Yumi Cleary1,2, Michael Gertz1, Felix Jaminion1, Sian Lennon-Chrimes3, Darren Bentley4 and Michael Derks3
1Roche Pharma Research and Early Development, Roche Innovation Center Basel, Basel, Switzerland, 2Centre for Applied Pharmacokinetic Research, University of Manchester, Manchester, UK; 3Roche Pharma Research and Early Development, Roche Innovation Center Welwyn, UK, 4Certara UK Ltd, Sheffield, UK.
Objectives:
Basmisanil is a potent and highly selective GABAA-α5 receptor negative allosteric modulator [1]. Basmisanil has been investigated in different indications, including intellectual disability in Down Syndrome and cognitive impairment associated with schizophrenia[1]. Since basmisanil is mostly metabolized by CYP3A and exhibits time dependent inhibition (TDI) of CYP3A in vitro, possible in vivo drug-drug interactions (DDI) were evaluated. Therefore, a strategy coupling mechanistic DDI studies and physiologically-based pharmacokinetic (PBPK) modelling was taken to assess the clinical relevance of CYP3A-mediated DDI of basmisanil to provide guidance on the use of various concomitant medications for patient populations.
Methods:
A PBPK model of basmisanil was developed by integrating physicochemical properties, in vitro experimental data and clinical data of basmisanil collected from healthy volunteers of four clinical pharmacology studies. The disposition of basmisanil was evaluated and refined using the basmisanil plasma concentration data after intravenous (iv) administration in healthy subjects [2]. Absorption was described by an estimated first-order absorption rate constant and the predicted fraction absorbed by a mechanistic absorption model [2].
After confirming suitability of the PBPK model to predict basmisanil PK after oral administration in healthy subjects, the model was extended by including relevant DDI components. The following steps were taken: 1) estimation of in vivo TDI parameters of the hepatic CYP3A and 2) the intestinal CYP3A of basmisanil, and 3) estimation of in vivo metabolic fraction of CYP3A (fmCYP3A) of basmisanil. Steps 1) and 2) were performed using the plasma concentration of midazolam, a prototypical CYP3A substrate, after iv or oral administration in the presence of basmisanil. The inactivation rate constant (kinact) was estimated in Step 1) and subsequently used for Step 2) to estimate the unbound fraction in enterocyte (fugut) of basmisanil. Step 3) used the basmisanil plasma concentration data in the presence and absence of itraconazole, a potent CYP3A inhibitor [3].
The PBPK modelling was performed using SimCYP version 19. A virtual population with matched demographics was created for each study. The simulated plasma concentration-time profiles and PK parameters by the PBPK model were compared with the corresponding study results.
Results:
The basmisanil PBPK model adequately predicted the plasma concentrations after oral administration of 120 and 240 mg basmisanil tablets in healthy subjects. The estimated in vivo kinact was 4.0 /h, approximately 40% lower than the in vitro estimate, and the estimated fugut was 0.2. The updated basmisanil PBPK model with the implementation of these estimated parameters predicted midazolam AUC and Cmax ratios with and without basmisanil within 0.8-1.25 fold of the observations (predicted vs. observed AUC ratios: 1.13 vs. 1.12 after iv midazolam and 1.31 vs. 1.37 after oral administration, predicted vs. observed Cmax ratios: 1.19 vs. 1.19 after oral administration). The estimated basmisanil fmCYP3A was 90%, indicating high sensitivity to hepatic CYP3A modulations. The combination of the estimated kinact and fmCYP3A adequately predicted the auto-inhibition of basmisanil. The predicted intestinal availability (FG) of basmisanil was >95% with the intrinsic clearance of CYP3A corresponding to fmCYP3A of 90% and the newly estimated fugut of 0.2, indicating negligible intestinal DDI risk and that the increase in basmisanil exposure by itraconazole was mostly due to inhibition of hepatic CYP3A. The basmisanil PBPK model with the implementation of the estimated kinact, fugut, fmCYP3A predicted basmisanil AUC and Cmax ratios with and without itraconazole within 0.8-1.25 fold of the observations (predicted vs. observed AUC ratios: 5.67 vs. 4.74, Cmax ratios: 5.01 vs. 4.12).
Conclusions:
The PBPK model of basmisanil mechanistically interpreted clinical DDI study data to estimate critical parameters, kinact, fugut, fmCYP3A in vivo. The model allows extrapolation of CYP3A mediated victim and perpetrator DDI and therefore, utility to support guidance on the use of concomitant medications in patient populations is expected.
References:
[1] Hipp, J.F., et al., Basmisanil, a highly selective GABAA-alpha5 negative allosteric modulator: preclinical pharmacology and demonstration of functional target engagement in man. Sci Rep, 2021. 11(1): p. 7700.
[2] Stillhart, C., et al., Characterising Drug Release from Immediate-Release Formulations of a Poorly Soluble Compound, Basmisanil, Through Absorption Modelling and Dissolution Testing. AAPS J, 2017. 19(3): p. 827-836.
[3] Jaminion, F., et al., PKPD and cardiac single cell modeling of a DDI study with a CYP3A4 substrate and itraconazole to quantify the effects on QT interval duration. J Pharmacokinet Pharmacodyn, 2020. 47(5): p. 447-459
Reference: PAGE 30 (2022) Abstr 9979 [www.page-meeting.org/?abstract=9979]
Poster: Drug/Disease Modelling - Absorption & PBPK