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Reference Scaled Average Bioequivalence: Scaling Approach For The Highly Variable Drugs

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International Journal of Pharmaceutical Research and Innovation, Vol. 4:20-21, 2011
REFERENCE SCALED AVERAGE BIOEQUIVALENCE: SCALING APPROACH FOR THE HIGHLY VARIABLE DRUGS

Jagruti Desai , Priyanka Jain

1 Novartis Healthcare Ltd, Hyderabad
2 CRBio, Division of RA Chem Pharma, Hyderabad, India

Description

Abstract
Bioequivalence (BE) studies are an integral component of the new drug development process. Additionally, they are required for the approval and marketing of generic drug products.Bioequivalence studies are performed to demonstrate in vivo that two pharmaceutically equivalent products (in the US) or alternative pharmaceutical products (in the EU) are comparable in their rate and extent to which the active ingredient of active moiety becomes available at the site of drug action. By definition, for highly variable drugs (HVDs), the estimated within-subject variability is >30%. HVDs often fail to meet current regulatory acceptance criteria for average bioequivalence (ABE). The determination of the bioequivalence of HVDs has been a vexing problem since the inception of the current regulations. It is of concern not only to the generic industry but also to the innovator industry. This article reviews the definition of HVDs, the present regulatory recommendations and the approaches proposed in the literature to deal with the bioequivalence problems of HVDs. The approach of scaled ABE (SABE) is proposed as the most adequate procedure to solve the problem. It is demonstrated that SABE has firm theoretical foundations. In fact, statistical tests similar to SABE are used in various fields, such as psychology and quality control. Algorithms and numerical examples are presented to calculate SABE from the data in conventional replicate-design studies. The most important feature of SABE is that a fixed sample size is adequate to demonstrate bioequivalence regardless of within-subject variability. We have compared simple replicated design approach and reference scale average bioequivalence approach in this paper. The data is considered using 5% error from the actual study.

Keywords: Replicate, Scaled Bioequivalence, Highly variable drug, Intra subject Variability

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