  the  parent  drug  may  provide  insight  into  the  underlying 900   
mechanism of interaction. In addition, some glucuronide metabolites are active or reactive and  901    may 
significantly  contribute  to  efficacy  or  safety  of  a  drug.  In  such  cases,  the  concentrations  of  902   
glucuronide conjugates should be measured in addition to parent drug concentrations. 
 
903    Genetic variation in certain UGT enzymes (for example, UGT1A1, UGT2B7, and UGT2B15) has 
904    been reported to contribute to variation in the pharmacokinetics of drugs metabolized by UGTs. 905   
In certain cases, comparative PK data in subjects with various UGT genotypes can be used to 906   
identify the importance of the UGT pathway(s) in the elimination of a drug in vivo and to estimate 907   
the extent of DDI with inhibitors of UGT. 
 
908    In addition, UGTs can also be induced, for example, by certain PXR agonists (e.g., moderate or 909   
strong  CYP3A  inducers).  The  impact  of  inducers  on  an  investigational  drug  that  is  mainly 910   
metabolized by UGTs should also be considered and evaluated depending on the likelihood of its 911   
concomitant  use  with  UGT  inducers  and  the  dose/exposure-efficacy  relationship  of  the 912   
investigational drug. 
 
913      3.2.4.2 Investigational Drug as an Inhibitor of UGTs 
914    Due to the limited availability of data from clinical DDI studies that evaluate inhibition of UGT 915   
isoenzymes, cutoffs for determining DDI risk using basic models like those for CYP enzymes have 916   
not been established. This is an area of ongoing research, and in the interim, sponsors can consider 917     
the same criterion as the one applied to CYPs (i.e., compare C /K < 0.02), or propose an 
max,u i,u 
  28   
918    alternative with justification. A decision on whether to perform a clinical DDI study to evaluate 919   
the effect of a drug as a UGT inhibitor should also take into consideration the likelihood of the 920  drugs 
concomitant use with known substrates of the UGT isoform (refer to Table 15, Section 7.5.2 921    for 
examples) and the safety profiles of those substrates. 
 
922      3.2.4.3 Investigational Drug as an Inducer of UGTs 
923    There is limited understanding about gene expression of UGTs. However, limited clinical DDI 924   
studies indicate certain UGTs may be induced by agonists of PXR and/or CAR, which also regulate 925   
CYP3A4 expression. UGTs are less inducible than CYP3A4. Thus, for a drug found to induce  926   
CYP3A4 in vitro and further evaluated with a clinical DDI study, the effect of the drug on CYP3A4 927   
substrates may inform its potential induction effect on UGTs. If a drug reduces the AUC of a 928   
sensitive substrate of CYP3A by 50%, a further clinical DDI study can be conducted with the 929  drug 
and a UGT substrate, depending on the magnitude of exposure change of the CYP3A 930  substrate, 
the likelihood of concomitant use of the investigational drug with  UGT substrates, 931    whether 
there are other enzymes/transporters involved in the pharmacokinetics of UGT substrates 932    which can 
also be regulated by PXR/CAR agonists, and the dose or exposure-efficacy relationship 933    of those 
UGT substrates. It is noted that some CYP3A4 inducers have their induction effect 934    overridden 
by their  inhibition  effect  on  CYP3A.  Thus,  while  those  drugs  inhibit  CYP3A4  in 935    clinical 
studies, they may exhibit induction effects on UGTs. 
 
936  3.2.5 Considerations for Evaluation of Transporter-Mediated Interactions 
 
937      3.2.5.1 Investigational Drug as a Substrate of Transporters 
938    If in vitro studies indicate that the investigational drug is a transporter substrate, sponsors should 
939    determine whether to conduct clinical DDI studies based on the drugs passive permeability, route 
940    of administration, in vivo absorption and elimination, putative site of action, safety profile, dose 
941    or exposure-response (efficacy and safety) relationship, and likely concomitant drugs that are 
942    known inhibitors or inducers of the transporters. The following general guidelines in Table 2 help 
943    to determine when a clinical DDI study is generally recommended for investigational drugs that 944   
are transporter substrates in vitro: 
945 
946      Table 2: Consideration for clinical evaluation of drug as substrate of transporters 
 
Transporters  When a clinical DDI study is generally recommended 
P-gp and BCRP  When intestinal absorption is limited, or biliary excretion/active 
renal secretion is a major elimination pathway. 
OATP1B1 and OATP1B3  When hepatic/biliary elimination is a significant clearance pathway 
(25%) for the investigational drug or the action site of the drug is 
in liver, and the drugs properties support the importance of active 
uptake of the drug into the liver. 
  29   
OAT1 and OAT3, OCT2,  When the investigational drug undergoes significant active renal 
MATE1, and MATE2-K  secretion (i.e., accounting for  25% of systemic clearance) or there 
are concerns about renal toxicity 
 
947    When evaluating an investigational drug as a victim in transporter-mediated DDIs, the selected 948   
perpetrator drug should be a known inhibitor of the transporter under investigation. Because of a 949   
general lack of index perpetrators for transporter-mediated pathways, the choice of transporter  950   
perpetrator  is  typically  based  on  the  likelihood  of  concomitant  use  (e.g.,  to  obtain  clinically 951   
relevant DDI information that can inform labeling regarding the management of a DDI). 
 
952    Transporter inhibitors can be used to understand the underlying mechanisms of DDIs or to 
953    determine the anticipated largest magnitude DDI. If in vitro studies indicate a drug is a substrate 
954    of multiple transporters, a clinical study can be conducted with a broad inhibitor of multiple 
955    transporters to determine the anticipated largest magnitude DDI. For example, cyclosporine, which 
956    inhibits intestinal P-gp and BCRP and hepatic OATPs, can be used as the inhibitor in a DDI study. 
957    Negative results from this kind of study may rule out the need to further evaluate the drug as a 958   
substrate for any of the individual transporters. If the study result is positive, additional studies 959    with 
more selective inhibitors of specific transporter pathways can be conducted to determine the 960    impact 
of inhibition of each transporter on the disposition of the substrate drug. The same paradigm 961    can apply 
to an investigational drug that is a substrate for both transporters and metabolic enzymes 962    (e.g., 
CYP3A and P-gp). 
 
963    If the goal of the study is to determine the role of a specific pathway in the pharmacokinetics of a 
964    substrate drug and resulting DDIs due to that pathway, then a more selective inhibitor should be 965   
used.  Use  of  these  inhibitors  in  clinical  studies  can  provide  a  mechanistic  understanding  of 966   
transporter-mediated DDIs. Some transporters, including OATP1B1 and BCRP, are encoded by 967   
genetically polymorphic genes (SLCO1B1 and ABCG2, respectively) for which phenotypes with 968   
reduced functionality exist. Similar to drugs that are substrates of CYPs encoded by polymorphic 969   
genes, the relative contribution of a specific transporter to the disposition of the investigational 970  drug 
can be evaluated in subjects with different transporter genotypes (refer to Section 4.1). 
 
971    Examples of transporter inhibitors are listed in Section 7.5.3.2. Many of them not only inhibit the 
972    specified  transporters  but  also  can  inhibit  other  transporters  and/or  CYP  enzymes.  Thus, 
973    extrapolation of results from transporter inhibition studies to other drugs can be challenging. 
974    Interpretation of the study results should consider the knowledge of transport and metabolic 
975    pathways for the investigational drug. 
 
