An Overview Of Bioequivalence Study For Drug Development And Testing

Posted by Ankit Shrivastava on January 9th, 2020

With soaring drug prices, the need for generic drugs has increased in the past decade and has been a debatable topic even in the political spectrum. Pharmaceutical companies are also on a daily hunt for receiving generic drug approval that would act as equivalents to brand-name versions.

Difference Between Drug Equivalents & Drug Alternatives

A completely New Drug Application (NDA) is not necessary for generic drugs, which can be applied under the abbreviated application, also known as ANDA. This is where bioequivalence study plays a role in drug development. It is focused on providing equivalents of brand-name drugs.

This equivalence is measured in terms of the formulation, i.e., both drugs have the same active ingredient in the same amount. Drug equivalents are different from drug alternatives. Drug alternatives are those having indistinguishable therapeutic moiety, but they do not necessarily have the same dosage of the active ingredient, ester, or salt.

Perfecting The Bioequivalence Study

A bioequivalence study is mainly focused on how the generic version releases the drug in the circulatory system in comparison to the reference product of Reference Listed Drug (RLD). In general, these studies have to be classified under two categories, crossover and non-crossover. These two types of studies are different, based on a few parameters.

Crossover type has the upper hand as it requires less number of patients for the study. In crossover-type, there is only a single group of study subjects who are first treated with a type of drug, which can be either RLD or the generic version. They are then subjected to treatment with the other drug. In a parallel or non-crossover study, there are two groups; each group is only treated with one type of drug.

The type of study required by a drug can always differ, but it has to be strategically built to provide accurate results. But a crossover study is mostly favored over other designs because of its accuracy in statistical value.