Physiologically Based Precision Dosing Approach for Drug‐Drug‐Gene Interactions: A Simvastatin Network Analysis
Open accessAbstract
Drug‐drug interactions (DDIs) and drug‐gene interactions (DGIs) are well known mediators for adverse drug reactions (ADRs), which are among the leading causes of death in many countries. Because physiologically based pharmacokinetic (PBPK) modeling has demonstrated to be a valuable tool to improve pharmacotherapy affected by DDIs or DGIs, it might also be useful for precision dosing in extensive interaction network scenarios. The presented work proposes a novel approach to extend the prediction capabilities of PBPK modeling to complex drug‐drug‐gene interaction (DDGI) scenarios. Here, a whole‐body PBPK network of simvastatin was established, including three polymorphisms (SLCO1B1 (rs4149056), ABCG2 (rs2231142), and CYP3A5 (rs776746)) and four perpetrator drugs (clarithromycin, gemfibrozil, itraconazole, and rifampicin). Exhaustive network simulations were performed and ranked to optimize 10,368 DDGI scenarios based on an exposure marker cost function. The derived dose recommendations were translated in a digital decision support system, which is available at simvastatin.precisiondosing.de. Although the network covers only a fraction of possible simvastatin DDGIs, it provides guidance on how PBPK modeling could be used to individualize pharmacotherapy in the future. Furthermore, the network model is easily extendable to cover additional DDGIs. Overall, the presented work is a first step toward a vision on comprehensive precision dosing based on PBPK models in daily clinical practice, where it could drastically reduce the risk of ADRs.
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Wojtiniak reported that only when the BCRP transporter was included in the blood cells were they able to recover the AUC changes observed for the poor transporter phenotype.
“In line with this, Wojtiniak 48 reported that only when the BCRP transporter was included in the blood cells were they able to recover the AUC changes observed for the poor transporter phenotype.”
From Does the choice of applied physiologically‐based pharmacokinetics platform matter? A case study on simvastatin disposition and drug–drug interaction (2022) · cites this paper as [48]
There are several previously published PBPK models for simvastatin: one in Simcyp, two in PK-Sim, and another semimechanistic PBPK model in NONMEM.
“There are several previously published PBPK models for simvastatin: one in Simcyp, 39 two in PK‐Sim 47 , 48 and another semimechanistic PBPK model in NONMEM. 49”
From Does the choice of applied physiologically‐based pharmacokinetics platform matter? A case study on simvastatin disposition and drug–drug interaction (2022) · cites this paper as [48]
The CYP3A4 contribution to SVA elimination has not been reported in previous published simvastatin PBPK models.
“The CYP3A4 contribution to SVA elimination has not been reported in previous published simvastatin PBPK models. 48 , 49”
From Does the choice of applied physiologically‐based pharmacokinetics platform matter? A case study on simvastatin disposition and drug–drug interaction (2022) · cites this paper as [48]
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Novel models for the prediction of drug–gene interactions
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InfluentialEffects of SLCO1B1 Genetic Variant on Metabolite Profile in Participants on Simvastatin Treatment
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- Authors
- Wojtyniak, J., Selzer, D., Schwab, M., & Lehr, T.
- Affiliations
- Dr. Margarete Fischer-Bosch-Institute of Clinical Pharmacology (DE)
- Saarland University (DE)
- Corresponding author
- Lehr, Thorsten
- Venue
- Clinical Pharmacology & Therapeutics
- Publisher
- Wiley
- Published
- 2020-12-06
- Volume
- 109
- Issue
- 1
- Pages
- 201-211
- ISSN
- 0009-9236 (ISSN-L)
- 1532-6535
- OpenAlex
- W3111705491
- Cited by
- 38
- References
- 48
- Citations by year
- 2026: 4 · 2025: 6 · 2024: 5 · 2023: 6 · 2022: 11 · 2021: 6
- FWCI
- 5.08
- Type
- journal article
- Language
- en
- Open access
- hybrid
- doi.org
- Licence
- Locations
- Clinical Pharmacology & Therapeutics (publishedVersion, cc-by-nc)
- PubMed (publishedVersion)
- Publications of the UdS (Saarland University)
- Funders
- Robert Bosch
- European Commission
- Horizon 2020 Framework Programme (668353)
- Deutsche Forschungsgemeinschaft
- Topics
- Life Sciences › Pharmacology, Toxicology and Pharmaceutics › Pharmacology › Pharmacogenetics and Drug Metabolism
- Health Sciences › Medicine › Pediatrics, Perinatology and Child Health › Pharmaceutical studies and practices
- Physical Sciences › Computer Science › Computational Theory and Mathematics › Computational Drug Discovery Methods
- Keywords
- precision dosing, drug-drug interactions, drug-gene interactions, simvastatin, physiologically based pharmacokinetic modeling, SLCO1B1, ABCG2, CYP3A5, clarithromycin, gemfibrozil, itraconazole, rifampicin, adverse drug reactions, digital decision support systems, individualized drug therapy
- MeSH terms
- ATP Binding Cassette Transporter, Subfamily G, Member 2, Adult, Computer Simulation, Drug Interactions, Humans, Male, Models, Biological, Polymorphism, Genetic, Simvastatin, Liver-Specific Organic Anion Transporter 1, Cytochrome P-450 CYP3A, Precision Medicine
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