976      3.2.5.2 Investigational Drug as an Inhibitor of Transporters 
977    If in vitro studies indicate that the investigational drug is a transporter inhibitor, the determination 
978    of whether to conduct a clinical DDI study should be based on likely concomitant drugs and safety 
979    considerations. When studying the investigational drugs potential to act as an inhibitor drug for a 
980      transporter,  a  substrate  drug  whose  pharmacokinetic  profile  is  markedly  altered  by 
  30   
981  coadministration of known inhibitors of that transporter and is also a likely concomitant drug is 
982  preferred. Some examples of transporter substrates that can be used in DDI studies are listed in 
983  Section 7.5.3.1. Because many drugs are substrates of multiple transporters and/or enzymes, the 
984  observed clinical interactions can be a result of the modulation of multiple pathways if the 
985  investigational drug is also an inhibitor or inducer for those pathways. Extrapolation of results 
986  from these studies to other drugs can thus be challenging. The choice of substrates can be 
987  determined by the therapeutic area of the investigational drug and the likely concomitant drugs 
988  that are known substrates of the transporters. 
989  In some cases, an alteration in drug transport may not be fully reflected by changes in plasma 
990  concentrations alone. Therefore, measurement of metabolite or pharmacodynamic markers to 
991  reflect altered distribution to the organs expressing the transporter should be included to interpret 
992  the potential for an interaction. 
993  Recent  literature  reports  indicate  potential  utility  of  endogenous  substrates  for  some  drug 
994  transporters (33-37). Evaluating the change in exposure of the endogenous substrate when the 
995  investigational drug is administered may provide information regarding the drugs potential as a 
996  transporter inhibitor. 
997  3.2.5.3 Investigational Drug as an Inducer of Transporters 
998  Since P-gp is co-regulated with CYP3A, for example by agonists of PXR and/or CAR, but is less 
999  inducible than CYP3A (38, 39), if an investigational drug reduces the AUC of a sensitive substrate 
1000  of CYP3A by 50% or more (i.e., being a moderate or strong inducer), a further clinical study to 
1001  evaluate potential induction effect of the drug on P-gp substrates should be considered, taking into 
1002  account  the following  factors:  the  magnitude  of CYP3A  substrate  AUC  change by the 
1003  investigational drug, the likelihood of concomitant use of the drug with P-gp substrates, whether 
1004  there are other enzymes/transporters involved in the pharmacokinetics of P-gp substrates which 
1005  can also be regulated by PXR and/or CAR agonists, and the dose or exposure-efficacy relationship 
1006  of P-gp substrates. It is noted that some CYP3A4 inducers have their induction effect overridden 
1007  by their inhibition effect on CYP3A. Thus, while those drugs inhibit CYP3A4 in clinical studies, 
1008  they may exhibit induction effects on P-gp. Sponsors should also consider whether to conduct 
1009  clinical DDI studies to evaluate the potential effect of a drug on other transporters regulated 
1010  through the same pathways as CYP3A. 
1011  3.2.6 Cocktail Studies-Considerations for CYP or Transporter Cocktail Studies 
1012  A cocktail approach can simultaneously evaluate a drugs inhibition or induction potential for 
1013  multiple CYPs and transporters if the study is properly designed. Ideal conditions for the cocktail 
1014  study are: (1) the substrates are specific for individual CYP enzymes or transporters; (2) there are 
1015  no interactions among the substrates; and (3) the study is conducted with a sufficient number of 
1016  subjects. If the first two conditions are not met, the lack of specificity or the interaction among 
1017  substrates should be understood and incorporated into the study results interpretation. Negative 
  31   
1018  results from a well-conducted cocktail study can eliminate the need for further evaluation of 
1019  particular CYP enzymes or transporters. Positive results from a well-conducted cocktail study that 
1020  includes all elements of a prospective DDI study can be interpreted the same way as positive results 
1021  from any other well-conducted DDI study. It should be noted that findings obtained with a 
1022  microdose of a substrate cannot always be extrapolated to a therapeutic dose of that substrate. 
1023  4. OTHER TOPICS 
1024  4.1 Pharmacogenetics 
1025  Pharmacogenetic variations in genes encoding drug metabolizing enzymes or drug transporters 
1026  can affect the pharmacokinetics of a drug, increase interindividual variability in drug exposure, 
1027  affect safety or efficacy, and alter the magnitude of DDIs. Important pharmacogenes include those 
1028  that encode phase 1 (e.g., CYP2C9, CYP2C19, CYP2D6) and phase 2 (e.g., NAT2, UGT1A1) 
1029  drug  metabolizing  enzymes  as well as  genes that encode  drug  transporters  (e.g., BCRP, 
1030  OATP1B1). Polymorphisms in metabolizing enzymes can lead to increased, normal, decreased, or 
1031  absent enzyme activity resulting in ultra-rapid (UM), normal or extensive (NM or EM, hereafter 
1032  referred to as NM), intermediate (IM), and poor (PM) metabolizers, respectively. Polymorphisms 
1033  in drug transporters can increase or decrease transport of a drug across membranes. These drug 
1034  metabolizing  enzyme  and  transporter  polymorphisms  can  affect  the  systemic  or  tissue 
1035  concentrations of a drug and/or its metabolite(s). 
1036  The scope of this section is limited to the evaluation of the impact of pharmacogenetics on DDIs 
1037  and on DDI evaluation. While the considerations described below use metabolizing enzymes as 
1038  examples, the concept can also be applicable to transporters with polymorphisms. 
1039  If an investigational drug is a substrate/inhibitor for a polymorphic enzyme and a DDI study with 
1040  an index inhibitor/substrate is conducted to evaluate pharmacokinetic changes, it is recommended 
1041  to prospectively characterize the subjects genotype. Exclusion of PMs is recommended, to allow 
1042  characterization of the greatest magnitude of interaction. If PMs are not excluded, the DDI effect 
1043  should be evaluated separately in subjects with different phenotypes (e.g., PM, IM, and NM), as 
1044  relevant. 
1045  If an investigational drug is subject to significant metabolism by an enzyme with a well-defined 
1046  PM phenotype (for example, CYP2D6, CYP2C19), exposure in PM is expected to be similar to 
1047  the effect of a strong inhibitor of that pathway. A comparison of the pharmacokinetic parameters 
1048  of the drug in individuals with the PM phenotype with those with a NM phenotype can substitute 
1049  for a DDI study of that pathway with a strong inhibitor. Similarly, the exposures in subjects with 
1050  a polymorphic PM phenotype could be estimated using the results of an in vivo DDI study with a 
1051  strong inhibitor. If there is a significant difference in exposure between individuals with the PM 
1052  and NM phenotypes, further studies to evaluate the DDI potential with moderate inhibitors or 
1053  inducers of the specific enzyme should be considered. 
  32   
1054  When an enzyme encoded by a polymorphic gene is one of two major elimination routes of an 
1055  investigational drug, the interaction effects of inhibiting the other enzymes is expected to vary in 
1056  different phenotypes of the polymorphic enzyme. In a DDI study evaluating the impact of 
1057  inhibitors of the other enzyme, prospective genotyping and enrichment of subjects with absent or 
1058  decreased function of the polymorphic gene besides NM subjects can help assess the interaction 
1059  effects in the various phenotypes. Because the DDI magnitude may become large in PMs or IMs 
1060  of the polymorphic enzyme when combined with an inhibitor of a parallel pathway, depending on 
1061  the safety profile of the drug, different doses should be considered in those subjects. PBPK 
1062  modeling can be useful to supplement such studies or to extrapolate the interaction effects in 
1063  different genotypes (refer to Section 7.3.2). 
1064  A retrospective pharmacogenetic analysis can help elucidate reasons for a high variability in a DDI 
1065  study. When study enrollment is not based on the genotype of a polymorphic metabolizing enzyme 
1066  or transporter, a retrospective analysis of the metabolizing enzyme or transporter of interest can 
1067  help to characterize differences in the magnitude of the DDI across genotype groups and explain 
1068  why some subjects have unanticipated increases or decreases in drug concentrations. 
1069  Guidance on DNA sample collection for prospective and retrospective pharmacogenetic analysis 
1070  can be found elsewhere (40, 41). As the frequency of certain pharmacogenetic variations can vary 
1071  across populations, when performing pharmacogenetic analysis, an individuals race/ethnicity 
1072  should be considered. In addition, regional regulations on sampling and analyzing human derived 
1073  materials need to be followed. 
1074  4.2 Therapeutic Protein DDIs 
1075  In general, the risk of pharmacokinetic DDIs is lower for proteins. The in vitro assays that are 
1076  applicable for small molecules are generally not applicable to proteins. 
1077  When evaluating the potential for a DDI between monoclonal antibodies and small molecules or 
1078  between monoclonal antibodies, the mechanisms of a potential DDI should be considered, taking 
1079  into account the pharmacology and clearance of the monoclonal antibodies as well as any co- 
1080  administered medications in the patient population. 
1081  4.2.1 Proinflammatory Cytokine-Related Mechanism 
1082  Certain therapeutic proteins may exert an indirect effect on expression of CYP enzymes and thus 
1083  affect the pharmacokinetics of small molecules. Therapeutic proteins that are proinflammatory 
1084  cytokines  (e.g.,  peginterferon)  or  that  can  increase  cytokine  levels  can  down-regulate  the 
1085  expression of CYP enzymes, thereby decreasing the metabolism of drugs that are CYP substrates 
1086  and increasing their exposure levels. The increase in cytokine levels as a result of drug treatment 
1087  can be transient or persistent; sponsors should consider this increase when determining whether to 
1088  conduct a DDI study as well as the design of that study. 
  33   
1089  Conversely, therapeutic proteins that reduce the elevated cytokine levels (e.g., inhibitors of tumor 
1090  necrosis factor) can relieve the CYP down-regulation from an inflammatory environment (e.g., 
1091  rheumatoid arthritis), thereby increasing CYP expression and activity and reducing exposure for 
1092  CYP substrates. 
1093  If the investigational drug is a cytokine or a cytokine modifier, sponsors should consider whether 
1094  to perform a clinical DDI study to evaluate the effects of the investigational therapeutic protein on 
1095  sensitive substrates for CYP enzymes. Known drug effects on metabolism in disease states with 
1096  similar or higher inflammatory burden, differences in exposure levels of sensitive CYP substrates 
1097  in healthy subjects versus patients in the indicated population, and the magnitude of the drug effect 
1098  on cytokine levels should be considered when determining whether to conduct a clinical study. In 
1099  some cases, a DDI study in the relevant indicated population should be conducted to further inform 
1100  instructions for use of the drug. Important design aspects include the disease type and severity in 
1101  the included patients and the dose and treatment time of the perpetrator drug. 
1102  4.2.2 Antibody-Drug Conjugates 
1103  For antibody-drug conjugates (ADCs), the small molecule drug component conjugated to the 
1104  antibody component can be released in unconjugated form. Therefore, the DDI potential of both 
1105  the antibody and the small molecule drug component should be considered. In general, for the 
1106  small molecule component, the potential to inhibit or induce enzymes and transporters should be 
1107  addressed in line with what is described elsewhere in this guideline. In many cases, however, the 
1108  systemic concentration of free drug might be too low to act as a perpetrator in vivo. 
1109  It is important to understand the formation, distribution and elimination kinetics of the small 
1110  molecule and to assess the systemic exposure of the small molecule drug component of the ADC. 
1111  It might be necessary to evaluate the small molecule component (administered as an ADC) as a 
1112  victim drug, in particular if increased levels of free drug may be associated with safety concerns. 
1113  Understanding  the  exposure-response  relationship  of  the  various  moieties  is  important  in 
1114  determining whether to conduct DDI studies and their significance. 
1115  5. REPORTING AND INTERPRETING CLINICAL DDI STUDY RESULTS 
1116  A DDI study report should include and justify the study design and data analysis method based on 
1117  what is known about the mechanism of the DDI and the PK properties of the perpetrator and victim 
1118  drugs. Data analysis of pharmacokinetic parameters (and pharmacodynamic parameters, when 
1119  relevant) should  include  all  subjects  enrolled  in  the  study who  have  evaluable  PK  and/or 
1120  pharmacodynamic  data.  If  a  subject  is  dropped  from  the  study  or  has  incomplete  plasma 
1121  concentration sampling during a treatment period, the possibility that the observation is due to an 
1122  interaction should be considered. When indicated, the interaction effect should be presented with 
1123  and without the individuals proposed for exclusion. 
  34   
1124  5.1 Pharmacokinetic Data Analysis 
1125  5.1.1 Non-Compartmental Analysis (NCA) 
1126  The following exposure measures should be determined for each subject: AUC , AUC , the 
0-inf 0-t
1127  percent extrapolated from AUC to AUC , C , and time to C (T ). For multiple-dose 
0-t  0-inf max max  max
1128  studies, C C , AUC at steady-state should also be reported. Additional parameters can help 
max,  min TAU 
1129  to interpret  the PK  results:  clearance, half-life, and volume of distribution. Parameters for 
1130  metabolites, when measured, should also be presented. NCA can be used to evaluate DDI studies 
1131  conducted to evaluate the investigational drug as a victim or perpetrator. 
1132  5.1.2 Population PK Analysis 
1133  PK data collected in nested DDI studies should typically be evaluated using population PK 
1134  methods. DDIs should be evaluated using all plausible structural elements of the PK model (e.g., 
1135  clearance (CL or CL/F), relative bioavailability, rate of absorption). Population PK analyses should 
1136  derive PK parameters appropriate for the study design and PK properties of the drug, such as AUC 
1137  and C . For multiple-dose studies, C , C and AUC at steady-state should be reported. 
max max min  0-TAU 
1138  5.2 Reporting DDI Results 
1139  Typical pharmacokinetics endpoints for DDI studies should include changes in drug exposure 
1140  parameters for the victim drug, such as AUC, C and in some situations, C . Pharmacokinetic 
max,  min
1141  results of DDI  studies should be reported as the geometric mean ratio of the observed 
1142  pharmacokinetic exposure measures with and without the perpetrator drug and the associated 90 
1143  percent confidence interval. Measures of the observed variability of the interaction, such as the 
1144  range of AUC or C ratios for individuals in a cross-over study, should be reported. A comparison 
max 
1145  of the individual pharmacokinetic parameters with and without concomitant medication should 
1146  also be presented graphically, e.g., as spaghetti-plots. 
1147  If pharmacodynamic endpoints are also assessed in the DDI study, the results should be reported 
1148  and summarized. 
1149  5.3. Interpreting DDI Study Results 
1150  5.3.1 Investigational Drug as a Victim of DDIs: Determination of No-Effect Boundaries 
1151  The results of a DDI study should be interpreted based on the no-effect boundaries for the victim 
1152  drug. No effect-boundaries represent the interval within which a change in systemic exposure 
1153  measure  is  considered  not  significant  enough  to  warrant  clinical  action  (e.g.,  avoiding 
1154  coadministration, dose or schedule adjustment, or additional therapeutic monitoring). 
1155  It is preferable for no-effect boundaries to be developed based on exposure-response relationships 
1156  derived from clinical trials, as well as other relevant information for the victim drug (e.g., safety 
  35   
1157  data and the maximum-tolerated dose). A good understanding of exposure-response relationships 
1158  for desirable and undesirable drug effects, as well as knowledge of the variability of exposures in 
1159  the indicated population, facilitates data interpretation. 
1160  In general, the point estimate for the ratio between the exposure of the victim with and without the 
1161  perpetrator can be used to evaluate the magnitude of the interaction and to determine whether 
1162  interventions such as dose adjustments should be considered. Sponsors should also consider the 
1163  variability of the interaction. As indicated in 3.2.1.1, the number of subjects included in the study 
1164  should be sufficient to provide a reliable estimate of the magnitude and variability of the 
1165  interaction. If the 90 percent confidence interval for the measured changes in systemic exposures 
1166  in the DDI study falls completely within the chosen no-effect boundary, no clinically relevant DDI 
