ReviewCPT: pharmacometrics & systems pharmacology2021
Examination of Physiologically-Based Pharmacokinetic Models of Rosuvastatin.
Review in CPT: pharmacometrics & systems pharmacology, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.
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
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
10 citing papers in PubMed, 18 citations in OpenAlex.
- Association between SLCO1B1, apolipoprotein E and ABCG2 genes and lipid response to rosuvastatin: a meta-analysis.Pharmacogenetics and genomics · 2026Article
- A Mechanistic Physiologically Based Pharmacokinetic (PBPK) modeling approach for fexofenadine: predictive pharmacokinetic insights in humans.Saudi pharmaceutical journal : SPJ : the official publication of the Saudi Pharmaceutical Society · 2025Article
- Variability in intestinal drug metabolizing enzymes and transporters in Crohn's disease and potential impact on oral drug absorption.British journal of clinical pharmacology · 2025Article
- Effect of folic acid and vitamin B12 plus rosuvastatin in the treatment of coronary heart disease combined with hyperlipidemia.Frontiers in cardiovascular medicine · 2025Article
- Membrane transporters in drug development and as determinants of precision medicine.Nature reviews. Drug discovery · 2024Review
- Clinical Evaluation of the Effect of Encorafenib on Bupropion, Rosuvastatin, and Coproporphyrin I and Considerations for Statin Coadministration.Clinical pharmacokinetics · 2024Article
- Physiologically Based Pharmacokinetic (PBPK) Model Predictions of Disease Mediated Changes in Drug Disposition in Patients with Nonalcoholic Fatty Liver Disease (NAFLD).Pharmaceutical research · 2024Article
- Building a Predictive PBPK Model for Human OATP Substrates: a Strategic Framework for Early Evaluation of Clinical Pharmacokinetic Variations Using Pitavastatin as an Example.The AAPS journal · 2024Article
- In Vitro Assessment of Transporter Mediated Perpetrator DDIs for Several Hepatitis C Virus Direct-Acting Antiviral Drugs and Prediction of DDIs with Statins Using Static Models.The AAPS journal · 2022Article
- Quantitative prediction of breast cancer resistant protein mediated drug-drug interactions using physiologically-based pharmacokinetic modeling.CPT: pharmacometrics & systems pharmacology · 2021Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Physiologically-based pharmacokinetic (PBPK) modeling is increasingly used to predict drug disposition and drug-drug interactions (DDIs). However, accurately predicting the pharmacokinetics of transporter substrates and transporter-mediated DDIs (tDDIs) is still challenging. Rosuvastatin is a commonly used substrate probe in DDI risk assessment for new molecular entities (NMEs) that are potential organic anion transporting polypeptide 1B or breast cancer resistance protein transporter inhibitors, and as such, several rosuvastatin PBPK models have been developed to try to predict the clinical DDI and support NME drug labeling. In this review, we examine five representative PBPK rosuvastatin models, discuss common challenges that the models have come across, and note remaining gaps. These shared learnings will help with the continuing efforts of rosuvastatin model validation, provide more information to understand transporter-mediated drug disposition, and increase confidence in tDDI prediction.
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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.