Impact of OATP1B1 Polymorphism on Pravastatin Pharmacokinetics during Pregnancy; Physiologically Based Pharmacokinetic model Prediction
Khaled Abduljalil, Sibylle Neuhoff, Iain Gardner
Certara UK Limited, Simcyp Division, Sheffield, United Kingdom
Objectives: Pravastatin treatment has been reported to reduce the incidence of pre-eclampsia by 61% and premature birth by 45% [1]. Pravastatin pharmacokinetics (PK) is known to be affected by OATP1B1 polymorphisms. However, Pravastatin PK data in different phenotypes during pregnancy are absent. Physiologically Based Pharmacokinetic (PBPK) modelling can help to explore pravastatin exposure during pregnancy in subjects with different OATP1B1 phenotypes. The objective of this work is to use the PBPK modelling approach to predict the maternal plasma exposure in virtual pregnant women at 32 gestational weeks (GWs) with either extensive transport (ET), intermediate (IT), or poor transport (PT) status with respect to hepatic OATP1B1.
Methods: The library compound model of pravastatin available in the Simcyp Simulator V22 that includes hepatic OATP1B1 and OATP1B3 uptake [2], renal clearance mediated by OAT3 and apical efflux transporters was used to simulate, as a baseline for pravastatin, a 40mg oral PK profile in virtual nonpregnant women with different OATP1B1 phenotypes [3]. Then a (20mg oral) PK profile for pravastatin in pregnant women was simulated, using the general pregnancy population system inputs that account for various physiological changes during pregnancy, including renal function and renal OAT3 activity. No change to the activity of hepatic OATP1B1 (and OATP1B3) during pregnancy was assumed. Predicted PK profiles and parameters were verified against observed data, where available [4]. Finally, the pregnancy pravastatin model was used to predict pravastatin (20mg oral) PK in pregnant women at 32 GWs with hepatic OATP1B1 transport protein activity is either accounted for as ET, IT, or PT. For these simulations, 20 virtual trials were used with 10 virtual subjects were allocated in each trial.
Results: Simulated area under the curve (AUC), maximum concentration (Cmax), and time to reach Cmax (Tmax) in nonpregnant women for different OATP1B1 polymorphisms where within 1.6-fold of the observed value [3]. The prediction of pravastatin exposure in pregnant subjects mimicking the trial design reported in a clinical study (4) showed good agreement with the changes reported during 18-24 gestational weeks (GWs) and 30-34 GWs compared to the PK in non-pregnant (≥4 months) post-partum subjects. The predicted to observed ratio of the pregnancy to nonpregnant baseline ratio was 1.1 and 1.9 for Cmax and 1.2 and 1.1-fold for AUC in the second and third trimester, respectively. Predicted pravastatin renal clearance (CLR) during pregnancy were 1.7-fold and 1.5-fold higher of the nonpregnant level during second, and third trimester, respectively. Likewise, the renal active uptake due to OAT3 was 2-fold, and 1.5-fold higher than pregnancy during the 22nd and 32nd GWs, respectively. PBPK Predictions for the different phenotypes at 32 GWs, compared to the same phenotypes of nonpregnant level, for the Cmax and AUC were 0.46-fold and 0.30-fold in ET group, 0.45-fold and 0.46-fold in IT group, and 0.44-fold and 0.88-fold in PT group.
Conclusions: Simulation studies could recover the observed changes in pravastatin PK in pregnancy without the need for a specific change in OATP activity to be considered. This suggests that either hepatic OATP1B1 activity does not change during pregnancy, or the changes are counteracted by an as so far unknown physiological change. The reduced pravastatin exposure during pregnancy is mainly due to the increase in pravastatin renal glomerular filtration rate as well as the increase in OAT3 activity. The predicted reductions in the in the AUC for the OATP1B1 ET and IT groups during pregnancy suggest a required pravastatin dose increase for ET group (wild type) and IT group, which are over 60% and 25%, respectively, of the Caucasian population.
References:
[1] Mészáros B et al. Front Med (Lausanne). 2023 Jan 13;9:1076372
[2] Chang M et al. Cancer Chemother Pharmacol. 2022 Mar;89(3):383-392.
[3] Niemi M et al. Clin Pharmacol Ther. 2006 Oct;80(4):356-66.
[4] Costantine MM et al. Am J Obstet Gynecol. 2021 Dec;225(6):666.e1-666.e15.