Guidance for Industry and FDA 
Staff  
 
Pharmacogenetic Tests and 
Genetic Tests for Heritable 
Markers 
 
 
 
 
 
 
Document issued on: June 19, 2007  
 
 
 
 
 
The draft of this guidance was issued on February 9, 2006 
 
 
 
 
 
 
 
 
 
 
 
U.S. Department of Health and Human Services 
Food and Drug Administration 
Center for Devices and Radiological Health 
Center for Drug Evaluation and Research 
Center for Biologics Evaluation and Research 
    Contains Nonbinding Recommendations 
 
Preface 
 
Comments 
 
Written comments and suggestions may be submitted at any time for Agency consideration 
to the Division of Dockets Management, Food and Drug Administration, 5630 Fishers Lane, 
Room 1061, (HFA-305), Rockville, MD, 20852. When submitting comments, please refer to 
the docket number 2006D-0012. Comments may not be acted upon by the Agency until the 
document is next revised or updated. 
 
For questions regarding this document contact Robert Becker at 240-276-0843, email 
robert.becker1@fda.hhs.gov, or Maria Chan at 240-276-0848, email maria.chan@fda.hhs.gov.   
 
For questions regarding proposed use of this document in relation to applications to CBER, 
contact CBERs Office of Communications, Training, and Manufacturers Assistance at 800-
835-4709 or 301-827-1800.  For questions relating to applications to CDER, contact Felix 
Frueh, Office of Clinical Pharmacology and Biopharmaceutics, HFD-850 10903 New 
Hampshire Avenue, Silver Spring, MD, 20993, or at 301-796-1530. 
 
 
Additional Copies 
 
Additional copies are available from the Internet at: 
http://www.fda.gov/cdrh/oivd/guidance/1549.pdf or http://www.fda.gov/cber/guidelines.htm 
You may also send an e-mail request to dsmica@fda.hhs.gov to receive an electronic copy of 
the guidance, or send a fax request to 240-276-3151 to receive a hard copy. Please use the 
document number 1549 to identify the guidance you are requesting.   
 
    Contains Nonbinding Recommendations 
 
 
Table of Contents 
 
I.  Introduction.................................................................................................................1 
II.  Pharmacogenetic Testing versus Genetic Testing....................................................3 
III.  Recommendations for the Preparation of the  Pharmacogenetic or Genetic Test 
  Applications.................................................................................................................3 
A. Intended Use of a Device.......................................................................................4 
B. Device Design..........................................................................................................5 
C. Analytical Studies...................................................................................................6 
D. Software and Instrumentation..............................................................................9 
E. Comparison studies using clinical specimens....................................................11 
F. Clinical Evaluation Studies Comparing Device Performance to Accepted 
Diagnostic Procedure(s).......................................................................................12 
G. Effectiveness of the Device..................................................................................13 
IV.   Labeling.....................................................................................................................14 
Appendix I: General considerations for planning and evaluating clinical studies.........17 
    Contains Nonbinding Recommendations 
 
 
Guidance for Industry and FDA Staff  
 
Pharmacogenetic Tests and Genetic Tests 
for Heritable Markers 
 
This guidance represents the Food and Drug Administration's (FDA's) current thinking 
on this topic.  It does not create or confer any rights for or on any person and does not 
operate to bind FDA or the public.  You can use an alternative approach if the approach 
satisfies the requirements of the applicable statutes and regulations.  If you want to discuss 
an alternative approach, contact the FDA staff responsible for implementing this 
guidance.  If you cannot identify the appropriate FDA staff, call the appropriate number 
listed on the title page of this guidance.  
 
I.  Introduction 
 
This guidance document is intended to facilitate progress in the field of pharmacogenomics 
and genetics by helping to shorten development and review timelines, facilitate rapid transfer 
of new technology from the research bench to the clinical diagnostic laboratory, and 
encourage informed use of pharmacogenomic and genetic diagnostic devices.  It provides 
recommendations to sponsors and FDA reviewers in preparing and reviewing premarket 
approval applications (PMA) and premarket notification (510(k)) submissions1 for 
pharmacogenetic and other human genetic tests, whether testing is for single markers or for 
multiple markers simultaneously (multiplex tests).  Array-based tests (commonly referred to 
as microarrays) are a subset of multiplex tests and are included in the scope of this document.  
The recommendations within this guidance for elements of a genetic test submission apply to 
pharmacogenetic (e.g., drug-metabolizing enzyme allele tests, single nucleotide 
polymorphism (SNP) analysis) and other types of genetic tests.  Tests of gene expression and 
tests for non-heritable (somatic) mutations are not specifically addressed, although many of 
the same principles may apply.  In addition, this guidance considers nucleic acid-based 
analysis only, but the principles may be applied to other matrices (e.g., protein) when the 
purpose is to provide genetic information. 
 
