Safety monitoring of drug interchangeability

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Safety monitoring of drug interchangeability

Generics/Research | Posted 20/11/2015 0 Post your comment

When a brand-name drug is going off patent protection, pharmaceutical or generics companies may file an abbreviated new drug application (ANDA) for approval of a generic drug. As indicated by the US Food and Drug Administration (FDA), two drug products are claimed to be bioequivalent (BE) if the 90% confidence interval (CI) for the geometric mean ratio is totally within the bioequivalent limits of (80%, 125%) based on log-transformed data [1, 2] and an approved generic drug can be used as a substitute for the brand-name drug. FDA, however, does not indicate that approved generics of the same brand-name drug can be used interchangeably. Assume a patient switches the generic drug from BE 125% to BE 80% or from BE 80% to BE 125%, the change of the drug concentration in blood are both dramatic. As more generics become available in the marketplace, it is a concern whether the approved generics are safe and can be used interchangeably.

From a previous study by Chow and Liu [3], a meta-analysis for a systemic overview of bioequivalence was proposed. According to this, the authors of this study proposed two safety margins as new bioequivalence limits for monitoring of drug interchangeability based on the simulated data [4].

Margin 1 (L₁, U₁). Let (L_m, U_m) be the 90% CI obtained from a meta-analysis. Set L₁=L_m-δ_Land U₁=U_m-δ_M, where δ_L=(L_m-0.8)/2 and δ_M=(1.25-U_m)/2.

Margin 2 (L₂, U₂). For each meta-analysis, we can get the lower margin (L) which is smaller than 95% of the lower bounds (L*) from the 90% CI of different studies, . Correspondingly, the upper margin (U) is larger than 95% of the upper bound (U*) from the 90% CI of different studies. Therefore, L₂ will be like the fifth percentile of the boundaries, and U₂ will be the 95^th percentile of the boundaries. We also change the probability to get the Margin 3 (P(L*≧L₃)=90%, P(U*≦U₃)=90%) and Margin 4 (P(L*≧L₄)=85%, P(U*≦U₄)=85%) to compare.The probability of the 90% CI for a study below the lower margin (Below L), or above the upper margin (Above U) can be calculated. Safety impact is when the efficacy of original drug is close to the lower margin and suddenly changes to the drug with efficacy close to the upper margin, which is calculated as

correspondingly, efficacy impact is calculate as

From the results, the CIs are similar when the true variances are the same, and they get larger when the true variances become larger. In addition, the Safety/Efficacy Impact seems to be smaller when the true mean is larger among Margin 2, 3 and 4. It is therefore not surprising that when the true variance gets larger, the Safety/Efficacy Impact also gets larger. The Below L and Above U have the same situation as the Safety/Efficacy Impact, and they dramatically increase for Margin 1 when the variance gets larger. Margin 1, 2, 3 and 4 are similar when variances are small. However, when variances get larger, they perform differently and Margin 1 is usually the narrowest one. From a regulatory point of view, if the criterion for Safety/Efficacy Impact is 30%, then we can see when the variance is small; all margins can meet this criterion. However, the variance in real data usually falls between 20 and 30, and Margin 1 meets this criterion. Therefore, the proposed Margin 1 is a useful tool for safety monitoring for interchangeability.

Conflict of interest
The authors of the research paper [4] did not provide any conflict of interest statement.

Abstracted by Wen-Wei Liu, Department of Biostatistics and Bioinformatics, Duke University School of Medicine, Durham, North Carolina, USA

Editor's comment
Readers interested to learn more about interchangeability of generics are invited to visit www.gabi-journal.net to view the following manuscript published in GaBI Journal:

Why bioequivalence and unconditional interchangeability of generic drugs are not the same

If you are interested in contributing a research article in a similar area to the GaBI Journal, please send us your submission here.

References
1. Chow SC, Liu JP. Design and Analysis of Bioavailability and Bioequivalence Studies. 3rd (Edn), 2008, Chapman Hall/CRC Press, Taylor & Francis, New York.
2. US Food and Drug Industry. Guidance for industry. Guidance on bioavailability and bioequivalence studies for orally administered drug products - general considerations [homepage on the Internet]. 2003 Feb 11 [cited 2015 Nov 20]. Available from: www.fda.gov/ohrms/dockets/ac/03/briefing/3995B1_07_GFI-BioAvail-BioEquiv.pdf
3. Chow SC, Liu JP. Meta-analysis for bioequivalence review. J Biopharm Stat. 1997;7(1):97-111.
4. Liu WW, Chow SC. Meta-analysis for safety monitoring of drug interchangeability. J Bioequiv Availab. 2015;7:5.

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