EP-021 - PBPK MODELING OF A NARROW THERAPEUTIC INDEX DRUG AND APPLICATION IN PREDICTING DOSE ESCALATION SCENARIOS, FOOD EFFECT, DDI AND SPECIAL POPULATION.

N. Rayad¹, H. Cheruvu²; ¹Parexel International, Durham, NC, USA, ²Parexel International, Brisbane, Australia.

Background: Currently, regulatory agencies and pharma industries are interested in PBPK models to supplement clinical studies. The aim of this work is to develop and verify a PBPK model of sirolimus, that can prospectively predict various scenarios viz. food effect, DDI and for special population.

Methods: PBPK model was constructed in PK-Sim® integrating experimental and physicochemical data of sirolimus as well as in vitro recombinant CYP enzyme metabolism data. Significant parameters were optimized using the parameter identification tool to achieve a better base model for the oral dose 0.8mg/m2. The model was verified using PK data from clinical studies at various doses and population: healthy adults, pediatrics and hepatically impaired (HI). The model was applied to prospectively predict DDI with diltiazem (moderate CYP3A4 inhibitor) and rifampicin (strong CYP3A4 inducer), fed condition, pediatrics, and HI population. Adequate predictions were achieved if the mean fold error (MFE) predicted over observed of PK parameters was within 2-fold.

Results: Rodgers and Rowland’s tissue partition method and optimal values of log P, specific intestinal permeability, dissolution shape and time of 4.67, 1.51e-5 cm/sec, 0.07, and 490.34 min respectively and Weibull suspension model produced the best description of sirolimus PK profile in adults. The MFE was 1.09 and 1.012, for Cmax and AUC parameters, respectively. The verification across various doses produced a high correlation of r > 0.995. In DDI predictions with diltiazem, the predicted AUC ratio was ~3.5 fold higher than sirolimus alone. The PBPK model successfully predicted PK profiles in different pediatrics and HI groups.

Conclusion: The developed PBPK models were successful in predicting PK profiles of the narrow therapeutic index sirolimus in various untested scenarios

1. Wagner, C. et al. Application of Physiologically Based Pharmacokinetic (PBPK) Modeling to Support Dose Selection: Report of an FDA Public Workshop on PBPK. CPT Pharmacometrics Syst Pharmacol. 4, 226-230 (2015).
2. Center for Drug Evaluation and Research, US FDA. Clinical Drug Interaction Studies — Cytochrome P450 Enzyme- and Transporter-Mediated Drug Interactions Guidance for Industry. https://www.fda.gov/regulatory-information/search-fda-guidance-documents/clinical-drug-interaction-studies-cytochrome-p450-enzyme-and-transporter-mediated-drug-interactions (January 2020). Accessed 30 Aug 2022.