This document is intended to recommend a basic framework for the types of data and 
regulatory issues that we believe should be addressed in a genetic test submission and 
                                                           
1 For information about PMA and 510(k) submissions, refer to the following website: 
http://www.fda.gov/cdrh/devadvice 
  1 Contains Nonbinding Recommendations 
 
provide a common baseline from which both manufacturers and scientific reviewers can 
operate.  The recommendations contained in this document are purposefully general.  It is 
well-known that each testing system will have an associated unique set of concerns, and we 
expect to identify and discuss these unique concerns with individual manufacturers, for 
example, through pre-IDE submission meetings. 
 
Although this document focuses on information to include in a 510(k), the general types of 
information are likely to be the same for PMAs.  However, we may request different types of 
data and statistical analyses in PMAs.  The appropriate information depends on the 
following: 
 
  intended use (e.g., to detect cytochrome P450 enzyme alleles) 
  indications for use (e.g., predictive or prognostic for disease, treatment response, or 
drug sensitivity) 
  methodology (e.g., polymerase chain reaction)  
  technical interpretation of results (e.g., positive for variant alleles)  
  quality control and assay limitations  
  performance (see sections C-E below)  
  clinical validity (e.g., false positives and negatives, see sections F-G below)  
  clinical interpretation 
  benefits and risks 
  claims made by the manufacturer (e.g., effectiveness)  
 
Technical aspects of this guidance may also be useful for other FDA applications that utilize 
these assay formats in support of product development, e.g., Investigational New Drug 
Applications (INDs), Biologics License Applications (BLAs), and New Drug Applications 
(NDAs).  We recommend that the sponsor or manufacturer consult with the appropriate 
review Office within the Center for Biologics Evaluation and Research (CBER) or Center for 
Drug Evaluation and Research (CDER) for these types of applications.  
 
The appropriate type of submission depends on claims and information available regarding 
the specific device.  We expect that most pharmacogenetic and genetic device submissions 
will be traditional 510(k)s or de novo classifications.   However, some devices will require 
submission of a PMA (see sections 513 and 515 of the Federal Food, Drug, and Cosmetic 
Act (Act) (21 U.S.C. 360c, 360e)).  We recommend that the sponsor or manufacturer consult 
with the Office of In Vitro Diagnostic Device Evaluation and Safety (OIVD), to determine 
the appropriate type of submission.  We also suggest that sponsors consider submitting 
protocols (pre-IDEs) before carrying out studies to ensure review issues are addressed and 
resolved prior to submission of a 510(k) or PMA.  Additional information on submission of 
pharmacogenomic information can be found in the Guidance for Industry: 
Pharmacogenomic Data Submissions (http://www.fda.gov/cder/guidance/6400fnl.pdf).  
FDA has also issued special controls guidance documents for some specific types of genetics 
tests, including  drug metabolizing enzyme genotyping systems, 
  2 Contains Nonbinding Recommendations 
 
(http://www.fda.gov/cdrh/oivd/guidance/1551.pdf) and cystic fibrosis transmembrane 
regulator gene mutation detection systems 
(http://www.fda.gov/cdrh/oivd/guidance/1564.pdf).    
 
FDA's guidance documents, including this guidance, do not establish legally enforceable 
responsibilities.  Instead, guidances describe the Agency's current thinking on a topic and 
should be viewed only as recommendations, unless specific regulatory or statutory 
requirements are cited.  The use of the word should in Agency guidances means that 
something is suggested or recommended, but not required.   
 
The Least Burdensome Approach 
 
The issues identified in this guidance document represent those that we believe need to be 
addressed before your device can be marketed.  In developing the guidance, we carefully 
considered the relevant statutory criteria for Agency decision-making.  We also considered 
the burden that may be incurred in your attempt to follow the statutory and regulatory criteria 
in the manner suggested by the guidance and in your attempt to address the issues we have 
identified.  We believe that we have considered the least burdensome approach to resolving 
the issues presented in the guidance document.  If, however, you believe that there is a less 
burdensome way to address the issues, you should follow the procedures outlined in the 
document, A Suggested Approach to Resolving Least Burdensome Issues.  It is available 
on our Center web page at: http://www.fda.gov/cdrh/modact/leastburdensome.html. 
 
II.  Pharmacogenetic Testing versus Genetic Testing 
 
Fundamentally, testing for pharmacogenetic polymorphisms and genetic mutations is the 
same and yields the same general types of results.  The target populations and how the test 
results are used, however, are expected to be quite different.  We consider pharmacogenetic 
tests for clinical use to be mostly those that are intended to provide information that may aid 
in selection of certain therapeutics.  When sufficient clinical information is available, they 
may also aid in dosage selection of the therapeutic.  Therefore, a pharmacogenetic test target 
population will typically be composed of candidates for a particular therapeutic.  Target 
populations of genetic tests, on the other hand, will usually be composed of those who are 
suspected of having, or are at risk of developing, a particular disease or condition.  The 
following recommendations will apply to both types of tests unless noted otherwise. 
 
