RE: unbalanced data set

Dear Zheng, This is indeed a fundamental and recurring problem in drug development. You have rich data from Phase 1 studies (single ascending dose, multiple ascending dose, others e.g. QTc) and sparse data from Phase 3 studies. Should you mix them all in one large meta-analysis and derive the definitive popPK model for that drug/project? After years of experience, I tend to not mix Phase 1 with Phase 3 data. Phase 1 can be used to establish the first popPK model which may contain special features such as nonlinearities/saturation effects as a consequence of the wide range of doses studied. This can be the starting point for the building of a fit-for purpose model using Phase 3 data only. I have come to believe that the specific patient population(s) of Phase 3 require their own popPK model that predicts exposure without bias. This is then used in the exposure-response (E-R) modelling that is important for market approval. Only a dedicated Phase 3 popPK model, that does not carry unnecessary legacies of Phase 1 development, is fit for E-R modelling and can give the important answers about the dose rate(s) to be put in the drug label. I would be interested to hear some other opinions. Good luck, Joachim Joachim Grevel, PhD Scientific Director BAST Inc Limited Science & Enterprise Park Loughborough University Loughborough, LE11 3AQ United Kingdom Tel: +44 (0)1509 222908 www.bastinc.eu http://www.bastinc.eu/