What is comparability? An updated perspective. Martijn van der Plas MEB

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2 What is comparability? An updated perspective Martijn van der Plas Senior assessor CBG MEB, Netherlands Personal views only, meant to initiate further discussion; may not necessarily reflect views/opinions of MEB, EMA or EDQM. I am not a statistician, nor do I pretend to be.

3 Historic roots of comparability The concept of comparability was developed late 1990s, as a pragmatic way to deal with manufacturing changes. FDA 1996; EMA 2000 FDA 1996: two products are comparable if the results of the comparability testing demonstrate that the manufacturing change does not affect safety, identity, purity, or potency.

4 Comparability: ICH Q5E (2004) Comparable A conclusion that products have highly similar quality attributes before and after manufacturing process changes and that no adverse impact on the safety or efficacy, including immunogenicity, of the drug product occurred. The body text of the latter guideline further stipulates that The demonstration of comparability does not necessarily mean that the quality attributes of the pre-change and post-change product are identical, but that they are highly similar and that the existing knowledge is sufficiently predictive to ensure that any differences in quality attributes have no adverse impact upon safety or efficacy of the drug product.

5 Comparability: ICH Q5E (2004) Remainder of guideline provides a number of considerations Importance of sensitive analytical techniques High flexibility/case by case approach implicit to tekst Guideline does not further discuss criteria and (statistical) methodology Formal statistics not/rarely used at that point in time

6 Happy state of affairs Guideline sufficiently clear to be useful Guideline not overtly prescriptive; provides flexibility Scientific driven case by case approach If it works, it ain t stupid However, some fundamental issues were never addressed.

7 Fundamental issues Different contexts of comparability CQA assessment and ranking ( criticality ) How to treat Low level CQAs Ranges or equivalence? Should (selected) parameters be equivalent? Implications for statistical methodology

8 Analytical comparability Not a guidance term but regularly used in regulatory practice The part of the comparability exercise which relies on physico-chemical and in vitro biological ( analytical ) data. This includes cell-free receptor binding (ELISA, SPR and comparable formats) Cell based assays borderline cases

9 Three contexts of comparability Manufacturing change comparability Original 1996 trigger for guidance Biosimilarity Same scientific base; compare A to B and link/extrapolate clinical data, see inter alia Weise et al. Blood 2012 Comparability during development Different from other two, in that the strict criterion of no impact on safety/efficacy may not be applicable; more fluid situation Usually: Are pre change (e.g. phase 1) data relevant for commercial product; establishment of benefit/risk?

10 CQA ranking (1) A product may have Quality Attributes which can be considered critical or at least somehow relevant Some form of ranking/filtering necessary Fingerprinting approach How many categories do you need? 3 tier approach suggested by US FDA scientists Red/orange/yellow/green; 5; or more? No EU guidance; company is free to choose a suitable approach

11 CQA ranking tool (2) Tools which are aimed/optimised for a binary assessment ( is it a CQA or not ), are not automatically suitable for finer granularity Severity x Uncertainty approaches tend to underestimate the I know it is Severe cases Corrections to deal with this often only compatible with binary assignments Ranking requires robust scientific knowledge about clinical relevance Cf. specifications for MAbs; specification often 95-99% monomer Human IvIG from plasma: Ph. Eur. monomer + dimer > 90%; multimers < 3% (dose g/kg)

12 Comparability ranges (1) Comparability ranges not a Q5E concept However, concept flows logically from assumptions in Q5E Commonly used, either explicitly or implicitly, for >20 years Whole range for a CQA is qualified/acceptable Mentioned in EU Quality biosimilar guideline, but actually independent of context Material B (post change) is comparable to A, if it is within the historical range of A If material B not within historical range of A, further justification to be provided why this is acceptable Approach in line with Q5E Increased scrutiny whether justification is sufficient

13 Comparability ranges (2) How to establish historical range? Manufacturing change context: (Extremely) large dataset for specification/routine test; not always for extended characterisation testing Additional characterisation may be limited with regard to number tests, and/or not performed on all pre-change batches Post-change dataset limited Biosimilar context: Dataset may be large; but issues with sampling/data being independent (only DP sampled; one DS may result in several correlated DPs) Comparability during development Common pitfalls: No retain samples, insufficient characterisation during early development, rushed to FIH.

14 Comparability ranges (3) How to establish historical range? Often limited/no option to enlarge dataset (pre- or post-) Basically two approaches: Min-Max, use all the available data as is Transform data into an interval using statistics Tolerance Interval commonly used, other Intervals sometimes promoted Discussions about which type of Interval to use may become irrelevant because actual Intervals often overlap. However, any comparability exercise should be internally consistent in this respect!

15 Low level CQAs: ranking and ranges Low level of an attribute = lower risk? In practice, low level is commonly accepted as low(er) risk Clearly stated for process related impurities Cf. EU biosimilarity quality guidance, with regard to process related impurities In contrast, process-related impurities may differ between the originator and biosimilar products, although these [impurities] should be minimised. (EMA Quality biosimilarity Guideline) No firm requirement for being in the same range Scientifically not meaningful Quantitative differences (if qualitatively the same) in absolute terms small

16 Low level CQAs: ranking and ranges Same scientific reasoning applies to product related impurities Low level of product related substance/impurity; Acceptable if below threshold(?); irrespective of range Which threshold? Cf. qualification limits for chemicals Cf. Aggregates in MAbs vs. Human IvIG from plasma Lower (not necessarily low) level acceptable w/o further justification? Common precedent

17 Ranges or equivalence? (1) Comparability ranges de facto accepted since 1990s Cf. EU biosimilarity quality guidance Strong scientific rationale The range can be considered clinically qualified Should (selected) CQAs be equivalent? In a formal, statistical sense? This would be at odds with Q5E which does not require that quality attributes are identical

18 Ranges or equivalence? (2) Equivalence seems to suppose that a certain Quality Attribute is batch independent Variation in parameter values is then only caused by analytical variability ; there is one underlying ( true ) value. This may actually only be correct for a small number of trivial CQAs; it is certainly not true for many relevant CQAs. Need both populations be statistically equivalent? (postchange population comparability also assured by specification control). Fundamental difference between Repeated measurement of the same batch/sample and Measurement of repeated (new) batches Fixed Mean vs Drifting Mean

19 3 tier system Suggested by FDA scientists Each tier linked to specific criterion (equivalence; ranges; raw/graphical) Intuitively attractive Is three the right number? Two? Four? Five? Continuum? Can each tier/category indeed be linked to a specific statistical criterion, which can then be formalised/tested statistically? Is this a valid link; is indeed the most suitable test chosen? Physicochemical assumptions valid?

20 Statistical methodology? Recent addition to scientific/regulatory toolbox Comparability >20 yrs; statistics approx. 5 yrs. Current approach seems to go from methodology to criteria From criteria to methodology would be more focussed Take into account a number of conditions/limitations Low number of batches High number of CQAs Intrinsic variability/drift of CQAs Sampling limitations Clinical biostatistics therefore not a suitable template for comparability statistics

21 Conclusion Comparability has been around for 20 years, this implies an enormous knowledge base Knowledge base is effectively used but codification is limited Further codification would be helpful regarding CQA ranking Criteria for judging if, for a certain CQA, a (meaningful) difference exists; or if it is considered similar Discussions regarding statistical tools/metrics will become easier if such criteria are made more explicit

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