1167  is present. However, because DDI studies are not typically powered for the 90 percent confidence 
1168  interval to fall within the chosen no-effect boundary, a strict statistical interpretation of the DDI 
1169  study may not be applicable. A method that determines the proportion of subjects that extend 
1170  beyond the no-effect boundary can also be used to interpret the results. 
1171  If the 90% confidence interval for the measured changes in systemic exposure in the DDI study 
1172  falls within 80-125%, the study can be interpreted as negative, unless the victim drugs safety or 
1173  efficacy  is  affected  by  small  changes  in  exposure.  Because  this  range  is  typically  overly 
1174  conservative, it is not the selected no-effect boundary in most cases. In the absence of a defined 
1175  exposure-response relationship, the totality of evidence should be considered when determining 
1176  the clinical impact of a DDI. 
1177  5.3.2 Investigational Drug as a Perpetrator of DDIs: Classification System 
1178  The classification system assists in the extrapolation of DDI study results to drugs that have not 
1179  been evaluated in a clinical DDI study. 
1180  If an investigational drug is a CYP inhibitor, it can be classified as a strong, moderate, or weak 
1181  inhibitor based on its effect on an index CYP substrate. The convention is to categorize CYP 
1182  inhibition in the following way: 
1183    A strong inhibitor increases the AUC of a sensitive index CYP substrate  5-fold. 
1184    A moderate inhibitor increases the AUC of a sensitive index CYP substrate by  2- to < 5- 
1185  fold. 
1186    A weak inhibitor increases the AUC of a sensitive index CYP substrate by  1.25- to < 2- 
1187  fold. 
1188  If an investigational drug is a CYP inducer, it can be classified as a strong, moderate, or weak 
1189  inducer based on its effect on an index CYP substrate.  The convention is to categorize CYP 
1190  induction in the following way: 
1191    A strong inducer decreases the AUC of a sensitive index CYP substrate by  80 percent. 
  36   
1192    A moderate inducer decreases the AUC of a sensitive index CYP substrate by  50 to < 80 
1193  percent. 
1194    A weak inducer decreases the AUC of a sensitive index CYP substrate by  20 to < 50 
1195  percent. 
1196  These categories generally describe the effect of the investigational drug when given at the highest 
1197  clinical dose and the shortest dosing interval within its therapeutic dose range/dosing regimen. It 
1198  is noted that the effects of some inhibitors or inducers are dose dependent. 
1199  Although CYP inhibitor and inducer classifications are typically based on DDI studies with index 
1200  substrates, if the metabolic properties of a sensitive substrate are well understood, it can be possible 
1201  to classify the investigational drug based on a study with the alternative substrate. 
1202  Currently, there are no classification systems for transporters or non-CYP enzymes, because the 
1203  magnitude of DDIs mediated by transporters or non-CYP enzymes (e.g., UGTs) has a more limited 
1204  range. Inhibition of these pathways often results in AUC increases around 3-fold or less, and the 
1205  interacting mechanisms may involve other transporters and/or enzymes, making it challenging to 
1206  classify inhibitors using the same criteria as those for CYP enzymes. 
1207  5.3.3 Extrapolating Study Results 
1208  Clinical evaluation of all possible combinations of drugs is not feasible. When possible, results 
1209  from DDI studies should be extrapolated to other drugs and clinical situations. Results from DDI 
1210  studies with index drugs generally represent the largest magnitude interaction by a specific 
1211  mechanism and can be used to predict the magnitude of other interactions by the same mechanism. 
1212  The classification system for CYP inhibitors and inducers assists the extrapolation. For example, 
1213  if there is no effect on the exposure of an investigational drug when co-administered with a strong 
1214  CYP3A index inhibitor, then one can generally assume that there is no effect when other strong, 
1215  moderate, or weak CYP3A4 inhibitors are co-administered with the investigational drug. If 
1216  administration of a strong CYP2D6 index inhibitor results in a significant increase in exposure of 
1217  the investigational drug, these results can be directly extrapolated to other strong CYP2D6 
1218  inhibitors. In some cases, extrapolation of positive findings to moderate and weak inhibitors can 
1219  be possible using mechanistic modeling. 
1220  Because of the lack of specific transporter substrates and inhibitors and the possible interplay with 
1221  metabolism,  it  is  generally  challenging  to  extrapolate  results  from  DDI  studies  evaluating 
1222  transporter-mediated DDIs or transporter-metabolism interactions from one drug to other drugs. 
1223  However, if the ADME properties of the investigational drug and potential concomitant drugs are 
1224  well understood, it is possible to estimate transporter-mediated interactions with other concomitant 
1225  drugs. 
  37   
1226  5.3.3.1 Extrapolating Complex Scenarios 
1227  Most DDI studies evaluate the interaction between two drugs and consider the effect on single 
1228  transporters or enzymes. However, DDIs for a specific drug may result from a combination of 
1229  mechanisms, and patients may receive more than two potentially interacting drugs. Some of the 
1230  resulting complex DDI scenarios are listed below: 
1231    Concurrent inhibition of an enzyme and a transporter by a drug. 
1232    Concurrent inhibition and induction of a drugs metabolic pathways, involving one or 
1233  more enzymes. 
1234    Increased inhibition of drug elimination by use of inhibitors of more than one enzyme 
1235  that metabolizes the drug. 
1236    Inhibition  of  an  enzyme  other  than  the  genetic  polymorphic  enzyme  in  poor 
1237  metabolizers taking a substrate that is metabolized by both enzymes. 
1238    Effect of enzyme/transporter inhibitors in subjects with varying degrees of impairment 
1239  of drug eliminating organs (e.g., liver or kidney). 
1240    The two drugs affect one anothers PK (both act as perpetrator and victim). 
1241  When there are multiple factors that affect the absorption and disposition of an investigational drug 
1242  as well as multiple mechanisms of DDIs, sponsors should consider evaluating the effect of the 
1243  combination of mechanisms and/or individual factors on drug exposure. The complex scenarios 
1244  can be evaluated by integrating knowledge from the relevant in vitro and clinical studies. PBPK 
1245  models can be used to: (1) integrate the information from multiple studies; (2) determine whether 
1246  a clinical study would be informative; and (3) inform the design of clinical studies. 
1247  6. RISK ASSESSMENT AND MANAGEMENT 
1248  Risk assessment should inform the use of DDI management strategies. A DDI is clinically relevant 
1249  if concomitant use of the drugs leads to safety, effectiveness, or tolerability concerns greater than 
1250  those present when the drugs are administered alone. 
1251  In general, DDI prevention and risk minimization strategies should result in drug concentrations 
1252  of the victim drug falling within the no-effect boundaries. The risk assessment and development 
1253  of risk minimization strategies should consider the following factors: 
1254    The exposure-response relationships for safety and efficacy. 
1255    The variability of the observed DDI data, if available. 
1256    The expected duration of concomitant drug use (e.g., acute, short-term, or chronic use 
1257  of one or both drugs). 
1258    The anticipated timing of the introduction of the concomitant medication. 
1259    The mechanism of the DDI (e.g., reversible or time-dependent inhibition, induction, 
1260  combined inhibition and induction). 
  38   
1261    The availability of monitoring parameters (e.g., therapeutic drug monitoring, laboratory 
1262  tests). 
1263    The ability to interrupt the investigational drug or concomitant interacting medication 
1264  and the availability of other therapeutic options for either drug. 
1265    The clinical importance of the relevant adverse outcome relative to the clinical benefit 
1266  of the drugs. 
1267  In addition to the above considerations, DDI risk minimization and prevention strategies can 
1268  include  the  following:  (Note  that  there  may  be  regional  regulatory  differences  in  how 
1269  recommendations are worded in labeling.) 
1270    Contraindicating or avoiding concomitant use. 
1271    Temporarily discontinuing one of the interacting drugs. 
1272    Modifying the dosage of one of the drugs. 
1273    Staggering drug administration (e.g., administer the investigational drug at a different 
1274  time than a concomitant drug). 
1275    Implementing  specific  monitoring  strategies  (e.g.,  therapeutic  drug  monitoring, 
1276  laboratory testing). 
1277    Replacing one of the interacting drugs with a drug not expected to interact. 
1278  7. APPENDICES 
1279  7.1 In Vitro Evaluation of Metabolism-Based DDIs 
1280  7.1.1 In Vitro Systems 
1281  Various hepatic in vitro systems can be used to evaluate the risk for enzyme-mediated interactions 
1282  for an investigational drug, including: 
1283    Subcellular  human  liver  tissue  fractions  such  as  microsomal  systems  (human  liver 
1284  microsomes (HLM); containing CYP450 and UGT enzymes), supernatants after 9000 g 
1285  centrifugation of liver homogenate (S9;  containing microsomal as well as cytosolic 
1286  enzymes such as sulfotransferases, glutathione transferases, aldehyde dehydrogenase, 
1287  aldehyde  oxidase  and  alcohol  dehydrogenase),  and  cytosol  (adding  co-factors  as 
1288  appropriate). For HLM, a pool of at least 10 donors is suggested. 
1289    Recombinant human CYP and UGT enzymes. These systems usually express only one 
1290  single enzyme. 
1291    Human liver tissues, including freshly prepared or cryopreserved hepatocytes that 
1292  preserve enzyme architecture and contain the full complement of phase 1 and 2 drug 
1293  metabolizing enzymes. For phenotyping and inhibition experiments, hepatocytes pooled 
1294  from at least 10 donors is suggested, whereas for induction experiments usually 
1295  hepatocytes from at least 3 individual donors should be used. 
  39   
1296  The in vitro systems used should be robust and reproducible. 
1297  Microsomal protein concentrations should be minimised, and standardised assay conditions (e.g., 
1298  buffer strength, type, and pH) should be used. An incubation time and an enzyme amount that 
1299  result in linear formation of the metabolite (at an initial rate of the metabolite formation) is 
1300  recommended. 
1301  For phenotyping experiments, the system should be characterized with in vitro probe substrates to 
1302  prove the activity of each enzyme.  In general, a probe substrate should be selective (e.g., 
1303  predominantly metabolized by a single enzyme), or a specific metabolite of a probe substrate is 
1304  primarily formed by a single enzyme. A list of examples of probe substrates with their marker 
1305  reactions and literature reported K values can be found in Table 4, Section 7.4.1.1. For studies of 
m 
1306  time-dependent inhibition or induction, appropriate inhibitors or inducers should be included as 
1307  positive controls (refer to Section 7.4.1 for more details). 
1308  For enzyme inhibition studies, if the investigational drug is metabolized by the enzymes present 
1309  in the incubation, the probe substrate should, if possible, have a markedly faster metabolism rate 
1310  than the investigational drug to  minimize the influence of  investigational  drug metabolism 
1311  (decreasing concentrations) on the estimation of inhibitory parameters. 
1312  Robust analytical methods should be used to quantify an investigational drug and its relevant 
1313  metabolite(s) in phenotyping experiments, as well as probe substrates and/or their relevant 
1314  metabolites in inhibition and induction experiments (when enzyme activities are measured). Good 
1315  laboratory practice (GLP) standard is not required, but a full description of the analytical methods 
1316  employed, including validation of the analytical parameters, should be provided (42). 
1317  It is recognized that obtaining high drug concentrations in the in vitro studies of enzyme inhibition 
1318  or induction may not be possible in some circumstances due to poor aqueous solubility or cell 
1319  toxicity. If limited by solubility, co-solvents can be used to reach the highest concentration 
1320  possible. Any organic solvents should be used at low concentrations (<1% volume/volume and 
1321  preferably < 0.5%) because some solvents can inhibit or activate enzymes. The experiment should 
1322  include a solvent (vehicle) control, and when appropriate, also a no-solvent control to evaluate 
1323  potential effect of solvent on enzyme reaction. There is at present much uncertainty regarding how 
1324  to interpret in vitro inhibition and induction data when sufficiently high concentrations cannot be 
1325  tested; thus the general recommendation is to test the DDI potential of these compounds in vivo, 
1326  unless in vitro testing is sufficiently justified. 
1327  Limited drug stability or non-specific binding in the incubations (e.g., with apparatus, microsomes 
1328  or hepatocytes) can also create experimental challenges in in vitro studies of enzyme inhibition or 
1329  induction. Actual unbound concentrations of the drug in the in vitro system (e.g., incubation 
1330  medium) should in general be used for extrapolating in vitro results to in vivo scenarios. When 
1331  non-specific binding or metabolic instability is encountered, sponsors should consider whether to 
1332  adjust experimental conditions or correct for non-specific binding or instability when interpreting 
  40   
1333  the data (e.g., derive Ki,u from Ki). Non-specific binding can be measured experimentally (e.g., 
1334  using equilibrium dialysis or ultrafiltration) or predicted using in silico methods (43, 44). For 
1335  highly lipophilic drugs, it is preferred to experimentally determine non-specific binding (45). 
1336  For induction experiments, sponsors are encouraged to measure concentrations of the parent drug 
1337  in the medium on the last day of incubation with hepatocytes and protein binding should also be 
1338  considered.  When measured concentrations are substantially lower than nominal concentrations, 
1339  sponsors should discuss the potential impact of the discrepancy on data interpretation (46, 47). 
1340  7.1.2 Investigational Drug as an Enzyme Substrate: Reaction Phenotyping 
1341  Drug metabolizing enzyme identification studies, often referred to as reaction phenotyping studies, 
1342  identify the specific enzymes contributing to the main elimination pathways of a drug. Along with 
1343  other information (e.g., in vivo pharmacokinetics, mass-balance study, pharmacogenetic data or 
1344  available DDI data), in vitro phenotyping data are often used to identify and quantify elimination 
1345  pathways of an investigational drug. 
1346  Although the main focus of this guideline is on hepatic CYP involved metabolism, in order to 
1347  identify the metabolic pathways for the individual investigational drug, non-CYP enzyme-based 
1348  metabolism and metabolism occurring in extra-hepatic tissues should also be considered for certain 
1349  drugs. 
1350  7.1.2.1 Metabolic Pathway Identification 
1351  Metabolic pathway identification experiments should be performed early in drug development to 
1352  identify the number and structures of metabolites formed when a drug is metabolized, and to 
1353  determine whether the metabolic pathways are parallel or sequential. These experiments use HLM, 
1354  intact human liver systems (e.g., hepatocytes), or recombinant enzyme systems. Data obtained 
1355  from metabolic pathway identification experiments help to determine whether and how to conduct 
1356  a reaction phenotyping study. 
1357  7.1.2.2 Metabolic Enzyme Identification 
1358  Reaction phenotyping can be done either in HLM or hepatocytes using selective enzyme inhibitors 
1359  (chemicals or antibodies) or in human recombinant enzymes. When using individual human 
1360  recombinant enzymes, the difference in the amount and enzyme activity of CYPs between the 
1361  recombinant CYP enzyme systems and the human liver should be considered. Whenever possible, 
1362  all experiments should be conducted with drug concentrations relevant to the clinical setting, and 
1363  under initial rate conditions (e.g., linearity of metabolite production rates with respect to time and 
1364  enzyme concentrations). 
1365  The contribution of individual enzymes to the overall metabolism of an investigational drug can 
1366  be examined by measurement of parent drug depletion or measurement of metabolite formation. 
1367  For the latter method, all of the major metabolites should have been identified and quantified in 
1368  metabolite formation experiments. The use of a radiolabelled drug substrate is advantageous 
  41   
because samples can be analysed using liquid chromatography coupled with a radioactivity 
1369 
detector and a mass spectrometer to identify and quantify drug-related species. Evaluation of 
1370 
individual isomers of racemic drugs is recommended when it is important to understand the 
1371 
different  disposition  characteristics  of  each  isomer  (e.g.,  when  two  isomers  have  different 
1372 
pharmacological activities). 
1373 
 
