Ioannis Loisios-Konstantinidis (1), Rodrigo Cristofoletti (2), David B. Turner (3), Jennifer Dressman (1,4)
(1) Institute of Pharmaceutical Technology, Goethe University, Frankfurt am Main, Germany, (2) Center for Pharmacometrics and Systems Pharmacology, Department of Pharmaceutics, College of Pharmacy, University of Florida, Orlando, Florida, USA, (3) Certara UK Limited, Simcyp Division, 1 Concourse Way, Sheffield S1 2BJ, United Kingdom, (4) Fraunhofer IME - Translational Pharmacology and Medicine, Carl-von-Noorden Platz 9, Frankfurt am Main, Germany
Objectives:
- Investigate the impact of CYP2C9 genetic polymorphism on flurbiprofen (FLU) PK in healthy Caucasian and Chinese populations.
- Investigate the impact of formulation and dissolution rate on flurbiprofen PK.
- Identify risk factors and guide the design of future bioequivalence trials.
Methods:
Ten clinical studies, including multiple arm studies, available in the open literature were used for the development and verification of the FLU whole body PBPK/PD model.[1]–[9] The initial model was built in Simcyp® simulator (v.18.2) from physicochemical & blood binding parameters, in vitro data and in silico predictors.[6], [10], [11] As flurbiprofen is a probe drug for CYP2C9 activity and the genetic polymorphisms of the enzyme are known, allelic-specific in vitro metabolism data were incorporated to capture differences in the PK between CYP2C9 1*/1* (wild-type), 1*/2* and 1*/3* genotypes. The distribution/elimination parameters (Kp scalar, ISEF) were optimized from IV and oral solution data and internal verification was performed by simulating the respective clinical trials. Furthermore, in vitro solubility experiments and biorelevant dissolution testing of the pure drug and several IR formulations were performed to inform the ADAM model. After stepwise modeling of the in vitro data in SIVA Toolkit® (v.3.0) and under an IVIVE approach, the confirmed biopharmaceutic parameters were incorporated into the PBPK model to mechanistically describe the oral absorption. External verification was performed by simulating 10 virtual trials (each with 10 subjects) for several clinical studies after oral administration in the fasted state of a wide dose range (40-300 mg) and by comparing the predicted with the observed exposure. Virtual populations of NEurCaucasian and Chinese volunteers were selected to match the demographics of the respective enrolled individuals in the in vivo studies. Wherever available, the PK of subjects with a specific CYP2C9 genotype was simulated by including only virtual individuals with the respective enzymatic status. Translation of the in vitro to in vivo release enabled simulations of formulation-dependent and media-specific in vivo dissolution scenarios using the Diffusion-Layer (DLM) submodel within ADAM. The verified PBPK model was then further coupled with a published inhibitory Emax pharmacodynamic model and the simulated response-time profile was compared with the observed one. The model predictive performance was evaluated by: i) visual predictive checks (VPCs) ii) Rpredictied/observed (=model-predicted/clinically observed) and ii) the method by Abduljalil et al. for AUC and Cmax.[12]
Results:
The model was able to adequately predict the mean exposure of FLU from different dosage forms in the dose range 40 to 300 mg (max was observed when 60 minutes rather than 2.5 minutes was required to reach 85% dissolved. On the other hand, this led to a 2-fold delay in tmax, which in turn resulted in a slightly delayed onset of pain relief but no change in the maximum response.
Conclusions:
The present study highlights the impact of CYP2C9 genetic polymorphism on the PK of flurbiprofen. These results suggest that FLU dose adjustment for CYP2C9 poor metabolizers (1*/2*,1*/3*,2*,3*) is recommended, especially for Caucasians. The high between-subject variability observed in FLU clinical studies can be attributed to CYP2C9 polymorphisms rather than to highly variable absorption. This can be of great importance, especially for bioequivalence trials, where prior genotyping and exclusion of PM could mitigate the risk of bioequivalence failure, regardless of the formulation strategy, for substrates of polymorphic enzymes/transporters. Finally, race differences can also impact the risk of BE failure due to the population-specific frequency of the polymorphic alleles.
References:
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[12] Abduljalil K. et al., Deciding on Success Criteria for Predictability of Pharmacokinetic Parameters from In Vitro Studies: An Analysis Based on In Vivo Observations, DRUG Metab. Dispos. Drug Metab Dispos, vol. 42, pp. 1478–1484, 2014.
Reference: PAGE () Abstr 9521 [www.page-meeting.org/?abstract=9521]
Poster: Drug/Disease Modelling - Absorption & PBPK