alexa Comparability of Pharmacodynamics Profiles with an Appl
ISSN: 2155-6180

Journal of Biometrics & Biostatistics
Open Access

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Research Article

Comparability of Pharmacodynamics Profiles with an Application to a Biosimilar Study

Jason JZ Liao1*, Yifang Li2 and Xinhua Jiang3

1Merck & Co., Inc, North Wales, PA 19454, USA

2Novartis Pharmaceuticals Corporation, Cambridge, MA 02139, USA

3Beijing University of Chemical Technology, Beijing, P.R. China

*Corresponding Author:
Liao JJZ
Merck & Co., Inc
North Wales, PA 19454, P.R. China
Tel: 7175317178
E-mail: [email protected]

Received Date: April 20, 2017; Accepted Date: April 25, 2017; Published Date: April 28, 2017

Citation: Liao JJZ, Li Y, Jiang X (2017) Comparability of Pharmacodynamics Profiles with an Application to a Biosimilar Study. J Biom Biostat 8: 345. doi: 10.4172/2155-6180.1000345

Copyright: © 2017 Liao JJZ, et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

 

Abstract

It is often interest of comparing two pharmacodynamics (PD) profiles in drug development. Currently the common practice is borrowing the bioequivalence (BE) rule in pharmacokinetics analysis for pharmacodynamics comparison in terms of the area under the effect curve (AUEC) of the pharmacodynamics profile. However, this may not be a feasible and sensitive enough approach since the bioequivalence approach is based on the summarized parameter of the pharmacodynamics profile rather than on directly comparison of the whole pharmacodynamics profile. In this paper, a simple but efficient and pragmatic pharmacodynamics comparability index is proposed to evaluate the comparability of pharmacodynamics profiles by comparing the whole pharmacodynamics profiles directly. Different biological products have different variability and the CV% can be in a very large range. The PD comparability index can take account of the reference knowledge into consideration in assessment but the AUEC BE type approach ignores the reference variability. The good properties of the proposed approach are illustrated through simulated data and a real dataset.

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