Predicting maternal-fetal cannabinoid exposure during pregnancy using physiologically-based pharmacokinetic modeling and simulation
Patilea-Vrana, Gabriela Ioana
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Maternal marijuana (cannabis) use during pregnancy is associated with reduced fetal growth and subtle but persistent neurodevelopmental effects. It is not possible to establish the independent risk associated with maternal cannabis use via prospective clinical studies due to ethical considerations. In vitro and animal studies identified (-)-Δ9-tetrahydrocannabinol (THC), the psychotropic component of cannabis, and its active hydroxy metabolite, 11-OH-THC, as potential perpetrators of fetal developmental risk. The observed toxicity to THC and 11-OH-THC may not be translated from preclinical studies to humans without knowing the exposure of these cannabinoids during pregnancy. As such, maternal-fetal cannabinoid (hereafter cannabinoid refers to THC and 11-OH-THC) exposure needs to be determined. However, sampling maternal and fetal cannabinoid plasma concentrations during pregnancy is logistically difficult or unethical. Physiological-based pharmacokinetic (PBPK) modeling and simulation can be used to predict drug exposure in silico. PBPK modeling incorporates physiological data, such as tissue composition and blood flows, with drug specific pharmacokinetic (PK) parameters, such as metabolism and transport, to mechanistically predict in vivo PK of a drug. We hypothesize that we can predict maternal and fetal THC and 11-OH-THC exposure using maternal-fetal-PBPK (m-f-PBPK) modeling and simulation. To do so, we first quantified the pertinent mechanistic drug parameters in vitro, which included the identification of enzymes, their contribution, and kinetics relevant to maternal THC/11-OH-THC hepatic disposition. Next, we extrapolated the in vitro mechanistic information to in vivo and built a THC/11-OH-THC PBPK model in nonpregnant women using PBPK software Simcyp®, and verified using observed data. Lastly, we incorporated the gestational-age dependent physiological changes via the m-f-PBPK model to predict THC and 11-OH-THC exposure in the maternal-fetal pair. By bridging cannabinoid disposition data with m-f-PBPK modeling, this project translated in vitro PK mechanistic information into predictions of maternal and fetal pharmacologically relevant cannabinoid exposure following THC consumption. The predicted THC and 11-OH-THC concentrations during pregnancy can then be used in preclinical studies to establish the toxicity of THC exposure during pregnancy.
- Pharmaceutics