Case: 1:16-cv-00651 Document #: 120-3 Filed: 07/15/18 Page 1 of 22 PageID #:4856
`Case: 1:16-cv—00651 Document #: 120-3 Filed: 07/15/18 Page 1 of 22 PageID #:4856
`
`EXHIBIT (cid:38)
`
`EXHIBIT
`
`

`

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`
`Guidance for Industry
`Q1E Evaluation of
`Stability Data
`
`U.S. Department of Health and Human Services
`Food and Drug Administration
`Center for Drug Evaluation and Research (CDER)
`Center for Biologics Evaluation and Research (CBER)
`
`June 2004
`ICH
`
`

`

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`
`Guidance for Industry
`Q1E Evaluation of
`Stability Data
`
`Additional copies are available from:
`
`Office of Training and Communication
`Division of Drug Information, HFD-240
`Center for Drug Evaluation and Research
`Food and Drug Administration
`5600 Fishers Lane
`Rockville, MD 20857
`(Tel) 301-827-4573
` http://www.fda.gov/cder/guidance/index.htm
`
`Office of Communication, Training, and
`Manufacturers Assistance, HFM-40
`Center for Biologics Evaluation and Research
` Food and Drug Administration
`1401 Rockville Pike, Rockville, MD 20852-1448
` http://www.fda.gov/cber/guidelines.htm.
` (Tel) Voice Information System at 800-835-4709 or 301-827-1800
`
`U.S. Department of Health and Human Services
`Food and Drug Administration
`Center for Drug Evaluation and Research (CDER)
`Center for Biologics Evaluation and Research (CBER)
`
`June 2004
`ICH
`
`

`

`Case: 1:16-cv-00651 Document #: 120-3 Filed: 07/15/18 Page 4 of 22 PageID #:4859
`
`TABLE OF CONTENTS
`
`INTRODUCTION (1.0)........................................................................................................ 1
`I.
`II. EVALUATION OF STABILITY DATA (2.0) .................................................................. 2
`A. General Principles (2.1).................................................................................................................2
`B. Data Presentation (2.2) ..................................................................................................................3
`C. Extrapolation (2.3).........................................................................................................................4
`D. Data Evaluation for Retest Period or Shelf Life Estimation for Drug Substances or Products
`Intended for Room Temperature Storage (2.4)...........................................................................4
`E. Data Evaluation for Retest Period or Shelf Life Estimation for Drug Substances or Products
`Intended for Storage Below Room Temperature (2.5) ...............................................................6
`F. General Statistical Approaches (2.6)............................................................................................8
`Appendix A: Decision Tree for Data Evaluation for Retest Period or Shelf Life Estimation for
`Drug Substances or Products (Excluding Frozen Products)....................................................10
`Appendix B: Examples of Statistical Approaches to Stability Data Analysis................................11
`
`

