Master Protocols for 
Drug and Biological 
Product Development 
Guidance for Industry 
 
 
 
DRAFT GUIDANCE 
 
  This guidance document is being distributed for comment purposes only. 
 
Comments and suggestions regarding this draft document should be submitted within 60 days of 
publication in the Federal Register of the notice announcing the availability of the draft 
guidance. Submit electronic comments to https://www.regulations.gov. Submit written 
comments to the Dockets Management Staff (HFA-305), Food and Drug Administration, 5630 
Fishers Lane, Rm. 1061, Rockville, MD 20852. All comments should be identified with the 
docket number listed in the notice of availability that publishes in the Federal Register. 
 
For questions regarding this draft document, contact (CDER) Scott N. Goldie at 301-796-2055, 
or (CBER) Office of Communication, Outreach and Development, 800-835-4709 or 240-402-
8010.  
 
 
U.S. Department of Health and Human Services 
Food and Drug Administration 
Center for Drug Evaluation and Research (CDER) 
Center for Biologics Evaluation and Research (CBER) 
 
December 2023 
Biostatistics / Clinical / Medical 
 
   
Master Protocols for 
Drug and Biological 
Product Development 
Guidance for Industry 
 
Additional copies are available from: 
Office of Communications, Division of Drug Information  
Center for Drug Evaluation and Research 
Food and Drug Administration 
10001 New Hampshire Ave., Hillandale Bldg., 4th Floor  
Silver Spring, MD 20993-0002  
Phone: 855-543-3784 or 301-796-3400; Fax: 301-431-6353 
Email: druginfo@fda.hhs.gov  
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and/or 
Office of Communication, Outreach and Development  
Center for Biologics Evaluation and Research 
 Food and Drug Administration 
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Phone: 800-835-4709 or 240-402-8010 
Email: ocod@fda.hhs.gov 
https://www.fda.gov/vaccines-blood-biologics/guidance-compliance-regulatory-information-biologics/biologics-guidances   
 
U.S. Department of Health and Human Services 
Food and Drug Administration 
Center for Drug Evaluation and Research (CDER) 
Center for Biologics Evaluation and Research (CBER) 
 
December 2023 
Biostatistics / Clinical / Medical 
 
  Contains Nonbinding Recommendations 
Draft  Not for Implementation 
TABLE OF CONTENTS 
 
 
 
I.  INTRODUCTION............................................................................................................. 1 
II.  BACKGROUND ............................................................................................................... 3 
III.  CONSIDERATIONS ON DESIGN AND ANALYSIS .................................................. 3 
A.  Randomization ............................................................................................................................... 4 
B.  Control Group ................................................................................................................................ 5 
C.  Informed Consent .......................................................................................................................... 7 
D.  Blinding to Treatment Assignment .............................................................................................. 8 
E.  Adaptive Design ............................................................................................................................. 9 
F.  Multiplicity ..................................................................................................................................... 9 
G.  Comparisons Between Drugs ...................................................................................................... 11 
H.  Safety ............................................................................................................................................. 11 
IV.  CONSIDERATIONS ON TRIAL OVERSIGHT, DATA SHARING, AND 
DISSEMINATION OF INFORMATION ................................................................................ 12 
V.  CONSIDERATIONS TO SUPPORT REGULATORY REVIEW ............................ 13 
A.  General Investigational New Drug Considerations .................................................................. 13 
B.  IND Cross-Referencing ............................................................................................................... 15 
C.  Protocol Amendments ................................................................................................................. 15 
D.  Communications and Safety Reporting ..................................................................................... 16 
VII.   REFERENCES ................................................................................................................ 17 
VI.  APPENDIX ...................................................................................................................... 18 
A.  Optimal Allocation Ratio ............................................................................................................ 18 
B.  Examples of Randomization Strategies for Partially-Blinded, Placebo-Controlled Studies . 18 
C.  Example of How to Use eCTD for a Master Protocol ............................................................... 21 
  Contains Nonbinding Recommendations 
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Master Protocols for Drug and Biological Product Development 
1 
Guidance for Industry1 
2 
3   
4   
5  This draft guidance, when finalized, will represent the current thinking of the Food and Drug 
6  Administration (FDA or Agency) on this topic. It does not establish any rights for any person and is not 
7  binding on FDA or the public. You can use an alternative approach if it satisfies the requirements of the 
8  applicable statutes and regulations. To discuss an alternative approach, contact the FDA staff responsible 
9  for this guidance as listed on the title page.  
10   
11   
12   
13   
14  I.  INTRODUCTION  
15   
16  This guidance document provides recommendations on the design and analysis of trials 
17  conducted under a master protocol as well as guidance on the submission of documentation to 
18  support regulatory review.2  
19   
20  For the purpose of this guidance, FDA defines the following terms: 
21   
22    Master protocol: a protocol designed with multiple substudies, which may have different 
23  objectives and involve coordinated efforts to evaluate one or more medical products in 
24  one or more diseases or conditions within the overall study structure.   
25   
26    Substudy: the information and design features (e.g., objectives, design, methodology, 
27  statistical considerations) related to evaluation of a single medical product in a single 
28  disease, condition, or disease subtype in the master protocol.  
29   
30  Examples of trial types that could utilize a master protocol include the following: 
31   
32    Umbrella trial: a trial designed to evaluate multiple medical products concurrently for a 
33  single disease or condition.  
34   
35    Platform trial: a trial designed to evaluate multiple medical products for a disease or 
36  condition in an ongoing manner, with medical products entering or leaving the platform. 
37   
 
1 This guidance has been prepared by the Office of Biostatistics and the Office of New Drugs in the Center for Drug 
Evaluation and Research in cooperation with the Center for Biologics Evaluation and Research at the Food and Drug 
Administration.  
2 FDA is issuing this guidance to satisfy, in part, a mandate under section 3607(b)(2)(C-F) of the Food and Drug 
Omnibus Reform Act of 2022 (FDORA). Consistent with the FDORA mandate, this guidance discusses 
recommendations for clinical trials to streamline logistics and facilitate the efficient collection and analysis of data, 
as well as important principles for the evaluation of effectiveness, recommendations for communication between 
sponsors and the FDA, and considerations related to ensuring participant safety and data integrity in such trials. 
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38    Basket trial: a trial designed to evaluate a medical product for multiple diseases, 
39  conditions, or disease subtypes.  
40   
41  For the purpose of this guidance, the term master protocol sponsor refers to the person or 
42  organization who takes responsibility for and initiates the master protocol.3 In many instances 
43  individual drugs chosen for evaluation in the master protocol will also be evaluated under 
44  separate Investigational New Drug Applications (INDs) independent of the master protocol. A 
45  sponsor responsible for the investigation of an individual drug evaluated under the separate IND 
46  is referred to as the individual drug sponsor. The master protocol sponsor and the individual drug 
47  sponsor may or may not be the same entity. This guidance uses the term sponsor when providing 
48  general recommendations that may be relevant to both the master protocol sponsor and 
49  individual drug sponsors.   
50   
51  The primary focus of this guidance is on randomized umbrella and platform trials that are 
52  intended to contribute to a demonstration of safety and substantial evidence of effectiveness of a 
53  drug.4 The concepts discussed may also be useful to consider for early-phase or exploratory 
54  umbrella and platform trials as well as those conducted to satisfy post-marketing commitments 
55  or requirements. The recommendations and considerations in this guidance do not apply to 
56  master protocols evaluating first-in-human drugs given the unique attributes from both a trial 
57  design and regulatory perspective that must be considered.5 
58   
59  The considerations in this guidance apply to a range of therapeutic areas.6 Sponsors considering 
60  master protocols in oncology should also consult Master Protocols: Efficient Clinical Trial 
61  Design Strategies To Expedite Development of Oncology Drugs and Biologics (March 2022).7 
62  Sponsors evaluating cellular and gene therapy products in early-phase development should 
63  consult the guidance for industry Studying Multiple Versions of Cellular or Gene Therapy 
64  Product in Early-Phase Clinical Trials (November 2022). 
65   
66  In general, FDAs guidance documents do not establish legally enforceable responsibilities. 
67  Instead, guidances describe the Agencys current thinking on a topic and should be viewed only 
68  as recommendations, unless specific regulatory or statutory requirements are cited. The use of 
 