Some chemical inhibitors are not specific for an individual CYP enzyme. The selectivity and 
1374 
potency of inhibitors should be verified in the same experimental conditions using probe substrates 
1375 
for each CYP enzyme (see Section 7.4.1.1 for more details). If specific antibodies are used instead 
1376 
of inhibitors, the inhibitory effect of an antibody to a CYP enzyme should be tested at sufficiently 
1377 
low and high concentrations to establish a titration curve and ensure the maximal inhibition of a 
1378 
particular pathway (ideally resulting in greater than 80 percent inhibition). The effect of an 
1379 
antibody should be verified using probe substrates of each CYP isoform in the same experimental 
1380 
conditions. 
1381 
 
For UGT enzymes, in vitro studies are most commonly performed with HLM or recombinant UGT 
1382 
enzymes as the enzyme source. When HLM used as enzyme source, either addition of alamethicin 
1383 
or sonication is necessary for activating HLM (1). Determination of the contribution of each UGT 
1384 
isoform to the overall elimination is sometimes challenging due to lack of selective inhibitors, 
1385 
variability of results depending on experiment conditions, and instability of glucuronide metabolite 
1386 
in feces from a mass balance study (48). 
1387 
 
1388  7.1.3 Investigational Drug as an Enzyme Inhibitor 
1389  The potential of an investigational drug to inhibit CYP enzymes is usually investigated using 
1390  selective probe substrates to determine the type of inhibition (e.g., reversible inhibition or time- 
1391  dependent inhibition (TDI)) and measure of inhibition potency (e.g., Ki for reversible inhibition, 
1392  and K and k for TDI). The in vitro systems used for these studies include pooled HLM, 
i  inact 
1393  microsomes obtained from recombinant CYP-expression systems, or pooled human hepatocytes. 
 
1394  For reversible inhibition, experiments with a high concentration of test drug can be performed first 
1395  to study its inhibition potential on a particular enzyme (e.g., 50 x Cmax,u or 0.1 x Dose/250 mL, 
1396  refer to Section 2.1.2.1). If clinical interaction cannot be excluded at the high concentration, lower 
1397  drug concentrations should be tested to estimate the drugs IC50 or Ki value; it is recommended to 
1398  examine at least four different concentrations of the investigational drug. Experiments with 
1399  varying concentrations of both the inhibitor and substrate concentrations to cover ranges above 
1400  and below the substrate's Km, should be tested to determine the Ki for inhibition. For competitive 
1401  inhibition or uncompetitive inhibition, IC50/2 can be used as an estimate for Ki  if the substrate 
1402  concentration in the incubation is the same as its Km value (49). If the substrate concentration is 
1403  much less than the Km value, then the IC50 value will approximate the Ki value for a competitive 
1404  inhibitor. More accurate estimation of the Ki value can be derived from the IC50 value using the 
1405  Cheng-Prusoff equation (50). For non-competitive inhibition, Ki value is equal to IC50 regardless 
1406  of substrate concentration used (51). Thus, IC50/2 can still be used as a conservative estimate. 
  42   
1407  There are various assays to identify TDI of CYP enzymes. For example, TDI can be detected by 
1408  assessing a difference  in  IC curves  generated  with  and  without a pre-incubation  with 
50  
1409  nicotinamide adenine dinucleotide phosphate (NADPH) (i.e., IC shift), decreases in enzyme 
50 
1410  activity (measurement of the pseudo first-order rate constant, k ) or percent activity loss with the 
obs
1411  inactivator over time (also called standard dilution methods). In the IC shift assay, pooled HLM 
50 
1412  should typically be pre-incubated for 30 min with the investigational drug at concentrations that 
1413  surround 10-fold (or greater, depending on the dilution factor) of their reversible IC values with 
50 
1414  or without NADPH. The pre-incubation samples should then be diluted (10-fold or greater) into 
1415  an incubation containing probe substrate (at a concentration around its K for the reaction) and 
m 
1416  NADPH. A left shift of the IC curve (e.g.,  1.5- or 2-fold) from the samples pre-incubated with 
50 
1417  NADPH  compared  to  those  without,  suggests  a  potential  for  enzyme  inactivation  by  the 
1418  investigational drug. The degree of the fold-shift to establish a positive result would be dependent 
1419  upon  the  demonstrated  sensitivity  of  the  experimental  system  used  to  detect  known  TDI 
1420  compounds, particularly at least one with a lower fold-shift (e.g. ritonavir) (52). 
1421  To rule out a TDI, the decreases in CYP enzyme activity with time can also be evaluated at a single 
1422  concentration of the investigational drug (e.g., k or percent activity loss). When such a method 
obs 
1423  is used, the test compound should be pre-incubated with pooled HLM with and without NADPH 
1424  typically for 30 min, the reaction should then be diluted appropriately (10-fold or greater to dilute 
1425  out the test compound). A vehicle control should be included to correct for potential enzyme 
1426  activity loss over the time of the study. The remaining CYP activity should be determined by 
1427  measurement of a select CYP probe substrate metabolism (in this case, a high concentration of 
1428  substrate can be used to help with the dilution of the test compound). A reduction in CYP enzyme 
1429  activity greater than a pre-defined threshold for the assay (e.g., of >20% reduction in activity or a 
1430  k value of >0.01 min-1) can be used to define a positive result. 
obs 
1431  When a drug is identified as a TDI with initial assessment as described above, definitive in vitro 
1432  studies should be performed to obtain TDI parameters (i.e., k and K) in pooled HLM for DDI 
inact  I
1433  predictions (4). Human hepatocytes and rhCYP can also be considered for TDI assessment. 
1434  7.1.4 Investigational Drug as an Enzyme Inducer 
1435  The potential of an investigational drug to act as an inducer of CYP enzymes is normally 
1436  investigated in plateable, cryopreserved or freshly isolated, human hepatocytes. Alternative in 
1437  vitro systems such as immortalized hepatic cell lines and cell receptor assays can be used, but the 
1438  results from these studies are generally considered supportive rather than definitive in nature. If an 
1439  alternative in vitro system is used as the main method, the sponsor should provide a justification 
1440  supporting the appropriateness of the in vitro system as well as data interpretation. 
1441  It is recommended to measure the extent of enzyme induction at the mRNA level. Enzyme activity 
1442  can also be measured, measuring only the enzyme activity is usually not recommended as the 
1443  induction could be masked in the presence of concomitant inhibition. For CYP2C19, enzyme 
  43   
1444  activity should be measured, since its mRNA change is often limited even in response to positive 
1445  control (53). 
1446  Regardless of which in vitro system and endpoint are chosen, the system should be validated to 
1447  show that all major CYP enzymes are functional and inducible with positive controls. The response 
1448  of positive controls (measured as mRNA fold change) is normally at least a 6-fold increase for 
1449  CYP1A2, 2B6, and 3A4, which is considered indicative of satisfactory sensitivity of hepatocyte 
1450  lots (refer to Section  2.1.4.1) (54).  It is  more  difficult to obtain satisfactory sensitivity of 
1451  hepatocytes for some other enzymes (e.g., CYP2C8, CYP2C9, CYP2C19) that are less inducible 
1452  (11, 12). Limited fold of increase in mRNA of these enzymes to positive controls (e.g., rifampin) 
1453  pose a challenge to get a conclusive interpretation of results. 
1454  Incubation of an investigational drug usually lasts for 48-72 hours to allow complete induction to 
1455  occur. Justification should be provided for shorter incubation time. Incubations normally include 
1456  a daily addition of the investigational drug, and the medium containing the drug should be changed 
1457  regularly. More frequent addition of a drug can be considered if its stability is low. The optimal 
1458  time course for incubation should allow detection of enzyme induction without causing cell 
1459  toxicity. If cytotoxicity occurs, reduced incubation durations can be used if adequate sensitivity of 
1460  the assay can be demonstrated. 
1461  Culture quality should be verified and documented by cell morphology and biochemistry tests. A 
1462  suitable viability assessment is normally performed before and at the end of the incubation period 
1463  to certify that cell toxicity is not influencing the induction response. If toxicity/loss of viability is 
1464  observed, influence on the study results should be discussed in the study report and in vivo studies 
1465  may be considered. 
1466  If hepatocytes from a donor (a) do not respond satisfactorily to the positive induction controls, (b) 
1467  demonstrate viability <80% at the start of the incubation, or (c) demonstrate viability at the end of 
1468  the incubation that deviates markedly from the viability at the beginning of the experiment, the 
1469  cells can be replaced by hepatocytes from a new donor. 
1470  To rule out that the investigational drug is an in vitro inducer, an induction study including 3 donor 
1471  hepatocytes can be run with at least 3 replicates of 3-5 different concentrations of the test 
1472  investigational drug, encompassing 15  C . The basic mRNA fold-change method can be used 
max,u
1473  to evaluate in vivo induction potential based upon the criteria described earlier (refer to Section 
1474  2.1.4.1). 
1475  If there is an induction signal, the sponsor can further use the correlation method or mechanistic 
1476  static models to predict the magnitude of a clinical induction effect of an investigational drug. 
1477  These methods utilize full concentration-response curves for induction, to estimate E and EC
max  50 
1478  of the investigational drug. In addition, to use these methods, a batch of hepatocytes should be 
1479  calibrated (13). For the correlation method, a large set of inducers (n  8) covering the full in 
1480  vivo induction potency range and including at least 2 weak inducers, are recommended for 
  44   
1481  calibration. Emax and EC50 are determined for all inducers and a correlation is established between 
1482  a certain matrix (incorporating E and/or EC and clinical concentrations of inducers) and in 
max  50 
1483  vivo change in the AUC of a sensitive substrate of a specific enzyme (e.g., midazolam for CYP3A) 
1484  for each inducer. For the mechanistic method, an empirical calibration factor, d factor to enable 
1485  in vitro to in vivo induction scaling, should be determined for a hepatocyte batch. The d factor 
1486  can be estimated by correlating the predicted and observed induction effects (i.e., AUC ratio of a 
1487  sensitive substrate of a particular enzyme) of a set of known inducers and performing a linear 
1488  regression to identify a d value that can minimize the prediction error (20). If the d factor is not 
1489  estimated, it should be set as a default value of 1. 
1490  For the correlation or mechanistic static methods, sponsors can use only one hepatocyte donor. 
1491  The calibration can be established once for that batch of hepatocytes rather than multiple times for 
1492  each experiment with investigational drugs. When performing the in vitro study evaluating the 
1493  induction potential of an investigational drug, a criteria for acceptable assay variability should be 
1494  established. At least 2 of the inducers (weak and strong) of the calibration set should be included 
1495  as controls with responses falling within the defined assay variability, in order to utilize the 
1496  calibration  set  of  that  hepatocyte  batch.  If  this  method  is  used,  both  the  calibration  data 
1497  set/calibration report and the data on the investigational new drug should be submitted. 
1498  7.2 In Vitro Evaluation of Transporter-Based DDIs 
1499  7.2.1 In Vitro Systems 
1500  Various in vitro transporter assays can be used to evaluate the risk for transporter-mediated 
1501  interactions of an investigational drug. Selecting the in vitro model can depend on the purpose of 
1502  the study and the questions to be addressed. Available in vitro systems include: 
1503    Membrane vesicles 
1504  In vitro systems using inside-out membrane vesicles from cells transfected with a 
1505  transporter can be used to evaluate whether an investigational drug is a substrate or 
1506  inhibitor of efflux transporters such as P-gp or BCRP but may fail to identify highly 
1507  permeable drugs or highly non-specific binding drugs as substrates. Vesicles can also be 
1508  used for MATE transporters evaluation. 
1509  P-gp and BCRP assays using membrane vesicles should directly measure the adenosine 
1510  triphosphate (ATP)-dependent, transporter-mediated uptake of drugs with control (non- 
1511  transfected) vesicles for comparisons. 
1512    Bi-directional transport assays with cell-based systems. 
1513  Bidirectional assays can be used to evaluate whether an investigational drug is a substrate 
1514  or inhibitor of efflux transporters such as P-gp or BCRP. 
  45   
1515  The permeability of the drug should be investigated in both directions, preferably under 
1516  sink conditions (the concentration on the receiver side is less than 10% of the concentration 
1517  on the donor side) unless the absence of sink conditions is compensated for in the 
1518  calculations. The apparent permeability (P ) of the drug in both the APBL (absorption: 
app
1519  apical  to  basolateral)  and  BLAP  (efflux:  basolateral  to  apical)  directions  can  be 
1520  calculated, as well as an efflux ratio (ER) of BLAP to APBL. 
 