`

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`Contains Nonbinding Recommendations
`
`Guidance for Industry1
`Q1E Evaluation of Stability Data
`
`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.
`An alternative approach may be used if such 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 (1.0)2
`
`This guidance provides recommendations on how to use stability data generated in accordance
`with the principles detailed in the ICH guidance Q1A(R2) Stability Testing of New Drug
`Substances and Products (parent guidance) to propose a retest period or shelf life in a
`registration application. This guidance describes when and how extrapolation can be considered
`when proposing a retest period for a drug substance or a shelf life for a drug product that extends
`beyond the period covered by available data from the stability study under the long-term storage
`condition (long-term data).
`
`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 recommendations in the evaluation and statistical analysis of stability data provided in the
`parent guidance are brief in nature and limited in scope. The parent guidance states that
`regression analysis is an appropriate approach to analyzing quantitative stability data for retest
`
`
`1 This guidance was developed within the Expert Working Group (Quality) of the International Conference on
`Harmonisation of Technical Requirements for Registration of Pharmaceuticals for Human Use (ICH) and has been
`subject to consultation by the regulatory parties, in accordance with the ICH process. This document has been
`endorsed by the ICH Steering Committee at Step 4 of the ICH process, February 2003. At Step 4 of the process, the
`final draft is recommended for adoption to the regulatory bodies of the European Union, Japan, and the United
`States.
`
`2 Arabic numbers reflect the organizational breakdown in the document endorsed by the ICH Steering Committee at
`Step 4 of the ICH process, February 2003.
`
`1
`
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`Contains Nonbinding Recommendations
`
`period or shelf life estimation and recommends that a statistical test for batch poolability be
`performed using a level of significance of 0.25. However, the parent guidance includes few
`details and does not cover situations where multiple factors are involved in a full- or reduced-
`design study. This guidance expands the recommendations presented in the evaluation sections
`of the parent guidance.
`
`This guidance covers:
`
`• The evaluation of stability data that should be submitted in registration applications for new
`molecular entities and associated drug products.
`• Recommendations on the establishment of retest periods and shelf lives for drug substances
`and drug products intended for storage at or below room temperature.*
`• Stability studies using single- or multi-factor designs and full or reduced designs.
`
`*Note: The term room temperature refers to the general customary environment and should not
`be inferred to be the storage statement for labeling.
`
`ICH Q6A and Q6B should be consulted for recommendations on the setting and justification of
`acceptance criteria, and ICH Q1D should be referenced for recommendations on the use of full-
`versus reduced-design studies.
`
`II.
`
`EVALUATION OF STABILITY DATA (2.0)
`
`A.
`
`General Principles (2.1)
`
`The design and execution of formal stability studies should follow the principles outlined in the
`parent guidance. The purpose of a stability study is to establish, based on testing a minimum of
`three batches of the drug substance or product, a retest period or shelf life and label storage
`instructions applicable to all future batches manufactured and packaged under similar
`circumstances. The degree of variability of individual batches affects the confidence that a
`future production batch will remain within acceptance criteria throughout its retest period or
`shelf life.
`
`Although normal manufacturing and analytical variations are to be expected, it is important that
`the drug product be formulated with the intent to provide 100 percent of the labeled amount of
`the drug substance at the time of batch release. If the assay values of the batches used to support
`the registration application are higher than 100 percent of label claim at the time of batch release,
`after taking into account manufacturing and analytical variations, the shelf life proposed in the
`application can be overestimated. On the other hand, if the assay value of a batch is lower than
`100 percent of label claim at the time of batch release, it might fall below the lower acceptance
`criterion before the end of the proposed shelf life.
`
`A systematic approach should be adopted in the presentation and evaluation of the stability
`information. The stability information should include, as appropriate, results from the physical,
`chemical, biological, and microbiological tests, including those related to particular attributes of
`the dosage form (for example, dissolution rate for solid oral dosage forms). The adequacy of the
`
`2
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`

