ArticlePharmaceutical research2022
Development of Physiology Based Pharmacokinetic Model to Predict the Drug Interactions of Voriconazole and Venetoclax.
Article in Pharmaceutical research, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers.
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Who cites it
16 citing papers in PubMed, 19 citations in OpenAlex.
- Assessing the Influence of CYP3A4 Inhibitors on Voriconazole Exposure across CYP2C19 Genotypes: A Physiologically Based Pharmacokinetic Model Analysis.Clinical pharmacokinetics · 2026Article
- Association between venetoclax concentration and febrile neutropenia in acute leukemia: a retrospective analysis.European journal of clinical pharmacology · 2026Article
- Analysis of interactions between posaconazole/voriconazole and venetoclax.Antimicrobial agents and chemotherapy · 2026Article
- [Simultaneous determination of selinexor， posaconazole， venetoclax， and voriconazole in human plasma using ultra-high performance liquid chromatography-tandem mass spectrometry].Se pu = Chinese journal of chromatography · 2026Article
- Population Pharmacokinetic Analyses and Exposure-Efficacy Relationships of Venetoclax in Chinese Pediatric Patients with Hematological Malignancy in a Real-World Setting.Drug design, development and therapy · 2026Article
- Comparative pharmacokinetics of voriconazole between elderly and young adult patients: a population pharmacokinetic study.Journal of pharmaceutical policy and practice · 2026Article
- Chinese population may require further venetoclax dose reduction beyond guidelines when combined with voriconazole: real-world evidence from China.Frontiers in pharmacology · 2025Article
- Utilizing Physiologically Based Pharmacokinetic Models to Support Rational Medication in Chinese Elderly Population.Drug design, development and therapy · 2025Article
- Venetoclax combined with ATRA shows promising therapeutic potential for TFG:: RARA variant APL: a case report.Frontiers in oncology · 2025Article
- Venetoclax concentration affects the incidence of haematological adverse events in patients with acute myeloid leukaemia.Frontiers in pharmacology · 2025Article
- Preclinical pharmacokinetic studies and prediction of human PK profiles for Deg-AZM, a clinical-stage new transgelin agonist.Frontiers in pharmacology · 2024Article
- A Physiologically Based Pharmacokinetic Approach to Recommend an Individual Dose of Tacrolimus in Adult Heart Transplant Recipients.Pharmaceutics · 2023Article
- Evaluation of the inhibitory effect of azoles on pharmacokinetics of lenvatinib in rats both in vivo and in vitro by UPLC-MS/MS.Thoracic cancer · 2023Article
- Application of physiologically based pharmacokinetics modeling in the research of small-molecule targeted anti-cancer drugs.Cancer chemotherapy and pharmacology · 2023Review
- Venetoclax with CAG regimen for early T-cell precursor acute lymphoblastic leukemia: a case report and literature review.International journal of hematology · 2023Review
- Comparing the Real-World Use of Isavuconazole to Other Anti-Fungal Therapy for Invasive Fungal Infections in Patients with and without Underlying Disparities: A Multi-Center Retrospective Study.Journal of fungi (Basel, Switzerland) · 2023Article
Corrections and comments
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Authors and funding
5 authors at 4 institutions in 2 countries.
Funding
Abstract
purposeVenetoclax (VEN), an anti-tumor drug that is a substrate of cytochrome P450 3A enzyme (CYP3A4), is used to treat leukemia. Voriconazole (VCZ) is an antifungal medication that inhibits CYP3A4. The goal of this study is to predict the effect of VCZ on VEN exposure.
methodTwo physiological based pharmacokinetics (PBPK) models were developed for VCZ and VEN using the bottom-up and top-down method. VCZ model was also developed to describe the effect of CYP2C19 polymorphism on its pharmacokinetics (PK). The reversible inhibition constant (K
resultVCZ model predicted VCZ exposure in the subjects of different CYP2C19 genotype and DDI related fold changes of sensitive CYP3A substrate with acceptable prediction error. VEN model can capture PK of VEN with acceptable prediction error. The DDI PBPK model predicted that VCZ increased the exposure of VEN by 4.5-9.6 fold. The increase in VEN exposure by VCZ was influenced by subject's CYP2C19 genotype. According to the therapeutic window, VEN dose should be reduced to 100 mg when co-administered with VCZ.
conclusionThe PBPK model developed here could support individual dose adjustment of VEN and DDI risk assessment. Predictions using the robust PBPK model confirmed that the 100 mg dose adjustment is still applicable in the presence of VCZ with high inter-individual viability.
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