3 See 21 CFR 312.3. 
4 For the purposes of this guidance, all references to drugs include both human drugs and biological products unless 
otherwise specified. 
5 This guidance does not address first-in-human expansion cohort studies in oncology as these master protocols 
evaluate drugs in a limited population with serious oncologic disease for which no satisfactory alternative therapies 
are available. For more information on this topic, see the guidance for industry Expansion Cohorts: Use in First-in-
Human Clinical Trials to Expedite Development of Oncology Drugs and Biologics (March 2022). 
6 In May 2021, FDA published the guidance for industry COVID-19: Master Protocols Evaluating Drugs and 
Biological Products for Treatment or Prevention, which focused on master protocols evaluating drugs for the 
treatment or prevention of COVID-19. That guidance was intended to remain in effect only for the duration of the 
public health emergency related to Coronavirus Disease 2019 declared by the Secretary of Health and Human 
Services under section 319 of the Public Health Service Act (section 319 public health emergency), which has now 
expired. FDA is issuing this draft guidance because many of the recommendations set forth in the 2021 guidance are 
applicable outside the context of the section 319 public health emergency and are applicable to other therapeutic 
areas, not just COVID-19. 
7 We update guidances periodically. For the most recent version of a guidance, check the FDA guidance web page at 
https://www.fda.gov/regulatory-information/search-fda-guidance-documents. 
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69  the word should in Agency guidances means that something is suggested or recommended, but 
70  not required.  
71   
72   
73  II.  BACKGROUND  
74   
75  Well-designed and -conducted trials using master protocols can accelerate drug development by 
76  maximizing the amount of information obtained from the research effort. Compared with stand-
77  alone trials under separate protocols, a master protocol may offer certain advantages by 
78  leveraging a shared control arm and other shared protocol elements (e.g., visit schedule, 
79  measurement procedures), shared infrastructure (e.g., recruitment efforts, network of clinical 
80  sites, central facilities, central randomization system, data management systems), and shared 
81  oversight (e.g., steering committee, data review committee). Such advantages may make master 
82  protocols particularly suitable in certain settings. For example, a master protocol may be useful 
83  in settings where subject recruitment is challenging, as comparing multiple drugs to a shared 
84  placebo arm can reduce the number of subjects on placebo relative to multiple trials comparing 
85  each drug to a placebo.  
86   
87  At the same time, master protocols add elements of complexity, which can increase start-up time 
88  and can lead to design challenges such as ensuring adequate blinding to treatment assignment 
89  (see section III.D). Additionally, master protocols involving multiple stakeholders will require a 
90  high degree of coordination. Sponsors should carefully weigh these considerations when 
91  deciding whether a master protocol is appropriate as part of a drug development program.  
92   
93  A master protocol can be used to generate different types of data including proof-of-concept, 
94  dose-ranging, effectiveness, and safety data. Sponsors should consider the role of the master 
95  protocol in the overall drug development program, as this will inform its objectives and design. 
96  For example, the choice of endpoint in a master protocol may differ depending on whether the 
97  objective is to screen multiple products rapidly to determine which ones to carry forward into 
98  later stage trials versus to contribute to a demonstration of substantial evidence of effectiveness. 
99  As with other types of trials, whether the data generated by a trial conducted under a master 
100  protocol will be adequate to contribute to a demonstration of substantial evidence of 
101  effectiveness will depend on the design and conduct of the trial and the persuasiveness of its 
102  results.8 A development program that includes a master protocol will often also include stand-
103  alone trials given the different types of data needed to support drug development.  
104   
105   
106  III.  CONSIDERATIONS ON DESIGN AND ANALYSIS  
107   
108  This section discusses important considerations for the design and analysis of master protocols, 
109  with a focus on randomized umbrella and platform trials that are intended to contribute to a 
110  demonstration of safety and substantial evidence of effectiveness.  
111   
 
8 See the draft guidance for industry Demonstrating Substantial Evidence of Effectiveness for Human Drug and 
Biological Products (December 2019). When final, this guidance will represent the FDAs current thinking on this 
topic. 
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112  A.  Randomization  
113   
114  FDA recommends randomization of subjects to receive one of the drugs being evaluated or a 
115  control to remove systematic imbalances between treatment arms in both measured and 
116  unmeasured prognostic factors and to ensure reliable inference on the safety and effectiveness of 
117  the drugs. Sponsors should consider using a randomization scheme that allocates more subjects 
118  to the control arm than each individual drug arm, as this can increase power for each drug versus 
119  control comparison for a given total sample size (Chandereng et al. 2020 and Appendix: section 
120  A). Note that although the randomization ratio that optimizes power involves greater-than-equal 
121  allocation to the control arm, the probability that an individual subject entering the trial will be 
122  assigned to control is less than in a typical two-arm controlled trial with 1:1 randomization. This 
123  disproportionate randomization also reduces the risk of a poorly or highly performing control 
124  arm leading to multiple correlated erroneous findings (see section III.F).  
125   
126  It is possible for the randomization ratio to change in the setting of a master protocol. This can 
127  occur when products enter or exit a platform trial over time with certain fixed randomization 
128  schemes (i.e., schemes where the randomization ratio does not depend on accumulating covariate 
129  or outcome data from the platform trial). For example, one randomization scheme (see 
130  Appendix: section A) could change the randomization ratio from 2:1:1 (control:drug A:drug 
131  B) to 3:1:1:1 (control:drug A:drug B:drug C) when a third drug, drug C, enters a trial that had 
132  been previously evaluating two drugs, drug A and drug B. If the randomization ratio for a drug 
133  relative to the control changes, the comparisons between the drug and control should account for 
134  time periods of different randomization ratios. Possible approaches are stratifying by the time 
135  period or inverse weighting by probabilities of treatment assignments.   
136   
137  In settings where it is reasonable for a subject to be treated simultaneously with more than one of 
138  the multiple drugs being evaluated under a master protocol, a factorial design could also be 
139  considered. For example, subjects at trial entry could be randomized to drug A or a placebo for 
140  drug A and also randomized to drug B or a placebo for drug B, such that some subjects are 
141  assigned to receive drug A and drug B in combination. This design provides data on drugs used 
142  in combination but would not be appropriate in many circumstances, such as when drugs A and 
143  B are hypothesized to be duplicative, antagonistic, or unsafe when used together. 
144   
145  It may be necessary for master protocols to utilize drug-specific eligibility criteria in some 
146  settings (e.g., with exclusion of subjects with diminished kidney function for a drug with kidney 
147  toxicity). In these situations, protocols and randomization processes should be designed to 
148  prevent subjects from being randomized to drugs they are not eligible to receive, as this would 
149  compromise subject safety and the integrity of the randomized comparison (see additional 
150  discussion in section III.B).  
151   
152   
153   
154   
155   
156   
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157  B.  Control Group  
158   
159  The choice of control group is a critical design element of any trial, including one conducted 
160  under a master protocol.9 This guidance focuses on master protocols that include randomization 
161  to an internal control group in their design, as opposed to use of an external control. While some 
162  of the considerations discussed in this guidance on the use of nonconcurrent control data may 
163  also be relevant for the use of external control data, specific considerations for external controls 
164  in a master protocol are outside the scope of this document.10 
165   
166  One important consideration in platform trials is the composition of the control group for a given 
167  drug. A platform trial allows products to enter and exit in an ongoing manner, such that the 
168  control arm spanning the duration of the trial includes both subjects randomized to the control 
169  who were concurrently enrolled and could have been randomized to a given drug, as well as 
170  subjects nonconcurrently randomized to the control who could not have been randomized to the 
171  given drug. For example, consider a platform trial that initially randomizes subjects to one of two 
172  drugs (drugs A and B) or a shared control. At later calendar times, two additional drugs, drug C 
173  and then drug D, enter the platform. The schematic in Figure 1 illustrates such a hypothetical 
174  platform trial and depicts concurrent and nonconcurrent controls for the evaluation of drug D.  
175   
176  Figure 1: A Schematic to Illustrate Concurrent and Nonconcurrent Control Arm Data for 
177  Evaluating Drug D in a Hypothetical Platform Trial 
178     
179   
180  The control group used for the primary comparison of any given drug in a master protocol should 
181  generally include only concurrently randomized subjects (i.e., a concurrent control) and should 
182  not include nonconcurrently randomized subjects. Use of a concurrent control preserves the 
183  integrity of randomized comparisons and ensures valid inference on the effects of the drug by 
 