`

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`Contains Nonbinding Recommendations
`
`mass balance should be assessed. Factors that can cause an apparent lack of mass balance should
`be considered, including, for example, the mechanisms of degradation and the stability-
`indicating capability and inherent variability of the analytical procedures.
`
`The basic concepts of stability data evaluation are the same for single- versus multi-factor studies
`and for full- versus reduced-design studies. Data from formal stability studies and, as
`appropriate, supporting data should be evaluated to determine the critical quality attributes likely
`to influence the quality and performance of the drug substance or product. Each attribute should
`be assessed separately, and an overall assessment should be made of the findings for the purpose
`of proposing a retest period or shelf life. The retest period or shelf life proposed should not
`exceed that predicted for any single attribute.
`
`The decision tree in Appendix A outlines a stepwise approach to stability data evaluation and
`when and how much extrapolation can be considered for a proposed retest period or shelf life.
`Appendix B provides (1) information on how to analyze long-term data for appropriate
`quantitative test attributes from a study with a multi-factor, full, or reduced design, (2)
`information on how to use regression analysis for retest period or shelf life estimation, and (3)
`examples of statistical procedures to determine poolability of data from different batches or other
`factors. Additional guidance can be found in the references listed; however, the examples and
`references do not cover all applicable statistical approaches.
`
`In general, certain quantitative chemical attributes (e.g., assay, degradation products,
`preservative content) for a drug substance or product can be assumed to follow zero-order
`kinetics during long-term storage (Carstensen 1977). Data for these attributes are therefore
`amenable to the type of statistical analysis described in Appendix B, including linear regression
`and poolability testing. Although the kinetics of other quantitative attributes (e.g., pH,
`dissolution) is generally not known, the same statistical analysis can be applied, if appropriate.
`Qualitative attributes and microbiological attributes are not amenable to this kind of statistical
`analysis.
`
`The recommendations on statistical approaches in this guidance are not intended to imply that
`use of statistical evaluation is preferred when it can be justified to be unnecessary. However,
`statistical analysis can be useful in supporting the extrapolation of retest periods or shelf lives in
`certain situations and can be critical in verifying the proposed retest periods or shelf lives in
`other cases.
`
`B.
`
`Data Presentation (2.2)
`
`Data for all attributes should be presented in an appropriate format (e.g., tabular, graphical,
`narrative) and an evaluation of such data should be included in the application. The values of
`quantitative attributes at all time points should be reported as measured (e.g., assay as percent of
`label claim). If a statistical analysis is performed, the procedure used and the assumptions
`underlying the model should be stated and justified. A tabulated summary of the outcome of
`statistical analysis and/or graphical presentation of the long-term data should be included.
`
`3
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`Contains Nonbinding Recommendations
`
`C.
`
`Extrapolation (2.3)
`
`Extrapolation is the practice of using a known data set to infer information about future data.
`Extrapolation to extend the retest period or shelf life beyond the period covered by long-term
`data can be proposed in the application, particularly if no significant change is observed at the
`accelerated condition. Whether extrapolation of stability data is appropriate depends on the
`extent of knowledge about the change pattern, the goodness of fit of any mathematical model,
`and the existence of relevant supporting data. Any extrapolation should be performed in such a
`way that the extended retest period or shelf life will be valid for a future batch released with test
`results close to the release acceptance criteria.
`
`An extrapolation of stability data assumes that the same change pattern will continue to apply
`beyond the period covered by long-term data. The correctness of the assumed change pattern is
`critical when extrapolation is considered. When estimating a regression line or curve to fit the
`long-term data, the data themselves provide a check on the correctness of the assumed change
`pattern, and statistical methods can be applied to test the goodness of fit of the data to the
`assumed line or curve. No such internal check is possible beyond the period covered by long-
`term data. Thus, a retest period or shelf life granted on the basis of extrapolation should always
`be verified by additional long-term stability data as soon as these data become available. Care
`should be taken to include in the protocol for commitment batches a time point that corresponds
`to the end of the extrapolated retest period or shelf life.
`
`D.
`
`Data Evaluation for Retest Period or Shelf Life Estimation for Drug
`Substances or Products Intended for Room Temperature Storage (2.4)
`
`A systematic evaluation of the data from formal stability studies should be performed as
`illustrated in this section. Stability data for each attribute should be assessed sequentially. For
`drug substances or products intended for storage at room temperature, the assessment should
`begin with any significant change at the accelerated condition and, if appropriate, at the
`intermediate condition, and progress through the trends and variability of the long-term data.
`The circumstances are delineated under which extrapolation of retest period or shelf life beyond
`the period covered by long-term data can be appropriate. A decision tree is provided in
`Appendix A as an aid.
`
`1.
`
`No significant change at accelerated condition (2.4.1)
`
`Where no significant change occurs at the accelerated condition, the retest period or shelf life
`would depend on the nature of the long-term and accelerated data.
`
`a.
`
`Long-term and accelerated data showing little or no change over time and
`little or no variability (2.4.1.1)
`
`Where the long-term data and accelerated data for an attribute show little or no change over time
`and little or no variability, it might be apparent that the drug substance or product will remain
`well within the acceptance criteria for that attribute during the proposed retest period or shelf
`life. In these circumstances, a statistical analysis is normally considered unnecessary but
`
`4
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`Contains Nonbinding Recommendations
`
`justification for the omission should be provided. Justification can include a discussion of the
`change pattern or lack of change, relevance of the accelerated data, mass balance, and/or other
`supporting data as described in the parent guidance. Extrapolation of the retest period or shelf
`life beyond the period covered by long-term data can be proposed. The proposed retest period or
`shelf life can be up to twice as long as, but should not be more than 12 months beyond, the
`period covered by long-term data.
`
`b.
`
`Long-term or accelerated data showing change over time and/or variability
`(2.4.1.2)
`
`If the long-term or accelerated data for an attribute show change over time and/or variability
`within a factor or among factors, statistical analysis of the long-term data can be useful in
`establishing a retest period or shelf life. Where there are differences in stability observed among
`batches or among other factors (e.g., strength, container size, and/or fill) or factor combinations
`(e.g., strength-by-container size and/or fill) that preclude the combining of data, the proposed
`retest period or shelf life should not exceed the shortest period supported by any batch, other
`factor, or factor combination. Alternatively, where the differences are readily attributed to a
`particular factor (e.g., strength), different shelf lives can be assigned to different levels within the
`factor (e.g., different strengths). A discussion should be provided to address the cause for the
`differences and the overall significance of such differences on the product. Extrapolation beyond
`the period covered by long-term data can be proposed; however, the extent of extrapolation
`would depend on whether long-term data for the attribute are amenable to statistical analysis.
`
`• Data not amenable to statistical analysis
`
`Where long-term data are not amenable to statistical analysis, but relevant supporting data are
`provided, the proposed retest period or shelf life can be up to one-and-a-half times as long as, but
`should not be more than 6 months beyond, the period covered by long-term data. Relevant
`supporting data include satisfactory long-term data from development batches that are (1) made
`with a closely related formulation to, (2) manufactured on a smaller scale than, or (3) packaged
`in a container closure system similar to, that of the primary stability batches.
`
`• Data amenable to statistical analysis
`
`If long-term data are amenable to statistical analysis but no analysis is performed, the extent of
`extrapolation should be the same as when data are not amenable to statistical analysis. However,
`if a statistical analysis is performed, it can be appropriate to propose a retest period or shelf life
`of up to twice as long as, but not more than 12 months beyond, the period covered by long-term
`data, when the proposal is backed by the result of the analysis and relevant supporting data.
`
`2.
`
`Significant change at accelerated condition (2.4.2)
`
`Where significant change* occurs at the accelerated condition, the retest period or shelf life will
`depend on the outcome of stability testing at the intermediate condition, as well as at the long-
`term condition.
`
`5
`
`

