PII-175 - PHYSIOLOGICALLY-BASED PHARMACOKINETIC (PBPK) MODEL FOR PANTOPRAZOLE IN CHILDREN WITH OBESITY.

K. Kyler¹, V. Shakhnovich², R. Selvarangan¹, A. Sasidharan¹, S. Chan¹, N. Artz¹, V. Williams³, C. Friesen⁴, R. Pearce¹, A. Gaedigk¹, J. Leeder¹, A. Galetin⁵, T. Johnson⁶; ¹Children's Mercy Kansas City, ²Ironwood Pharmaceuticals, ³Nemours Children's Health, ⁴University of Kansas Medical Center, ⁵University of Manchester, ⁶Certara.

Background: Applying PBPK models to personalized dosing1 requires a detailed knowledge of the covariates impacting drug pharmacokinetics (PK). The aim of this study was to investigate the role of multiple factors associated with age and obesity on the ability to predict pantoprazole PK in pediatric patients with and without obesity using PBPK modeling.

Methods: A PBPK model was developed in Simcyp v22, accounting for age, sex, weight category, liver volume, and CYP2C19 genotype in individual virtual subjects. Impact of inflammatory cytokines and liver fat was also explored as potential variables for future inclusion in the model. Simulations were assessed against clinical data obtained in a single-center PK study of intravenous (IV) pantoprazole administered to children aged 7-21 years of different weight categories (normal weight, overweight, obese, morbidly obese). Simulations were considered acceptable if 90% of the observed concentration data fell within the simulated 5th and 95th percentiles.

Results: A total of 33 subjects were individually simulated, of which 23 (67%) were successful: 6/9 (67%), 5/6 (83%), 9/14 (64%) and 2/4 (50%) in the four increasing weight categories, respectively. Representative subjects are shown in Fig 1A-D. Four of the subjects (2 in obese and 2 in morbidly obese) could be explained by high Interleukin (IL) 6 concentrations (Fig 1E) or high liver fat (Fig 1F). No associations were identified with any of the other factors investigated. The other mis-predictions remained unexplained.

Conclusion: The pantoprazole PBPK model included CYP2C19 genotype, liver size and weight category and predicted IV pantoprazole PK well compared with observed data in our study population. Expanding the existing PBPK model to include the effect of other relevant covariates (in addition to suppression of CYP2C19 activity by IL-6 and liver fat) is important prior to validation of this approach and use for individualized therapy.