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RE: Using MCP-MOD in dose finding for Phase 3

From: Smith, Mike K <mike.k.smith>
Date: Mon, 23 Mar 2015 14:45:01 +0000

Dear Nele,

The EMA Scientific Advice on MCP-Mod is really worth reading here. http://=
All materials from the qualification:

Some key sentences from the CHMP qualification opinion:
"The MCP-Mod approach is efficient in the sense that it uses the available =
data better than the commonly applied pairwise comparisons.
It is fully appreciated that certain benefits that may be derived from an M=
CP-Mod approach would also be derived from other model-based approaches and=
 that modelling approaches are not restricted to those based on dose-respon=
se. MCP-Mod represents one tool in the toolbox of the well-informed drug de=
veloper. In that sense, this opinion does not preclude any other statistica=
l methodology for model-based design and analysis of exploratory dose findi=
ng studies from being used."

In other words - Many dose-response analyses that are seen by EMA use pairw=
ise comparisons between doses, despite ICH-E4 saying (>20 years ago) "Study=
 designs usually should emphasize elucidation of the dose-response function=
, not individual pairwise comparisons." So MCP-Mod meets that criteria ("on=
e tool in the toolbox"), as do the other methods you discuss. Many other ap=
proaches could (and should) be used to properly characterise and learn abou=
t Dose-Exposure-Response.

You can go to town in using a "fit all models" Bayesian model averaging tec=
hnique, but in the end "ALL models are wrong" and if you use that technique=
 then I'd guess that the majority would be "sub-optimal". Question is, how =
to best learn what's going on for your drug in this population so that you =
can then successfully pick a dose and confirm efficacy? I'm not sure there'=
s a "best" or one size fits all solution.

Prespecification means that you can easily write a protocol stats section a=
nd SAP, hand off the analysis to a third party and expect a result within 3=
 days of the database unblinding. Learning fully about the disease progress=
ion, pharmacology, characterising benefit risk takes a little more work, ti=
me and careful consideration however...


Mike K. Smith
Pfizer, Sandwich
Tel: +44 (0)1304 643561

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Received on Mon Mar 23 2015 - 10:45:01 EDT

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