(W-062) SEMI-PHYSIOLOGIC POPULATION PHARMACOKINETIC MODEL TO EVALUATE THE EFFECT OF HEPATIC-UPTAKE TRANSPORTER GENE SLC22A1 POLYMORPHISM ON PHARMACOKINETICS OF PROGUANIL AND ITS METABOLITE, CYCLOGUANIL

Eunsol Yang, PhD – PostDoc, Department of Bioengineering and Therapeutic Sciences, University of California, San Fransisco, San Fransisco, CA, United States of America; Chan Song Park, NA – Researcher, Department of Clinical Pharmacology and Therapeutics, Seoul National University College of Medicine and Hospital, Seoul, Republic of Korea; Sang Chun Ji, PhD – Researcher, Department of Clinical Pharmacology and Therapeutics, Seoul National University College of Medicine and Hospital, Seoul, Republic of Korea; Kyung-Sang Yu, MD, PhD – Professor, Department of Clinical Pharmacology and Therapeutics, Seoul National University College of Medicine and Hospital, Seoul, Republic of Korea; SeungHwan Lee, MD, PhD – Professor, Department of Clinical Pharmacology and Therapeutics, Seoul National University College of Medicine and Hospital, Seoul, Republic of Korea

Objectives: Proguanil, an antimalarial drug, is metabolized into cycloguanil by the cytochrome P450 2C19 (CYP2C19). Interestingly, hepatic uptake via the organic transporter 1 (OCT1), encoded by the polymorphic gene SLC22A1, has been reported to affect the biotransformation of proguanil. Building on this, we developed a semi-physiologic population pharmacokinetic (PK) model of proguanil and cycloguanil to evaluate the effect of the SLC22A1 1022 C>T genetic polymorphism on the metabolism of proguanil to cycloguanil.

Methods: A semi-physiologic population PK model of proguanil and cycloguanil was developed based on a total of 160 plasma concentration-time data each for proguanil and cycloguanil from 16 healthy subjects (NCT04568772). For the analysis of the genotype effect, SLC22A1 genotype data of 13 subjects was used. For the 3 subjects without genotype data, estimated genotype was applied, derived from a mixture model based on known allele frequency. The structure model with 1- and 2- compartment for both proguanil and cycloguanil, with or without the liver compartment was tested. The population PK model was evaluated using goodness-of-fit plots and a visual predictive check. The analysis was performed using NONMEM 7.5.

Results: A parent 2-compartment and metabolite 1-compartment population PK model with first-order absorption and elimination including a liver compartment, well described the concentration-time profile of proguanil and cycloguanil. The SLC22A1 genotype was evaluated as a covariate for hepatic extraction, and it was estimated that the hepatic extraction was 0.55-fold lower in subjects with the CT genotype compared with the CC genotype. This aligned well with the prior descriptive analysis for systemic exposure and metabolic ratio of cycloguanil according to genotypes.

Conclusions: A semi-physiologic parent 2-compartment metabolite 1-compartment population PK model incorporating a liver compartment successfully characterized the PK of proguanil and cycloguanil and quantitatively evaluated the degree of its metabolism according to hepatic uptake capabilities of OCT1 by SLC22A1 genotypes.

Citations: NA