`

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`Contains Nonbinding Recommendations
`
`*Note: The following physical changes can be expected to occur at the accelerated condition
`and would not be considered significant change that calls for intermediate testing if there is no
`other significant change:
`
`• Softening of a suppository that is designed to melt at 37ºC, if the melting point is clearly
`demonstrated.
`• Failure to meet acceptance criteria for dissolution for 12 units of a gelatin capsule or gel-
`coated tablet if the failure can be unequivocally attributed to cross-linking.
`
`However, if phase separation of a semi-solid dosage form occurs at the accelerated condition,
`testing at the intermediate condition should be performed. Potential interaction effects should
`also be considered in establishing that there is no other significant change.
`
`a.
`
`No significant change at intermediate condition (2.4.2.1)
`
`If there is no significant change at the intermediate condition, extrapolation beyond the period
`covered by long-term data can be proposed; however, the extent of extrapolation would depend
`on whether long-term data for the attribute are amenable to statistical analysis.
`
`• Data not amenable to statistical analysis
`
`When the long-term data for an attribute are not amenable to statistical analysis, the proposed
`retest period or shelf life can be up to 3 months beyond the period covered by long-term data, if
`backed by relevant supporting data.
`
`• Data amenable to statistical analysis
`
`When the long-term data for an attribute are amenable to statistical analysis but no analysis is
`performed, the extent of extrapolation should be the same as when data are not amenable to
`statistical analysis. However, if a statistical analysis is performed, the proposed retest period or
`shelf life can be up to one-and-half times as long as, but should not be more than 6 months
`beyond, the period covered by long-term data, when backed by statistical analysis and relevant
`supporting data.
`
`b.
`
`Significant change at intermediate condition (2.4.2.2)
`
`Where significant change occurs at the intermediate condition, the proposed retest period or shelf
`life should not exceed the period covered by long-term data. In addition, a retest period or shelf
`life shorter than the period covered by long-term data can be appropriate.
`
`E.
`
`Data Evaluation for Retest Period or Shelf Life Estimation for Drug
`Substances or Products Intended for Storage Below Room Temperature (2.5)
`
`6
`
`

