#267 
Biomarkers and Surrogate Endpoints 
in Clinical Studies to Support 
Effectiveness of New Animal Drugs 
Guidance for Industry 
Submit comments on this guidance at any time.  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 FDA-2020-D-1402. 
For further information regarding this document, contact AskCVM@fda.hhs.gov. 
Additional copies of this guidance document may be requested from the Policy and Regulations 
Staff (HFV-6), Center for Veterinary Medicine, Food and Drug Administration, 7500 Standish 
Place, Rockville MD 20855, and may be viewed on the Internet at either 
https://www.fda.gov/animal-veterinary or https://www.regulations.gov. 
U.S. Department of Health and Human Services 
Food and Drug Administration 
Center for Veterinary Medicine (CVM) 
October 2021 Contains Nonbinding Recommendations 
 
Table of Contents 
 
I.  Introduction ....................................................................................................................... 3 
II.  Background ....................................................................................................................... 3 
III.  Scope................................................................................................................................... 4 
IV.  Biomarkers and Surrogate Endpoints in Veterinary and Human Medicine .............. 5 
A.  Regulatory Comparisons ............................................................................................ 5 
B.  Biomarkers as Drug Development Tools .................................................................. 6 
C.  Biomarkers as Surrogate Endpoints ......................................................................... 6 
V.  Explanation of Applicable Terms for Use within this Document ................................. 6 
A.  Biomarker .................................................................................................................... 6 
B.  Validation..................................................................................................................... 7 
C.  Endpoint and Outcomes ............................................................................................. 8 
D.  Surrogate Endpoints ................................................................................................... 9 
VI.  Analytical Considerations ................................................................................................ 9 
VII.  Biomarker Use in Effectiveness Studies ........................................................................ 13 
A.  Context of Use ........................................................................................................... 13 
B.  Considerations for Different Stages of Drug Development ................................... 16 
C.  Statistical Considerations ......................................................................................... 20 
VIII.  Labeling Considerations ................................................................................................. 20 
IX.  Establishing a Biomarker as a Surrogate Endpoint for Effectiveness Studies ......... 21 
X.  Statistical Considerations for Studies to Establish a Biomarker as a Surrogate 
Endpoint........................................................................................................................... 23 
XI.  Obtaining CVM Feedback on Use of Biomarkers and Surrogate Endpoints ........... 25 
A.  When to submit information regarding the use of biomarkers and surrogate 
endpoints .................................................................................................................... 25 
B.  How to submit information regarding the use of biomarkers and surrogate 
endpoints .................................................................................................................... 26 
XII.  References ........................................................................................................................ 27 
  2  Contains Nonbinding Recommendations 
 
Biomarkers and Surrogate Endpoints in Clinical Studies to Support 
Effectiveness for New Animal Drugs 
 
Guidance for Industry 
 
This guidance represents the current thinking of the Food and Drug Administration (FDA or 
Agency) on this topic.  It does not establish any rights for any person and is not binding on FDA 
or the public.  You can use an alternative approach if it satisfies the requirements of the 
applicable statutes and regulations.  To discuss an alternative approach, contact the FDA staff 
responsible for this guidance as listed on the title page. 
 
I.  Introduction 
FDA is issuing this Guidance for Industry (GFI), as required under section 305 of the Animal 
Drug and Animal Generic Drug User Fee Amendments of 2018 (Pub. L. 115-234), to assist 
sponsors in incorporating biomarkers and surrogate endpoints into proposed clinical 
investigation protocols and applications for new animal drugs under the Federal Food, Drug, and 
Cosmetic Act (FD&C Act).  Section 305 of Pub. L. 115-234, among other things, directed FDA 
to hold a public meeting for interested parties to discuss innovative animal drug investigation 
designs and to issue guidance addressing the incorporation of the use of such elements of 
investigations as complex adaptive and other novel investigation designs, data from foreign 
countries, real-world evidence (including ongoing surveillance activities, observational studies, 
and registry data), biomarkers, and surrogate endpoints into clinical investigation protocols and 
applications to support the effectiveness of new animal drugs. 
The contents of this document do not have the force and effect of law and are not meant to bind 
the public in any way, unless specifically incorporated into a contract.  This document is 
intended only to provide clarity to the public regarding existing requirements under the law. 
FDA guidance documents, including this guidance, 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. 
II.  Background 
In the Federal Register of July 9, 2019 (84 FR 32749), FDAs Center for Veterinary Medicine 
(CVM) published a notice of a public meeting entitled Incorporating Alternative Approaches in 
Clinical Investigations for New Animal Drugs giving interested persons until August 17, 2019, 
to comment on the topics discussed at the public meeting and the questions published in the 
meeting notice (84 FR at 32750-32751).1  On August 13, 2019, we published a notice 
 
1 https://www.fda.gov/animal-veterinary/workshops-conferences-meetings/public-meeting-incorporating-alternative-
approaches-clinical-investigations-new-animal-drugs 
  3  Contains Nonbinding Recommendations 
announcing the extension of the comment period to September 16, 2019 (84 FR 40071).  CVM 
received numerous comments on the topics discussed at the public meeting and the questions 
published in the meeting notice and those comments were considered as draft guidance was 
developed. 
This document describes recommendations  for designing, conducting, and reporting the results 
for investigations or studies including biomarkers and/or surrogate endpoints to demonstrate 
substantial evidence of effectiveness or a reasonable expectation of effectiveness of drugs 
intended for use in animals and to support the approval of a new animal drug application 
(NADA) or an application for conditional approval of a new animal drug (CNADA).  This 
guidance also provides information about obtaining feedback from CVM with respect to 
incorporating biomarkers and/or surrogate endpoints in investigations and study protocols for 
new animal drugs.  Other centers within FDA, including the Center for Drug Evaluation and 
Research (CDER), the Center for Biologics Evaluation and Research (CBER), and the Center for 
Devices and Radiological Health (CDRH), have released draft and final guidance documents on 
the topics of biomarkers and surrogate endpoints.  This guidance document provides CVMs 
recommendations specific to investigations for animal drugs. 
CVM will consider all biomarkers and surrogate endpoints in submissions to investigational new 
animal drug (INAD) files, NADAs, and CNADAs to demonstrate substantial evidence of 
effectiveness or a reasonable expectation of effectiveness.  This guidance document provides 
CVMs recommendations specific to investigations for animal drugs. 
Some concepts and language in the recommendations for animal drugs are intended to be similar 
or the same as those in other guidance documents issued by FDA on the same or similar topics.  
Because these recommendations are specific to investigations for animal drugs, they have been 
tailored to the unique aspects of and considerations for animal drug development. 
III.  Scope 
The purpose of this guidance is to describe how CVM intends to evaluate biomarkers, including 
surrogate endpoints, to determine whether they may be used to support substantial evidence of 
effectiveness for an NADA or reasonable expectation of effectiveness for a CNADA.  In 
addition, this guidance describes the process by which sponsors may obtain feedback from CVM 
on technical issues related to the use of biomarkers before the submission of an application.  This 
guidance does not address the use of biomarkers, including surrogate endpoints, to support 
technical sections of an application other than Effectiveness or Reasonable Expectation of 
Effectiveness. 
CVM considers biomarker and surrogate endpoint evidence from individual drug sponsors in 
addition to evidence from the broader scientific, veterinary, and human medical communities, as 
applicable, as part of a development program for a specific new animal drug.  CVM does not 
have, and is not proposing, a formal qualification2 program to assess and qualify biomarkers, 
 