9 The control could be placebo or active and could be used for superiority and/or non-inferiority comparisons. 
General considerations about the choice of control, such as those discussed in the ICH guidance for industry E10 
Choice of Control Group and Related Issues in Clinical Trials (May 2001), are outside the scope of this document. 
10 For additional considerations on the use of external controls, see the draft guidance for industry Considerations 
for the Design and Conduct of Externally Controlled Trials for Drug and Biological Products (February 2023). 
When final, this guidance will represent the FDAs current thinking on this topic. 
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184  avoiding systematic differences between groups with respect to both known and unknown factors 
185  that are prognostic of the key outcomes. Systematic differences between a drug and 
186  nonconcurrent control could be caused by temporal shifts in subject characteristics,11 trial 
187  conduct, or standard of care, especially for a long-running platform trial or in a rapidly changing 
188  clinical setting. In the presence of such temporal shifts, use of nonconcurrent control data can 
189  lead to bias in treatment effect estimates and alter the type I and type II error probabilities even if 
190  attempts are made to account for potential trends in the analysis (e.g., Lee and Wason 2020 and 
191  Jiao et al. 2019). Notably, the use of a shared control arm in platform trials leads to considerable 
192  efficiency gains relative to stand-alone trials even if comparisons for a given drug utilize only 
193  concurrent control data.  
194   
195  In addition to including only concurrent control data, it also important to ensure that the primary 
196  analysis for a given drug utilizes only those control arm subjects who underwent randomization 
197  that could have assigned them to that drug. For example, consider the scenario where the master 
198  protocol has some drug-specific eligibility criteria. The control arm used in the comparison for a 
199  drug should include only those subjects who met the drug eligibility criteria and could have been 
200  randomized to the given drug but were instead concurrently randomized to the control arm. 
201  Subjects who were not eligible to receive the drug and were concurrently randomized to the 
202  control should not be included in the analysis.  
203   
204  While use of a concurrent control group is the preferred approach to support the most robust 
205  conclusions, there may be rare circumstances in which sponsors can justify use of nonconcurrent 
206  control data. Use of nonconcurrent control data can increase the precision of inference on the 
207  treatment effect due to the increased number of subjects in the control arm. This may be 
208  particularly relevant in settings where there are different bias-variance tradeoffs, such as early-
209  phase exploratory trials and trials in rare diseases with feasibility constraints, as long as the 
210  approach can be scientifically justified. Sponsors considering the use of nonconcurrent control 
211  data in a platform trial intended to contribute to substantial evidence of effectiveness should 
212  discuss their rationale for such an approach with the Agency early on in their planning. 
213  Information relevant to this discussion include: the feasibility of relying on only concurrent 
214  control data, the likelihood of temporal changes that could affect the treatment comparison; the 
215  amount of nonconcurrent control data to be utilized; the expected separation in calendar time 
216  between randomization of nonconcurrent control subjects and initiation of randomization to the 
217  drug of interest; and statistical methods intended to account for potential temporal changes and 
218  their underlying assumptions.  
219   
220  In those circumstances where use of nonconcurrent control data may be justified, sponsors 
221  should incorporate methods to address potential bias. The decision to use nonconcurrent control 
222  data should be made and agreed upon with FDA prior to the start of the trial as this will avoid a 
223  scenario where a sponsor proposes to utilize nonconcurrent data after seeing desirable results 
224  (e.g., a poorly performing control arm). Additionally, the master protocol should ensure uniform 
225  approaches to trial design and conduct, especially for characteristics likely to affect the outcome 
226  of interest and should specify the collection of known baseline prognostic variables and post-
 
11 There are many reasons why characteristics of subjects entering a trial may change over time. For example, 
subjects entering a trial at the beginning may be more likely to have existing disease and a worse prognosis than 
subjects entering the trial later who may be more likely to have newly diagnosed disease.  
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227  baseline influences on the outcome (e.g., concomitant medications).12 The planned primary 
228  analysis should incorporate approaches to mitigate potential for confounding due to changes in 
229  prognostic factors over time. For example, options may include adjustment for a function of 
230  calendar time and baseline prognostic factors, a dynamic approach for the amount of 
231  nonconcurrent control data borrowing (e.g., with a Bayesian hierarchical model), and/or a 
232  network meta-analysis to combine comparisons between concurrently randomized treatment 
233  arms. The underlying assumptions of the analysis should be described, and the operating 
234  characteristics of the analysis should be evaluated in different settings (e.g., in the presence of 
235  temporal shifts). Additionally, sensitivity analyses should be planned and conducted to 
236  understand the effect of the use of nonconcurrent control data on the evaluation of the treatment 
237  effect. For example, these may include an evaluation of the treatment effect based on only 
238  concurrent control data and/or based on increased weighting of the concurrent control data (and 
239  decreased weighting of the nonconcurrent control data) relative to the primary analysis. 
240   
241  Another situation that sponsors should carefully consider is when it may be appropriate to 
242  incorporate a drug evaluated under the master protocol into the trial either as part of the control 
243  arm or as background therapy. Such a change is complex because it may affect various design 
244  and analysis considerations such as whether the primary comparison for other drugs is to 
245  evaluate superiority or noninferiority, sample size calculations, and considerations around 
246  integrating data before and after the change for drugs with ongoing evaluation at the time of the 
247  change. Therefore, sponsors should seek concurrence from the Agency before implementing any 
248  such changes to the control arm or background therapy. 
249   
250  C.  Informed Consent  
251   
252  The informed consent process should cover all treatment arms in the trial to which the subject 
253  could be randomized.13,14 In a platform trial allowing drugs to enter and leave the trial over time, 
254  the consent form should be modified over time to reflect the drugs currently under evaluation.  
255   
256  The informed consent process should occur prior to a subjects randomization and avoid 
257  substudy-specific consent. Consent that occurs after subjects have been randomized to one of the 
258  substudies may result in subjects with different prognostic characteristics across substudies, 
259  raising concern about the comparability of each drug group with the shared control group 
260  (comprised of control subjects from different substudies). To illustrate the concern, consider a 
261  master protocol with two drugs (drug A and drug B) in which the subject consents to screening 
262  and randomization to a substudy as part of the master protocol, with a substudy-specific 
263  informed consent process to occur after randomization to that substudy; after the substudy-
264  specific consent, the subject is then randomized to the drug or its matched control. With this 
265  process, comparing drug A against the shared control arm (including subjects who received 
266  either control for drug A or control for drug B) may result in noncomparable groups if subjects 
 