`

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`Contains Nonbinding Recommendations
`
`1.
`
`Drug substances or products intended for storage in a refrigerator (2.5.1)
`
`Data from drug substances or products intended to be stored in a refrigerator should be assessed
`according to the same principles as described in section II.D for drug substances or products
`intended for room temperature storage, except where explicitly noted in the section below. The
`decision tree in Appendix A can be used as an aid.
`
`a.
`
`No significant change at accelerated condition (2.5.1.1)
`
`Where no significant change occurs at the accelerated condition, extrapolation of retest period or
`shelf life beyond the period covered by long-term data can be proposed based on the principles
`outlined in section II.D.1, except that the extent of extrapolation should be more limited.
`
`If the long-term and accelerated data show little change over time and little variability, the
`proposed retest period or shelf life can be up to one-and-a-half times as long as, but should not
`be more than 6 months beyond, the period covered by long-term data normally without the
`support of statistical analysis.
`
`Where the long-term or accelerated data show change over time and/or variability, the proposed
`retest period or shelf life can be up to 3 months beyond the period covered by long-term data if
`(1) the long-term data are amenable to statistical analysis but a statistical analysis is not
`performed, or (2) the long-term data are not amenable to statistical analysis but relevant
`supporting data are provided.
`
`Where the long-term or accelerated data show change over time and/or variability, the proposed
`retest period or shelf life can be up to one-and-a-half times as long as, but should not be more
`than 6 months beyond, the period covered by long-term data if (1) the long-term data are
`amenable to statistical analysis and a statistical analysis is performed, and (2) the proposal is
`backed by the result of the analysis and relevant supporting data.
`
`b.
`
`Significant change at accelerated condition (2.5.1.2)
`
`If significant change occurs between 3 and 6 months’ testing at the accelerated storage condition,
`the proposed retest period or shelf life should be based on the long-term data. Extrapolation is
`not considered appropriate. In addition, a retest period or shelf life shorter than the period
`covered by long-term data could be appropriate. If the long-term data show variability,
`verification of the proposed retest period or shelf life by statistical analysis can be appropriate.
`
`If significant change occurs within the first 3 months’ testing at the accelerated storage
`condition, the proposed retest period or shelf life should be based on long-term data.
`Extrapolation is not considered appropriate. A retest period or shelf life shorter than the period
`covered by long-term data could be appropriate. If the long-term data show variability,
`verification of the proposed retest period or shelf life by statistical analysis can be appropriate.
`In addition, a discussion should be provided to address the effect of short-term excursions
`outside the label storage condition (e.g., during shipping or handling). This discussion can be
`
`7
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`

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`Contains Nonbinding Recommendations
`
`supported, if appropriate, by further testing on a single batch of the drug substance or product at
`the accelerated condition for a period shorter than 3 months.
`
`2.
`
`Drug substances or products intended for storage in a freezer (2.5.2)
`
`For drug substances or products intended for storage in a freezer, the retest period or shelf life
`should be based on long-term data. In the absence of an accelerated storage condition for drug
`substances or products intended to be stored in a freezer, testing on a single batch at an elevated
`temperature (e.g., 5°C ± 3°C or 25°C ± 2°C) for an appropriate time period should be conducted
`to address the effect of short-term excursions outside the proposed label storage condition (e.g.,
`during shipping or handling).
`
`3.
`
`Drug substances or products intended for storage below -20°C (2.5.3)
`
`For drug substances or products intended for storage below -20°C, the retest period or shelf life
`should be based on long-term data and should be assessed on a case-by-case basis.
`
`F.
`
`General Statistical Approaches (2.6)
`
`Where applicable, an appropriate statistical method should be employed to analyze the long-term
`primary stability data in an original application. The purpose of this analysis is to establish, with
`a high degree of confidence, a retest period or shelf life during which a quantitative attribute will
`remain within acceptance criteria for all future batches manufactured, packaged, and stored
`under similar circumstances.
`
`In cases where a statistical analysis was employed to evaluate long-term data due to a change
`over time and/or variability, the same statistical method should also be used to analyze data from
`commitment batches to verify or extend the originally approved retest period or shelf life.
`
`Regression analysis is considered an appropriate approach to evaluating the stability data for a
`quantitative attribute and establishing a retest period or shelf life. The nature of the relationship
`between an attribute and time will determine whether data should be transformed for linear
`regression analysis. The relationship can be represented by a linear or nonlinear function on an
`arithmetic or logarithmic scale. In some cases, a nonlinear regression can better reflect the true
`relationship.
`
`An appropriate approach to retest period or shelf life estimation is to analyze a quantitative
`attribute (e.g., assay, degradation products) by determining the earliest time at which the 95
`percent confidence limit for the mean intersects the proposed acceptance criterion.
`
`For an attribute known to decrease with time, the lower one-sided 95 percent confidence limit
`should be compared to the acceptance criterion. For an attribute known to increase with time,
`the upper one-sided 95 percent confidence limit should be compared to the acceptance criterion.
`For an attribute that can either increase or decrease, or whose direction of change is not known,
`two-sided 95 percent confidence limits should be calculated and compared to the upper and
`lower acceptance criteria.
`
`8
`
`

`

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`Contains Nonbinding Recommendations
`
`The statistical method used for data analysis should take into account the stability study design to
`provide a valid statistical inference for the estimated retest period or shelf life. The approach
`described above can be used to estimate the retest period or shelf life for a single batch or for
`multiple batches when the data are combined after an appropriate statistical test. Examples of
`statistical approaches to the analysis of stability data from single or multi-factor, full- or reduced-
`design studies are included in Appendix B. References to current literature sources can be
`found in Appendix B.6.
`
`APPENDICES (3)
`
`9
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`