2 Qualification is a determination by the Secretary that a drug development tool and its proposed context of use can 
be relied upon to have a specific interpretation and application in drug development and regulatory review under 
[the FD&C Act].  FD&C Act  507(e)(7). 
  4  Contains Nonbinding Recommendations 
including surrogate endpoints, for use in effectiveness studies for the approval of new animal 
drugs, independent from their use in a specific new animal drug development program.  Animal 
drug sponsors or other stakeholders considering qualification of a biomarker or surrogate 
endpoint should refer to the resources available for human drug or device development and 
discuss with CVM their applicability to new animal drug development before starting the 
qualification process.3,4,5   
CVM encourages sponsors to explore a variety of design options in the planning of clinical 
effectiveness study designs and to proactively discuss their considerations with CVM.  Some 
recommendations in this guidance may be highly technical and we recommend you consult with 
the appropriate CVM experts to help facilitate use of these principles. 
IV.  Biomarkers and Surrogate Endpoints in Veterinary Medicine 
A.  Regulatory Framework 
An NADA must include, among other things, a scientific rationale and purpose the new 
animal drug is to serve:  (a) Clinical purpose.6  In this guidance, clinical purpose is 
equated with intended use, which we have described as the disease or condition to be 
treated, prevented, mitigated, or cured or the structure or function of the body to be 
affected.7  Depending on the intended use, the new animal drugs clinical purpose may 
provide either clinical benefits or biological effects or both.  A clinical benefit is defined 
as a clinically meaningful effect of a drug on how an animal feels, functions, or survives.  
A biological effect is defined as a meaningful effect on the structure or function of the 
body or a clinically relevant pathophysiologic manifestation or characteristic of a disease 
or condition.  Sponsors must submit substantial evidence of effectiveness consisting of 
one or more adequate and well-controlled studies to demonstrate that a new animal drug 
is effective for each intended use and associated conditions of use.8  Generally, a sponsor 
should use endpoints that provide direct evidence of the effectiveness of the intervention 
with respect to the intended use.  This may include the use of biomarkers alone or in 
conjunction with clinical or biological outcomes as primary variables or, where 
appropriate, the use of a biomarker as a surrogate endpoint.  Surrogate endpoints should 
predict either the intended clinical benefit or biologic effect. 
 
3 https://www.fda.gov/drugs/drug-development-tool-qualification-programs/cder-biomarker-qualification-program 
4 https://www.fda.gov/medical-devices/science-and-research-medical-devices/medical-device-development-tools-
mddt 
5 See Draft GFI, Biomarker Qualification: Evidentiary Framework, (December 2018). When final, this guidance 
will represent FDAs current thinking on this topic. 
6 21 CFR 514.1(b)(2)(ii)  
7 See 62 FR 59830 at 59831 (November 5, 1997), which describes the characteristics of substantial evidence of 
effectiveness. 
8 21 CFR 514.4(b)(2) 
  5  Contains Nonbinding Recommendations 
B.  Biomarkers as Drug Development Tools 
Sponsors may choose to use biomarkers as a part of early animal drug development or 
within clinical effectiveness studies.  A context of use (COU) is a statement that fully and 
clearly describes the way the biomarker is to be used and the drug product development-
related purpose of the use.9  Depending on its intended COU, the use of previously 
accepted biomarkers, including those used as surrogate endpoints, may require limited 
justification.  However, for the use of novel biomarkers, including the use of previously 
accepted biomarkers in a different species, the individual sponsor may be responsible for 
providing evidence supporting all aspects of the proposed biomarker and its proposed 
COU.   
C.  Biomarkers as Surrogate Endpoints 
Sponsors of new animal drugs may propose to use a biomarker as a surrogate endpoint to 
predict a clinical benefit or biological effect.  If a surrogate endpoint is known to predict 
a clinical benefit or biological effect, it could be used to support substantial evidence of 
effectiveness.  Biomarkers that have not been fully established as surrogate endpoints 
may be used to demonstrate a reasonable expectation of effectiveness for conditional 
approval of certain new animal drugs.10  The animal drugs effectiveness would then be 
verified in studies using an established outcome to demonstrate substantial evidence of 
effectiveness.  For sponsors seeking to establish a biomarker as a validated surrogate 
endpoint, see section IX. Establishing a Biomarker as a Surrogate Endpoint for 
Effectiveness Studies below. 
V.  Explanation of Applicable Terms for Use within this Document 
The terms related to biomarkers and study endpoints have been used and understood in different 
ways in the various contexts of animal drug development.  This section of the guidance seeks to 
provide consistent, clear definitions of terms related to biomarkers and clinical study endpoints 
for new animal drug approvals. 
A.  Biomarker 
CVM considers a biomarker to be a defined characteristic that is measured as an indicator 
of normal biological processes, pathogenic processes, or responses to an exposure or 
 
9 https://www.ncbi.nlm.nih.gov/books/NBK338448/#IX-C 
10 The Minor Use and Minor Species Animal Health Act (21 U.S.C. 360ccc) allows for the conditional approval of 
new animal drugs intended for use in minor species (those other than horses, dogs, cats, cattle, pigs, turkeys, and 
chickens) or for minor uses in major species (i.e., MUMS drugs).  The Animal Drug and Animal Generic Drug User 
Fee Amendments of 2018 (ADUFA IV) expanded the conditional approval pathway to include new animal drugs 
that are intended to treat a serious or life-threatening disease or condition or address an unmet animal or human 
health need and for which it is determined that a demonstration of effectiveness would require a complex or 
particularly difficult study or studies.  The need to develop a biomarker for an effectiveness endpoint, such as a 
surrogate endpoint, would qualify for expanded conditional approval assuming all other criteria are met.  See CVM 
GFI #261, Eligibility Criteria for Expanded Conditional Approval of New Animal Drugs, (July 2021). 
  6  Contains Nonbinding Recommendations 
intervention, including therapeutic interventions.  More simply, biomarkers are measures 
that can help characterize a baseline state, a disease process, or a response to a treatment.  
Therefore, they can reflect physiological states, disease characteristics or processes, or 
pharmacological responses in animals.  A biomarker does not assess how an individual 
feels, functions, or survives, (i.e., it does not assess the clinical benefit).  In contrast to a 
biomarker, an assessment of how an individual feels, functions, or survives is referred to 
as a clinical outcome assessment.11  Clinical outcome assessments can be made through 
reports by a clinician, a patient, or a non-clinician observer or through a performance-
based assessment.  Therefore, biomarkers are not themselves assessments of a clinical 
outcome. 
Biomarkers are organized by type and category.  The biomarker source or material for 
measurement determines the biomarker type (e.g., molecular, histologic, radiographic, 
physiologic characteristic, etc.).  The biomarkers use determines the biomarker category 
(e.g., susceptibility/risk, diagnostic, monitoring, prognostic, predictive, 
pharmacodynamic/response, or safety).  For example, a susceptibility/risk biomarker is 
used to assess an apparently healthy individuals risk of developing a disease or medical 
condition and may be based on a molecular, histologic, radiographic, or physiologic 
characteristic.  Changes in biomarkers after treatment reflect a biological response to the 
drug product and may predict or identify safety problems related to a drug candidate (a 
safety biomarker) or reveal a pharmacological activity expected to predict an eventual 
desired outcome from treatment (a pharmacodynamic/response biomarker).  These also 
may be based on a molecular, histologic, radiographic, or physiologic characteristic. 
A biomarker test is an assessment system used to detect or measure a biomarker and 
comprises three essential components: (1) source or materials for measurement; (2) an 
assay for obtaining the measurement; and (3) method and/or criteria for interpreting those 
measurements.  Examples of biomarker tests include an instrument or method for 
measuring physiologic variables such as blood pressure, heart rate, or body temperature; 
a test for measuring an enzyme in blood; or a medical imaging tool used to measure 
tumor size.  
B.  Validation 
Adequate and well-controlled studies must use a method of selecting animals that 
provides adequate assurances that the animals are suitable for the purposes of the study 
(21 CFR 514.117(b)(5)) and methods to assess animal response (endpoints/outcomes) 
that are well-defined and reliable to establish effectiveness relative to the proposed 
clinical purpose (intended use) of the new animal drug (21 CFR 514.117(b)(8)).  Use of 
fit-for-purpose biomarkers is one way to meet these characteristics of an adequate and 
well-controlled study.  Fit-for-purpose is a conclusion that the level of validation 
associated with a biomarker is sufficient to support its COU.  
 