12 In addition, sponsors of new drugs that may enter a platform trial should consider the availability of important 
data for previously enrolled (nonconcurrent) control subjects, such as on baseline characteristics used for drug-
specific eligibility criteria.  
13 Some consent processes allow a subject to be randomized in the trial even if the subject only consents to a subset 
of the drugs under evaluation; under such a process, subjects should not have the potential to be randomized to drugs 
for which they do not consent. 
14 See the guidance for IRBs, Clinical Investigators, and Sponsors Informed Consent (August 2023).  
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267  who would consent to participating in the drug A substudy differ from subjects who would 
268  consent to participating in the drug B substudy. 
269   
270  D.  Blinding to Treatment Assignment  
271   
272  The approach to blinding is a critical design element in any clinical trial. A double-blind trial, 
273  where the subjects, investigators, and sponsor staff are unaware of the assigned treatment, is the 
274  optimal approach to avoid bias.15 Ensuring that subjects and investigators are completely blinded 
275  to treatment assignment (i.e., are unaware of both a subjects assigned drug-specific substudy 
276  and whether the subject is receiving a drug or the control) becomes more complex as the number 
277  of drugs with different routes of administration or dosing schedules increases. While different 
278  degrees of blinding can be achieved depending on the blinding strategy, whether the chosen 
279  approach adequately addresses the potential sources of bias is situation-dependent and informed 
280  by several factors such as the trial design choices (e.g., endpoint selection) and the stage of drug 
281  development. Given the unique challenges related to blinding in umbrella and platform trials, 
282  sponsors should discuss their proposed approach with the Agency early in their planning. This 
283  section discusses different blinding strategies and some factors sponsors should consider when 
284  proposing a strategy.  
285   
286  In a placebo-controlled trial, one approach is a multiple-dummy design where subjects are 
287  completely blinded to their assigned treatment arm. For example, in a trial with three drugs, a 
288  subject would receive three placebos or one drug and two placebos. In this design, there is 
289  complete blinding to both the potential study drug the subject could receive (i.e., to the drug-
290  specific substudy) and to whether the subject is receiving an investigational drug or a placebo. A 
291  strategy that achieves complete blinding does the best job of mitigating potential bias.  
292   
293  Another approach is to use a distinct, blinded placebo control for each drug where subjects have 
294  knowledge of their assigned drug-specific substudy but are blinded to whether they are receiving 
295  the given drug or its matched placebo (i.e., partial blinding). In this case, subjects could be first 
296  randomized to one of the drug-specific substudies for which they are eligible and then 
297  randomized to either that drug or its matched placebo (e.g., see Appendix section B.).  
298   
299  In an active-controlled trial, blinding could be implemented through a multiple-dummy approach 
300  to achieve complete blinding or a double-dummy approach for each substudy, if necessary,16 to 
301  achieve partial blinding to whether the subject is receiving the investigational drug or the active 
302  control product. For the partial blinding approach, subjects could be first randomized to a drug-
303  specific substudy (among those they are eligible for) and then randomized to either: (1) that drug 
304  + the placebo for the active control or (2) the matched placebo for the drug + the active control. 
305   
306  As the number of drugs evaluated under the master protocol increases, it may be both appropriate 
307  and more feasible to use a partial blinding strategy. However, if the primary analysis for a drug is 
308  based on a comparison to the shared control group of subjects receiving different matched 
309  controls, it is critical to consider whether this strategy adequately addresses sources of potential 
 