III.  Recommendations for the Preparation of the 
  Pharmacogenetic or Genetic Test Applications 
 
The following are areas that you should address in the preparation of a submission for a 
medical device that measures pharmacogenetic or genetic information.  
  3 Contains Nonbinding Recommendations 
 
A. Intended Use of a Device 
 
An application for premarket approval or clearance of a device must include a 
statement of the intended use of the device.  21 CFR 807.92(a)(5), 814.20(b)(3)(i). 
The intended use of the device for which approval or clearance is sought should 
specify the marker the device is intended to measure, the clinical purpose of 
measuring the marker, and the populations to which the device is targeted, where 
appropriate. 
 
Some devices may have multiple intended uses.  We encourage separate applications 
for each intended use, if each has unique and separate supporting studies; however, in 
certain cases of pharmacogenetic tests, we would consider application of test results 
in multiple therapeutic settings as a single intended use.  For example, determination 
of CYP2D6 alleles for the purpose of providing information to aid in drug selection, 
without reference to a particular drug, would be an appropriate single intended use, 
given that it is well known that CYP2D6 affects the metabolism of many drugs.  In 
other cases, it may be necessary to identify multiple intended uses.  For example, a 
genetic test for a disease-causing mutation could be used for testing for carriers, 
prenatal testing, or for diagnosis.  Each of these scenarios would have studies using 
different populations.  In addition, the different uses might have different risk profiles 
and, therefore, might have separate intended use claims and submissions.  In these 
cases, you should provide appropriate data to support each claimed intended use.  
You should consult the appropriate review divisions in OIVD for advice on 
submitting tests with multiple intended uses. 
 
In this document, "screening" as an intended use is considered to be an indication to 
test an asymptomatic individual who is not necessarily at increased risk due to a 
positive family history. We recommend that if you are presenting data to support this 
type of intended use, you carefully consider the issues listed below.  
      
  Some alleles, genotypes, and mutations will have very low prevalence in 
given populations.  In these cases, samples from many patients should be 
obtained in order to detect a significant number of positives.  Furthermore, 
some alleles, genotypes, or mutations might only be present in particular 
ethnic groups, which should therefore participate in the study in significant 
numbers.  Enrichment can sometimes be appropriate to address these types of 
problems.  However, one of the drawbacks of enrichment is that sensitivity 
can be affected by spectrum bias due to irregular retrospective selection of 
cases.  Also, predictive values are dependent on the prevalence in the intended 
use population, which cannot be characterized from a study in which 
enrichment is used.  We recommend that you contact OIVD for feedback if 
you are considering using sample enrichment in your studies. 
  When many samples are tested for rare events, false positive results could 
become problematic in that they may be more common than true positives, 
due to test error and low prevalence.   
  4 Contains Nonbinding Recommendations 
 
  In some cases, properly banked samples may be studied to establish a 
predictive screening indication in healthy or asymptomatic individuals.  In 
other cases, a study including long-term follow-up may be the only way to 
prove that the test was indeed predictive and to evaluate issues such as 
penetrance.  In select cases, it may be possible to use postmarket studies to 
support this type of indication. 
 
We recommend that you consult OIVD about study design if your device is intended 
for screening or detection of rare mutations or variants. 
 
B. Device Design 
 
An application for premarket approval or clearance of a device must include 
information on the design of the device.  21 CFR 807.92(a)(4), 814.20(b)(3)(ii), 
814.20(b)(4).  We recommend that you carefully characterize design of 
pharmacogenetic and genetic testing devices.  For example, you should describe the 
following elements where applicable:  
 
  Test platform (e.g., flow cytometry, instrumentation for clinical multiplex test 
systems).  
  Composition and layout in spatially fixed platforms, including feature (e.g., 
probe) identity and placement, where applicable.  
  Methods used in attaching the probe material to a solid surface, if applicable. 
  Sequence or identity of oligonucleotides, primers, probes, or other capture 
elements. 
  Hybridization conditions, washing procedures, and drying conditions (e.g., 
temperature, length of time). 
  Assay components such as buffers, enzymes, fluorescent dyes, 
chemiluminescent reagents, other signaling and signal amplification reagents, 
instruments, software, etc. 
  Specificity of probes for locus of interest; this is especially important when 
pseudogenes or sequence-related genes exist. 
  Methodology for DNA extraction that you provide or that you recommend for 
users, and other applicable preanalytical elements. 
  Range of input sample concentrations that meet performance specifications. 
  Internal controls and external controls that you recommend or provide. 
  Stability and reproducibility of the platform when used for its intended use.   
  For multiplex tests in which the target molecules will contact a number of 
different probes, the methods used to mitigate the risk for specific and non-
specific probe cross-hybridization.  
  5 Contains Nonbinding Recommendations 
 
  For multiplex tests that utilize many probes, the methods used to address the 
potential for probe cross-contamination..  
 