11 https://www.fda.gov/about-fda/clinical-outcome-assessments-coa-frequently-asked-questions#COADefinition 
  7  Contains Nonbinding Recommendations 
Validation is a process to establish that the performance of a test, tool, or instrument is 
acceptable for its intended purpose.  Biomarker test validation (analytical validation) is 
separate from validation of the biomarker itself (clinical validation).  Validation of 
biomarker tests is important because reliable tests help ensure the quality of the 
biomarker data obtained.  Analytical validation is a process to establish that the 
performance characteristics of a test, tool, or instrument are acceptable in terms of its 
sensitivity, specificity, accuracy, precision, and other relevant performance characteristics 
using a specified technical protocol (which may include specimen collection, handling 
and storage procedures).  This is validation of the tests, tools, or instruments technical 
performance but is not validation of the items usefulness.  (See section VI. Analytical 
Considerations for additional discussion on this topic.)  In contrast, clinical validation is 
a process to establish that the test, tool, or instrument acceptably identifies, measures, or 
predicts the concept of interest.  For biomarkers this means establishing that the 
biomarkers relationship with the outcome of interest is acceptable for the proposed 
COU.  Analytical validation and clinical validation are distinct processes.  However, the 
two processes are iterative and dependent on one another.  A reliable test should be used 
to measure the biomarker.  Through this iterative process, experience with the biomarker 
and the biomarker test could lead to improvements in the technical performance of the 
test and the understanding of the biomarkers biological and clinical significance. 
C.  Endpoint and Outcomes 
Within this guidance document, CVM considers a study outcome to be a measurable 
characteristic (e.g., clinical outcome assessment, biological outcome assessment, or 
biomarker) that is influenced or affected by an individuals baseline state or an 
intervention to evaluate what happens to individuals in a clinical trial; whereas endpoints 
are the analyzed parameter intended to reflect an outcome of interest.  Endpoints are 
defined based on the type of assessments made, the timing of those assessments, the 
assessment tools used, and possibly other details, as applicable, such as how multiple 
assessments within an individual are to be combined.  For example, for an analgesic drug 
intended to control post-operative pain, the study outcome may be the pain scale, whereas 
the endpoint encompasses how the pain scale is assessed, such as the classification of that 
score into the analyzed parameter of success or failure.  The most reliable study 
outcomes are those that directly measure the clinical benefit or biological effect. 
CVM considers a clinical outcome to be an outcome that describes or reflects how an 
individual (i.e., the animal) feels, functions or survives.  Clinical outcomes generally 
correspond to therapeutic indications for the diagnosis, cure, mitigation, treatment, or 
prevention of disease.  Examples of clinical outcomes are clinical outcome assessments, 
such as rating scales for pain or clinical scoring systems for bovine respiratory disease.  
In some cases, biomarkers may be combined with clinical outcome assessments to 
establish effectiveness of a new animal drug. 
In the context of this guidance document, CVM considers a biological outcome to be an 
outcome that describes or reflects an effect on the structure or any function of the body of 
a target animal; a consumers response to or evaluation of products, such as meat or milk, 
derived from the target animal; or a molecular, histologic, radiographic, or physiologic 
  8  Contains Nonbinding Recommendations 
characteristic (i.e., biomarker) of a recognized disease or condition.  Biological outcomes 
may correspond to either production or therapeutic indications, depending on the 
intended biological effect of the drug.  Examples of biological outcomes include the 
measurement of rate of weight gain for a production drug, measurement of the carriage or 
shedding status of a human pathogen, assessment of meat aroma and flavor, or the 
measure of the infection level of a gastrointestinal nematode using worm counts. 
D.  Surrogate Endpoints 
For new animal drugs, CVM considers a surrogate endpoint to be an endpoint that is used 
in clinical studies as a substitute for a direct measure of a biological or clinical outcome 
(Myers et al., 2017).  In other words, an effect on the surrogate endpoint predicts a 
clinical benefit or biological effect based on epidemiologic, therapeutic, 
pathophysiologic, or other scientific evidence rather than measure the effect directly. 
Surrogate endpoints are used when a clinical or biologic endpoint might take a very long 
time to study, or in cases where the relationship between the change in the clinical or 
biological outcome and the change in the surrogate endpoint is well understood.  
Generally, clinical studies are needed to show that surrogate endpoints can be relied upon 
to predict, or correlate with, a clinical benefit or biological effect.  A surrogate endpoint 
is considered validated after a sponsor demonstrates a clear mechanistic rationale and 
submits strong evidence that an effect on the surrogate endpoint predicts a clinical 
outcome or biological effect.  When establishing a biomarker as a surrogate endpoint, it is 
important to have a high level of confidence in the biomarker tests analytical 
performance when confirming the relationship between a biomarker and the clinical 
outcome or biological effect of interest, and generally, studies intended to confirm this 
relationship should be conducted using a validated test. 
Validation is especially important when a surrogate endpoint biomarker is the basis for a 
conclusion about substantial evidence of effectiveness of a new animal drug.  A 
biomarker that fails to represent disease processes or structural or functional changes and 
the intended effectiveness of the new animal drug may lead to erroneous decisions (either 
for approval or not) in new animal drug evaluation, even if the test for the biomarker is 
analytically valid.  If the effect of treatment on the biomarker does not adequately reflect 
the effect on the traditionally accepted clinical or biological outcome, erroneous 
conclusions might be drawn about the safety or effectiveness of the new animal drug. 
A reasonably likely surrogate endpoint is an endpoint supported by strong mechanistic 
and/or epidemiologic rationale such that an effect on the surrogate endpoint is expected 
to be correlated with an outcome of primary interest, but without sufficient clinical data 
to show that it is a validated surrogate endpoint. 
VI.  Analytical Considerations 
Academic researchers, pharmaceutical companies, and diagnostic companies have published 
white papers and reviews in an effort to establish best practices and industry standards for 
analytical validation of biomarkers.  FDAs guidance for industry, Bioanalytical Method 
  9  Contains Nonbinding Recommendations 
Validation,12 incorporates recommendations only pertaining to the validation of assays to 
measure in vivo biomarker concentrations in biological matrices such as blood or urine.  Because 
biomarkers can be used for a wide variety of purposes during drug development, a fit-for-
purpose (FFP) approach should be used when determining the appropriate extent of method 
validation.  The guidance suggests that the approach used for drug assays should be the starting 
point for validation of biomarker assays, although the FDA realizes that some characteristics 
may not apply or that different considerations may need to be addressed.  
Not all biomarkers are evaluated using assays. Some are measured by imaging, rulers, scales, or 
other measuring devices.  Therefore, the analytical validation studies and performance 
characteristics vary greatly according to the biomarker type (molecular, histologic, radiographic, 
and physiologic characteristic) and technology of the biomarker test.13  The specifics of the 
validation methodology will depend on the measurement technology, the biomarker, and COU.  
However, in general, the validation of the analytical procedure should determine if the 
measurement method is able to discriminate the change in the biomarker needed to support 
clinical validation, and a validation should demonstrate that measured changes, as applicable, are 
acceptable for the COU.  
Specific recommendations for assessing the performance characteristics of biomarker 
measurements other than assays are beyond the scope of this guidance.  However, the analytical 
validation process of a biomarker measurement method is similar regardless of the biomarker 
type, technology used for biomarker measurement, or the proposed COU and generally includes 
the following:  
  Description of the biomarker measurand(s) and measurement approach; 
  Technical protocols to limit introduction of variability and improve reliability; 
  Performance characteristics of the measurement method; and 
  Analytical validation to ensure performance under COU conditions is suitable (accurate and 
reliable). 
Unlike the predefined acceptance criteria established for small and large molecule 
pharmacokinetic assays, determining assay acceptance criteria for biomarker assays is likely the 
most challenging exercise for a biomarker assay validation (Piccoli and Sauer, 2019).  It should 
be emphasized that the acceptance criteria for biomarker assays will depend heavily on the 
intended use of the assay and should be based on physiological variability as well (Lee et al., 
2006).  Analytical validation includes evidence to demonstrate that the test provides accurate and 
precise measurements, including the determination of a cutoff, if necessary, for the interpretation 
of the biomarker results.  The cutoffs should be defined before the biomarker test is analytically 
validated.  Sufficient data should be provided to adequately describe the performance 
 