15 See the ICH guidance for industry E9 Statistical Principles for Clinical Trials (September 1998).  
16 A double-dummy would be necessary for drug-specific substudies evaluating a drug that differs from the active 
control in route and/or frequency of administration. 
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310  bias for the main outcomes of interest. This strategy mitigates potential bias due to knowledge of 
311  whether the subject is receiving an investigational drug or the control. However, there is still the 
312  potential for bias if the main outcomes of interest are likely to be affected by different routes 
313  and/or schedules of administration, or by knowledge of the assigned drug-specific substudy. In 
314  trials utilizing a primary analysis with a shared control and partial blinding, a sensitivity analysis 
315  can be performed comparing each drug to only those subjects receiving the matched control. 
316  This analysis preserves the integrity of a randomized, completely blinded comparison but may be 
317  underpowered. 
318   
319  If there is concern about bias with a partial blinding strategy, FDA recommends the use of a 
320  multiple-dummy design to achieve complete blinding or the use of a primary analysis with 
321  comparisons for a given drug based on only its matched control. Another option might be to 
322  restrict the master protocol to only evaluate products with similar routes and schedules of 
323  administration.  
324   
325  A final option is to use an open-label design. Only in rare circumstances can this be justified and 
326  viewed as an adequate and well-controlled trial, for example, if the endpoint is both objective 
327  and unlikely to be influenced by differences in supportive care or subject behavior caused by 
328  knowledge of treatment assignment and if blinding is highly impractical. Sponsors should 
329  consult with FDA before considering this approach.  
330   
331  E.  Adaptive Design  
332   
333  Master protocols often include adaptive design elements, such as interim analyses to potentially 
334  stop enrollment in a substudy of a drug due to efficacy or futility, to modify the sample size, 
335  and/or to modify the randomization ratio. The important principles discussed in the guidance for 
336  industry Adaptive Designs for Clinical Trials of Drugs and Biologics (November 2019) are 
337  generally applicable to adaptive designs for master protocols. However, incorporating adaptive 
338  design elements into a master protocol can present some unique challenges. For example, 
339  consider an umbrella or platform trial with an interim analysis based on blinded pooled data to 
340  re-estimate the sample size needed to ensure adequate power to detect an effect. Conducting the 
341  analysis separately for each drug-specific substudy based on pooled data across that drug and the 
342  shared control arm may result in dissemination of information about the comparative efficacy of 
343  the drugs, particularly if the drugs entered the trial around the same time (see section IV.). In 
344  contrast, conducting the analysis based on pooled data across all the drug arms and the control 
345  arm would better protect confidentiality of interim results, but this approach may provide less 
346  accurate estimates of the sample size needed to ensure adequate power for the evaluation of each 
347  drug.  
348   
349  F.  Multiplicity  
350   
351  Master protocols have multiple comparisons involving the primary endpoint; however, FDA 
352  generally does not recommend the use of multiplicity adjustments to strongly control the 
353  probability of making at least one type I error across the multiple comparisons of different drugs 
354  to the control in an umbrella or platform trial. Such comparisons of different drugs to the control 
355  are aligned with distinct clinical objectives that would typically be evaluated in multiple 
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356  independent clinical trials without adjustments for multiplicity across the trials. Furthermore, 
357  while the probability distribution for the number of type I errors17 differs depending on whether 
358  multiple drugs are evaluated in independent trials or in a single trial (i.e., a platform or umbrella 
359  trial) with a shared control group (Proschan and Follmann 1995), the expected total number of 
360  type I errors is the same in the two scenarios due to the linearity of expectation.18 Additionally, 
361  due to the correlation between hypothesis test statistics for different drugs in a platform or 
362  umbrella trial, the overall probability of committing at least one type I error is lower than when 
363  there are separate comparisons in independent trials. However, that same correlation can lead to 
364  an increased chance of multiple type I errors (e.g., Howard et al. 2018). Therefore, the 
365  probability distribution for the number of type I errors should be considered both in evaluating a 
366  proposed design and analysis plan and in evaluating the persuasiveness of results. For example, 
367  as noted in section III.A, use of a randomization ratio other than equal allocation to have a 
368  greater proportion of subjects in the control group may be considered to reduce the chance of 
369  multiple correlated erroneous findings (and to optimize power).  
370   
371  There may be some exceptions where there are different recommendations related to handling 
372  multiplicity, in particular, when multiple products being evaluated under the umbrella or 
373  platform trial are very closely related. For example, it is generally important to control the type I 
374  error probability across the evaluation of multiple doses, administrations, or formulations of the 
375  same drug, as such comparisons represent closely related questions about the same molecular 
376  entity. Evaluations of fixed-combination drug products also may have unique considerations, 
377  such as an expectation that the trial demonstrates contributions of each of the components to 
378  satisfy FDA regulations on fixed-combination prescription drugs for humans.19  
379   
380  In addition, while FDA does not generally recommend controlling for multiplicity across 
381  comparisons of different drugs to the control, it is important to control the familywise type I 
382  error probability for each individual drug across other sources of multiplicity (e.g., multiple 
383  endpoints), just as in trials that are not umbrella or platform trials.20 There are also other 
384  important factors (e.g., the clinical relevance of the endpoint and estimated treatment effect, the 
385  quality of design and conduct, the magnitude of the p-value, and information from relevant 
386  external studies) in evaluating the evidence of effectiveness of a drug beyond the results of 
387  hypothesis testing in a single trial (e.g., a substudy of an umbrella or platform trial).21 
388   
 
17 Consider an example setting in which three drugs are being evaluated. Under the global null hypothesis that all 
three drugs are ineffective, the analyses of the trial(s) conducted could lead to false conclusions of efficacy for none 
of the drugs, one drug, two drugs, or all three drugs (i.e., could lead to zero, one, two, or three type I errors). The 
probability distribution for the number of type I errors refers to the probabilities of each of these outcomes.  
18 The linearity of expectation is the property that the expected value of the sum of random variables is equal to the 
sum of their individual expected values, regardless of whether the random variables are independent or dependent. 
Given this property, for any point in the null hypothesis (i.e., the global null scenario where all drugs are ineffective 
or a scenario where some drug(s) are ineffective and some drug(s) are effective), the expected number of type I 
errors would be equivalent. 
19 See 21 CFR 300.50. 
20 See the guidance for industry Multiple Endpoints in Clinical Trials (October 2022).  
21 See the draft guidance for industry Demonstrating Substantial Evidence of Effectiveness for Human Drug and 
Biological Products (December 2019). When final, this guidance will represent the FDAs current thinking on this 
topic. 
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389  G.  Comparisons Between Drugs  
390   
391  In an umbrella or platform trial evaluating multiple drugs, the primary focus of the trial is to 
392  evaluate the efficacy and safety of each individual drug as compared to the control arm; 
393  however, there may also be interest in comparing drugs with each other. While FDA does not 
394  require such comparisons, they may be useful for comparative effectiveness research and 
395  informing treatment guidelines. Sponsors planning on conducting these comparisons should 
396  prespecify them in the statistical analysis plan.  
397   
398  Additionally, sponsors should consider the potential for nontransitivity in comparisons. Even if 
399  all comparisons are based on the same concurrently randomized control and drugs enter the study 
400  at the same time, certain analyses can lead to counterintuitive nontransitive results. For example, 
401  there could be a scenario in which drug A is superior to drug B, drug B is superior to drug C, and 
402  drug C is superior to drug A (e.g., Brown and Hettmansperger 2002). Nontransitivity can make it 
403  challenging to use the analysis to order treatment groups and may happen with Wilcoxon rank 
404  tests, log-rank tests, or proportional odds or Cox regressions that are fit for each pairwise 
405  comparison. Nontransitivity can occur when outcome distributions in treatment groups cannot be 
406  stochastically ordered (e.g., crossing survival curves). It generally does not occur with population 
407  summary measures such as comparisons of response rates for binary endpoints, comparisons of 
408  averages, comparisons of quantiles such as medians, or comparisons of other summary measures 
409  based on first reducing the outcome distribution in each group to a single number.   
410   
411  H.  Safety  
412   
413  As noted in Section II, a development program may include both master protocols and stand-
414  alone trials. An individual drug development program needs to provide sufficient safety data at 
415  the time a marketing application is submitted to demonstrate that the drug is safe, which requires 
416  a showing that the drugs benefits for a particular indication outweigh its risks.22 The data from a 
417  master protocol can be considered as part of the overall safety database and benefit-risk 
418  assessment but data from additional sources may be needed to support approval. The size and 
419  duration of the safety database and approach for evaluating safety, including the use of standard 
420  adverse event definitions, toxicity grading, and data collection to allow for integrated safety 
421  analyses, should be discussed with the relevant review division. FDA encourages these 
422  discussions as safety and benefit-risk considerations for individual development programs will 
423  be drug- and disease-specific.23  
424   
425  The type of master protocol and drugs expected to be evaluated will impact the approach to 
426  safety data collection. For example, some safety outcomes (e.g., injection site reactions) may be 
427  expected to differ depending on the route and/or schedule of administration. In such 
428  circumstances, it would be appropriate for the analysis of these specific safety outcomes for a 
429  given drug to utilize only the control subjects receiving a placebo with a matched route and/or 
430  schedule of administration. If such analyses are not sufficient to evaluate these safety outcomes, 
431  sponsors may need to consider a multiple-dummy, complete blinding approach (see section 
 