We recommend that you describe in detail the test systems methodology for 
detecting alleles, genotypes, or mutations.  You should briefly outline your risk 
analysis relating to the test system methodology and describe device design elements 
that resulted from optimization of the test system for the analyte to be tested, if 
applicable.   
 
We recommend that you include illustrations or photographs of non-standard 
equipment or methods because these can be helpful in understanding novel 
methodologies and your approach to risk management, including incorporation of 
features to minimize potential device failures and user errors. 
 
C. Analytical Studies 
 
For performance data that is included in your 510(k) (21 CFR 807.92(b)), or PMA 
(21 CFR 814.20(b)(3)(v), we recommend that you describe the analytical studies you 
used to evaluate the following performance characteristics, including protocols and 
results.  Where applicable, you should include the following information for each 
allele, genotype, or mutation and for each matrix claimed in the intended use 
statement:  
 
1. General analytical performance considerations  
 
You should demonstrate the devices ability to accurately and reproducibly 
differentiate genotypes, alleles, or mutations using both the lowest and highest 
nucleic acid input concentrations recommended in product labeling. When 
fresh samples for rare alleles, genotypes, or mutations are scarce, we will 
consider the use of archived or retrospective samples.  Although natural 
samples are preferred, we will also consider artificially prepared materials, 
such as plasmid DNA or amplified gene segments.  These artificially prepared 
materials should mimic natural matrices to the greatest degree possible.  In 
particular, when using cloned or amplified material, the copy number tested 
should approximate that found in a natural sample.  If appropriate, you should 
demonstrate that your assay can distinguish between hetero- and 
homozygotes, since this is one of the critical aspects in assessing analytical 
performance of a genetic assay.    
 
2.  Sample characterization and specifications   
 
If you intend to provide reagents for specimen processing, you should 
demonstrate that the chosen sample preparation method consistently provides 
quality nucleic acid samples that yield reproducible test results for each 
specimen type with which your test is intended to be used. (See also Section 
  6 Contains Nonbinding Recommendations 
 
4, Precision.)  If your sample preparation method involves preparation of an 
RNA intermediate, you should evaluate your procedure to ensure that residual 
contaminating genomic DNA is either absent or, if present, will not interfere 
with assay results.  If you do not intend to provide sample preparation 
reagents in your kits, you should provide specifications for assessing the 
quality of the assay input sample so that users can validate their own sample 
preparation method and reagents.  You should provide justification for these 
specifications in the submission.  We also recommend that you carefully 
characterize sample stability and validate your storage and handling 
recommendations. 
 
3. Effect of excess sample and limited sample  
 
You should investigate the range of nucleic acid sample concentrations that 
reproducibly yield acceptable results.  You should also determine the 
minimum amount of testable input DNA sample that provides acceptable 
performance and approximate the amount of patient specimen needed to 
generate this minimum amount of sample.  We recommend that you determine 
the minimum amount of input nucleic acid needed to obtain a correct 
genotype, such that the lower bound of the 95% confidence interval for the 
estimated correct call fraction is greater than 95%.  The recommended 
minimum sample input in your labeling may fall above this amount in order to 
improve performance of the test.    
 
4. Precision (Repeatability/Reproducibility)   
 
You should perform studies to determine estimates of total variability for each 
specimen type.  For information on precision studies, we recommend that you 
consult Evaluation of Precision Performance of Clinical Chemistry Devices; 
Approved Guideline-2nd Edition, CLSI (Clinical Laboratory Standards 
Institute), EP5-A2 and User Protocol for Evaluation of Qualitative Test 
Performance; Approved Guideline, CLSI, EP12-A.  Information on obtaining 
these documents is available at http://www.clsi.org/.  You should include, as 
appropriate, repeatability (same day, site, operator, instrument, and lot) and 
reproducibility (between runs, days, sites, operators, instruments, and lots) 
studies.  Precision panels should be designed to evaluate the lowest and 
highest nucleic acid input concentrations recommended in product labeling.  
We recommend that you carry out reproducibility at three or more sites.  
Multiple operators with skill levels the same as those of your intended users 
should perform the test, preferably using multiple lots of devices and reagents.  
You should also perform testing over several weeks and at different times of 
the day to maximize detection of potential sources of variability.  The 
protocol should include evaluation of sample preparation reagents provided 
with the kit.  If you do not include sample preparation reagents in the test kit, 
each site should use and validate its own specimen processing procedures and 
demonstrate that the resulting sample meets manufacturer-supplied 
  7 Contains Nonbinding Recommendations 
 
specifications.  Likewise, if you do not include or recommend a specific 
instrument with the kit, each site should use its own instrument during testing, 
as appropriate.   
 