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`Contains Nonbinding Recommendations
`
`Appendix A: Decision Tree for Data Evaluation for Retest Period or Shelf Life
`Estimation for Drug Substances or Products (Excluding Frozen Products)
`
`Tabulate and/or plot
`stability data on all
`attributes at all storage
`conditions and evaluate
`each attribute separately
`
`Significant
`change at
`accelerated
`condition within
`6 months?
`
`No
`
`No extrapolation; shorter
`retest period or shelf life and
`data covering excursions
`can be appropriate;
`statistical analysis if long-
`term data show variability
`
`Yes
`
`Significant
`change at
`accelerated
`condition within
`3 months?
`
`Yes
`
`No
`
`Yes
`
`Intended
`to be stored in a
`refrigerator?
`
`No
`
`Significant
`change
`at intermediate
`condition?
`
`Yes
`
`No extrapolation; shorter
`retest period or shelf life
`can be appropriate;
`statistical analysis if long-
`term data show variability
`
`Long- term
`data show: (1) little or
`no change over time
`and (2) little or no
`variability?
`
`No to (1) or
`(2) or both
`
`Yes to both
`
`Accelerated
`data show: (1) little or
`no change over time
`and (2) little or no
`variability?
`
`No to (1) or
`(2) or both
`
`(1) Long- term
`data amenable to
`statistical analysis and
`(2) statistical analysis
`performed?
`
`No to (1)
`or (2)
`
`Yes to both
`
`Yes to both
`
`No
`
`(1) Long- term
`data amenable to
`statistical analysis and
`(2) statistical analysis
`performed?
`
`Yes to both
`
`No to (1)
`or (2)
`
`If backed by relevant
`supporting data:
`Y = up to X + 3 months
`
`If backed by statistical
`analysis and relevant
`supporting data: Y = up
`to 1.5X, but not
`exceeding X + 6 months
`
`Statistical analysis
`is normally
`unnecessary
`
`Y = Proposed retest period or shelf life
`X = Period covered by long-term data
`
`Y= up to 2X, but not
`exceeding X + 12 months;
` or if refrigerated,
`Y = up to 1.5X, but not
`exceeding X + 6 months
`
`If backed by statistical
`analysis and relevant
`supporting data: Y = up to
`2X, but not exceeding X +
`12 months; or if refrigerated,
`Y = up to 1.5X, but not
`exceeding X + 6 months
`
`If backed by relevant
`supporting data: Y = up
`to 1.5X, but not
`exceeding X + 6 months;
`or if refrigerated, Y = up
`to X + 3 months
`
`10
`
`

`

`Case: 1:16-cv-00651 Document #: 120-3 Filed: 07/15/18 Page 15 of 22 PageID #:4870
`Contains Nonbinding Recommendations
`
`Appendix B: Examples of Statistical Approaches to Stability Data Analysis
`
`Linear regression, poolability tests, and statistical modeling, described below, are examples of
`statistical methods and procedures that can be used in the analysis of stability data that are
`amenable to statistical analysis for a quantitative attribute for which there is a proposed
`acceptance criterion.
`
`B.1
`
`Data Analysis for a Single Batch
`
`In general, the relationship between certain quantitative attributes and time is assumed to be
`linear (Carstensen 1977). Figure 1 (page 18) shows the regression line for assay of a drug
`product with upper and lower acceptance criteria of 105 percent and 95 percent of label claim,
`respectively, with 12 months of long-term data and a proposed shelf life of 24 months. In this
`example, two-sided 95 percent confidence limits for the mean are applied because it is not
`known ahead of time whether the assay would increase or decrease with time (e.g., in the case of
`an aqueous-based product packaged in a semi-permeable container). The lower confidence limit
`intersects the lower acceptance criterion at 30 months, while the upper confidence limit does not
`intersect with the upper acceptance criterion until later. Therefore, the proposed shelf life of 24
`months can be supported by the statistical analysis of the assay, provided the recommendations
`in sections II.D and II.E are followed.
`
`When data for an attribute with only an upper or a lower acceptance criterion are analyzed, the
`corresponding one-sided 95 percent confidence limit for the mean is recommended. Figure 2
`(page 18) shows the regression line for a degradation product in