PII-080 - POPULATION PHARMACOKINETIC/PHARMACODYNAMIC (PK/PD) MODELING AND SIMULATION FOR TIGULIXOSTAT, A NOVEL XANTHINE OXIDASE INHIBITOR FOR THE TREATMENT OF GOUT WITH HYPERURICEMIA.

W. Denney¹, M. Lee², N. Lee², H. Jun², J. Seo², J. Lee²; ¹Human Predictions, Cambridge, MA, USA, ²LG Chem, Seoul, South Korea.

Background: Tigulixostat is a novel non-purine selective xanthine oxidase inhibitor currently under development as a treatment of hyperuricemia in adults with gout. Population PK/PD models were developed to describe PK of tigulixostat and its effect on serum uric acid (sUA).

Methods: The PK/ PD data from a total of 5 Phase 1 studies in healthy subjects, and one Phase 2 study in patients with gout were utilized for the development of population PK and PK/PD models. The pooled data included PK/PD with single and multiple oral dosing of tigulixostat (10 to 800 mg in healthy subjects; 50, 100, and 200 mg in patients). The models were estimated using NONMEM (version 7.5) with first-order conditional estimation with interaction. The best structural model was selected based on biological relevance, objective function value and goodness of fit. Following modeling, clinical trial simulations (CTS) was performed to estimate the dose responsive PK and PD.

Results: Tigulixostat PK was well characterized with a first-order absorption, two-compartment model with absorption lag time and allometric scaling of body weight on clearance and volume of distribution. The best PD model was a proportional Emax model of sUA formation rate with sUA baseline and elimination rate estimated for the sUA compartment. CTS found that doses of 75 mg tigulixostat and above were generally better than 300 mg allopurinol and titrated allopurinol for achieving < 5 or < 6 mg/dL sUA. Depending on the sUA target concentration, the CTS illustrated that the doses of >150 mg tigulixostat may be superior to allopurinol.

Conclusion: The models reasonably well described the tigulixostat PK and PD. CTS supported that tigulixostat is likely to be more efficacious than allopurinol. The models will be used to facilitate dose selection for further studies.