PI-015 - DEVELOPMENT OF USER-FRIENDLY BAYESIAN PREDICTIVE PLATFORM FOR BLOOD BORON-10 PHARMACOKINETICS FOLLOWING INTRAVENOUS INFUSION OF [10B]L-4-BORONOPHENYLALANINE.

W. Kim¹, S. Choi², S. Lee², H. Lim^3,2; ¹DawonMedax Co., Ltd., Seoul, Republic of Korea, ²University of Ulsan, Seoul, Republic of Korea, ³Asan Medical Center, Seoul, Republic of Korea.

Background: Boron neutron capture therapy (BNCT) allows high-precision radiotherapy against tumor using boron-10 (10B) with tumor-localizing characteristics and strong tendency to capture thermal neutrons. It is important to accurately predict the blood 10B concentration during the neutron irradiation to deliver the prescribed dose as planned. This study was performed to develop user-friendly Bayesian predictive platform for pharmacokinetics (PK) of 10B which is clinically applicable in BNCT.

Methods: Population PK model for 10B was constructed using blood 10B concentration over time data following intravenous infusion of boronophenylalanine (BPA) which were digitized from previous study results, which was used as a prior distribution model for the Bayesian prediction. The predictive model was implemented in NONMEM® 7.4 (ICON Development Solutions, USA), and NONMEM was executed using R (version 4.03) with user-friendly interface provided by Shiny package. Individual blood 10B concentration over time was predicted, which were graphically displayed with relevant numerical information. Simulation and sensitivity analyses were conducted to evaluate the predictive performance of the platform and identify optimal PK sampling time for blood 10B.

Results: Population PK model for 10B predicted observed concentrations reasonably well. Sensitivity analysis suggested optimal sampling time and number for the individual PK prediction. Predictive platform worked stable and predicted the 10B concentration with high accuracy and precision.

Conclusion: The predicted platform constructed in this study will help evaluate the therapeutic effect of BNCT more accurately in a clinical trial and improve the therapeutic outcome.