ArticleClinical pharmacology and therapeutics2022
Physiologically Based Pharmacokinetic Modelling to Investigate the Impact of the Cytokine Storm on CYP3A Drug Pharmacokinetics in COVID-19 Patients.
Article in Clinical pharmacology and therapeutics, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.
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Who cites it
9 citing papers in PubMed, 24 citations in OpenAlex.
- Trial
- Is PBPK useful to inform product label on managing clinically significant drug interactions mediated by cytokine release syndrome?CPT: pharmacometrics & systems pharmacology · 2024Article
- Evaluating drug interaction potential from cytokine release syndrome using a physiologically based pharmacokinetic model: A case study of teclistamab.CPT: pharmacometrics & systems pharmacology · 2024Article
- Virus-Induced Epilepsy vs. Epilepsy Patients Acquiring Viral Infection: Unravelling the Complex Relationship for Precision Treatment.International journal of molecular sciences · 2024Review
- Evaluation of the potential impact on pharmacokinetics of various cytochrome P450 substrates of increasing IL-6 levels following administration of the T-cell bispecific engager glofitamab.CPT: pharmacometrics & systems pharmacology · 2024Article
- Assessment of CYP3A-mediated drug interaction via cytokine (IL-6) elevation for mosunetuzumab using physiologically-based pharmacokinetic modeling.CPT: pharmacometrics & systems pharmacology · 2024Article
- Physiologically Based Pharmacokinetic Modeling Approaches for Patients With SARS-CoV-2 Infection: A Case Study With Imatinib.Journal of clinical pharmacology · 2022Article
- Inflammation and cardiovascular status impact midazolam pharmacokinetics in critically ill children: An observational, prospective, controlled study.Pharmacology research & perspectives · 2022Observational
- Therapeutic targets and functions of curcumol against COVID-19 and colon adenocarcinoma.Frontiers in nutrition · 2022Article
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Authors and funding
4 authors at 3 institutions in 2 countries.
Funding
Abstract
Patients with coronavirus disease 2019 (COVID-19) may experience a cytokine storm with elevated interleukin-6 (IL-6) levels in response to severe acute respiratory syndrome-coronavirus 2 (SARS-CoV-2). IL-6 suppresses hepatic enzymes, including CYP3A; however, the effect on drug exposure and drug-drug interaction magnitudes of the cytokine storm and resulting elevated IL-6 levels have not been characterized in patients with COVID-19. We used physiologically-based pharmacokinetic (PBPK) modeling to simulate the effect of inflammation on the pharmacokinetics of CYP3A metabolized drugs. A PBPK model was developed for lopinavir boosted with ritonavir (LPV/r), using clinically observed data from people living with HIV (PLWH). The inhibition of CYPs by IL-6 was implemented by a semimechanistic suppression model and verified against clinical data from patients with COVID-19, treated with LPV/r. Subsequently, the verified model was used to simulate the effect of various clinically observed IL-6 levels on the exposure of LPV/r and midazolam, a CYP3A model drug. Clinically observed LPV/r concentrations in PLWH and patients with COVID-19 were predicted within the 95% confidence interval of the simulation results, demonstrating its predictive capability. Simulations indicated a twofold higher LPV exposure in patients with COVID-19 compared with PLWH, whereas ritonavir exposure was predicted to be comparable. Varying IL-6 levels under COVID-19 had only a marginal effect on LPV/r pharmacokinetics according to our model. Simulations showed that a cytokine storm increased the exposure of the CYP3A paradigm substrate midazolam by 40%. Our simulations suggest that CYP3A metabolism is altered in patients with COVID-19 having increased cytokine release. Caution is required when prescribing narrow therapeutic index drugs particularly in the presence of strong CYP3A inhibitors.
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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.