Using Simcyp® to project human oral pharmacokinetic variability in early drug research to mitigate mechanism-based adverse events.

Positive allosteric modulators (‘potentiators’) of the α-amino-3-hydroxy-5-methyl-4-isoxazolepropionic acid receptor (AMPAR) have been shown to display a mechanism-based exposure-response continuum in preclinical species with procognitive electrophysiological and behavioral effects (‘efficacy’) at low exposures and motor coordination disruptions at progressively higher exposures. Due to the dose-capping nature of such motor coordination deficits, an exposure threshold-mediated adverse event (CAE), the adequacy of separation between the maximal total plasma compound concentration (Cmax) at a predicted clinically efficacious oral dose and this adverse event (AE) was explored in early drug research with three AMPAR potentiators considered potential candidates for clinical trials. In vitro metabolism studies in human liver microsomes and human hepatocytes demonstrated the metabolic clearance for each compound was predominately due to cytochromes P450 (CYP). Thus, for each compound’s anticipated clinically efficacious dose, human Cmax variability following oral administration was assessed using Simcyp® software, which combines its virtual human populations database using extensive demographic, physiological and genomic information with routinely collected compound-specific in vitro biochemical data to simulate and predict drug disposition. Using a combination of experimentally determined recombinant human CYP intrinsic clearances for CYP1A2, CYP2C8, CYP2C9, CYP2C19, CYP2D6 and CYP3A4, human binding factors, expected fraction absorbed and estimated steady-state volume of distribution, Simcyp® simulations demonstrated that two of the three potentiators had acceptable projected Cmax variability (i.e. the 95th percentile Cmax did not breach CAE. This evaluation aided in the selection of compounds for preclinical progression, and represents a novel application of pharmacologically based pharmacokinetic (PBPK) software approaches to predict interpatient variability.

Christopher L. Shaffer, Renato J. Scialis, Haojing Rong, R. Scott Obach
March 1, 2012
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