5.  Controls and calibrators  
 
For external controls and calibrators, you should describe the following: 
  nucleic acid levels  
  matrix  
  your method of preparation, value assignment, and validation  
  your protocol and acceptance criteria for determining stability 
  how you established the recommended calibration and control testing 
frequency   
If you do not provide external controls or calibrators, you should indicate 
commercial availability of these materials or describe a method that users can 
follow to prepare them (or both).  You should describe the reactions and 
functions monitored by internal controls.  For different technologies, these 
controls may differ, but the controls should enable users to determine if 
critical reactions have proceeded properly.  Controls should contain nucleic 
acid levels at the low end of the input concentrations recommended in product 
labeling in order to adequately stress the system. 
 
6. Cut-off  
 
We recommend you provide the following to support an analytical 
characterization of your cut-off(s), if applicable:   
  study design and analytical data to support the established cut-off  
  rationale for the units, cut-off, and/or categories of the results 
  a description of specimen preparation, including analyte levels, matrix, 
and how levels were established 
  statistical methods used [e.g., Receiver Operating Characteristic 
(ROC) Analysis] 
 
7. Analytical specificity (interference and cross-reactivity studies)   
 
Potential inhibitors present in patient specimens may not be efficiently 
removed by sample preparation procedures and may even interfere with 
sample preparation itself.  We recommend that you examine potential 
interfering substances commonly present in the indicated patient specimens 
for their effects on sample preparation and assay performance.  Test samples 
should be chosen to evaluate the lowest and highest nucleic acid input 
concentrations recommended in product labeling.  For more information on 
interference studies we recommend that you consult Interference Testing in 
  8 Contains Nonbinding Recommendations 
 
Clinical Chemistry; Approved Guideline, CLSI, EP-7A.  For both cross-
reactive and interfering substances tested, we recommend you include the 
following:  
  the concentrations at which these substances were present in the 
samples 
  sample description and preparation, including matrix and nucleic acid 
levels  
  the number of replicates tested for each substance 
  how interference and cross-reactivity were defined in relation to the 
results obtained for the reference positive and negative control 
samples 
  a description of the degree of interference or cross-reactivity observed 
  results demonstrating that your test rejects sequences similar to the 
target sequence, at nucleic acid levels that include the lowest and 
highest input concentrations recommended in product labeling, where 
applicable 
 
8. Assay conditions 
 
As applicable, you should verify hybridization conditions (for thermocycling, 
cycling conditions), concentration of reactants, and control of non-specific 
activity.  In the case of multiplex tests, you should examine and describe 
optimization of multiple simultaneous target detection. When thermocycling 
is used, you should verify optimization, specificity, and robustness of 
amplification. 
 
9. Potential for sample carryover and cross-hybridization  
 
We recommend that you assess the potential for sample carryover and cross-
hybridization, and that you provide instructions in your labeling for 
preventing carryover and reducing or eliminating cross-hybridization. 
 
10. Limiting factors of the device   
 
You should describe any known limitations of the device.  Examples are when 
the device does not measure all possible alleles, genotypes, or mutations, or 
when the range of alleles, genotypes or mutations is not known. 
 
D. Software and Instrumentation 
 
1. Data processing 
 
  9 Contains Nonbinding Recommendations 
 
If your device includes software, you should include specific information 
about the software in your submission.  We recommend that computational 
methods be developed and verified using the CDRH software development 
and validation guidance documents that are available at 
http://www.fda.gov/search/databases.html.   
 
You should provide support for your selection of the appropriate level of 
concern.  You also must demonstrate that the software design has been 
verified as required by 21 CFR 820.30(f).  For more information on levels of 
concern, you should refer to FDAs Guidance for the Content of Premarket 
Submissions for Software Contained in Medical Devices, May 11, 2005. 
(http://www.fda.gov/cdrh/ode/guidance/337.pdf ).  If applicable, you should 
describe how computational concerns such as probe saturation level, 
background correction, normalization, etc., are addressed by the software. 
 
2. Validation of instrumentation 
 
You should provide specifications in your labeling for any generic instrument 
needed to run the test, so that users may select an instrument that is suitable 
for their purposes.  You should base your recommendations on performance 
testing of various instruments with your device (see Precision, Section C4, 
above).  If you provide, or recommend, specific instrumentation for your 
device, whether manufactured by you or by another company, you should 
include specific information about the instrument(s) in your submission, and 
you should perform testing described in this guidance document using this 
instrument.  We recommend that you describe the following and include test 
results to support your descriptions, where appropriate: 
a. Characterization: You should characterize the instruments.  We recommend 
that you include information on how the instrument assigns values to, or 
interprets, assay variables such as feature location, size, concentration, 
volume, drying of small samples, and effects of small volume reactions.  
You should also include information on how these types of variables 
impact test performance, especially results.  
 
b. Calibration: You should describe how the instrument is calibrated and the 
materials used in calibration.  You should indicate the recommended 
calibration frequency and how it was established.   
 
c. Uncertainties: You should describe potential sources and estimates of 
uncertainties in results introduced by hardware components such as 
scanners, LCD cameras, etc. 
 