22 See the draft guidance for industry Benefit-Risk Assessment for New Drug and Biological Products (September 
2021). 
23 See the guidance for industry Premarket Risk Assessment (March 2005). 
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432  III.D) or a design with greater allocation to each matched control and also may need to provide 
433  additional data from studies outside of the master protocol. 
434   
435  In settings where the safety profile of the drug(s) is well established, sponsors may wish to 
436  pursue a selective approach to safety data collection.24 In a master protocol with selective safety 
437  data collection for some but not all drugs that share a control arm (e.g., with partial blinding to 
438  treatment assignment), the comparisons for a given drug should utilize only the subset of 
439  subjects in the control group for whom the appropriate safety data were planned to be collected. 
440  Additionally, if the safety data collection strategy differs between some treatment arms (e.g., 
441  differs between substudies), sponsors should address the impact of such differences in their risk-
442  based monitoring plans given the increased potential of data collection errors.25  
443   
444   
445  IV.  CONSIDERATIONS ON TRIAL OVERSIGHT, DATA SHARING, AND 
446  DISSEMINATION OF INFORMATION 
447   
448  The use of shared oversight committees may result in a need for fewer resources and allow for 
449  standardization of various aspects of the trial conducted under the master protocol. Oversight 
450  committees ensure the protection of trial subjects and promote trial integrity. FDA recommends a 
451  central institutional review board (IRB) to review the master protocol, informed consent, and 
452  other relevant documents associated with trial monitoring. FDA also recommends that the 
453  sponsor appoint an independent, external data monitoring committee (DMC) or other appropriate 
454  independent entity to oversee accumulating safety and efficacy data.26 Depending on the trial 
455  design, the sponsor may decide to have an endpoint assessment or adjudication committee to 
456  review data on important efficacy and/or safety endpoints in the trial.  
457   
458  Inadvertent dissemination of information from an ongoing trial conducted under a master 
459  protocol may pose a risk to trial integrity. For example, in an event-driven umbrella or platform 
460  trial in which multiple drugs enter the study at the same time, the fact that one drug versus 
461  control comparison has reached the target number of events for the final analysis could imply 
462  that other drugs still in the trial have had fewer events. If the endpoint represents the time to an 
463  event capturing a poor outcome (e.g., time to death) and the trial reports that the first drug is 
464  superior to the control, this could suggest that a drug remaining in the trial is also superior to the 
465  control because it has had even fewer events of poor outcomes. Conversely, if the endpoint 
466  represents the time to an event capturing a good outcome (e.g., recovery) and the trial reports 
467  futility for the first drug, this could suggest futility for a drug still under evaluation in the trial 
468  because it would have had even fewer events of good outcomes. This dissemination of 
469  information could potentially impact trial conduct and integrity by affecting recruitment, 
470  adherence, retention, or crossover. As another example, consider a case in which unblinded 
471  comparative results are reported for one drug in an umbrella or platform trial while another drug 
 
24 See the guidance for industry E19 A Selective Approach to Safety Data Collection in Specific Late-Stage Pre-
Approval or Post-Approval Clinical Trials (December 2022). 
25 See the guidances for industry Oversight of Clinical Investigations  A Risk-Based Approach to Monitoring 
(August 2013) and A Risk-Based Approach to Monitoring of Clinical Investigations, Questions and Answers (April 
2023).  
26 See the guidance for industry Establishment and Operation of Clinical Trial Data Monitoring Committees (March 
2006). 
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472  remains under evaluation. If a shared control group is used, knowledge of blinded pooled data 
473  for the drug still in the trial (i.e., pooled across the drug and shared control groups) in addition to 
474  the comparative results reported for the first drug may lead to partial unblinding of comparative 
475  results for the drug still being evaluated. Hence, it may be important to limit access to these 
476  pooled data if results are to be reported for other drugs with overlapping control groups. 
477   
478  In general, the DMC and study team should carefully consider data access plans and how best to 
479  plan analyses and communicate results for individual drugs without leading to inadvertent 
480  dissemination of information for other drugs. Steps to maintain trial integrity should be proposed 
481  and discussed with the Agency at the design stage.  
482   
483  FDA also recommends that sponsors consider entering into data-sharing agreements to allow for 
484  leveraging of information across drugs. Available data on other drugs evaluated under a master 
485  protocol can add information relevant for the assessment of a specific drug. For example, 
486  leveraging information across multiple related drugs with similar mechanisms of action can 
487  improve the understanding of specific types of adverse reactions related to that mechanism. In 
488  addition, the availability of data can enable comparisons between drugs (see section III.G).  
489   
490  However, the leveraging of data from other drugs still under ongoing evaluation necessitates 
491  some degree of access to unblinded interim results. This access to unblinded data has the 
492  potential to negatively affect trial conduct (e.g., recruitment, adherence, or retention); therefore, 
493  such approaches should be considered only in conjunction with a careful data access plan to 
494  maintain trial integrity. A data access plan should include steps to limit, to the maximum extent 
495  possible, those with access to unblinded interim results for drugs that remain active in the master 
496  protocol. In some cases, the risks to trial integrity may outweigh the potential advantages of 
497  leveraging data from other drugs. 
498   
499   
500  V.  CONSIDERATIONS TO SUPPORT REGULATORY REVIEW 
501     
502  This section of the guidance provides regulatory considerations and recommendations for the 
503  submission of documentation to FDA for umbrella and platform trials that are intended to 
504  contribute to a demonstration of safety and substantial evidence of effectiveness. The regulatory 
505  considerations for a master protocol have increased complexity compared to those for a protocol 
506  for a stand-alone trial given the involvement of additional stakeholders, the potential for frequent 
507  changes, and the quantity of documentation. Because of these complexities, each master protocol 
508  should be submitted as a new IND to FDA. 
509   
510  A.  General Investigational New Drug Considerations 
511   
512  Master protocol sponsors should take the following general considerations into account when 
513  submitting a master protocol IND:  
514   
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515    A master protocol sponsor should request a pre-IND meeting to discuss the protocol and 
516  submission details.27 The cover letter for these meeting requests should clearly state 
517  REQUEST FOR MEETING-MASTER PROTOCOL (Meeting Type B). 
518   
519    The master protocol IND should only include information regarding the master protocol 
520  trial and its substudies. A clinical investigation using a master protocol should be 
521  conducted under the master protocol IND only. 
522   
523    INDs containing master protocols are subject to all applicable requirements under 21 
524  CFR 312.  
525   
526    The drugs to be evaluated in master protocols designed to contribute to a demonstration 
527  of substantial evidence of effectiveness are expected to have undergone previous clinical 
528  testing in humans and, therefore, to have a separate IND file. In rare cases where there 
529  may not be a separate IND for the drug (e.g., a drug developed solely outside of the 
530  United States), master protocol sponsors should consult FDA. 
531   
532    Most clinical investigations using master protocols will be required to be conducted 
533  under an IND; however, a clinical investigation using a master protocol may be exempt28 
534  from this requirement in select circumstances. For example, if all the substudies of a 
535  master protocol meet the criteria for an IND exemption under 21 CFR 312.2(b)(1), the 
536  clinical investigation using a master protocol is exempt from the requirement to be 
537  conducted under an IND. 
538   
539  o  If an IND is not submitted for a master protocol because the clinical investigation 
540  is exempt and, subsequently, changes are anticipated that would render the 
541  clinical investigation no longer exempt from the requirement for an IND,29 the 
542  master protocol sponsor should submit an IND before making those changes.  
543   
544  o  If any of the substudies of a master protocol do not meet the IND exemption 
545  criteria, the clinical investigation using the master protocol must be conducted 
546  under an IND.30 
547   
548    The master protocol sponsor should provide a separate Investigators Brochure (IB) for 
549  each drug being evaluated in the master protocol rather than a single IB that covers all the 
550  drugs being evaluated. 
551   
552   
553   
 