12 See GFI, Bioanalytical Method Validation (May 2018) 
13 See footnote 5 on page 5 
  10  Contains Nonbinding Recommendations 
characteristics of the tool.  Commercial availability of a test does not automatically imply that it 
has sufficient analytical validation for its proposed COU. 
As stated above, the FFP approach with validation criteria that are appropriate for the intended 
use of the resulting data should be used.  Whenever appropriate, recommendations and 
acceptance criteria in FDAs 2018 Bioanalytical Method Validation GFI should generally be 
considered during method validation.  Accordingly, analytical method validation for biomarker 
assays should include the following analytical parameters.  
Accuracy 
The accuracy, sometimes termed trueness, of an analytical procedure expresses the closeness 
of the determined value to the value that is accepted either as a conventional true value or an 
accepted reference value.  It is calculated as (the determined value/the true value) x 100%. 
Accuracy should be established using at least three independent chromatographic assay runs or 
six ligand binding assay (LBA) runs; four to five quality control (QC) levels per run (lower limit 
of quantification (LLOQ), low (L), middle (M), high (H), upper limit of quantification (ULOQ)); 
and three chromatographic assay replicates or five LBA replicates per QC level. 
Precision 
The precision of an analytical procedure expresses the closeness of agreement (i.e., degree of 
scatter) among a series of measurements obtained from multiple sampling of the same 
homogenous sample under the prescribed conditions.  Precision encompasses repeatability and 
reproducibility and is expressed as the percent coefficient of variation of a series of 
measurements.  
  Repeatability is the closeness of agreement between results of successive measurements of 
the same samples carried out in the same laboratory under the same operating conditions 
within short intervals of time (Lee et al., 2006). 
  Reproducibility is the closeness of agreement of results measured under significantly 
changed conditions (e.g., inter-laboratory or alternate vendor of a critical reagent) (Lee et al., 
2006). 
Precision should be established using at least three independent chromatographic assay runs or 
six LBA runs; four to five quality control (QC) levels per run (LLOQ, L, M, H, ULOQ); and 
three chromatographic assay replicates or five LBA replicates per QC level. 
Sensitivity 
Sensitivity is defined as the lowest analyte concentration in the matrix that can be measured with 
acceptable accuracy and precision (i.e., LLOQ). 
Specificity 
Specificity is the ability of the method to unequivocally assess the analyte in the presence of 
other components that are expected to be present (e.g., impurities, degradation products, matrix 
  11  Contains Nonbinding Recommendations 
components, etc.).  The method specificity should be assessed for interference by cross-reacting 
molecules, concomitant medications, bio-transformed species, etc.  Sponsors should make a 
scientific judgment about the need to assess these (and any other) potential interferences during 
method development. 
Selectivity 
Selectivity is the extent to which the method can determine a particular compound in the 
analyzed matrices without interference from matrix components.  Selectivity should be 
established by analyzing blank samples of the appropriate biological matrix from at least six 
individual sources in chromatographic assays, or at least 10 individual sources in LBAs.  For 
LBAs, it is important to investigate any interference originating from structurally or 
physiologically similar analytes (i.e., exogenous interference) or matrix effects (i.e., endogenous 
interference).  Matrix effects evaluation involves comparing calibration curves in multiple 
sources of the biological matrix against a calibration curve in the matrix for parallelism (serial 
dilution of incurred samples) and nonspecific binding.14 
Parallelism 
Parallelism is the extent to which the dose-response relationship between two materials (i.e., 
calibrator versus unknown specimens) is constant for the examined range of concentrations 
(Piccoli and Sauer, 2019).  The absence of suitable blank matrices means that many biomarker 
assays use calibrators prepared in a substitute matrix that differs from the test sample matrix (Lee 
et al., 2006).  If study samples are available, parallelism between the calibration standard curve 
and serially diluted study samples should be assessed to detect possible matrix effect or differing 
affinities for metabolites (EMA, 2011).  A minimum of four serial dilutions of each sample 
should be performed (Piccoli and Sauer, 2019).  Parallelism between dilution curves, where 
dilution of test samples in the range of the calibration curve does not result in substantially 
different extrapolated analyte concentrations, validates the use of the substitute matrix for 
calibrator preparation.  Results of these experiments may also define suitable dilution ranges 
should dilution be necessary to alleviate matrix effects (Lee et al., 2006). 
Quantification (Calibration) Range 
Quantification (Calibration) Range is the range of concentrations, including the ULOQ and the 
LLOQ that can be reliably and reproducibly quantified with accuracy and precision with a 
concentration-response relationship. 
The choice of a curve fitting model for calibration curves should be tailored to each analytical 
method because of the wide variety of assay formats and analytes in biomarker applications (Lee 
et al., 2006).  The simplest regression model for chromatographic methods and a four- or five-
parameter logistic model for LBAs are usually used, but other models may be acceptable with 
 
14 See footnote 12 on p. 10 
  12  Contains Nonbinding Recommendations 
justification.15  The appropriate calibration model should be confirmed with at least six 
validation runs, with a blank and at least six, non-zero calibrator levels analyzed per each 
validation run.  
Stability 
During method development, the sponsor should determine the chemical stability of an analyte in 
a given matrix under specific conditions for given time intervals, including the effects of sample 
collection, handling, and storage of the analyte.  The sponsor should assess autosampler, 
benchtop, processed or extracted sample, freeze-thaw, stock solution, and long-term stability of 
the analyte.  The sponsor should assess the stability in the same matrix as that intended for in-
study samples; however, when the matrix is rare, the sponsor may explore the use of suitable 
surrogate matrices.  Stability determinations should be performed using at least three replicates at 
L and H QC concentrations.  
Sample Integrity 
Results from biomarker assays are valid only if sample integrity is maintained from sample 
collection through analysis.  Early, consistent application of predefined sample collection and 
handling techniques is especially important when such manipulations might affect sample and/or 
biomarker integrity.  Provision of a detailed sample collection and storage protocol and adequate 
training of clinical trial site personnel are especially important when extraordinary measures are 
necessary to assure analyte integrity (Lee et al., 2006).  
In-study Use of Validated Biomarker Assays 
The sponsor should ensure that the assay continues to perform as per predefined specifications in 
each study run (i.e., to ensure the assay remains in control) (Lee et al., 2006), by use of 
appropriate QC samples (typically L, M, and H QCs, in duplicate at each level); using the same 
curve fitting method, weighting, and goodness-of-fit test determined during the validation stage; 
by performing incurred sample reanalysis; and reanalysis of samples based on reasons described 
in a preexisting standard operating procedure.16  The specific recommendations and acceptance 
criteria for in-study use of bioanalytical methods in GFI, Bioanalytical Method Validation, 
could be used as a general guidance.  However as in the validation stage, these recommendations 
may be modified with justification, depending on the specific type of bioanalytical method. 
VII.  Biomarker Use in Effectiveness Studies 
A.  Context of Use 
The information and level of evidence needed to support the use of a biomarker as part of 
the development plan to establish the effectiveness of a new animal drug will depend on 
its COU.  For a new animal drug, the COU includes two components:  (1) the biomarker 
 
