IV-18

Evaluating the clinical influence of UGT2B15 genotype on the pharmacodynamic response of the PPAR agonist, sipoglitazar

Fran Stringer (1), Joost DeJongh (2), Graham Scott (3) and Meindert Danhof (4)

(1) Clinical Pharmacology Dept, Takeda Pharmaceutical Company, Osaka, Japan; (2) LAP&P Consultants BV, Leiden, The Netherlands; (3) Clinical Pharmacology, Takeda Global Research & Development Centre Ltd. Europe, London, United Kingdom; (4) Leiden-Amsterdam Centre for Drug Research, Division of Pharmacology, Leiden, The Netherlands

Objectives: Sipoglitazar, a pan-PPAR agonist was targeted for treating type 2 diabetes (T2D). Sipoglitazar undergoes conjugation catalyzed by UGT.1 UGT2B15 genotype is a covariate for clearance in individual patients as reported previously from a PK analysis.2 The objectives of this analysis were to evaluate the role of UGT (UGT2B15*1/*1, UGT2B15*1/*2, and UGT2B15*2/*2) driven exposure differences on the pharmacodynamic response for sipoglitazar in both FPG and HbA1c.

Methods: Efficacy of sipoglitazar was assessed in T2D patients in 2 Phase II studies (sipoglitazar QD: 8, 16, 32, 64 mg; BID: 16 or 32 mg, placebo or rosiglitazone 8mg). FPG and HbA1c samples were collected throughout (-1, 0, 2, 4, 6, 8, 10 and 12 weeks). Changes in FPG and HbA1c levels over time were described as a function of individual drug exposure using a simultaneous, cascading indirect response model structure.3

Results: The effects on FPG and HbA1c could successfully be described for placebo, rosiglitazone and sipoglitazar treated groups in all three UGT2B15 genotypes.4 The Emax for sipoglitazar was estimated at 49% and AUC50 was 1.2 mg.day/L. Rosiglitzone treatment effect was estimated at 28% for the studied dose level.

The simulated mean change from baseline in FPG at 6 months for 64mg sipoglitazar was -1.2 mmol/L, -1.6 mmol/L and -2.1 mmol/L for UGT2B15*1/*1, UGT2B15*1/*2 and UGT2B15*2/*2 genotypes respectively (rosiglitazone 8mg, -2.0 mmol/L).

A simulation study was performed evaluating genotype-based dosing vs. single treatment approach. Using a single treatment approach, a comparable result to rosiglitazone was achieved in all genotype groups at a dose of 96mg. However for genotyped-based dose assignment a comparable result was achieved with lower doses for UGT2B15*1/*2 and UGT2B15*2/*2 groups.

FPG time profiles for genotyped and titration-based dosing were simulated. Genotype-based dosing can achieve glycemic control in a shorter duration. The difference in time to 90% of FPG steady state between genotyped and titration-based dosing was approx. 1-2 months. However, the magnitude of FPG reduction achieved for the 2 approaches would be expected to be the same.

Conclusions: In summary the genotype effect on the PK of the drug does translate to differences in FPG and HbA1c response. The application of genotyped-based dosing could be utilized to normalize clinical response between individuals. However when comparing genotyped-based dosing with a titration approach, the magnitude of response would be comparable with only a 1-2 month difference in reaching the maximum effect.

References:
[1] Stringer F, Scott G, Valbuena M, Kinley J, Nishihara M, Urquhart R. The effect of genetic polymorphisms in UGT2B15 on the pharmacokinetic profile of sipoglitazar, a novel anti-diabetic agent. Eur J Clin Pharmacol. 2013 Mar;69(3):423-30.
[2] Stringer F, Ploeger BA, DeJongh J et al. Evaluation of the Impact of UGT Polymorphism on the Pharmacokinetics and Pharmacodynamics of the Novel PPAR Agonist Sipoglitazar. J Clin Pharmacol. 2013 Mar;53(3):256-63.
[3] de Winter WA et al. Mechanism-based disease progression model for comparison of long-term effects of pioglitazone, metformin and gliclazide on disease processes underlying type 2 diabetes mellitus. J. Pharmacokinet Pharmacodyn. 2006;33:313-343.
[4] Stringer F, DeJongh J, Scott G, Danhof M. A Model Based Approach to Analyze the Influence of UGT2B15 Polymorphism Driven Pharmacokinetic Differences on the Pharmacodynamic Response of the PPAR Agonist Sipoglitazar J Clin Pharmacol. 2013 Nov 11. doi: 10.1002/jcph.227.

Reference: PAGE 23 (2014) Abstr 3033 [www.page-meeting.org/?abstract=3033]

Poster: Drug/Disease modeling - Endocrine