1521 
1522 
   
  PPmmpppp,BBmmmmPP 
1523  EEmm = 
PPmmpppp,mmPPBBmm 
1524  When using transfected cell lines, efflux ratios of the transfected cell line should be 
1525  compared with appropriate control conditions to account for endogenous transporter 
1526  activity and non-specific binding. One approach is to compare the efflux ratios from 
1527  transfected cell line to the parental or empty vector-transfected cell line. 
1528   
1530 
 EEmmiiccmmccddooddcciidddd  
mmddii EEmm = 
  1529    EEmmppmmccddcciimmcc 
1531  The integrity of monolayer membrane should be measured before and after experiments 
1532  by examining whether transepithelial/transendothelial electrical resistance (TEER) values 
1533  or permeability of paracellular markers fall within the pre-defined acceptance range. 
1534    Uptake assays with cell-based systems: 
1535  Uptake assays can be used to evaluate whether an investigational drug is a substrate or 
1536  inhibitor of solute carrier (SLC) transporters such as OCTs, OATs, OATPs and MATEs, 
1537  but can also be used to investigate efflux transporters. 
1538  When transfected cell lines are used to evaluate whether a drug is a substrate of a 
1539  transporter, the drug uptake in the transfected cell line should be compared to the parental 
1540  or empty vector-transfected cell line, or a comparison of the uptake with or without an 
1541  inhibitor of the transporter should be performed. When assessing a drug as an inhibitor of 
1542  a transporter, evaluation of the uptake of a known probe substrate using transporter- 
1543  transfected cell lines alone can be sufficient.  Besides transfected cell  lines,  human 
1544  hepatocytes or hepatic cell lines in suspension or plated can be used. 
1545  The model system and experimental conditions should be validated, including culture and transport 
1546  assay conditions. Transport studies should be performed under linear transport rate conditions 
1547  (probe substrate concentration used is usually below its K for the transporter). Appropriate 
m 
1548  positive controls should be included in the test study to ensure the validity of the studys results. 
  46   
1549  The assays should be optimized to ensure consistent transporter function (e.g., uptake, efflux) with 
1550  control experiments (e.g., positive and negative controls for substrates/inhibitors (refer to Tables 
47 
   
1551  10 and 11, Section 7.4.3 for some examples), non-transfected control cells). The following 
1552  conditions should be considered whenever applicable: the source of the membrane vesicles or 
1553  cells, cell culture conditions (e.g., cell passage number, seeding density, monolayer age), probe 
1554  substrate/inhibitor concentrations, incubation time, buffer/pH conditions, sampling interval, and 
1555  methods for estimating parameters such as the IC , K, and K . In addition, adding serum or 
50 i m
1556  plasma proteins to the media can also affect transport activity. 
 
1557  Laboratory acceptance criteria for study results should be established (e.g., monolayer integrity, 
1558  passive permeability, efflux or uptake of probe substrates, Km for a probe substrate, IC50 for a 
1559  probe inhibitor). The Km value of a probe substrate or the IC50 value of a probe inhibitor should be 
1560  comparable to literature-reported values. 
1561  The substrate should be readily measured with no interference from the assay matrix. 
1562  Any organic solvents should only be used at low concentrations (< 1% volume/volume and 
1563  preferably < 0.5%) because some solvents can affect cell integrity or transporter function. The 
1564  experiment should include a solvent (vehicle) control, and when appropriate, also a no-solvent 
1565  control. 
1566  For both substrate and inhibitor studies, the sponsor should demonstrate sufficient total recovery 
1567  of the drugs (e.g., 80% (55)). 
1568  7.2.2 Investigational Drug as a Transporter Substrate 
1569  The concentration range of an investigational drug should be relevant to the site of transport and 
1570  should be based on the expected clinical concentration range. For transporters expressed in 
1571  multiple organs (e.g., P-gp, BCRP), the sponsors should provide justification for the choice of 
1572  concentrations taking into consideration the sites where the transporter is likely to play a role for 
1573  drug disposition. When a range of drug concentrations is relevant, it is important to assure that low 
1574  concentrations are included, as high concentrations may saturate transporters that are still active at 
1575  lower drug concentrations. 
1576  If the in vitro system expresses multiple transporters (e.g., Caco-2 cells, hepatocytes), the sponsor 
1577  should conduct additional experiments to confirm the findings with two or more known potent 
1578  inhibitors, including the ones that are relatively specific for individual transporters. 
1579  If active transport is concluded, the passive permeability in the absence of transporters is one of 
1580  the factors that could be taken into account to estimate the clinical importance of the transporter. 
1581  For intestinal transporters, the role of these transporters may be limited if the permeability in the 
1582  absence of transporters is high ( the permeability constant of the highly permeable control drug). 
1583  In this case, the effect of active drug transport may be negligible as compared to the passive, 
1584  concentration-gradient driven absorption of the drug. To estimate the permeability of a drug in the 
1585  absence of transporters, for bi-directional assays (e.g., Caco-2 cells) the permeability constant can, 
  48   
1586  for example, be determined at concentrations high enough to completely saturate the transporters 
49 
   
1587  (assessed as an ER ratio of 0.5  2). If this approach is used, it should be established that the cell 
1588  monolayer is unaffected. Alternatively, the permeability of a drug can be measured in the presence 
1589  of a broad inhibitor of transporters. The investigation should include a well validated, high and 
1590  low permeable reference substance (for example, metoprolol and mannitol; refer to (55) for more 
1591  details). 
1592  7.2.3 Investigational Drug as a Transporter Inhibitor 
1593  Normally the investigation of transporter inhibition starts with testing a high concentration of the 
1594  test drug, for example, 10  C for OAT1/3 and OCT2, 50  C for MATEs, 10  liver inlet 
max,u  max,u 
1595  C for OATP1B1/3, and 0.1  the highest therapeutic dose/250 mL for orally administered P- 
max,u 
1596  gp or BCRP inhibitors. The drug concentration should, however, not exceed the drugs solubility 
1597  limits or cause deleterious effects (e.g., cytotoxicity) in the cells. There is at present much 
1598  uncertainty regarding how to  extrapolate in vitro results to in vivo  when sufficiently high 
1599  concentrations cannot be tested, thus the general recommendation is to test the DDI potential of 
1600  these compounds in vivo, unless in vitro results are sufficiently justified. 
1601  Several factors may cause actual drug concentrations in the in vitro assays to deviate from nominal 
1602  concentrations, including poor aqueous solubility, non-specific binding, and instability. Correction 
1603  for binding or stability or solubility issues should be conducted when interpreting the data. 
1604  Sponsors are encouraged to measure unbound drug concentrations in the medium. 
1605  If the test drug demonstrates inhibitory activity at the recommended cut-off concentration, the 
1606  sponsor should test additional concentrations to estimate IC or K values. The sponsor should 
50  i 
1607  evaluate at least four concentrations of the investigational drug with the probe substrate. The 
1608  sponsor can then compare IC or K values to clinical plasma or estimated intestinal concentrations 
50  i 
1609  of a drug to predict the potential for DDIs. 
1610  For some transporters (e.g., OATP1B1 and OATP1B3) and experimental systems, it can be 
1611  relevant to determine IC or K following pre-incubation with the investigational drug, since some 
50  i 
1612  inhibitors demonstrated more inhibition potency after pre-incubation (56-60). This is an area of 
1613  emerging information, and sponsors are encouraged to follow current literature for information on 
1614  transporters of interest and relevant experimental protocols. 
1615  7.3. Predictive Modeling 
1616  This section describes how modeling approaches can be used to: (1) characterize the potential for 
1617  DDIs, (2) indicate whether a dedicated clinical DDI study should be conducted, and (3) support 
1618  clinical recommendations in the absence of a clinical DDI study. The modeling approaches 
1619  discussed are static mechanistic models and dynamic mechanistic models (also known as PBPK 
1620  models). 
1621  Various  mathematical  and  mechanistic  modeling  approaches  can  help  translate  in  vitro 
1622  observations into predictions of potential clinical DDIs. In some cases, findings from in vitro and 
  50   
1623  early clinical studies, in conjunction with model-based predictions, can be used to determine 
1624  whether initial or additional clinical investigations of a drugs DDI potential as a victim or 
1625  perpetrator of CYP enzyme- or transporter-mediated interaction should be conducted. 
1626  Section 3 of this guideline describes the evaluation of in vitro metabolism and transporter studies 
1627  to determine whether further evaluation of a drug as a victim or perpetrator of CYP enzyme- or 
1628  transporter-mediated interactions should be conducted. If those assessments indicate further 
1629  evaluations should be conducted, they may be conducted using mechanistic static models or PBPK 
1630  models (if adequate data are available, as described below) or by conducting a clinical DDI study. 
1631  For each drug development program, multiple approaches for assessing DDI risk may be feasible. 
1632  Depending on the results of the mechanistic static or PBPK modeling, follow-up clinical DDI 
1633  studies could be needed. 
1634  The use of appropriate in vitro experimental conditions is critical to any model used for a 
1635  quantitative prediction. 
1636  7.3.1 Using Mechanistic Static Models for DDI Predictions 
1637  A mechanistic static model incorporates detailed drug disposition and drug interaction mechanisms 
1638  for both interacting and substrate drugs (61, 62). The model includes the effect of reversible and 
1639  time dependent enzyme inhibition, as well as enzyme induction. Thus, the model can estimate the 
1640  effect of several interaction processes. The overall effect of the perpetrator drug on the substrate 
1641  drug is represented as AUCR (ratio of the AUC of the substrate drug in the presence and absence 
1642  of the perpetrator drug) and is given by the equation below. 
1643  7.3.1.1. Evaluation of an Investigational Drug as a DDI Perpetrator 
1644  For a drug that is both an inhibitor and an inducer of an enzyme, in addition to the combination of 
1645  inhibition and induction, a drugs inhibition potential alone (A and B only, assuming C is equal to 
1646  1 in the equation below), and induction potential alone (C only, assuming A and B are equal to 1 
1647  in the equation below) should be conducted. Concurrent prediction can lead to a false negative 
1648  prediction if the inhibition potential is over-predicted, thus masking the induction effect (63). If 
1649  the induction potential is over-predicted, it will mask the inhibition effect. 
1650  7.3.1.2. Evaluation of Investigational Drug as a Victim of CYP-Mediated DDIs 
1651  In principle, mechanistic static models can be used to predict DDI effects with a less potent 
1652  perpetrators after the model has been confirmed with index perpetrators. 
1653  7.3.1.3. Evaluation of The Potential for Transporter-Mediated DDIs 
1654  Although there are fewer examples, with adequate data about transporters involved and the fraction 
1655  of drug transported at various tissues (ft), the mechanistic static models as noted below and in 
1656  Table 3 can be used to evaluate transporter-mediated DDIs (64-68). The potential applications and 
  51   
1657  considerations listed for PBPK modeling (refer Section 7.3.2.2) are also relevant for mechanistic 
1658  static modeling. 
1659  Equation to calculate AUCR of the substrate drugs (AUC plus investigational drug/AUC 
1660  minus investigational drug) 
1661 
1  1 
mmAACCmm = (  )  (  ) 
dd dd dd dd dd 
[mm   BB   CC ]  (1  FF ) + FF [mmh  BBh  CCh]  oomm + (1  oomm) 
1662  The equation assumes that the drug has negligible extrahepatic clearance. 
  1663  A is the effect of reversible inhibitions. 
1664  B is the effect of TDI. 
1665  C is the effect of induction. 
1666  Fg is the fraction available after intestinal metabolism. 
1667  fm is the fraction of hepatic clearance of the substrate mediated by the CYP enzyme that is subject to 
1668  inhibition/induction. 
1669  Subscripts h denote liver. 
1670  Subscripts g denote gut. 
1671   
  Gut  Liver 
1672  Table 3: Equations to calculate AUCR of the substrate drug for reversible and time- 
Reversible inhibition 
1673  dependent inhibition 
1  1 
mmdd =   mmh =  
   Time-dependent inhibition  BBdd =  1kk + dddd  [ddIIKK,dd]ii dd     BBh =  1kk + dddd [ddIIKK,]hii h   
  [II]   kk  [II]   kk 
dd  iiccmmccii  h  iiccmmccii 
Induction 
  kkdddddd,dd +  kkdddddd,h + 
[II]dd + KKII  [II]h + KKII 
     CCdd = 1 + dd  EEmmmmmm  [II]dd  CCh = 1 + dd  EEmm  mmmm  [II]h 
[II] dd  + EECC 50  [II] h + EECC 50 
 
