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European Medicines Agency, 2017. Reproduction is authorised provided the source is acknowledged.

23 March 2017 1 EMA/CHMP/138502/2017 2 Committee for Human Medicinal Products (CHMP) 3

Reflection paper on statistical methodology for the 4 comparative assessment of quality attributes in drug 5 development 6 Draft 7

Disclaimer: This reflection paper has been written to provide current regulatory considerations 8 regarding statistical aspects for the comparative assessment of quality attributes where these are 9

used, or are proposed for use, in drug development and Marketing Authorisation Applications. It was 10 also prepared to invite comments in relation to the opportunities and limitations related to inferential 11 statistical methodology applied on quality attributes' data in the exploration of similarity of two drug 12 products. Whilst in some parts the paper describes Frequentists statistical methods, the field is also 13

open to explore alternative approaches, e.g. following Bayesian methodology. 14 The current document does not contain explicit guidance on which statistical approaches are most 15

suitable. It rather tries to establish a framework and a common language to facilitate future 16 discussions among stakeholders. 17

The content of this reflection paper and its implications shall be further discussed at a European 18 Medicines Agency's public work shop at the end of the 12-month public consultation phase. A longer 19 than usual consultation period will allow companies to come forward to EMA via interaction with the 20

Scientific Advice Working Party with proposals that may include the principles and methods discussed 21 in this document or alternative approaches that are not discussed in this document. 22

23

Draft agreed by Biostatistics Working Party February 2017

Adopted by CHMP for release for consultation 23 March 2017

Start of public consultation 01 April 2017

End of consultation (deadline for comments) 31 March 2018

24 Comments should be provided using this template. The completed comments form should be sent to RP-stats-QA@ema.europa.eu 25 Keywords Statistical methodology, comparative assessment, quality attributes,

drug development, manufacturing changes, biosimilars, generics, dissolution, inferential statistical methods, similarity assessment

http://www.ema.europa.eu/docs/en_GB/document_library/Template_or_form/2009/10/WC500004016.docmailto:RP-stats-QA@ema.europa.eu

Reflection paper on statistical methodology for the comparative assessment of quality attributes in drug development

EMA/CHMP/138502/2017 Page 2/24

Table of contents 26

Executive Summary ..................................................................................... 3 27

1. Introduction ............................................................................................ 4 28

2. Legal basis and relevant guidelines ......................................................... 5 29

3. Definitions and delineations .................................................................... 6 30

4. Settings where the comparison on the quality level is of particular 31 relevance in regulatory decision-making ..................................................... 7 32 4.1. Pre/post manufacturing change .............................................................................. 7 33 4.2. Biosimilar developments........................................................................................ 8 34 4.3. Other settings and generic developments ................................................................ 9 35

5. Approaching the comparison task from the statistical perspective and 36 associated obstacles .................................................................................. 10 37 5.1. The choice of characteristics to be compared and related comparison objectives ........ 10 38 5.1.1. Within-specification claim ................................................................................. 11 39 5.1.2. One-sided comparison objective, non-inferiority claim .......................................... 11 40 5.1.3. Two-sided comparison objective, similarity/equivalence claim ............................... 11 41 5.2. Understanding sources of variability in quality data and 'the unit of observation' ........ 12 42 5.3. Random Sampling / Experimental Approach........................................................... 12 43 5.4. Finding a metric to describe the difference between two manufacturing processes ...... 13 44 5.5. Statistical intervals to quantify uncertainty of claims based on sample data ............... 13 45 5.5.1. Comparison approaches based on intervals commonly seen .................................. 14 46 5.5.2. Guiding principles for the use/computation of statistical intervals for QA data 47 comparison .............................................................................................................. 15 48 5.6. Definition/justification of an equivalence/similarity criterion, acceptance range .......... 16 49 5.7. Defining an overall 'success criterion' to claim equivalence/similarity in presence of a 50 large number of QAs ................................................................................................. 16 51

6. Reflections of issues raised, implications for planning and assessment 17 52 6.1. Specific issues for the pre/post-manufacturing change setting ................................. 19 53 6.2. Specific issues for Biosimilar setting...................................................................... 19 54 6.3. Specific issues for generic/hybrid developments and dissolution comparisons ............ 21 55

7. Appendix ............................................................................................... 22 56

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Reflection paper on statistical methodology for the comparative assessment of quality attributes in drug development

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Executive Summary 58

This reflection paper identifies three areas of interest from the regulatory perspective, where the 59 comparative evaluation of drug products quality characteristics plays an important role, either during 60 drug development, during drug lifecycle, or during in decision making processes potentially leading to 61 marketing authorisation. The document focusses on methodological aspects in relation to statistical 62 data-comparison approaches for the settings of: pre- and post-manufacturing change, biosimilar 63 developments as well as generics development. For all these settings defined, the reflection paper 64 raises open issues from a statistical perspective addressing question related to comparison objectives, 65 sampling strategies, sources of variability, options for statistical inference and acceptance ranges. 66

This document is targeted to both, experts from industry and regulatory assessors. The paper tries to 67 connect to other available regulatory guidance where the issue of comparative data assessment 68 concerning quality attributes is discussed for certain contexts, but where more detailed guidance of 69 how to actually carry out the comparison task (based on empirical sample data) is lacking. 70

From the methodological perspective, the reflection paper is supposed to establish a common language 71 and to improve understanding among all experts concerned with quality characteristics data 72 comparison. It is also supposed to trigger further discussion of realistic requirements to demonstrate 73 'similarity on the quality level' in the different contexts mentioned above. The paper however also 74 discusses likely limitations hampering statistical inference, pointing towards meaningful but 75 expectedly less stringent alternatives. 76

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1. Introduction 77

Comparison of empirical data from quality characteristics of drug products (quality attributes) is of 78 importance in many areas of drug development. There are at least three areas where the comparative 79 evaluation of quality characteristics plays a major role in decision making on the manufacturer's as 80 well as on the regulator's side: 81

the comparison of a particular drug product in versions pre- and post-manufacturing change, 82 the comparison of a candidate biosimilar product to a reference medicinal product, 83 the comparison of a candidate generic product to the reference medicinal product; 84

In these areas, many different methodological approaches to set up a framework for the comparison of 85 quality characteristics are followed and often require regulatory assessment. In many instances, the 86 suggested comparison approach contains statistical elements in order to support the assertion that the 87 quality profile of two (versions of a) drug products can be considered similar. This frequently involves 88 the definition of 'similarity'-criteria, mostly based on information regarding known or expected 89 variability of quality data associated with the underlying manufacturing processes. However, 90 conclusions drawn from comparative data analyses (e.g. "a manufacturing change has not substantially 91 altered the product quality") are often based on rather limited information available, e.g. a small 92 number of manufacturing batches. 93

Making use of inferential statistical methods means quantify