If you specify a particular instrument (by manufacturer or brand), you should 
assure that any changes made to the instrument (by you or the manufacturer) 
are tracked and evaluated to determine whether there is any effect on assay 
  10 Contains Nonbinding Recommendations 
 
performance, in accordance with the quality system regulation (21 CFR Part 
820).  If changes in instrumentation introduce new or different assay 
performance issues, you will be responsible for validation of your device 
under the changed conditions and you should determine whether you need to 
submit this information to FDA.  21 CFR 820.30(g).  (See 
http://www.fda.gov/cdrh/ode/510kmod.html  and 21 CFR 807.81, 814.39.) 
 
E. Comparison studies using clinical specimens 
 
Where comparison studies are appropriate to establish performance of a device, we 
recommend that you describe your evaluation protocol and results, including the 
items listed below.  You should include in your evaluation all matrix types with 
which your device is intended to be used.   
 
1.  Comparison to a Reference Method 
 
For pharmacogenetic and genetic tests, we recommend that you validate your 
assay by performing studies that compare results obtained with your device to 
those obtained with bidirectional sequencing.  Bidirectional sequencing is 
considered the reference method2 for sequence analysis (sometimes also 
referred to as the gold standard).  For large deletion, rearrangement or 
insertion mutations, or other cases where bidirectional sequencing may not be 
an appropriate comparator, we recommend that you consult with OIVD to 
discuss an appropriate study design. In your description of this study, you 
should include your protocol, the sample types you used, any selection criteria 
you applied, and results.  If the population tested is representative of the 
population for which the device is intended, results may be reported as clinical 
sensitivity and specificity.  You should address the quality of the bidirectional 
sequencing by an appropriate metric and include it in your submission. 
 
2.  Comparison to another device 
 
You may also choose to describe comparison studies with another well-
characterized or predicate device, in addition to comparison with the reference 
method. You should generally report results as positive and negative percent 
agreement. While comparison to another device can be useful, FDA believes 
that the best measure of test performance will come from comparison to 
bidirectional sequencing.    
 
3.  Resolution of Comparison Discrepancies  
 
                                                           
2 In this document, we use the term "reference method" to refer to a well-validated analytical 
procedure sufficiently free of systematic or random error to make it useful for validating 
proposed new analytical procedures for the same analyte.  
  11 Contains Nonbinding Recommendations 
 
You should identify discrepant results.  If you perform discrepancy resolution, 
you should report the result of that testing.  FDA strongly discourages the use of 
resolved results in calculations of device performance unless unbiased statistical 
techniques can be used.  FDA has developed a guidance document on statistical 
analysis that you may refer to for further discussion of this subject.  See the 
guidance, Statistical Guidance on Reporting Results from Studies Evaluating 
Diagnostic Tests; Guidance for Industry and FDA Staff 
(http://www.fda.gov/cdrh/osb/guidance/1620.pdf). 
 
4.  Failure Rates  
 
You should identify incorrect results obtained due to device failure.  You should 
also provide estimates of expected failure rates (e.g., when result is no call 
due to device failure or sample inadequacy). 
 
5.  Evaluation of devices employing quantitative measurement techniques 
 
You should evaluate the effects of random and systematic error in comparison 
to the reference method.  You should calculate bias when possible and 
appropriate.  For more information, you should also refer to Method 
Comparison and Bias Estimation Using Patient Samples Approved Guideline, 
2nd Edition, CLSI, EP-9A2.   
 
6. Confidence Intervals 
 
For any device, you should calculate and report confidence intervals around the 
point estimates of performance measures. 
 
F. Clinical Evaluation Studies Comparing Device Performance to Accepted 
Diagnostic Procedure(s) 
 
Where clinical studies are needed to establish safety and effectiveness of a 
pharmacogenetic or genetic testing device, you should address the points listed 
below. You should include in your evaluation all matrix types with which your device 
is intended to be used.  In addition, you may refer to Appendix I for more points to 
consider in designing studies.  You should provide appropriate clinical data to 
support each intended use.   
 
