Trial reportThe AAPS journal2020
Physiologically Based Pharmacokinetic Modeling of Oral Absorption, pH, and Food Effect in Healthy Volunteers to Drive Alpelisib Formulation Selection.
Trial report in The AAPS journal, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 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.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
12 citing papers in PubMed, 21 citations in OpenAlex.
- Predicting and Confirming Bioequivalence of Alpelisib Oral Granules and Tablets for Patients With PIK3CA-Related Disorders.AAPS PharmSciTech · 2025Trial
- Trial
- Machine Learning Enables Rapid Prediction of Acid-Reducing Agent Drug Interactions: A Streamlined Complement to PBPK Modeling.CPT: pharmacometrics & systems pharmacology · 2026Article
- Quantitative Estimation of Clinical Intrasubject Variability of a Pharmacokinetic Parameter.The AAPS journal · 2026Article
- In Vivo PK-PD and Drug-Drug Interaction Study of Dorzagliatin for the Management of PI3Kα Inhibitor-Induced Hyperglycemia.Pharmaceuticals (Basel, Switzerland) · 2025Article
- Advancements in Virtual Bioequivalence: A Systematic Review of Computational Methods and Regulatory Perspectives in the Pharmaceutical Industry.Pharmaceutics · 2024Review
- Advances in Modeling Approaches for Oral Drug Delivery: Artificial Intelligence, Physiologically-Based Pharmacokinetics, and First-Principles Models.Pharmaceutics · 2024Review
- Application of physiologically based pharmacokinetics modeling in the research of small-molecule targeted anti-cancer drugs.Cancer chemotherapy and pharmacology · 2023Review
- Streamlining Food Effect Assessment - Are Repeated Food Effect Studies Needed? An IQ Analysis.The AAPS journal · 2023Article
- Prediction of gastric pH-mediated drug exposure using physiologically-based pharmacokinetic modeling: A case study of itraconazole.CPT: pharmacometrics & systems pharmacology · 2023Article
- In-Depth Analysis of Physiologically Based Pharmacokinetic (PBPK) Modeling Utilization in Different Application Fields Using Text Mining Tools.Pharmaceutics · 2022Review
- Prediction for optimal dosage of pazopanib under various clinical situations using physiologically based pharmacokinetic modeling.Frontiers in pharmacology · 2022Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
8 authors at 3 institutions in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
A physiologically based pharmacokinetic (PBPK) human model for alpelisib, an oral α-specific class I phosphatidylinositol-3-kinase (PI3K) inhibitor, was established to simulate oral absorption and plasma pharmacokinetics of healthy subjects to allow model-informed drug development. The GastroPlus™ model consisted of an advanced absorption gut model, which was linked to a 2-compartmental model. Systemic clearance and volume of distribution were estimated using population pharmacokinetics (popPK). Various food effect and pH-mediated absorption drug-drug interaction (DDI) scenarios were modeled. In fasted healthy subjects, simulated absorption was lower (ca. 70% for a 300-mg dose) due to pH and bile acid concentration-dependent solubility. Ranitidine showed a significant pH-mediated DDI effect only in the fasted but not fed state. The PBPK model identified that more drug is absorbed in the fed state, and alpelisib intestinal permeability is rate limiting to systemic exposure. Simulations for healthy subject showed a positive food effect with ca. 2-fold increase in plasma Cmax and 1.5-fold increase in AUC0-inf with a meal compared with fasted conditions. The PBPK model was verified using clinical food effect data with pivotal clinical formulation (PCF) and then applied to predict the performance of a commercial formulation (CF) in healthy volunteers. The model successfully predicted the outcome of a clinical bioequivalence study for PCF and CF with included in vitro dissolution data, both fasted and fed state. Estimated predictive errors (based on plasma Cmax, AUC0-t) were equal or below 30%. The alpelisib model for healthy subjects enables future bioequivalence formulation assessments, in fasted, fed, or altered pH conditions. Graphical Abstract.
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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.