 
  1674   
 
1675  Each value can be estimated with the following equations: 
1676  [I]h = fu,p  (Cmax + (FaFgkaDose)/Qh/RB) (69). 
1677  [I]g = FakaDose/Qen (70). 
1678  fu,p is the unbound fraction in plasma. The fu,p should be set to 1% if experimentally determined to be < 1% 
1679  (also refer to Section 2.1.2.1). Since the potential impact of fu,p on the prediction of DDI is high, sensitivity 
1680  analyses for fu,p should be provided for highly protein bound drugs. 
1681  Cmax is the maximal total (free and bound) inhibitor concentration in the plasma at steady state. 
1682  Fa is the fraction absorbed after oral administration; a value of 1 should be used when the data are not 
1683  available. 
1684  Fg is the fraction available after intestinal metabolism; a value of 1 should be used when the data are not 
1685  available. 
1686  ka is the first order absorption rate constant in vivo; a value of 0.1 min-1 (69) can be used when the data 
1687  are not available. 
  52   
1688  Qen is the blood flow through enterocytes (e.g., 18 L/hr/70 kg (71)). 
1689  Qh is the hepatic blood flow (e.g., 97 L/hr/70 kg (72)). 
1690  RB is the blood-to-plasma concentration ratio. 
53 
   
1691  d is a scaling factor determined in a calibrated hepatocyte batch based on positive control inducers (20, 
1692  61, 63). If not determined, it is assumed to be 1 (20, 63). A different value can be used if supported by prior 
1693  experience with the system used (18). 
1694  Reports of modeling exercises and results should provide support for input parameters based on 
1695  data and/or scientific literature. 
1696  If the model estimates AUCR between 0.80 to 1.25, the risk of a clinically relevant interaction is 
1697  low, and additional evaluations of the drug as a perpetrator for the studied enzyme are not needed. 
1698  If AUCR is outside 0.80 to 1.25, further evaluation should be conducted to quantify the effect. 
1699  Alternatively, sponsors should provide sufficient justification(s) if no further assessments are 
1700  planned. 
1701  Mechanistic static models are currently used to determine whether the potential for a DDI can be 
1702  ruled out. This use, along with the current equations used for drug concentrations in the gut and 
1703  liver (above), can be overly conservative and thus result in false positive results. There are ongoing 
1704  efforts to determine the most relevant drug concentrations in gut and liver (6, 62). The results of 
1705  these efforts could lead to the use of mechanistic static models to provide quantitative estimates of 
1706  interactions due to CYPs and/or transporters. If additional research supports the use of the models 
1707  in a more quantitative manner, reports of results should include justifications for both system- and 
1708  drug-dependent parameters and sensitivity analyses when relevant. 
1709  7.3.2 Using PBPK Models to Predict Enzyme or Transporter-Based DDIs 
1710  PBPK models can assist in the evaluation of the DDI potential of an investigational drug and/or a 
1711  metabolite as a victim or perpetrator of enzyme or transporter-mediated interactions. Compared 
1712  with a mechanistic static model, since a PBPK model considers changes in concentration over time, 
1713  information regarding time-dependent interactions can be obtained in more detail. When PBPK 
1714  modeling is used to support drug development and regulatory decisions, it is important to justify 
1715  any model assumptions, the physiological and biochemical plausibility of the model, variability, 
1716  and uncertainty measures. PBPK analysis reports should include a description of the context of 
1717  use for the model, model structure and development plan, the sources and justifications for both 
1718  system- and drug-dependent parameters, and an adequate sensitivity analysis plan. When using 
1719  predefined models (structural and error) from commercially available software, the software 
1720  version and any deviations from predefined models should be described (73). In some scenarios, 
1721  simulation data from a robust PBPK model can be used to conclude the DDI potential of an 
1722  investigational drug instead of a dedicated clinical DDI study. 
1723  In general, broad recommendations for PBPK model verification, validation and the reporting of 
1724  the results are beyond the scope of this guideline (refer to (74-78) for guidance on these topics). 
1725  Instead, this guideline describes the utility of PBPK modeling for the evaluation of DDIs, with the 
1726  understanding that models should be demonstrated as fit-for-purpose. Specific best practice 
1727  considerations for use of PBPK modeling for the evaluation of DDIs are also described below. 
  54   
1728  7.3.2.1 Potential Applications of PBPK to the Evaluation of CYP-Mediated DDIs 
1729  Related to evaluation of CYP-mediated DDIs, PBPK models can help select key DDI studies for 
1730  a development program and support the study design for clinical DDI studies. They can also be 
1731  used to explain PK observations, such  as observed PK differences that  are due to genetic 
1732  polymorphism. 
1733  When evaluating a drug as a potential victim of CYP-mediated DDIs, PBPK models can be used 
1734  to predict DDI effects with a less potent perpetrator after the model has been confirmed with index 
1735  perpetrators. They can also predict clinically relevant DDI scenarios, such as the effect following 
1736  multiple dose administration of the substrate drug if only single dose administration is evaluated 
1737  in a clinical DDI study. 
1738  When evaluating a drug as a potential perpetrator of CYP-mediated DDIs, PBPK models can be 
1739  used to support the lack of clinical DDI potential and to predict DDI effects under different dosing 
1740  regimens after the model has been confirmed with an index substrate. 
1741  7.3.2.1.1 Modeling Considerations - PBPK for Evaluation of CYP Interactions for Drugs as 
1742  Substrates 
1743  Sponsors should consider the following when using PBPK modeling to predict the DDI potential 
1744  of the investigational drug (including clinically relevant metabolite(s)) as a CYP enzyme substrate: 
1745    The base PBPK model of the investigational drug should describe the available clinical PK 
1746  data using different dosing regimens (e.g., a dose proportionality study, repeated dosing) 
1747  and dosing routes (e.g., intravenous or oral). 
1748    The major metabolic and other elimination pathways should be quantitatively assigned in 
1749  the investigational drugs model according to available in vitro and clinical data. 
1750    The uncertainty of the PBPK model parameters should be assessed using sensitivity 
1751  analysis. For example, since the potential impact of f on the prediction of DDI is high, 
u,p 
1752  sensitivity analyses for f is expected for highly protein bound drugs. 
u,p 
1753    The index perpetrator models should describe the available clinical PK data using different 
1754  dosing regimens (e.g., a dose proportionality study) and, as appropriate, different dosing 
1755  routes (e.g., intravenous or oral). 
1756    The acceptability of index perpetrator models should be independently confirmed with 
1757  regard to their modulating effect on the PK of sensitive enzyme substrates in humans. 
1758    If complex metabolic and transport mechanisms are expected, the substrate and perpetrator 
1759  models should include the relevant disposition and interaction mechanisms and should be 
1760  deemed fit-for-purpose. 
  55   
1761  7.3.2.1.2 Modeling Considerations - PBPK for Evaluation of CYP Interactions for Drugs as 
1762  Perpetrators 
1763  Sponsors should consider the following when using PBPK modeling to predict the drug interaction 
1764  potential of an investigational drug (including clinically relevant metabolite(s)) as a CYP enzyme 
1765  perpetrator: 
1766    The base PBPK model of the investigational perpetrator (and its metabolites, when 
1767  relevant) should describe the available clinical PK data using different dosing regimens 
1768  (e.g., a dose proportionality study, repeated dosing) and, as appropriate, dosing routes (e.g., 
1769  intravenous or oral). 
1770    The DDI parameters should be assigned in the perpetrators model according to available 
1771  in vitro and clinical data such as clinical DDI study(ies). 
1772    For perpetrators that exhibit both inhibition and induction, the inhibition and induction 
1773  mechanisms should be separately considered, in addition to the combination of inhibition 
1774  and induction, to ensure a conservative prediction of in vivo enzyme inhibition or induction. 
1775  In most cases, the clinically relevant effect of interest is the combined effect. 
1776    The index substrate models should describe the available clinical PK data using different 
1777  dosing regimens (e.g., a dose proportionality study) and as appropriate, different dosing 
1778  routes (e.g., intravenous or oral). 
1779    Sensitive index substrate models should be independently confirmed with regard to the 
1780  effect of a strong index perpetrator-mediated altered enzyme activity on its PK in humans. 
1781    The simulation should include the highest clinical dose and shortest dosing interval of the 
1782  investigational perpetrator. The PK and modulating effect of the highest dose should be 
1783  confirmed before use in the simulation. 
1784    Sensitivity  analyses should be conducted for parameters exhibiting high levels of 
1785  uncertainty. 
1786  7.3.2.2 Potential Applications of PBPK to the Evaluation of Transporter-Mediated DDIs 
1787  Related to evaluation of transporter-mediated DDIs, PBPK models can be used to support the 
1788  initial study design for clinical DDI studies when a DDI liability is identified. 
1789  When evaluating a drug as a potential victim of transporter-mediated DDIs, PBPK models can be 
1790  used to explain PK observations, such as PK differences that are due to genetic polymorphism 
1791  (e.g., OATP1B1). PBPK models can also be used to explore involvement of specific transporters 
1792  in a drugs ADME. 
1793  When evaluating a drug as a potential inhibitor of transporter-mediated DDIs, PBPK models can 
1794  support negative DDI prediction when the drug is an in vitro inhibitor for a basolateral uptake 
  56   
1795  transporter. They can also be used to evaluate the effect of an investigational drug on the PK of a 
1796  transporter substrate with a well characterized pathway. 
1797  7.3.2.2.1 Modeling Considerations - Drug as a Transporter Substrate 
1798  In  general,  quantitatively confirming the  model  regarding  the  involvement  of  the  specific 
1799  transporter in the relevant organ(s) is challenging. Comprehensive model exploration and/or 
1800  clinical studies should be conducted for quantitative model confirmation. 
1801  7.3.2.2.2 Modeling Considerations - Drug as a Transporter Inhibitor 
1802  In general, when using PBPK models to evaluate a drug as a transporter inhibitor, the substrate 
1803  model should be confirmed for the relevant transporter(s). Further, the analysis report should 
1804  include a sensitivity analysis for the inhibition constant. 
1805  7.4. List of Drugs that can be used in In Vitro Studies 
1806  7.4.1 CYP Enzymes 
1807  7.4.1.1 CYP Enzyme Substrates for In Vitro Studies 
1808  Probe substrates are used to measure perpetrator properties of a drug candidate on individual CYP 
1809  enzymes (see Table 4 for examples of substrates). The substrates should be selective, or the 
1810  formation of a specific metabolite is selective for a CYP enzyme. Concentration of the substrate 
1811  should be at or below its Km for the reaction. 
  57   
Table 4: Examples of probe substrates for CYP enzymes (in vitro studies) 
1812 
 