  12 Contains Nonbinding Recommendations 
 
a)  You should define clinical truth as it will be used in evaluating the 
clinical performance of the device.  For the purposes of this guidance, we 
define clinical truth as the best clinical evidence for a specific diagnosis or 
allele assignment.  If you use discrepant resolution in your analysis, you 
should describe the strategy used.   
 
b)  We recommend that you validate genotype/phenotype correlations, if 
necessary, on a statistically determined number of specimens for each 
intended use.  You should include the following information, when 
defining the population(s) used: 
 
  Number of specimens from the normal population, summarized 
according to appropriate demographic characteristics. 
  Number of specimens included in each disease, condition, 
genotype, or group summarized according to appropriate 
demographic characteristics. 
 
c)  You should include clinical samples for all matrices included in your 
intended use statement.  For more information on evaluating matrix 
effects, see Evaluation of Matrix Effects Approved Guideline, CLSI, 
EP-14A.  
  
d)  Clinical cut-off (where applicable):  You should describe clinical 
validation of the established cut-off and its validation for the new device.  
You should identify clinical cut-off points in a training set and validate 
these in a separate, independent test data set.  You may also provide 
literature references that support clinical cut-offs. 
 
e)  You should describe statistical methods used and confidence intervals for 
calculations, where appropriate.   
 
f)  If you are establishing clinical validity through retrospective or 
prospective studies using a genotyping method other than the method you 
are submitting, we recommend you consult with OIVD to determine the 
appropriateness of this approach for your device. 
 
g)  When you plan to use literature to support clinical validity, we 
recommend that you consult OIVD to determine the suitability of 
literature, and techniques for its evaluation, to supplement or substitute for 
clinical performance studies.   
 
G. Effectiveness of the Device 
 
  13 Contains Nonbinding Recommendations 
 
For PMAs, you must provide valid scientific evidence to establish reasonable 
assurance of the safety and effectiveness of the new device and for de novo 
classification submissions, you must provide valid scientific evidence to establish 
which general and special controls are necessary to provide a reasonable assurance of 
safety and effectiveness of the device (see sections 513 and 515 of the Act (21 U.S.C. 
360c, 360e)).  For both PMA and de novo submissions, we recommend you submit 
clinical data.  
 
1.  New markers 
  
When you demonstrate the clinical validity and test performance3 of a device 
that utilizes new markers, such as mutations, patterns, and/or other outputs of 
pharmacogenetic and genetic tests, you must meet the requirements for 
determining safety and effectiveness for the tests' intended use, as outlined in 
21 CFR 860.7.   
 
2.  Established Markers 
 
For established markers, you may use appropriate information in the medical 
literature as evidence of the effectiveness of the marker or mutation.  If you 
use peer-reviewed literature to support clinical validity and/or test 
performance, you should provide copies of all relevant articles, as well as a 
justification for the use of the literature in place of clinical studies.  You 
should establish comparability between the new device and the device used in 
the published literature in order to ensure that the data can be confidently 
extrapolated.  We recommend that you consult OIVD to determine the 
suitability of literature, and techniques for its evaluation, to supplement or 
substitute for clinical validity and/or test performance studies. 
   
IV. Labeling 
 
For 510(k)s, the submission must include labeling in sufficient detail to satisfy the 
requirements of 21 CFR 807.87(e).  For PMAs, your application must include copies of all 
proposed labeling for the device. (see 21 CFR 814.20(b)(10)). The following suggestions are 
aimed at assisting you in preparing proposed labeling that satisfies these requirements and 
final labeling that satisfies 21 CFR Parts 801 and 809. 
Directions for Use 
                                                           
3 For the purpose of this guidance, clinical validity of the marker is defined as the 
determination that the device marker(s) are truly informative (e.g., predictive) as claimed in 
the intended use; and test performance is defined as the determination that the test reliably 
and reproducibly identifies the marker(s) in a clinical setting. 
 
  14 Contains Nonbinding Recommendations 
 
 
You should provide clear instructions that delineate the technological features of the 
specific device and how the device is to be used on patients.  Instructions should 
encourage local/institutional training programs to familiarize users with the features of 
the device and how to use it in a safe and effective manner.  Devices incorporating 
nucleic acid amplification should provide sample work-flow recommendations in the 
labeling. 
Quality Control 
 
We recommend that you provide a description of quality control measures that the 
laboratory should follow to help ensure proper device performance.  
Interpretations and Precautions 
 
We recommend that you provide the key for interpretations of results and specify the 
language to be used in reporting results.  You should provide a reference for the 
nomenclature system that you are using to describe alleles, genotypes, and mutations. 
 
We recommend that you address the limitations of your device with statements in the 
labeling, for example: 
 
  This test does not identify all alleles of CYP2D6.  
  It is suspected that some mutations, alleles, or genotypes are private (found 
only in a small population or single family) and may not be detected by this 
test.   Therefore, you should interpret the results of the test with caution. 
  This test should not be used for (name a reason or reasons). 
  The presence of other (rare) mutations or polymorphisms may result in false 
positive or false negative results for this test. 
Stability 
 
You must include information on the reagent shelf life. (See 21 CFR 809.10(a)(5) and 
809.10(a)(6) regarding labeling; 809.10(b)(5)(i) regarding the package insert 
814.20(b)(6)(i) regarding additional information for premarket approval applications.)  
You should also include recommendations for handling and collecting specimens based 
on your specimen stability data  
Performance 
 