15 See footnote 12 on p. 10 
16 See footnote 12 on p. 10 
  13  Contains Nonbinding Recommendations 
category; and (2) the biomarkers proposed use in drug development.  The biomarker 
may have multiple COUs in a drug development plan.  If a sponsor is considering the use 
of a biomarker in an effectiveness study, CVM encourages sponsors to discuss their 
proposed COU with CVM early in the development process.  Early communication with 
CVM is especially important if the biomarker is to be an outcome used as the basis of a 
decision regarding substantial evidence of effectiveness.  
1.  Biomarker category: 
Biomarkers can be disease-related or treatment-related and should be classified 
according to the following list:  
  diagnostic biomarker:  a biomarker used to detect or confirm presence of a disease 
or condition of interest to identify individuals with a subtype of a disease;  
  monitoring biomarker:  a biomarker measured serially for assessing the status of a 
disease or medical condition or for evidence of exposure to (or the effect of) a 
medical product or an environmental agent;  
  pharmacodynamic/response biomarker:  a biomarker used to show that a 
biological response has occurred in an individual exposed to a medical product or 
an environmental agent;  
  predictive biomarker:  a biomarker used to identify individuals more likely than 
similar individuals without the biomarker to experience a favorable or 
unfavorable effect from exposure to a medical product or an environmental agent;  
  prognostic biomarker:  a biomarker used to identify the likelihood of a clinical 
event or disease recurrence or progression in individuals having the disease or 
medical condition of interest;  
  safety biomarker:  a biomarker measured before or after an exposure to a medical 
product or an environmental agent to indicate the likelihood, presence, or extent 
of toxicity as an adverse event; and 
  susceptibility/risk biomarker:  a biomarker that indicates the potential for 
developing a disease or medical condition in an individual not currently having 
clinically apparent disease or the medical condition. 
2.  Proposed use in drug development 
The proposed use in drug development (pertinent to the effectiveness plan) should 
include a consideration of some or all of the following points, as appropriate.  
a)  Purpose of use in drug development (e.g., a diagnostic biomarker to define 
enrollment criteria in a clinical study; a prognostic biomarker to support 
enrichment of a field study for a particular disease; a safety biomarker to evaluate 
drug-induced liver injury within a field effectiveness study; or a 
  14  Contains Nonbinding Recommendations 
pharmacodynamic/response biomarker as an outcome to demonstrate drug 
effectiveness).  Sponsors should discuss the biomarkers purpose of use in drug 
development in the context of the proposed clinical purpose for the new animal 
drug (e.g., indication for use).  If a biomarker is being used as a primary endpoint 
in an effectiveness study, the biomarkers proposed use should include whether 
the biomarker will be used alone or together with other biomarkers or clinical 
endpoints or if the biomarker is being proposed as a surrogate endpoint. 
b)  Proposed stage of drug development (e.g., exploratory/discovery phase, dosage 
characterization, reasonable expectation of effectiveness, and/or substantial 
evidence of effectiveness). 
c)  Clinical study population or model system (e.g., healthy animals; animals 
undergoing surgery or diagnosed with a particular disease; cultured white blood 
cells; etc.). 
d)  Mechanism of action (MOA) of the new animal drug for which the biomarker is 
intended to have value, provided that the MOA is relevant to the biomarkers 
biology, the biomarkers proposed COU, and the intended effect of the new 
animal drug (e.g., both the MOA and the biomarker are within the same biologic 
pathway or process) (Fleming and Powers, 2012).  For some biomarker uses, such 
as a diagnostic biomarker used for enrollment or a prognostic biomarker used to 
support enrichment of a field study for a particular disease, information about the 
MOA of the new animal drug may not be a necessary component of the COU for 
the biomarker.  However, in situations where biomarkers are used as primary 
effectiveness endpoints, including their use as surrogate endpoints or as a 
predictive biomarker used to support enrichment of a field study for improved 
drug effectiveness, information about the MOA of the new animal drug may 
impact the evaluation of the biological or scientific plausibility of the biomarkers 
proposed COU. 
Sponsors should consider, and in some cases submit to CVM for comment, an 
assessment of the benefits and risks17 of the use of the biomarker for the proposed 
COU, as well as any potential risk mitigation strategies.  The overall balance of 
benefits, risks, and risk mitigation efforts are important to determine the level of 
evidence needed to support the use of the biomarker. 
The potential benefits of a biomarker for use in drug development depend on the 
biomarkers proposed COU.  Biomarker use could benefit study animals participating 
in clinical trials (e.g., earlier identification of toxicity with a safety biomarker) or 
general drug development and regulatory decision making (e.g., a prognostic or 
 
17 The terms benefit, risk, and risk mitigation that are used in the context of biomarker evaluation for new 
animal drugs have specific meanings that are relevant to biomarker development and evaluation, and these meanings 
are separate and distinct from how these terms are used in the context of evaluating the safety and effectiveness of 
medical products. 
  15  Contains Nonbinding Recommendations 
predictive biomarker used to enrich a patient population might reduce the sample size 
needed to achieve statistical significance). 
The potential risks of using a biomarker in the effectiveness assessment of a new 
animal drug should address the consequences of incorrect decision making or harm to 
study animals if the biomarker does not perform as expected and should consider 
factors that might mitigate harm.  For example, if a pharmacodynamic/response 
biomarker fails to accurately establish the effectiveness of a new animal drug, study 
animals may be unnecessarily used in a clinical study and an effective drug may not 
actually be approved.  Alternatively, if a pharmacodynamic/response biomarker 
without sufficient validation is used in a clinical study and appears to demonstrate 
effectiveness, where effectiveness does not exist, there is the risk of approving an 
ineffective new animal drug.  These risks (e.g., inaccurately establishing 
effectiveness) could be mitigated, in part, by using the proposed biomarker along 
with clinical outcomes or other biological outcomes as part of a multi-component 
endpoint, rather than as a stand-alone assessment for the establishment of 
effectiveness.  In another example, a prognostic biomarker intended for clinical study 
enrichment might fail to identify study animals with more rapid disease progression.  
In this case, the mitigation strategies might include incorporating an interim analysis 
for sample size re-estimation. 
Evidence to support biomarker use consists of data to support analytical validation 
and clinical validation.  These data may be derived from various sources, including 
pilot studies, clinical trials, foreign studies, veterinary records, and other sources, 
discussed further below.  The level of evidence needed to use a biomarker in the 
effectiveness evaluation for a new animal drug depends on the selection of the 
appropriate biomarker for the proposed COU, the quality of the biomarker 
measurement, and if necessary, the correlation of the biomarker with the outcome of 
interest.  
B.  Considerations for Different Stages of Drug Development 
Exploratory/discovery phase 
During early drug development, sponsors may use biomarkers to identify reasons for 
differences between responders and non-responders to a drug (e.g., using certain genetic 
markers), which is important to inform later study designs, such as enrichment 
strategies,18 and potentially the development of companion diagnostic tests; development 
of prognostic information to understand the natural history of a disease; or to identify 
potential disease targets for therapy. 
Dosage characterization 
 
18 See CVM GFI #268, Adaptive and Other Innovative Designs for Effectiveness Studies of New Animal Drugs, 
(October 2021) 
  16  Contains Nonbinding Recommendations 
For the purposes of dosage characterization, sponsors should submit a justification of the 
dosage (dose or dose range, dosing frequency, and the dosing duration) and a 
characterization of the critical aspects of the dose response relationship related to each 
intended use and associated conditions of use.  Dosage characterization information may 
be derived from dose titration studies, pilot studies, foreign studies,19 or scientific 
literature.  A biomarker, such as a pharmacodynamic marker, may also be used to select 
the dosage to be used in studies to demonstrate reasonable expectation of effectiveness or 
substantial evidence of effectiveness.  Although CVM does not expect the sponsor to 
submit a discussion of the COU, or an assessment of the benefits and risks of the use of a 
biomarker for the purposes of dosage characterization, sponsors should consider the 
quality of the analytical and clinical validation, the reliability of the biomarker(s) used for 
dosage characterization, and the impact of the biomarker use on the drug development 
plan and on the confidence in the dosage selection for use in studies to demonstrate 
reasonable expectation or substantial evidence of effectiveness. 
Reasonable expectations of effectiveness 
CVM would not expect biomarkers used in studies to demonstrate reasonable expectation 
of effectiveness (for conditional approval, as described in section IV. Biomarkers and 
Surrogate Endpoints in Veterinary Medicine of this guidance) to have the same level of 
analytical and/or clinical validation as biomarkers used as primary endpoints in studies 
used to demonstrate substantial evidence of effectiveness.  However, insufficient 
analytical and/or clinical validation could lead to a failure to accurately predict 
effectiveness in studies used to generate substantial evidence of effectiveness.  
A need to develop and qualify effectiveness endpoints such as biomarkers to conduct 
the clinical study to demonstrate substantial evidence of effectiveness may qualify a 
project for the expanded conditional approval pathway if all other requirements for 
conditional approval are met.20 
Substantial evidence of effectiveness 
Biomarkers may be used in a variety of ways in studies designed to demonstrate 
substantial evidence of effectiveness including providing information to inform the 
design of the study or serving as a primary endpoint, including their use as a validated 
surrogate endpoint.  
1.  Use of biomarkers in the design of clinical effectiveness studies 
Biomarkers may be used to determine whether an animal meets enrollment criteria 
(e.g., to confirm a diagnosis of disease in enrolled animals), to refine the population 
 
