ArticleJournal of pharmacokinetics and pharmacodynamics2020
Prediction of maternal pharmacokinetics using physiologically based pharmacokinetic models: assessing the impact of the longitudinal changes in the activity of CYP1A2, CYP2D6 and CYP3A4 enzymes during pregnancy.
Article in Journal of pharmacokinetics and pharmacodynamics, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 33 papers, 1 of them a synthesis that pooled it.
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Who cites it
33 citing papers in PubMed, 1 synthesis or guideline pooled it, 56 citations in OpenAlex.
- Trimesters induced changes in pharmacokinetic parameters of antipsychotics.Archives of women's mental health · 2026Pooled it
- Modelling the tail-phase pharmacokinetics of long-acting cabotegravir and rilpivirine from early pregnancy to postpartum at steady state.Journal of pharmacokinetics and pharmacodynamics · 2026Article
- Pregnancy-related effect on elexacaftor, tezacaftor and ivacaftor pharmacokinetics in women with cystic fibrosis.British journal of clinical pharmacology · 2026Observational
- Physiologically Based Pharmacokinetic (PBPK) Modeling of Antidepressants: A Scoping Review of Existing Models, Applications, and Software Tools.Clinical pharmacokinetics · 2026Article
- Physiologically-Based Pharmacokinetic Modeling to Investigate Piperaquine Exposure in Pregnant Women Using an Individualized Profile Approach.Clinical and translational science · 2026Article
- A review of immunosuppressive therapy in the context of uterine VCA and pregnancy.Frontiers in transplantation · 2026Review
- Pharmacometric modeling of opioid disposition in pregnancy: a systematic review of PopPK and PBPK approaches, model limitations, and future directions.Frontiers in pharmacology · 2026Review
- Prediction of Maternal and Fetal Exposure to Escitalopram, Sertraline, and Paroxetine by Combining Human Ex Vivo Placenta Perfusion Data and Physiologically Based Pharmacokinetic Modeling.Clinical pharmacokinetics · 2025Article
- Predicting Maternal and Fetal Exposures of Elexacaftor-Tezacaftor-Ivacaftor during Pregnancy through Physiologically Based Pharmacokinetic Models.Clinical pharmacology and therapeutics · 2025Article
- Application of a Physiologically Based Pharmacokinetic Approach to Predict Tenofovir Pharmacokinetics During Pregnancy.The AAPS journal · 2025Article
- Prediction of lacosamide concentrations to support dose optimization during pregnancy.Epilepsia · 2025Observational
- Postpartum changes in maternal physiology and milk composition: a comprehensive database for developing lactation physiologically-based pharmacokinetic models.Frontiers in pharmacology · 2025Article
- Using PBPK modeling to supplement clinical data and support the safe and effective use of dolutegravir in pregnant and lactating women.CPT: pharmacometrics & systems pharmacology · 2024Article
- Physiologically based pharmacokinetic modeling of drug-drug interactions between ritonavir-boosted atazanavir and rifampicin in pregnancy.CPT: pharmacometrics & systems pharmacology · 2024Observational
- Ideal Time to Conduct a Pharmacokinetic Investigation After Delivery to Fully Capture the Effect of Pregnancy on Drug Exposure.Open forum infectious diseases · 2024Article
- Physiologically Based Pharmacokinetic Modeling in Pregnancy, during Lactation and in Neonates: Achievements, Challenges and Future Directions.Pharmaceutics · 2024Article
- Forecasting Fetal Buprenorphine Exposure through Maternal-Fetal Physiologically Based Pharmacokinetic Modeling.Pharmaceutics · 2024Article
- PBPK/PD Modeling of Nifedipine for Precision Medicine in Pregnant Women: Enhancing Clinical Decision-Making for Optimal Drug Therapy.Pharmaceutical research · 2024Article
- Utility of Physiologically Based Pharmacokinetic Modeling to Investigate the Impact of Physiological Changes of Pregnancy and Cancer on Oncology Drug Pharmacokinetics.Pharmaceutics · 2023Article
- Article
Corrections and comments
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Authors and funding
3 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Concerns over gestational effects on the disposition of drugs has highlighted the need for a better understanding of drug distribution and elimination during pregnancy. This study aimed at predicting maternal drug kinetics using a physiologically based pharmacokinetic (PBPK) modelling approach focusing on the observed gestational changes in three important Cytochrome P450 metabolizing enzymes, namely, CYP1A2, CYP2D6 and CYP3A4 at different gestational weeks (GWs). The Pregnancy PBPK model within the Simcyp Simulator V19 was used to predict the pharmacokinetics of sensitive probes to these enzymes; namely caffeine, theophylline, metoprolol, propranolol, paroxetine, midazolam, nifedipine and rilpivirine. PBPK model predictions were compared against clinical data collated from multiple studies for each compound to cover a wide spectrum of gestational ages. Pregnancy PBPK model predictions were within 2-fold error and indicated that CYP1A2 activity is approximately 0.70, 0.44 and 0.30 fold of the non-pregnant level at the end of the first, second and third trimesters, respectively. On the other hand, CYP2D6 activity increases by 1.36, 2.16 and 3.10 fold of the non-pregnant level at the end of the first, second and third trimesters, respectively. Likewise, CYP3A4 activity increases by 1.25, 1.75 and 2.32 fold of the non-pregnant level at the end of the first, second and third trimesters, respectively. The enzymes activity have been qualified throughout pregnancy. Quantified changes in drug dosing are most relevant during the third trimester, especially for drugs that are mainly eliminated by CYP1A2, CYP2D6 and CYP3A4 enzymes. The provided functions describing the continuous changes to the activity of these enzymes during pregnancy are important when modelling long term pharmacokinetic studies where longitudinal modelling or time-varying covariates are used.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.