You should describe device performance in comparison to the reference method 
(bidirectional sequencing).  Useful formats include 2 x 2 (or other N x N) tables, 
sensitivity and specificity, percent agreement, or other illustrative examples.  You 
should calculate the sensitivity and specificity or percent agreement with their 
  15 Contains Nonbinding Recommendations 
 
respective confidence intervals using all tested samples.  The number of failed (invalid) 
assays by your device (e.g., inability to genotype the sample) should be reported in 
your performance characteristics. 
  16 Contains Nonbinding Recommendations 
 
 
Appendix I: General considerations for planning and evaluating clinical studies 
 
We recommend that you consult with the appropriate OIVD review divisions to determine 
the most appropriate strategies for your clinical studies. The following are some general 
recommendations that may be used when planning and evaluating clinical studies.   An 
additional resource to consider when seeking guidance on reporting clinical and/or method 
comparison studies is the STARD (Standards for Reporting of Diagnostic Accuracy) 
statement (1), which was published in 2003 and is a roadmap for improving the quality of 
reporting of studies of diagnostic accuracy.4 
 
1)  Plan studies to support the intended use claim for the device with data that are 
representative of the population for whom the device is intended (e.g., ethnicity, 
gender, clinical condition, as appropriate).   
 
2)  Describe all protocols for internal and external evaluation studies.  Clearly define the 
study population and inclusion and exclusion criteria and the chosen clinical 
endpoint.  If literature is to be used to support your intended use, you should clearly 
explain the study population, inclusion/exclusion criteria, and endpoints in the 
publication and reflect how the device will be used in practice. 
 
3)  Establish uniform protocols for all external evaluation sites prior to study and follow 
them consistently throughout the course of data collection. 
 
4)  Use investigational sites and populations appropriate to the intended use and claims 
being sought.  You should clearly outline efforts to define population sampling bias 
when this issue may impact performance. 
 
5)  Determine sample size prior to beginning the clinical study.  The sample size should 
have sufficient statistical power to detect differences of clinical importance for each 
marker, mutation, or pattern.  FDA will consider other approaches in cases with a 
small available sample size, for example, a disease allele having a low prevalence in 
the intended use population.   
 
6)  Describe the sampling method used in the selection and exclusion of patients.  If it is 
necessary to use archived specimens or a retrospective design, provide pre-specified 
inclusion and exclusion criteria for samples, and adequate justification for why the 
sampled population is relevant to the patient population targeted for the intended use. 
 
                                                           
4Bossuyt PM, Reitsma JB, Bruns DE, Gatsonis CA et al.  The STARD statement for 
reporting studies of diagnostic accuracy:  explanation and elaboration.  Clin Chem. 
2003;49(1):7-18. 
 
  17 Contains Nonbinding Recommendations 
 
7)  For genetic tests, you should include samples from individuals with diseases or 
conditions that may cause false positive or false negative results with the device (i.e., 
within the differential diagnosis), if appropriate.  
 
8)  Analyze data for each individual test site and pooled over sites, if statistically and 
clinically justified.  Justification of data pooling over sites should address variation 
between sites in prevalence, age, gender, and race/ethnicity.   
 
9)  Describe how the cut-off point (often the distinction between positive and negative, 
or the medical decision limit) will initially be set, and how it will be verified, if 
appropriate.  If a cut-off is specified for each of multiple alleles, genotypes or 
mutations, describe the performance characteristics of each cutoff as it relates to its 
respective allele, genotype or mutation.  The description of how each cut-off is 
determined should include the statistical method used [e.g., receiver operating 
characteristic (ROC) curve]. 
 
10) Diagnostic devices that assay the presence of a particular pattern (e.g., single 
nucleotide polymorphism (SNP) set, haplotype pattern), should ideally be validated in 
a prospective clinical trial. An example of such a device would be a test using a 
defined SNP set to discriminate between patients who may or may not experience an 
adverse event associated with a particular drug.  Since it is statistically problematic to 
validate discrimination patterns in the same study in which they were defined, the 
simplest way to address this is to validate the pattern with an independent data set.  
Determination of the statistical significance of a retrospectively determined feature 
pattern may not be possible or minimally would call for careful use of complex 
statistical procedures, such as bootstrapping, or an explicit cross-validation scheme.  
Given that it can be easy to obtain a low misclassification rate for a retrospectively 
determined feature pattern even on random data, you should provide a valid 
procedure for obtaining the statistical significance of such a pattern.  The simplest 
approach statistically is to evaluate the pattern on an independent data set from a 
prospective clinical trial, if that is feasible.   
 
11) Account for all individuals and samples.  Perform appropriate data audits and 
verification before submitting to FDA.  Give specific reasons for excluding any 
patient or test result after enrollment. 
 
12) Perform studies using appropriate methods for quality control.  Describe the materials 
and methods used to assess quality control. 
  
 
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