Use of Population Modeling to Characterize the Pharmacokinetics of Oxcarbazepine And Its Metabolite in Children and Adolescents with Obesity
Publication Type
Conference Paper
Year of Publication
2022
Authors
Sinha, J; Zimmerman, KO; Balevic, S; Muller, W; Hornik, CD; Rathore, M; Finkelstein, Y; Chen, J; Lipscomb, D; Gonzalez, D; Best Pharmaceuticals for Children Act – Pediatric Trials Network Steering Committee
Secondary
Annual Meeting of American Society for Clinical Pharmacology and Therapeutics (ASCPT)
Date Published
03/2022
Location
Virtual
Abstract
Background: Oxcarbazepine (OXZ) is approved to manage partial-onset seizures in children >2 years of age. OXZ’s antiepileptic effect is linked to the pharmacokinetics (PK) of its active metabolite, mono-hydroxy derivative (MHD), which is affected by body weight (WT) differences in children. However, the extent to which obesity affects MHD’s PK remains unknown. The aim was to characterize MHD’s disposition in children with obesity.
Methods: Children receiving OXZ per standard of care were enrolled through two multi-center, open-label trials. One of the trials (ClinicalTrials.gov # NCT01431326) included children with and without obesity, while the second trial (NCT0299386) enrolled only children with obesity. Plasma OXZ and MHD concentrations were measured by a validated LC-MS/MS assay. A population PK analysis using NONMEM 7.4 was performed, and the influence of age, body size (as WT and fat-free mass [FFM]), and hepatic and renal function on PK were assessed.
Results: A total of 100 participants (52% obese) were enrolled with a median (90% interval) age, WT, and BMI percentile of 9.2 years (1.1 - 19.2), 27.2 kg (7.6 - 97.5), and 96 (1.8 - 99.8). Altogether 212 and 213 concentrations of OXZ and MHD were available. A one-compartment model with linear input-output and bi-directional transformation between OXZ and MHD best characterized the PK data. We found that only the body size metrics were statistically significant covariates of MHD’s clearance (〖CL〗_MHD) and volume of distribution (V_MHD). Among them, the estimated between-subject variability in V_MHD was less for the WT- (73%) than FFM- (>100%) based model. Thus, the final model included with estimated exponents: V_MHD (L)=〖50×(WT/70)〗^0.66and 〖CL〗_MHD (L/h)=〖2.82×(WT/70)〗^0.54.
Conclusion: Our analysis suggests that WT adequately accounts for MHD’s PK variation in children with obesity.