27 See the guidance for industry Formal Meetings Between the FDA and Sponsors or Applicants of PDUFA 
Products (December 2017). 
28 See the guidance for clinical investigators, sponsors and IRBs Investigational New Drug Applications (INDs)  
Determining Whether Human Research Studies Can Be Conducted Without an IND (September 2013).   
29 For example, when there is an addition of a new arm in a platform trial that does not meet exemption criteria. 
30 See 21 CFR 312.2. 
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554  B.  IND Cross-Referencing  
555   
556  FDA review of investigational drugs evaluated in a master protocol will typically need to rely on 
557  previously submitted information about the individual drugs. The following should be considered 
558  regarding cross-references between the master protocol and individual drug INDs:  
559   
560    The master protocol, in its entirety, should not be incorporated into other INDs via cross-
561  reference.  
562   
563    Individual drug INDs for drugs being evaluated in a master protocol can cross-reference 
564  limited elements of the master protocol IND (e.g., the drug-specific substudy).  
565   
566    The master protocol IND should cross-reference information in the INDs for the 
567  individual investigational drugs, such as nonclinical study findings, drug product quality 
568  specifications, and clinical data.  
569   
570    To cross-reference information in another sponsors IND, a signed, written statement 
571  from that sponsor authorizing such cross-reference must be provided.31 
572   
573  C.  Protocol Amendments  
574   
575  Given the potentially rapid pace of changes associated with master protocols, FDA recommends 
576  the following procedures regarding protocol amendments: 
577   
578    A new drug proposed for evaluation (i.e., a new substudy) in the master protocol should 
579  be submitted as a protocol amendment to the master protocol IND.  
580   
581  o  For master protocols submitted electronically, FDA requires that Study Tagging 
582  Files be used to identify the master protocol and each of its substudies. Relevant 
583  documentation under the master protocol and each substudy must use appropriate 
584  file-tags (e.g., protocol and/or amendment, study report body). Use of the Study 
585  Tagging File will improve the organization of the electronic common technical 
586  document (eCTD) and facilitate FDAs review of the submissions (see Figure 
587  B.).32  
588   
589    The master protocol sponsor should clearly mark the cover letter for protocol 
590  amendments with Protocol Amendment-MASTER PROTOCOL, and include a clean 
591  and track changes version of the document as well as a document specifying what 
592  changes are being made.  
593   
594  o  FDA recommends that the cover letter include updates on the status of each drug 
595  in the master protocol.  
 
31 See 21 CFR 312.23(b). 
32 Additional information on eCTD submission standards can be found at: https://www.fda.gov/drugs/electronic-
regulatory-submission-and-review/electronic-common-technical-document-ectd.  
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596   
597    The master protocol sponsor should submit protocol amendments that substantively affect 
598  the safety, quality, or scope of the master protocol at least 30 days before initiation of the 
599  changes. For example, to add a new drug to the master protocol, the master protocol 
600  sponsor should submit the protocol amendment at least 30 days before initiation of that 
601  substudy.  
602   
603    The master protocol sponsor should notify the regulatory project manager at least 48 
604  hours before submitting any protocol amendment that could substantively affect the 
605  safety, quality, or scope of the master protocol. 
606   
607  D.  Communications and Safety Reporting  
608   
609  The master protocol IND should include a well-designed communication plan to ensure timely 
610  and effective communications between many stakeholders and help ensure compliance with legal 
611  requirements. FDA recommends that a communication plan be employed by the master protocol 
612  sponsor to ensure the dissemination of information and advice from FDA to the individual drug 
613  sponsor(s). Additionally, the master protocol sponsor should establish a systematic approach that 
614  ensures the rapid communication of serious safety issues to clinical investigators and FDA under 
615  IND safety reporting regulations.33 This should include a process for rapid implementation of 
616  protocol amendments to address serious safety issues.34 With regard to safety reporting, sponsors 
617  should be aware of the following:35 
618   
619    All clinical investigators are required to submit safety reports to the master protocol 
620  sponsor.36  
621   
622    Master protocol sponsors are required to submit IND safety reports to FDA and all 
623  participating investigators when they determine that a serious adverse event is 
624  unexpected, and there is a reasonable possibility that the drug caused the serious adverse 
625  event (i.e., there is evidence to suggest a causal relationship between the drug and the 
626  adverse event).37 
627   
 
33 See 21 CFR 312.32. 
34 See 21 CFR 312.30(b)(1) and 312.30(b)(2)(ii).  
35 For additional information regarding safety reporting, see the guidance for industry and investigators Safety 
Reporting Requirements for INDs and BA/BE Studies (December 2012). Also, see the draft guidance for industry 
Sponsor Responsibilities - Safety Reporting Requirements and Safety Assessment for IND and 
Bioavailability/Bioequivalence Studies (June 2021). When final, this guidance will represent the FDAs current 
thinking on this topic. 
36 See 21 CFR 312.64(b)). Also, see the guidance for industry Investigator Responsibilities-Safety Reporting for 
Investigational Drugs and Devices (September 2021). 
37 See 21 CFR 312.32(c)(1). Sponsors are also required under 21 CFR 312.55(b) to keep each participating 
investigator informed of any new observations discovered or reported to the sponsor on the drug, particularly with 
respect to adverse events and safe use.  
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628    FDA expects that the master protocol sponsor will also forward all initial IND safety 
629  reports to the relevant individual drug sponsors. Those sponsors in turn, are required to 
630  promptly review the information.38  
631   
632  o  The individual drug sponsor should review each safety report, add any relevant 
633  context or additional information, and submit a modified report to their active IND(s) 
634  for the investigational drug, if required,39 as a follow-up safety report40 that references 
635  the initial IND safety report submitted by the master protocol sponsor. 
636   
637   
638  VII.   REFERENCES41  
639   
640  Brown, BM and TP Hettmansperger, 2002, Kruskal-Wallis, Multiple Comparisons and Efron 
641  Dice, Australian and New Zealand Journal of Statistics 44(4): 427438.  
642   
643  Chandereng, T, X Wei, and R Chappell, 2020, Imbalanced Randomization in Clinical Trials. 
644  Statistics Medicine, 39(16): 21852196.  
645   
646  Howard, DR, JM Brown, S Todd, and WM Gregory, 2018, Recommendations on Multiple 
647  Testing Adjustment in Multi-arm Trials with a Shared Control Group, Statistical Methods in 
648  Medical Research, 27(5): 1513-1530. 
649   
650  Jiao, F, W Tu, S Jimenez, and YF Chen, 2019, Utilizing Shared Internal Control Arms and 
651  Historical Information in Small-Sized Platform Clinical Trials, Journal of Biopharmaceutical 
652  Statistics, 29(5): 845-859. 
653   
654  Lee, KM, and J Wason, 2020, Including Non-Concurrent Control Patients in the Analysis of 
655  Platform Trials: is it Worth it?, BMC Medical Research Methodology, 20: 165. 
656   
657  Proschan, MA and DA Follmann, 1995, Multiple Comparisons with Control in a Single 
658  Experiment Versus Separate Experiments: Why Do We Feel Differently?, The American 
659  Statistician, 49: 144. 
660   
661   
662 
 
