ArticleClinical and translational science2023
Physiologically-based pharmacokinetic model to investigate the effect of pregnancy on risperidone and paliperidone pharmacokinetics: Application to a pregnant woman and her neonate.
Article in Clinical and translational science, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers, 1 of them a synthesis that pooled it.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
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Who cites it
8 citing papers in PubMed, 1 synthesis or guideline pooled it, 10 citations in OpenAlex.
- Trimesters induced changes in pharmacokinetic parameters of antipsychotics.Archives of women's mental health · 2026Pooled it
- A Review of Virtual Twins in Physiologically-Based Pharmacokinetic Modeling and Simulation.Clinical pharmacology and therapeutics · 2026Review
- Physiologically-Based Pharmacokinetic Modeling to Investigate Piperaquine Exposure in Pregnant Women Using an Individualized Profile Approach.Clinical and translational science · 2026Article
- From Population-Based PBPK to Individualized Virtual Twins: Clinical Validation and Applications in Medicine.Journal of clinical medicine · 2026Review
- A Step-by-Step Workflow for Performing In Silico Clinical Trials With Nonlinear Mixed Effects Models.CPT: pharmacometrics & systems pharmacology · 2025Article
- Advances in Psychotropic Treatment for Pregnant Women: Efficacy, Adverse Outcomes, and Therapeutic Monitoring.Journal of clinical medicine · 2024Review
- Article
- Physiologically-based pharmacokinetic model to investigate the effect of pregnancy on risperidone and paliperidone pharmacokinetics: Application to a pregnant woman and her neonate.Clinical and translational science · 2023Article
Corrections and comments
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Authors and funding
11 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
This study aimed to determine the effects of pregnancy and ontogeny on risperidone and paliperidone pharmacokinetics by assessing their serum concentrations in two subjects and constructing a customized physiologically-based pharmacokinetic (PBPK) model. Risperidone and paliperidone serum concentrations were determined in a pregnant woman and her newborn. PBPK models for risperidone and paliperidone in adults, pediatric, and pregnant populations were developed and verified using the Simcyp simulator. These models were then applied to our two subjects, generating their "virtual twins." Effects of pregnancy on both drugs were examined using models with fixed pharmacokinetic parameters. In the neonatal PBPK simulation, 10 different models for estimating the renal function of neonates were evaluated. Risperidone was not detected in the serum of both pregnant woman and her newborn. Maternal and neonatal serum paliperidone concentrations were between 2.05-3.80 and 0.82-1.03 ng/ml, respectively. Developed PBPK models accurately predicted paliperidone's pharmacokinetics, as shown by minimal bias and acceptable precision across populations. The individualized maternal model predicted all observed paliperidone concentrations within the 90% prediction interval. Fixed-parameter simulations showed that CYP2D6 activity largely affects risperidone and paliperidone pharmacokinetics during pregnancy. The Flanders metadata equation showed the lowest absolute bias (mean error: 22.3% ± 6.0%) and the greatest precision (root mean square error: 23.8%) in predicting paliperidone plasma concentration in the neonatal population. Our constructed PBPK model can predict risperidone and paliperidone pharmacokinetics in pregnant and neonatal populations, which could help with precision dosing using the PBPK model-informed approach in special populations.
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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 Socratic graph.