Prediction of CYP-mediated DDIs involving inhibition: Approaches to address the requirements for system qualification of the Simcyp Simulator.

Physiologically-based pharmacokinetic (PBPK) modeling is being increasingly used in drug development to avoid unnecessary clinical drug-drug interaction (DDI) studies and inform drug labels. Thus, regulatory agencies are recommending, or indeed requesting, more rigorous demonstration of the prediction accuracy of PBPK platforms in the area of their intended use. We describe a framework for qualification of the Simcyp Simulator with respect to competitive and mechanism-based inhibition (MBI) of CYP1A2, CYP2D6, CYP2C8, CYP2C9, CYP2C19, and CYP3A4/5. Initially, a DDI matrix, consisting of a range of weak, moderate, and strong inhibitors and substrates with varying fraction metabolized by specific CYP enzymes that were susceptible to different degrees of inhibition, were identified. Simulations were run with 123 clinical DDI studies involving competitive inhibition and 78 clinical DDI studies involving MBI. For competitive inhibition, the overall prediction accuracy was good with an average fold error (AFE) of 0.91 and 0.92 for changes in the maximum plasma concentration (Cmax ) and area under the plasma concentration (AUC) time profile, respectively, as a consequence of the DDI. For MBI, an AFE of 1.03 was determined for both Cmax and AUC. The prediction accuracy was generally comparable across all CYP enzymes, irrespective of the isozyme and mechanism of inhibition. These findings provide confidence in application of the Simcyp Simulator (V19 R1) for assessment of the DDI potential of drugs in development either as inhibitors or victim drugs of CYP-mediated interactions. The approach described herein and the identified DDI matrix can be used to qualify subsequent versions of the platform.

Assessment of in vivo CYP2D6 activity: differential sensitivity of commonly used probes to urine pH.

Drug/metabolite ratios (MRs) are used as in vivo markers of enzyme activity. The ratios are potentially confounded by the renal clearance of the drug (urine-based MRs) or metabolite (plasma-based MRs). The authors have investigated the relative sensitivity of urinary MR of 3 in vivo probe substrates of CYP2D6 debrisoquine (DB), dextromethorphan (DM), and metoprolol (MP) to changes in urine pH. Three groups of healthy volunteers each comprising 12 individuals were given DB (10 mg), DM (25 mg), or MP (100 mg) on 3 occasions. In 1 study arm, urine was acidified by the oral intake of ammonium chloride; in another, it was alkalinized by intake of sodium bicarbonate; and in the third, urine pH was uncontrolled. Urinary MP/alpha-hydroxy-MP, DM/dextrorphan, and DB/4-hydroxy-DB ratios were calculated. The mean(geo) MR for DB was not significantly different in any of the study arms, whereas those for MP and DM were significantly different under acidified and alkalinized urine conditions compared to uncontrolled urine pH (P < .01) and were correlated with urine pH (P < .001). Without control of urine pH, in vivo estimates of CYP2D6 metabolic activity are likely to be less precise using DM or MP as probe substrates compared to DB. Although this is unlikely to cause any problem in distinguishing the large functional differences in CYP2D6 in poor metabolizer (PM) and extensive metabolizer (EM) phenotypes, this may contribute to difficulties in differentiating in vivo metabolic activity among allelic variants within the overall CYP2D6 EM phenotype using MP or DM. However, because DB is not available in many countries (eg, United States), alternative in vivo markers of CYP2D6 with low sensitivity to urine pH should be sought.