38 See 21 CFR 312.32(b). 
39 See 21 CFR 312.32(c)(1). 
40 See 21 CFR 312.32(d). 
41 Some of the listed references also apply to the Appendix. 
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663  VI.  APPENDIX1 
664   
665  A.  Optimal Allocation Ratio 
666   
667  In certain scenarios, such as trials to evaluate more than two treatment groups compared to a 
668  common control, unequal allocation can improve efficiency (Chandereng et al. 2020). Here is a 
669  derivation in a simple case that power can be increased with disproportionately greater 
670  randomization to the control group in an umbrella or platform trial with a fixed total sample size. 
671  Consider an umbrella trial in which there are N total subjects, k drugs, and 1 control group. For 
672  some fraction p suppose that Np subjects are assigned to control and N(1p)k subjects 
673  are assigned to each drug. Also, suppose that the treatment effect  is the same for each drug and 
674  that outcomes for all groups have the same variance. The power of a z-test is determined by , 
675  where 2 is the variance of the (treatment  control) difference in means and is proportional to 
676  f(p) = 1[N(1p)k]+1(Np). Considering p as continuous in (0,1) (even though 
677  strictly speaking the number of treatment and control subjects should be integers) the first 
678  derivative of f(p) is 1N[k(1p)2 1p2]. The second derivative of f(p) is 
679  1N[2k(1p)3 +2p3] > 0, so the function f(p) is convex, and thus variance is 
680  minimized by setting the first derivative to zero. This is achieved at p = 1(1+k) which is 
681  equivalent to a randomization ratio for the control relative to a given drug of k:1. In contrast, 
682  equal allocation to all treatment groups would correspond to p = 1(1+k). This example 
683  illustrates a simple case, and the Chandereng et al. 2020 paper shows more generally, that the 
684  optimal allocation will have disproportionate randomization to the control group when k > 1. 
685   
686  The intuitive reason why power can increase with disproportionate randomization is that it can 
687  lead to a larger sample size for each (drug  control) comparison, and the power with an 
688  unequally randomized large sample size comparison can in some cases exceed the power of an 
689  equally randomized small sample size comparison. Consider an example under the paradigm 
690  above where the total sample size for the master protocol is fixed at 600 subjects and there are 4 
691  drugs and 1 shared control group. Optimal allocation of 200 subjects (p = 1/3) to the shared 
692  control group and 100 subjects to each drug group would result in 300 subjects and optimal 
693  power for the comparison of a given drug to the control group. Equal allocation to all groups 
694  (p = 1/6) would result in 120 subjects allocated to each drug group and to the control group, 
695  resulting in only 240 subjects for the comparison of a given drug to the control group. 
696   
697  B.  Examples of Randomization Strategies for Partially-Blinded, Placebo-
698  Controlled Studies 
699   
700  Example 1: Randomization Process for 1:1 Allocation Ratio  
701   
702  Here is one example of a 2-step randomization process that maintains a 1:1 allocation ratio for 
703  the pooled placebo arm relative to a given drug: 
704   
705  1.  Randomize with equal probability (1:1:...:1) to one of the drugs the subject is eligible to 
706  receive 
 
1 The references cited in the Appendix are listed in the References section of the guidance. 
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707   
708  2.  Randomize to the drug or matching placebo version of that product with allocation k:1, 
709  where k is the number of drugs for which the subject is eligible 
710   
711  There are alternative randomization strategies that also target a 1:1 allocation ratio for a given 
712  drug and the pooled placebo arm. One alternative strategy is to first randomize subjects to one of 
713  the drugs or the pooled placebo arm with equal probability, and then randomize subjects in the 
714  pooled placebo arm to one of the drug-specific placebos with equal probability. A second 
715  alternative strategy is to first randomize subjects to drug or placebo in a k:1 ratio, and then 
716  randomize subjects to a specific drug or drug-specific placebo with equal probability. 
717   
718  Example 2: Randomization Process for k:1 Allocation Ratio  
719   
720  Here is one example of a 2-step randomization process that targets a k:1 allocation ratio for the 
721  pooled placebo arm relative to a given drug, intended to increase power with greater-than-equal 
722  allocation to placebo (see Appendix: section A): 
723   
724  1.  Randomize with equal probability (1:1:...:1) to one of the drugs the subject is eligible to 
725  receive 
726   
727  2.  Randomize to the drug or matching placebo version of that product with allocation k:1, 
728  where k is the number of drugs for which the subject is eligible 
729   
730  Illustrative Figure and Table 
731   
732  The following figure illustrates the two example randomization processes described above in a 
733  trial with four drugs for a subject who is eligible to receive all four drugs. The following table 
734  describes key randomization probabilities and ratios for these examples. 
735   
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736  Figure A: Schematic to Illustrate Examples of Randomization Processes for a Partially-
737  Blinded, Placebo-Controlled Study
738    
739  Left (Example 1): 1:1 allocation ratio for the pooled placebo arm relative to a given drug  
740  Right (Example 2): k:1 allocation ratio for the pooled placebo arm relative to a given drug 
741   
742   
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743  Table A: Randomization Probabilities and Ratios for Examples of Randomization 
744  Processes for a Partially-Blinded, Placebo-Controlled Study 
  Example 1  Example 2 
Allocation ratio for the pooled  1:1  k:1 
placebo arm relative to a given drug 
 
Example calculations with four drugs (i.e., k = 4) 
Randomization probability     
 Individual drug (e.g., drug A)  1 4 1 1 2 1
 =    =  
4 5 5 4 3 6
 Individual placebo (e.g., placebo A)  1 1 1 1 1 1
 =    =  
4 5 20 4 3 12
 Pooled placebo  1 1 1 1 1 1
4  =   4  =  
4 5 5 4 3 3
 Any drug  1 4 4 1 2 2
4  =   4  =  
4 5 5 4 3 3
Randomization ratio     
 Pooled placebo: Individual drug  1:1  2:1 (4:1) 
 (e.g., pooled placebo: drug A) 
 Individual placebo: Individual drug   1:4  1:2 
 (e.g., placebo A:drug A) 
745   
746   
747  C.  Example of How to Use eCTD for a Master Protocol 
748   
749  The figure below illustrates an example of eCTD organization for a master protocol with 
750  multiple substudies.  
751   
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752  Figure B. eCTD of an IND with Master Protocol MP PROTOCOL 123 and Substudies S-
753  1, S-2, and S-3 
 
  1. Regional  
  2. Common Technical Document Summaries  
  5. Clinical Study Reports 
  5.3.5 Reports of Efficacy and Safety Studies [Indication] 
  5.3.5 INDICATION  
  5.3.5.2 MP PROTOCOL 123 Master Protocol MP PROTOCOL 123 
  5. 3.5.2 MP PROTOCOL 123-S1- Drug X 
  Protocol or Amendment  
  Protocol Amendment Version 1- DATE 
  Protocol Amendment Version 1 - Tracked changes 
  Protocol Amendment Version 3 - Summary of Changes 
  IEC IRB Consent Form List  
  Documentation of statistical methods and interim analysis plans 
    5.3.5.2 MP PROTOCOL 123-S2- Drug Y 
    5.3.5.2 MP PROTOCOL 123-S3- Drug Z 
754   
755  eCTD = electronic common technical document 
756   
  22