Konstantinos Biliouris (1), Mirjam N. Trame (1), Stephan Schmidt (1), Lanyan (Lucy) Fang (2), Lawrence J. Lesko (1)
(1) Center for Pharmacometrics and Systems Pharmacology, Department of Pharmaceutics, College of Pharmacy, University of Florida, Orlando, USA, (2) Food and Drug Administration, Office of Generic Drugs, Silver Spring, MD
Objectives: Antiepileptic drugs (AEDs) have recently been at the epicenter of the controversy over generic-brand drug substitution due to purported lack of seizure control or adverse events (AEs). The objective of this work was to interrogate the comparative safety of brand-name and generic AEDs using the FDA Adverse Event Reporting System (FAERS) [1].
Methods: We have undertaken a risk-based approach to examining how the AEs from brand-name AEDs compared with the AEs from their generic product counterparts throughout a 10-year time window (2004-2014). The focus was on three AEDs, phenytoin, levetiracetam and gabapentin. First, we conducted data mining in FAERS to identify the frequency, nature and corresponding patient outcome of AEs linked with these three brand-name and generic AEDs. Next, we exploited the Molecular Analysis of Side Effects (MASE) [2] integrated software platform to dissect the molecular basis of the purported AEs, to assess causality and to generate hypotheses about the mechanism of observed differences in AEs.
Results: The difference in AEs frequency between brand-name and generic AEDs was not compelling. In some instances, however, the nature of the most commonly observed AEs differed between brand-name and generic drugs. Exploiting MASE, we identified the top 20 molecular targets (CYP enzymes, transporters and pharmacological receptors) of the active pharmaceutical ingredient in the products which allowed us to elucidate hypotheses about the mechanistic origin of purported AEs but not the reasons for differences in the nature of AEs between brand-name and generic products.
Conclusions: We used a versatile and mechanistic approach that combines data mining and systems pharmacology principles to compare the AEs from brand-name and generic AEDs and to explain the reasons for differences. Our approach, when coupled with physiologically based pharmacokinetic modelling and pharmacokinetic-pharmacodynamic modelling, could be implemented by regulatory agencies for identifying the AEs of a drug and for validating whether or not purported AEs are biologically plausible.
References:
[1] http://www.fda.gov/Drugs
[2] https://mase.molecularhealth.com
Reference: PAGE 24 (2015) Abstr 3430 [www.page-meeting.org/?abstract=3430]
Poster: Drug/Disease modeling - Safety