19 See CVM GFI #265, Use of Data from Foreign Investigational Studies to Support Effectiveness of New Animal 
Drugs, (October 2021) 
20 See CVM GFI #261, Eligibility Criteria for Expanded Conditional Approval of New Animal Drugs, (July 
2021). 
  17  Contains Nonbinding Recommendations 
to enroll (e.g., to enrich for specific study population), or to establish appropriate 
randomization factors (e.g., appropriate allocation of animals at various disease 
stages across treatment groups).  For example, a threshold fecal egg count value may 
be used to include or exclude animals in an anthelmintic dose confirmation study; 
radiography may be used to confirm a diagnosis of osteoarthritis in dogs for an 
analgesic study; and special stains used at the time of histopathology may be used to 
enrich for a specific study population (e.g., proliferative index of mast cell tumors).21 
2.  Biomarkers as primary endpoints in clinical effectiveness studies 
Any method used to assess an animals response to treatment in a clinical study, 
including biomarkers, must be well-defined and reliable (21 CFR 514.117(b)(8)) and 
be used in such a way to allow for a conclusion that the measured parameters and 
responses reliably reflect the effectiveness of the new animal drug.  
Depending on the clinical purpose of the drug, as reflected in the indication (the 
intended use) and associated conditions of use, effects on a biomarker may be used as 
a primary endpoint in conjunction with clinical outcomes to demonstrate biological 
effects or clinical benefit, as the sole primary endpoint to demonstrate certain 
biological effects, or as a surrogate endpoint to predict biological effects or clinical 
benefit.  For biomarkers used as primary outcome variables, including as surrogate 
endpoints, appropriate statistical analysis methods should be chosen according to the 
distribution of the biomarker following the general principles of statistics. 
a.  Use of biomarkers in conjunction with clinical or biological outcomes 
Biomarkers that have not been validated as a biological outcome for a biological 
effect or as a surrogate endpoint to substitute for a clinical outcome to predict a 
clinical benefit should not be used as the only outcome for the demonstration of 
substantial evidence of effectiveness.  However, it may be appropriate to use the 
biomarker(s) in conjunction with clinical outcomes or other biological outcomes, 
depending on the COU.  An example is the use of serum total T4 levels in 
conjunction with improvement in clinical signs to evaluate the effectiveness of 
antithyroid drugs for the treatment of hyperthyroidism in cats; and the use of the 
Na+ and K+ levels or the Na+/K+ ratio along with resolved or reduced clinical 
signs to evaluate the effectiveness of mineralocorticoid drugs for use as 
replacement therapy for mineralocorticoid deficiency in dogs with primary 
hypoadrenocorticism. 
b.  Use of biomarkers as the sole outcome to demonstrate a biological effect 
In some cases, a biomarker that is not validated as a surrogate endpoint may be 
used as a biological outcome, and effects on the biomarker serve as the primary 
 
21 See section V.A. Enrichment Strategies of CVM GFI #268, Adaptive and Other Innovative Designs for 
Effectiveness Studies of New Animal Drugs, (October 2021) 
  18  Contains Nonbinding Recommendations 
endpoint for a biological effect indication.  In these situations, the purpose of the 
new animal drug (i.e., the biological effect) should have appropriate utility to the 
end user. 
An example is the measurement of ammonia gas emissions (biomarker/biological 
outcome) from cattle in chambers to demonstrate the effectiveness of a new 
animal drug to reduce ammonia gas emissions (the biological endpoint) in cattle 
in feedlots.  Another example is the use of nematode worm counts to demonstrate 
the effectiveness of a drug to treat and control gastrointestinal parasite infections. 
In this situation, worm counts are evaluated to demonstrate a biological effect that 
has utility to the veterinarian and end user (treatment and control of the parasite 
species), rather than a clinical outcome (such as clinical signs of diarrhea, anemia, 
or weight loss) to demonstrate a clinical benefit.  
c.  Use of biomarkers as surrogate endpoints 
For some clinical studies, the development and use of a biomarker as a substitute 
(surrogate) for a clinical outcome or certain types of biological outcomes may be 
desirable.  If a surrogate endpoint biomarker can be measured earlier or more 
easily than the clinical outcome (such as mortality or a pain score, respectively), it 
may help avoid studies of excessively long duration or with invasive or difficult-
to-obtain endpoints.  For example, in veterinary oncology, a consensus framework 
using the human response evaluation criteria in solid tumors (RECIST v1.1) 
outlined by the Veterinary Cooperative Oncology Group provides guidelines for 
the use of response criteria that may be used as surrogate endpoints for survival in 
the evaluation of treatment effectiveness of solid tumors in dogs (Nguyen et al., 
2015).  In another example, CVM accepted sperm count as a surrogate endpoint 
for male sterility as a substitute for an evaluation of the dogs ability to reproduce 
clinically, for the approval of a drug indicated for chemical sterilization in dogs.22  
Biomarkers proposed as surrogate endpoints in studies to demonstrate substantial 
evidence of effectiveness should be validated, such that they accurately represent 
and predict clinical effectiveness, are analytically valid, and fit the specific 
intended context of the proposed indication (i.e., its intended COU).  The 
evidence used to validate a biomarker as a surrogate endpoint for substantial 
evidence of effectiveness should be generated separately from the data used to 
determine effectiveness for a specific drug.  Use of a surrogate endpoint does not 
change the requirement for substantial evidence of effectiveness but offers an 
alternate method of measuring effectiveness.  
3.  Biomarkers as secondary endpoints 
Biomarkers used as secondary endpoints (i.e., ancillary information that may be 
supportive) may not be fully validated but they should always be shown to be fit-for-
 
22 NADA 141-217, available on Animal Drugs @FDA 
  19  Contains Nonbinding Recommendations 
purpose. Biomarkers that are used as part of a multi-component primary endpoint are 
not considered secondary endpoints.  
C.  Statistical Considerations 
For surrogate endpoints that need to be established through studies, we recommend that 
you refer to section IX. Establishing a Biomarker as a Surrogate Endpoint for 
Effectiveness Studies of this guidance for statistical considerations and consult with FDA 
statisticians regarding the detailed analysis plan you will be undertaking in your study.  
When biomarkers are used as part of a multi-component primary endpoint to demonstrate 
substantial evidence of effectiveness, the basis of study conclusion and analysis should be 
prospectively specified to avoid a problem with multiplicity.23 
VIII.  Labeling Considerations 
Determining the indication may be straightforward for many intended uses (e.g., the disease, 
condition, manifestation, or clinical signs of the disease or condition being treated, prevented, 
mitigated, cured, or diagnosed; the structural or functional changes; or alterations in clinically 
relevant pathophysiologic manifestations of a disease or condition).  In such circumstances, the 
indication should convey the clinical benefit or biologic effect.  For prescription new animal 
drugs, the descriptions of specific outcomes and endpoints should be summarized in the 
effectiveness section of labeling and should not be included in the indication. 
When biomarkers and surrogate endpoints are used as primary variables to demonstrate the 
effectiveness of a drug for an intended use, they are typically not described in the labeling except 
for within the description of the effectiveness studies.  However, there are three circumstances 
when identifying a biomarker or surrogate endpoint in the indication may be appropriate. 
First, if a drug only affects certain manifestations of a disease or condition or biological outcome 
and this effect was directly measured using a biomarker, the indication should be worded to 
reflect the intended outcomes with respect to that biomarker. 
Second, it may be appropriate to include additional context about the approval in the indication 
by identifying the clinical benefit(s) or biological effect(s) that are expected (based on the effect 
demonstrated on the surrogate endpoint) but not yet established.  Such circumstances should be 
determined on a case-by-case basis and are most common with CNADAs because they are 
approved based on a reasonable expectation of effectiveness rather than substantial evidence of 
effectiveness. 
Third, in some cases, a broad indication for a disease or biological effect may not be appropriate 
and an indication identifying an outcome or endpoint, including a biomarker or surrogate 
endpoint, may be considered.  Such cases include when the drugs effect on the overall disease or 
biological outcome is not well understood; when different drugs have different effects on various 
 
