Development of a PBPK model to quantitatively understand absorption and disposition mechanism and support future clinical trials for PB-201

CPT Pharmacometrics Syst Pharmacol. 2023 Jul;12(7):941-952. doi: 10.1002/psp4.12964. Epub 2023 Apr 20.

Abstract

PB-201 is the second glucokinase activator in the world to enter the phase III clinical trials for the treatment of type 2 diabetes mellitus (T2DM). Combined with the efficacy advantages and the friendly absorption, distribution, metabolism, and excretion characteristics, the indication population of PB-201 will be broad. Because the liver is the primary organ for PB-201 elimination, and the elderly account for 20% of patients with T2DM, it is essential to estimate PB-201 exposure in specific populations to understand the pharmacokinetic characteristics and avoid hypoglycemia. Despite the limited contribution of CYP3A4 to PB-201 metabolism in vivo, the dual effects of nonspecific inhibitors/inducers on PB-201 (substrate for CYP3A4 and CYP2C9 isoenzymes) exposure under fasted and fed states also need to be evaluated to understand potential risks of combination therapy. To grasp the unknown information, the physiologically-based pharmacokinetic (PBPK) model was first developed and the influence of internal and external factors on PB-201 exposure was evaluated. Results are shown that the predictive performance of the mechanistic PBPK model meets the predefined criteria, and can accurately capture the absorption and disposition characteristics. Impaired liver function and age-induced changes in physiological factors may significantly increase the exposure under fasted state by 36%-158% and 48%-82%, respectively. The nonspecific inhibitor (fluconazole) and inducer (rifampicin) may separately increase/decrease PB-201 systemic exposure by 44% and 58% under fasted state, and by 78% and 47% under fed state. Therefore, the influence of internal and external factors on PB-201 exposure deserves attention, and the precision dose can be informed in future clinical studies based on the predicted results.

MeSH terms

  • Aged
  • Computer Simulation
  • Cytochrome P-450 CYP3A / metabolism
  • Diabetes Mellitus, Type 2* / drug therapy
  • Drug Interactions
  • Humans
  • Models, Biological
  • Rifampin / pharmacokinetics

Substances

  • Cytochrome P-450 CYP3A
  • Rifampin