 
CYP Enzyme  Probe substrate  Marker reaction 
 
  CYP1A2  Phenacetin  Phenacetin O-deethylation 
  7-Ethoxyresorufin  7-Ethoxyresorufin-O-deethylation 
  CYP2B6  Bupropion  Bupropion hydroxylation 
  Efavirenz  Efavirenz hydroxylation 
  CYP2C8  Paclitaxel  Paclitaxel 6-hydroxylation 
  Amodiaquine  Amodiaquine N-deethylation 
 
CYP2C9  S-warfarin  S-warfarin 7-hydroxylation 
 
Diclofenac  Diclofenac 4-hydroxylation 
 
CYP2C19  S-Mephenytoin  S-Mephenytoin 4-hydroxylation 
 
CYP2D6  Bufuralol  Bufuralol 1-hydroxylation 
 
Dextromethorphan  Dextromethorphan O-demethylation 
 
CYP3A  Midazolam  Midazolam 1-hydroxylation 
 
(recommend using  Testosterone  Testosterone 6-hydroxylation 
 
two structurally 
 
different substrates) 
 
   
  1813    7.4.1.2 CYP Enzymes Perpetrators for In Vitro Studies 
 
 
1814    The enzyme inhibitors and inducers are used to phenotype individual CYP enzymes involved in 
 
 
1815  the drug candidate metabolism in vitro. In general, the inhibitors/inducers should be selective at 
 
 
  1816    the concentration used. The following tables are provided to help sponsors design in vitro studies 
  1817    and to evaluate the interaction potential (Tables 5-7). These tables are not exhaustive, and sponsors 
  1818    can use other inhibitors/inducers with appropriate justification. 
 
 
 
  1819    Table 5: Examples of inhibitors for CYP enzymes (in vitro studies) 
 
   
 
CYP Enzyme  Inhibitor 
 
CYP1A2  -Naphthoflavone, Furafylline* 
 
CYP2B6  Clopidogrel*, Ticlopidine*, Thiotepa* 
 
  CYP2C8  Gemfibrozil glucuronide*, Montelukast, Phenelzine* 
 
CYP2C9  Sulfaphenazole, Tienilic acid* 
 
CYP2C19  Loratadine, Ticlopidine* 
 
  CYP2D6  Paroxetine*, Quinidine 
 
CYP3A  Azamulin*, Itraconazole, Ketoconazole, Troleandomycin* 
 
* Designated as time dependent inhibitor. When used, those inhibitors should be pre-incubated with the 
1820 
experimental system. 
1821 
  58   
Table 6: The turnover rate constant (K ) and half-life (t ) of major CYP enzymes to aid 
1822  deg 1/2
in the assessment of time-dependent inhibition 
1823 
 
 
Enzymes (hepatic)  t1/2 (hr)  Kdeg (/min) 
 
CYP1A2 (79)  38  0.00030 
 
  CYP2B (80)  32  0.00036 
  CYP2C8 (81)  22  0.00053 
 
CYP2C9 (80)  104  0.00011 
 
CYP2C19 (80)  26  0.00044 
 
  CYP2D6 (82, 83)  51  0.00023 
 
CYP3A4 (10)  36  0.00032 
 
CYP3A4 (intestinal) (84, 85)  24  0.00048 
 
   
Table 7: Examples of inducers for CYP enzymes (In Vitro Studies) 
1824 
 
 
CYP Enzyme  Inducer 
 
CYP1A2  Omeprazole 
 
CYP2B6  Phenobarbital 
 
CYP2C8  Rifampicin 
 
  CYP2C9  Rifampicin 
  CYP2C19  Rifampicin 
  CYP3A4  Rifampicin 
   
7.4.2 UGTs 
1825 
 
1826  7.4.2.1 UGT Substrates for In Vitro Studies 
1827  The list provided in Table 8 is not exhaustive, and sponsors can use other substrates with 
1828  appropriate justification. 
1829  Table 8: Examples of substrates for UGTs (In Vitro Studies) 
 
UGT enzyme  Substrate 
UGT1A1  -Estradiol, PF-06409577 
UGT1A3  Telmisartan 
UGT1A4  Trifluoperazine, 1'-Hydroxymidazolam 
UGT1A6  Deferiprone, 5-Hydroxytryptophol, Serotonin 
UGT1A9  Mycophenolic acid, Propofol 
UGT2B7  Morphine, Zidovudine 
UGT2B10  Cotinine, RO5263397 
  59   
UGT2B15  S-Oxazepam 
UGT2B17  Testosterone 
60 
   
1830  7.4.2.2 UGT Inhibitors for In Vitro Studies 
1831  There is a lack of relatively selective inhibitors for UGT1A3, UGT1A6, UGT2B7, and UGT2B15. 
1832  In the absence of selective inhibitors, a combination of methods including use of recombinant UGT 
1833  isoform, HLM expressing polymorphic variants of UGT isoform (where appropriate), the relative 
1834  activity factor (RAF) or relative expression factor (REF) approach, and activity correlation 
1835  approach can be employed. Comparative studies with multiple inhibitors can also help assess the 
1836  involvement of a particular isoform. When using individual recombinant enzyme preparations, the 
1837  difference in the amount and enzyme activity of UGTs between the recombinant enzyme systems 
1838  and the human liver should be considered. 
1839  The list provided in Table 9 is not exhaustive, and sponsors can use other inhibitors with 
1840  appropriate justification. 
1841  Table 9: Examples of inhibitors for UGTs (In Vitro Studies) 
 
UGT enzyme  Inhibitor 
UGT1A1  Nilotinib, Regorafenib 
UGT1A3  - 
UGT1A4  Hecogenin 
UGT1A6  - 
UGT1A9  Magnolol, Niflumic acid 
UGT2B7  16- and 16-Phenyllongifolol*, fluconazole** 
UGT2B10  Desloratadine 
UGT2B15  - 
UGT2B17  Imatinib 
  1842  *16- and 16-Phenyllongifolol also inhibit UGT2B4. Their effects on UGT2B10 remains unknown.   
1843  ** Fluconazole also inhibits UGT2B10 and UGT2B17.   
 
1844  7.4.3 Transporters 
1845  Some substrates are not specific for an individual transporter. When an experimental  system 
1846  expressing multiple transporters is used, a more specific substrate is preferred. The following tables 
1847  provide examples of transporter substrate and inhibitors for in vitro studies (Tables 10 and 11). 
  61   
Table 10: Examples of substrates for transporters (In Vitro Studies) 
1848 
 
 
Transporter  Substrate 
 
  P-gp  Digoxin, N-methyl-quinidine (NMQ), Quinidine, Vinblastine 
  BCRP  Estrone-3-sulfate, 2-amino-1-methyl-6-phenylimidazo[4,5- 
  b]pyridine (PhIP), Prazosin, Rosuvastatin, Sulfasalazine 
 
OATP1B1, OATP1B3  Cholecystokinin octapeptide (CCK-8, selective for 
 
OATP1B3), Estradiol-17-glucuronide, Pitavastatin, 
 
Pravastatin, Rosuvastatin 
 
OAT1  Adefovir, Cidofovir, p-aminohippurate (PAH), Tenofovir 
 
  OAT3  Benzylpenicillin, Estrone-3-sulfate, Methotrexate 
  MATE1, MATE2-K  Creatinine, Metformin, 1-methyl-4-phenylpyridinium 
  (MPP+), Tetraethylammonium (TEA) 
 
OCT2  Creatinine, Metformin, Tetraethylammonium (TEA) 
 
1849 
Table 11: Examples of inhibitors for transporters (In Vitro Studies) 
1850 
 
Transporter  Inhibitor 
P-gp  GF120918 (dual P-gp/BCRP inhibitor), Verapamil, Valspodar 
(PSC833), Zosuquidar (LY335979) 
BCRP  Fumitremorgin C, GF120918 (dual P-gp/BCRP inhibitor), 
Ko143, Novobiocin 
OATP1B1, OATP1B3  Bromosulfophthalein (BSP), Cyclosporine, Rifampin, 
Rifamycin SV 
OAT1, OAT3  Benzylpenicillin*, Probenecid 
MATE1, MATE2-K  Cimetidine, Pyrimethamine, Quinidine 
OCT2  Cimetidine, Clonidine 
1851  * Relatively selective inhibitor for OAT3. 
1852  7.5 List of Drugs that can be used in Clinical Studies 
1853  7.5.1 CYPs Enzymes 
1854  7.5.1.1 CYP Enzyme Substrates for Clinical Studies 
1855  Ideally, drugs selections should be based on sensitivity, specificity, safety profiles, and reported 
1856  clinical DDI studies with inhibitors, as well as an absence of studies that indicate the drug does 
1857  not meet the criteria. 
1858    Index  substrates  predictably  exhibit  exposure  increase  due  to  inhibition  of  a  given 
1859  metabolic pathway and results are available from prospective clinical DDI studies. These 
1860  drugs  can  be  safely  administered  with  potential  inhibitors,  sometimes  with  a  dose 
  62   
1861  reduction. 
63 
   
1862    Sensitive index substrates are index drugs that demonstrate an increase in AUC of 5-fold 
1863  with strong index inhibitors of a given metabolic pathway in clinical DDI studies. 
1864    Moderately sensitive substrates are drug that demonstrate an increase in AUC of 2- to <5- 
1865  fold with strong index inhibitors of a given metabolic pathway in clinical DDI studies. 
1866  Sponsors are encouraged to consider the unique characteristics of each drug when designing DDI 
1867  studies. For example, a drug could be a substrate for multiple CYPs or a CYP plus a transporter. 
1868  In such a case, the selection of an index drug for a study should take into consideration the 
1869  knowledge about the potential perpetrator (enzymes and/or transporters which it could inhibit). 
1870  The drugs listed in Table 12 below have been identified as appropriate index substrates for clinical 
1871  DDI studies. Other drugs can be proposed, considering the criteria above. 
1872  Table 12: Examples of index substrates for CYP enzymes (Clinical studies) 
 
CYP Enzyme  Sensitive  index  substrate  Comments 
(unless otherwise noted) 
CYP1A2  Caffeine   
CYP2B6  Bupropion  Bupropion is metabolized by CYP2B6 
and non-CYP enzymes. Thus, by itself 
is not a sensitive substrate. 
Hydroxybupropion should also be 
measured, since it is primarily formed 
by CYP2B6. Hydroxybupropion 
concentration changes should be 
considered when determining clinical 
significance, since it is the major 
active moiety. 
CYP2C8  Repaglinide  Also metabolized by CYP3A though 
to a lesser extent. Transported by 
OATP1B1. 
CYP2C9  S-warfarin, Flurbiprofen  Moderately sensitive substrate 
CYP2C19  Omeprazole  Also metabolized by CYP3A though 
to a lesser extent. Measurement of 
metabolite concentrations should be 
considered when there are multiple 
interacting mechanisms involved. 
CYP2D6  Desipramine,   
Dextromethorphan, Nebivolol 
CYP3A  Midazolam, Triazolam   
 
1873  7.5.1.2 CYP Enzyme Inhibitors for Clinical Studies 
  64   
1874  Index inhibitors predictably inhibit metabolism via a given pathway, and results are available from 
1875  prospective clinical DDI studies. Strong and moderate inhibitors are drugs that increase the AUC 
1876  of sensitive index substrates of a given metabolic pathway 5-fold and 2- to <5-fold, respectively. 
1877  Ideally, index inhibitors should be selected based on potency and selectivity of inhibition, safety 
1878  profiles, availability of reported clinical DDI studies with different in vivo substrates, as well as 
1879  an absence of studies that indicate the drug does not meet the criteria. 
1880  Sponsors are encouraged to consider the unique characteristics of each drug when designing DDI 
1881  studies.  For example, a drug could inhibit multiple CYPs or a CYP plus a transporter. Sponsors 
1882  should select an index inhibitor for a study based on knowledge about the potential CYPs and 
1883  transporters involved with the substrates disposition. 
1884  The drugs listed in Table 13 below have been identified as appropriate index inhibitors for clinical 
1885  DDI studies. Other drugs can be proposed, considering the criteria described above. 
1886  Table 13: Examples of index inhibitors for CYP enzymes (Clinical Studies) 
 
 
CYP Enzyme  Strong index inhibitors  Comments 
CYP1A2  Fluvoxamine  Also strong inhibitor of CYP2C19; moderate 
inhibitor of CYP3A; weak inhibitors of 
CYP2C9 and CYP2D6. 
CYP2B6    Ticlopidine can be used as a CYP2B6 
inhibitor. It decreases hydroxybupropion 
formation by more than 80%. 
CYP2C8  Gemfibrozil  Also inhibits OATP1B1 and OAT3. 
CYP2C9  Fluconazole (moderate  Also strong inhibitor of CYP2C19; moderate 
inhibitor)  inhibitor CYP3A. 
CYP2C19  Fluvoxamine  Fluvoxamine: Also strong inhibitor of 
Fluconazole  CYP1A2; moderate inhibitor of CYP3A; weak 
inhibitor of CYP2C9 and CYP2D6 
Fluconazole: Also moderate inhibitor of 
CYP2C9 and CYP3A. 
CYP2D6  Fluoxetine  Fluoxetine: Also strong inhibitor of CYP 
Paroxetine  2C19. 
CYP3A  Clarithromycin  Clarithromycin and itraconazole both inhibit P- 
Itraconazole  gp. 
 