23 See Draft GFI, Multiple Endpoints in Clinical Trials, (January 2017).  When final, this guidance will represent 
FDAs current thinking on this topic. 
  20  Contains Nonbinding Recommendations 
manifestations of a disease or aspects of a biologic outcome; when studies evaluated only one or 
some of the manifestations of the disease or aspects of a biologic outcome; or when the 
endpoints are different from typical effectiveness measures. 
IX.  Establishing a Biomarker as a Surrogate Endpoint for Effectiveness Studies 
For a biomarker development effort to be successful, the biomarker should be clearly identified 
and characterized, including its source material or matrix and its method of measurement.  The 
biomarker should be clearly identified based on the specific analyte (e.g., fibrinogen), anatomic 
feature (e.g., joint angle), or physiological characteristic (e.g., blood pressure) being measured.  
For composite biomarkers, it is important to list the individual biomarker components and how 
these components are interrelated (e.g., a description of an algorithm or scoring system).  If 
individual components have differential weighting, the description should include the biologic 
rationale to support this decision.  Because biomarkers are measured entities, it is important to 
describe the biomarker source or material for measurement, which determines the biomarker 
type (e.g., molecular, histologic, radiographic, or physiologic characteristic).  For example, a 
molecular biomarker obtained from a biofluid should state the sample matrix (e.g., plasma, urine, 
etc.), and a radiographic biomarker should include the organ or tissue imaged (e.g., kidney).  
The items that should be considered when determining the type and level of evidence sufficient 
to support the use of a biomarker as a surrogate endpoint consists of several components.  The 
items include:  (1) describing the drug development need; (2) defining the COU; (3) considering 
potential benefits if the biomarker is accepted for use; and (4) considering potential risks 
associated with the proposed use of the biomarker in a drug development program. 
Ultimately, whether there is sufficient evidence to support acceptance of a biomarker as a 
surrogate endpoint depends on the selection of the appropriate biomarker for the proposed COU, 
the quality of the biomarker measurement, and the correlation of the biomarker with the outcome 
of interest.  Evidence to support biomarker acceptance consists of data to support clinical 
validation and analytical validation.  As defined above, clinical validation is the process to 
establish that the test, tool, or instrument acceptably identifies, measures, or predicts the concept 
of interest.  Clinical validation establishes that a biomarkers relationship with the outcome of 
interest is acceptable for the proposed COU. 
The sponsor should describe what is known about the biomarkers role in the causal or outcome 
pathway of interest, as well as describe knowledge gaps about the pathophysiology and 
molecular underpinnings of the disease, condition, or outcome of interest.  Describing the 
biomarkers position in the physiologic or pathologic pathway, if applicable, helps to support the 
biological plausibility of the biomarkers role in the proposed COU.  The sponsor should provide 
data supporting the relationship between the biomarker and the outcome of interest. This 
relationship should be supported by statistical analyses (see section X. Statistical Considerations 
below) and should come from multiple independent data sources, if possible.  Together this 
information can establish the clinical validity of a biomarker for a specified COU. 
When assessing whether the association between a biomarker and an outcome of interest is 
acceptable for the proposed COU, a key consideration is how to define the outcome of interest.  
In some settings, there might not be a current standard outcome, or a standard outcome with 
  21  Contains Nonbinding Recommendations 
known limitations is used for comparative purposes.  For example, changes in serum creatinine 
are widely used in biomarker development as the current standard for predicting changes in 
kidney function.  However, changes in serum creatinine levels are neither highly sensitive nor 
highly specific for changes in kidney function.  In a setting in which the current standard 
outcome has significant limitations or a current standard outcome does not exist, it is important 
to consider the totality of all available data that may provide sufficient information to establish 
that the biomarker can be acceptably relied upon for the proposed COU.  
Sponsors should provide evidence of the prognostic and/or predictive value of the biomarker as a 
surrogate endpoint.  Sponsors also should provide evidence and sufficient justification that the 
biomarker test is analytically fit-for-purpose within the specific context of the proposed 
indication.  This evidence should be collected separately from the data that will be used to 
support substantial evidence of effectiveness of a new animal drug.  CVM encourages sponsors 
to establish biomarkers for use as surrogate endpoints as early in the development phase as 
possible, ideally prior to seeking concurrence on an effectiveness study protocol in which the 
biomarker is used as a surrogate endpoint. 
Sponsors should also provide evidence to support analytical validation of the biomarker for use 
as a surrogate endpoint (see section VI. Analytical Validation for Biomarkers). 
Sponsors should consider and address, as appropriate, the following regarding the use of 
surrogate endpoints.  
1.  What is the outcome the surrogate endpoint is proposed to predict?  
2.  What is the rationale for using a surrogate endpoint rather than a clinical outcome or 
traditionally measured biological outcome (e.g., feasibility, study duration, sample size, 
etc.)?  
3.  What evidence exists to support the relationship between the surrogate endpoint and the 
outcome of interest (e.g., epidemiologic studies, randomized controlled trials, real world 
evidence generated using data from veterinary medical records, disease registries, and/or data 
from mobile or remote sensing devices24; data generated from therapeutic products from the 
same class, etc.)?  
4.  If the surrogate endpoint is proposed based on prior publications and general scientific 
community acceptance, discuss the current body of evidence and the use of the surrogate 
endpoint in clinical studies.  
5.  What is the relationship of the surrogate endpoint with the causal pathway for the disease or 
the predicted biological effect? 
6.  How much do changes in the surrogate endpoint reflect changes in the outcome of interest or 
the probability of the outcome occurring?  
 
24 See CVM GFI #266, Use of Real World Data and Real World Evidence to Support Effectiveness of New Animal 
Drugs, (October 2021) 
  22  Contains Nonbinding Recommendations 
7.  What is the extent and timing of change in the surrogate endpoint that would predict the 
outcome of interest?  
8.  Is the change in the surrogate endpoint stable or does it only occur for a short time?  
9.  If a minimum threshold for change has been selected (both size and duration), how was this 
value determined (include studies conducted and data generated)?  What information is 
available about the sensitivity and specificity of any measurement tools used?  
10. How does the surrogate endpoint predict the outcome across different subgroups of the 
targeted population (e.g., animal class, disease severity, co-existing conditions, concomitant 
medications typical of the population, etc.)?  
11. Is there data showing that the surrogate endpoint predicts the response similarly across 
relevant subgroups of the targeted population?  
12. What is the evidence that a drug-induced change in the surrogate endpoint will be predictive 
of a change in the outcome (e.g., the surrogate endpoint is a correlate vs. the surrogate 
endpoint has actual predictive value)? 
X.  Statistical Considerations for Studies to Establish a Biomarker as a Surrogate 
Endpoint 
The goal of statistical analyses to establish a biomarker as a surrogate endpoint is to evaluate the 
degree and certainty of association between a biomarker and the outcome of interest.  This 
subsection describes the general considerations in the study design, sources of data, statistical 
analysis methods in assessing the biomarker, and the criteria to establish the biomarker as a 
surrogate endpoint. 
Statistical evidence for establishing a biomarker as a surrogate endpoint is usually based on trial-
level analysis.  Patient-level analysis can be used as secondary supporting evidence.  Some of the 
statistical approaches for assessment of biomarker surrogacy include the following: 
  The strongest level of evidence to support the association of a biomarker with an outcome of 
interest comes from prospective controlled studies that are specifically designed to assess the 
association.  In designing a study to demonstrate the association between a biomarker and an 
outcome, many of the general statistical principles for clinical trials, such as randomization, 
masking, sample size, and multiplicity issues, are relevant and useful.  However, special 
considerations should be taken as follows: 
  The purpose of such studies is to establish the association between a biomarker and an 
o
outcome, not to test for significant differences.  Therefore, the correlation and its 
confidence interval may be more useful, and over-reliance on p-values should be avoided, 
unless the study is designed to test the null hypothesis of no relationship of the biomarker 
to the outcome of interest. 
  When multiple candidate biomarkers are evaluated in one study, the potential for false 
o
positive results is increased; therefore, the analysis plan should control for multiplicity. 
  23  Contains Nonbinding Recommendations 
  Systematic review may be used to evaluate the association of a biomarker with an outcome.  
Systematic review is a process where data from multiple studies, including those published in 
the scientific literature, are identified and evaluated, with a prospective study design and 
analysis plan. 
  Meta-Analysis based on published data is another approach to evaluate the association of a 
biomarker with an outcome.  The general statistical principles for performing meta-analysis 
should be followed. 
  Other innovative statistical approaches, such as a Bayesian method including prior 
information and hierarchical models, may be considered to evaluate the association of a 
biomarker with an outcome.  As with any innovative statistical proposal, CVM recommends 
sponsors discuss with the appropriate CVM review division the approaches to be undertaken 
in the study. 
Data used to assess the relationship between a biomarker and an outcome of interest may come 
from a variety of sources. Some examples are as follows: 
  Randomized, controlled clinical trials; 
  Open-label/historical-control clinical trials; and 
  Observational studies, such as longitudinal cohort studies, case-control studies, cross-
sectional data, and case reports. 
The sponsor should develop a detailed plan on how the data will be collected and selected for the 
intended use.  When published data are used, certain limitations and gaps, such as publication 
bias and data quality assurance, should be considered and specified a priori.  
An appropriate statistical analysis method for quantitative evaluation of the relationship between 
the biomarker and the biological or clinical outcome should be pre-specified in the study 
protocol.  Typically, the analysis plan should include definitions of the biomarker variable and 
the biological or clinical outcome, as well as the statistical analysis model.  The analysis method 
should be consistent with the study design and the distribution properties of the variables of 
interest.  For example, for continuous measures, results can be evaluated using regression 
models.  For binary variables, results can be evaluated using sensitivity and specificity.  When 
continuous measurements are categorized, the level of cutoff values should be clinically 
meaningful. 
The success criteria to establish the biomarker as a surrogate endpoint should be pre-specified.  
There are no standard quantitative criteria for determining whether the relationship between the 
biomarker and the biological or clinical outcome is sufficiently strong to support surrogacy.  The 
evidence of strong association may vary, depending on the characteristics of the biomarker and 
the biological or clinical outcome.  The sponsor should discuss with CVM the criteria before the 
study is conducted. 
  24  Contains Nonbinding Recommendations 
XI.  Obtaining CVM Feedback on Use of Biomarkers and Surrogate Endpoints 
There are various approaches that sponsors may take to open a discussion with CVM on the use 
of biomarkers and surrogate endpoints as part of their development program to demonstrate 
effectiveness or a reasonable expectation of effectiveness.  The sponsors decision regarding 
which approach to select may be affected by where the project is in the development process.  
Communication about biomarkers and surrogate endpoints may occur at any point in the 
development process. 
The Office of New Animal Drug Evaluation (ONADE) project managers (PMs) serve as a 
central point of contact for drug sponsors and can provide information about the new animal 
drug review process and ONADEs regulatory procedures.  If you have questions about the 
approval process and do not have an ONADE PM assigned to your company, you can contact the 
PMs through the CVM mailbox AskCVM@fda.hhs.gov. 
A.  When to submit information regarding the use of biomarkers and surrogate 
endpoints 
There are a variety of points in the development process and a variety of submission 
types that can be used to obtain feedback.  CVM encourages sponsors interested in using 
biomarkers and surrogate endpoints as part of their development program for a new 
animal drug to inform CVM as early in the product development process as possible. 
Sponsors planning to incorporate biomarkers and surrogate endpoints to demonstrate 
effectiveness or reasonable expectation of effectiveness are encouraged to inform CVM 
of their intent either as part of their initial request to open a General Correspondence 
(GC) file or an INAD file (A-0000), or as part of their initial presubmission conference 
with CVM to discuss the drug product development plan (Z-submission product 
development meeting).  If one or more studies incorporating biomarkers and surrogate 
endpoints are already complete, CVM recommends sponsors submit the information 
described in section XI.B. How to submit information regarding the use of biomarkers 
and surrogate endpoints prior to the initial presubmission conference.  While CVM 
cannot make a determination if existing data satisfies technical section requirements 
outside of a data submission, if the sponsor submits sufficient information about existing 
data early, we can provide feedback to help inform the development plan.25  Sponsors are 
also encouraged to contact their assigned PM for assistance in determining the most 
appropriate method for obtaining feedback from CVM. 
 
