Drug-drug interaction pattern recognition.

Abstract

Background and Objective: Drug-drug interaction (DDI) is an important aspect of drug development, especially for safety. When a drug is used concomitantly with other drug(s), one of the major concerns is the change of exposures, including the rate and extent of drug absorption, distribution, metabolism and elimination. To address the concerns, a common practice is to measure and report the differences between the exposure in the presence and in the absence of concomitant medication (COMED). The area under the plasma concentration versus time curve (AUC), maximum plasma concentration (Cmax) and time to reach the Cmax (tmax) changes are usually measured in DDI studies. A usual observation is the different extents of changes among AUC, Cmax and tmax, which may raise concerns in certain therapeutic areas or some special agents. The objective of this study was to investigate the variation among changes of AUC, Cmax and tmax in DDI studies, and its pharmacokinetic manifestation.Data Sources: Based on a list of DDI results from the literature, with the assumptions that the primary parameters of a drug of interest were altered during a DDI, two sets of simulated data were generated according to a single oral dose, one-compartment model. The first set including 24 cases with different half-lives and absorption constants (ka) considered the exposure changes upon independent variation of bioavailability (F), clearance (CL), volume of distribution (Vd) and ka up to 50-fold increases or decreases. The second set considered the exposure changes with simultaneous variation of F, CL, Vd, and ka within 5-fold range (increase or decrease) for a case selected from the first set.Study Selection, Data Extraction and Synthesis: Parameter fold changes (defined in a fashion showing fold increase or fold decreases, including CL fold change, F fold change, Vd fold change and ka fold change) and exposure changes (AUC fold change, Cmax fold change, tmax fold change and fold change difference [AUC fold change — Cmax fold change]) were used to generate plots demonstrating various relationships between parameter fold changes and exposure changes. Based on the observations that AUC was influenced by CL and F, Cmax was affected by all four parameters, tmax was mainly determined by CL and ka, F did little for tmax and ka was unrelated to AUC, a chart was created for DDI pattern recognition.Conclusion: An approach, named DDI pattern recognition, is proposed for didactical purposes. It provides a quick initial estimate for interpreting the DDI results based on the exposure changes. This approach entails the following stages: (i) performing a drug interaction study; (ii) calculating the exposure changes in the presence of COMED compared to those in the absence of COMED, and the fold change difference; (iii) selecting the parameter fold changes that may play important roles in a specific DDI, by estimating their possible ranges; and (iv) interpreting the DDI by integrating all the information available, such as the possible mechanism involved. A quicker and better understanding about the processes, which dominate a DDI, has been achieved using this approach by focusing on integration of all information available and mechanistic interpretation.