1887  7.5.1.3 CYP Enzyme Inducers for Clinical Studies 
1888  Inducers in Table 14 below were selected based on potency of induction, safety profiles, and 
1889  availability of clinical DDI studies with different clinical substrates. Due to the mechanisms of 
1890  induction, inducers usually regulate the expression of multiple enzymes and transporters. 
1891  Strong and moderate inducers decrease the AUC of sensitive index substrates of a given metabolic 
1892  pathway by 80% and 50% to <80%, respectively. 
  65   
Table 14: Examples of inducers for CYP enzymes (Clinical Studies) - the list is not exhaustive 
1893 
and other inducers can be used 
1894 
 
1895 
CYP Enzyme  Strong inducers  Moderate inducers 
 
  CYP1A2*    Phenytoin, Rifampin, Smoking 
  CYP2B6  Carbamazepine  Rifampin, Efavirenz 
  CYP2C8    Rifampin 
 
CYP2C9    Rifampin 
 
CYP2C19  Rifampin   
 
CYP3A  Carbamazepine, Phenytoin,  Efavirenz 
 
Rifampin, 
 
  1896    *CYP1A2: Phenytoin, rifampin, and cigarette smoking are weak-to-moderate inducers based on limited number of 
  1897    clinical DDI studies conducted with caffeine, tizanidine, and theophylline. 
 
 
1898    7.5.2 UGTs 
 
 
  1899    UGT substrates and perpetrators that are useful for clinical DDI studies are listed below (Tables 
  1900    15-17). These lists are not exhaustive, other substrates/perpetrators can be used with appropriate 
   
1901  justifications. 
   
 
  1902  Table 15: Examples of substrates for UGTs (Clinical Studies) 
 
 
   
  UGT enzyme  Substrates 
  UGT1A1  Bictegravir, Cabotegravir, Dolutegravir, SN-38 (active 
  metabolite of irinotecan) 
  UGT1A4  Lamotrigine (also by UGT2B7), Pexidartinib 
  UGT1A9  Canagliflozin, Dapagliflozin, Ertugliflozin 
  UGT2B7  Bempedoic acid, Indomethacin, Naproxen, Zidovudine 
 
UGT2B15  Lorazepam, Oxazepam 
 
 
1903 
Table 16: Examples of inhibitors for UGTs (Clinical Studies) 
1904 
 
 
UGT enzyme  Inhibitors 
 
UGT1A1  Atazanavir* 
 
UGT1A4  Probenecid**, Valproic acid (also inhibit UGT2B7) 
 
UGT1A9  Mefenamic Acid 
 
UGT2B7  Probenecid 
 
UGT2B15  Probenecid 
 
* Atazanavir is also an inhibitor of CYP3A. 
1905 
** Probenecid is an inhibitor of OAT1 and OAT3 transporters. 
1906 
  66   
Table 17: Examples of inducers for UGT (Clinical Studies) 
1907 
 
UGT enzyme  Inducers 
UGT1A1  Carbamazepine, Efavirenz, Phenobarbital, Rifampin, St. Johns 
wort, Tipranavir combined with ritonavir 
UGT1A4  Carbamazepine, Lopinavir combined with ritonavir, 
Phenobarbital, Phenytoin, Rifampin 
UGT1A9  Rifampin 
UGT2B7  Rifampin 
UGT2B15  Rifampin, Phenytoin 
 
1908  7.5.3 Transporters 
1909  7.5.3.1 Transporter Substrates for Clinical Studies 
1910  Transporter substrates that are useful for clinical DDI studies are listed in Table 18 below. Many 
1911  of them are substrates of multiple transporters and/or enzymes. Thus, the extrapolation of results 
1912  from these studies to other drugs can be challenging and as indicated earlier (refer to main text), 
1913  index substrates are not available for transporters. Interpretation of the study results should take 
1914  into consideration the knowledge of the transporter inhibition properties for the investigational 
1915  drug as well as its effect on metabolic enzymes. It is most useful to select a transporter substrate 
1916  that is likely to be administered in the intended patient population for the investigational drug. 
1917  The listed substrates exhibit markedly altered PK profiles following co-administration of known 
1918  inhibitors of the transporter, meeting the criteria below. In addition, they are generally safe for use 
1919  in clinical DDI studies. 
1920  Criteria 
1921  The criteria below were used to select recommended transporter substrates for use in DDI studies 
1922  to characterize a drugs transporter inhibition properties. Results from studies conducted with 
1923  clinically relevant doses were used for selection of drugs. When possible, drugs most relevant for 
1924  global drug development programs were selected. 
1925    P-gp:  (1)  AUC  fold-increase  2  with  itraconazole,  quinidine,  or  verapamil  co- 
1926  administration, (2) in vitro transport by P-gp expression systems, and (3) not extensively 
1927  metabolized in vivo. 
1928    BCRP: (1) AUC fold-increase 2 with pharmacogenetic alteration of ABCG2 (421C>A) 
1929  and (2) in vitro transport by BCRP expression systems. 
1930    OATP1B1/OATP1B3:  (1)  AUC  fold-increase  2  with  rifampin  (single  dose)  or 
1931  cyclosporine co-administration, or pharmacogenetic alteration of SLCO1B1 (521T>C) and 
1932  (2) in vitro transport by OATP1B1 or OATP1B3 expression systems. 
1933    OAT1/OAT3: (1) AUC fold-increase 2 with probenecid co-administration, (2) fraction 
1934  excreted into urine as an unchanged drug 0.5, and (3) in vitro transport by OAT1 and/or 
  67   
1935  OAT3 expression systems. 
68 
   
1936    OCT2/MATEs: (1) AUC fold-increase 2 with dolutegravir or pyrimethamine; (2) fraction 
1937  excreted into urine as an unchanged drug 0.5, and (3) in vitro transport by OCT2 and/or 
1938  MATEs expression system. 
1939  Note: The list is not exhaustive and sponsors can use substrates that are not listed in the table if 
1940  the drugs transport properties are well understood and similar to the criteria above. 
1941  Table 18: Examples of substrates for transporters (Clinical Studies) 
 
Transporter  Substrates  Comments* 
P-gp  Dabigatran etexilate  Dabigatran etexilate**  only affected by 
Digoxin  intestinal P-gp. 
Fexofenadine  Fexofenadine  also substrate for OATP1B1, 
1B3 and 2B1. 
BCRP  Rosuvastatin  Rosuvastatin  also a substrate for OATP1B1, 
Sulfasalazine  1B3, 2B1, and OAT3. 
Sulfasalazine  only affected by intestinal 
BCRP. 
OATP1B1,  Atorvastatin  Atorvastatin  also a substrate of BCRP, P-gp, 
OATP1B3  Bosentan  and CYP3A. 
Pitavastatin  Pravastatin  also a substrate of MRP2 and 
Pravastatin  OAT3. 
Rosuvastatin  Rosuvastatin  also a substrate for BCRP, 
Simvastatin acid  OAT3, and OATP2B1. 
Simvastatin  also a substrate of CYP3A. 
OAT1  Adefovir  Adefovir  Higher contribution of OAT1 than 
OAT3  Baricitinib  OAT3. 
Cefaclor  Baricitinib, cefaclor and Penicillin G  Higher 
Furosemide  contribution of OAT3 than OAT1. 
Oseltamivir carboxylate  Furosemide  dual substrate of OAT1/OAT3 
is also a substrate of BCRP, OATP2B1, and 
UGT. 
MATE1, MATE2-  Metformin   
K, OCT2 
  1942  *Due to the evolving nature of the understanding, some of the drugs listed in the table could be substrates of other 
1943  transporters that are not listed here. 
1944  **. Dabigatran etexilate is a pro-drug and converted by carboxylesterase (CES) to dabigatran which is the measured 
1945  moiety (dabigatran is not a substrate of P-gp). Thus, for correct interpretation of clinical DDI results, preassessment 
1946  of the inhibitory effects of an investigational drug on CES activity should be considered. 
1947  ***. Adefovir is the active moiety of its pro-drug, adefovir dipivoxil, which is a substrate of P-gp. 
1948  7.5.3.2. Transporter Inhibitors for Clinical Studies 
1949  Transporter inhibitors that are useful for clinical DDI studies are listed in Table 19 below. Many 
1950  of them not only inhibit the specified transporters but also inhibit some other transporters and/or 
1951  CYP enzymes. Thus, extrapolation of results from these studies to other drugs can be challenging 
1952  as indicated  earlier (refer to main text), index inhibitors are not available for transporters. 
  69   
1953  Interpretation of the study results should take into consideration the knowledge of transport and 
1954  metabolic/elimination pathways for the investigational drug. It is most useful to select a transporter 
1955  inhibitor that is likely to be administered in the intended patient population for the investigational 
1956  drug. 
1957  The listed inhibitors lead to markedly altered PK profiles of known substrates of the transporter 
1958  following co-administration, meeting the criteria below. In addition, they are generally safe for use 
1959  in clinical DDI studies. 
1960  Criteria 
1961  The criteria below were used to select recommended transporter inhibitors for use in DDI studies 
1962  to characterize a drugs properties as a transporter substrate. Results from studies conducted with 
1963  clinically relevant doses were used for selection of drugs. When possible, drugs most relevant for 
1964  global drug development programs were selected. 
1965    P-gp: (1)  AUC fold-increase of digoxin, dabigatran, or fexofenadine 2 with co- 
1966  administration and (2) in vitro inhibitor. 
1967    BCRP: (1) AUC fold-increase of rosuvastatin 2 or close to 2-fold with co-administration 
1968  and (2) in vitro inhibitor. 
1969    OATP1B1/OATP1B3: (1) AUC fold-increase 2 for at least one of the clinical substrates 
1970  with co-administration and (2) in vitro inhibitor. 
1971    OAT1/OAT3: (1) AUC fold-increase 2 for at least one of clinical the substrates with co- 
1972  administration and (2) in vitro inhibitor. 
1973    OCT2/MATE: (1) AUC fold-increase of metformin  2 with co-administration and (2) in 
1974  vitro inhibitor. 
1975  Note: The list is not exhaustive and sponsors can use inhibitors that are not listed in the table if the 
1976  drugs transporter inhibition properties are well understood and similar to the criteria above. 
1977  Table 19: Examples of inhibitors for transporters (Clinical Studies) 
 
Transporter  Inhibitor  Comments 
P-gp  Itraconazole  Itraconazole  also inhibits BCRP and CYP3A 
Quinidine  Verapamil  also inhibit CYP3A 
Verapamil 
BCRP  Cyclosporine  Cyclosporine  also inhibits OATP1B1, 1B3, 
Darolutamide  MRP2, and P-gp. 
Fostamatinib  Fostamatinib  also inhibits P-gp 
OATP1B1,  Rifampin (single dose)  Rifampin  also inhibits P-gp 
OATP1B3  Cyclosporine  Cyclosporine  also inhibits MRP2, P-gp and 
BCRP 
OAT1, OAT3  Probenecid  Probenecid  also inhibits OATP1B1. 
  70   
MATE1, MATE2-  Dolutegravir  Dolutegravir  a relatively specific inhibitor for 
K, OCT2  Pyrimethamine  OCT2 
Pyrimethamine  a relatively specific inhibitor 
of MATEs. 
   1978   
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