25 See CVM Program Policy and Procedures (P&P) Manual 1243.2200 Submission and Review of Early 
Information (EI) Prior to Presubmission Conferences and Protocol Review (June 2020) and CVM P&P Manual 
1243.3050 Determining Technical Section Requirements for New Animal Drug Product Approval (May 2019) 
  25  Contains Nonbinding Recommendations 
B.  How to submit information regarding the use of biomarkers and surrogate 
endpoints 
There are several ways that sponsors may submit detailed information about plans for 
incorporating biomarkers and surrogate endpoints into their development program to 
demonstrate substantial evidence of effectiveness or reasonable expectation of 
effectiveness.  The regulatory pathway selected (CNADA versus NADA), the stage of 
development, the information available, and the feedback being sought from CVM, 
among other factors, may influence the submission type selected. 
Sponsors may seek general guidance on the use of biomarkers and surrogate endpoints to 
a GC file prior to opening an INAD file.  Sponsors may submit information to support 
use of data from biomarkers and surrogate endpoints as part of their initial request to 
open an INAD file; as part of a meeting request for a presubmission conference (Z-
submission) to discuss the Effectiveness technical section requirements; or as part of an 
information submission (H-submission) or meeting request (Z-submission) to discuss 
study protocol design. 
Sponsors considering incorporating biomarkers and surrogate endpoints into future 
studies to demonstrate effectiveness or reasonable expectation of effectiveness should, 
prior to conducting a study, submit a study protocol for review (E-submission).  
Obtaining CVM input regarding study design will make reaching protocol concurrence 
more efficient.  
Sponsors may also open a Veterinary Master File (VMF) to hold detailed information 
regarding a specific study design, including those regarding pre-investigational 
discussions about the use of biomarkers and surrogate endpoints, or if the information 
will be used in the development of multiple applications.26  The VMF is confidential and 
is typically used when a holder wishes the material in the VMF to remain proprietary, 
although the material may be referenced by multiple third-party products or files (INAD, 
NADA, or CNADA).  Alternatively, if multiple sponsors are cooperating on product 
development, sponsors may establish a Public Master File (PMF) to allow all cooperators 
to reference the information.  As suggested by the name, the information in a PMF is 
publicly available. 
Regardless of how information is submitted to CVM, sponsors should submit an 
organized and focused information package.  This will allow CVM the best opportunity 
to provide appropriate recommendations in response.  Although full information may not 
be available in the early stages of the development process, the amount of information 
provided and the level of detail of the information provided should be commensurate 
with the submission type.  The information should address some or all of the following 
elements, as appropriate for the submission type:  
 
26 See CVM P&P Manual 1243.2400 Veterinary Master Files with Manufacturing Information (August 2019) 
  26  Contains Nonbinding Recommendations 
1.  The proposed COU, including the category of biomarker and its proposed use in 
biomarker development;  
2.  An assessment of the benefits and risks27 of the use of the biomarker for the proposed 
COU;  
3.  A description of the sponsors plan for analytical and clinical validation, as 
appropriate;  
4.  A discussion of known prior uses of the biomarker (e.g., in clinical practice settings, 
other countries, etc.); and 
5.  A statement regarding whether other FDA Centers have qualified the biomarker for 
the same or similar purposes in the target animal or other species. 
Additional questions and considerations specific to surrogate endpoints are presented in 
section IX. Establishing a Biomarker as a Surrogate Endpoint for Effectiveness Studies. 
XII.  References 
EMA, 2011. European Medicines Agency Guideline on Bioanalytical Method Validation 
available at: https://www.ema.europa.eu/en/documents/scientific-guideline/guideline-
bioanalytical-method-validation_en.pdf 
Fleming, TR and JH Powers. 2012. Biomarkers and surrogate endpoints in clinical trials. Stat 
Med 31(25): 2973-2984. 
Lee, JW, V Devanarayan, YC Barrett, R Weiner, J Allinson, S Fountain, S Keller, I Weinryb, M 
Green, L Duan, JA Rogers, R Millham, PJ O'Brien, J Sailstad, M Khan, C Ray, and JA Wagner. 
2006. Fit-for-purpose method development and validation for successful biomarker 
measurement. Pharm Res no. 23 (2):312-28. doi: 10.1007/s11095-005-9045-3. 
Myers, MJ, ER Smith, and PG Turfle. 2017. Biomarkers in Veterinary Medicine. Annu Rev 
Anim Biosci no. 5:65-87. doi: 10.1146/annurev-animal-021815-111431. 
Nguyen, SM, DH Thamm, DM Vail, and CA London. 2015. Response evaluation criteria for 
solid tumours in dogs (v1.0): a Veterinary Cooperative Oncology Group (VCOG) consensus 
document. Vet Comp Oncol 13(3): 176-183. 
Piccoli, SP, and JM Sauer. 2019. Points to Consider Document: Scientific and Regulatory 
Considerations for the Analytical Validation of Assays Used in the Qualification of Biomarkers 
in Biological Matrices. edited by Biomarker Assay Collaborative Evidentiary Considerations 
Writing Group. 
 
27 See footnote 5 on page 5 
  27