Gene/Protein Disease Symptom Drug Enzyme Compound
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Query: EC:2.3.1.21 (CPT)
 4,580 document(s) hit in 31,850,051 MEDLINE articles (0.00 seconds)

Sirolimus is an inhibitor of mammalian target of rapamycin (mTOR) and is increasingly being used in transplantation and cancer therapies. Sirolimus has low oral bioavailability and exhibits large pharmacokinetic variability. The underlying mechanisms for this variability have not been explored to a large extent. Sirolimus metabolism was characterized by in vitro intrinsic clearance estimation. Pathway contribution ranked from CYP3A4 > CYP3A5 > CYP2C8. With the well stirred and Qgut models sirolimus bioavailability was predicted at 15%. Interindividual differences in bioavailability could be attributed to variable intestinal CYP3A expression. The physiologically-based pharmacokinetics (PBPK) model developed in Simcyp predicted a high distribution of sirolimus into adipose tissue and another elimination pathway in addition to CYP-mediated metabolism. PBPK model predictive performance was acceptable with Cmax and area under the curve (AUC) estimates within 20% of observed data in a dose escalation study. The model also showed potential to assess the impact of hepatic impairment and drug-drug interaction (DDI) on sirolimus pharmacokinetics.CPT: Pharmacometrics & Systems Pharmacology (2013) 2, e59; doi:10.1038/psp.2013.33; published online 24 July 2013.
CPT Pharmacometrics Syst Pharmacol 2013 Jul 24
PMID:Development of a Physiologically-Based Pharmacokinetic Model for Sirolimus: Predicting Bioavailability Based on Intestinal CYP3A Content. 2388 7

Evaluation of a potential risk of metabolic drug-drug interactions (DDI) is of high importance in the clinical setting. In this study, a physiologically based pharmacokinetic (PBPK) model was developed for oxycodone and its two primary metabolites, oxymorphone and noroxycodone, in order to assess different DDI scenarios using published in vitro and in vivo data. Once developed and refined, the model was able to simulate pharmacokinetics of the three compounds and the DDI extent in case of coadministration with an inhibitor, as well as the oxymorphone concentration variation between CYP2D6 extensive metabolizers (EM) and poor metabolizers (PM). The reliability of the model was tested against published clinical studies monitoring different inhibitors and dose regimens, and all predicted area under the concentration-time curve (AUC) ratios were within the twofold acceptance range. This approach represents a strategy to evaluate the impact of coadministration of different CYP inhibitors using mechanistic incorporation of drug-dependent and system-dependent available in vitro and in vivo data.
CPT Pharmacometrics Syst Pharmacol 2014 Dec 17
PMID:Prediction of Metabolic Interactions With Oxycodone via CYP2D6 and CYP3A Inhibition Using a Physiologically Based Pharmacokinetic Model. 2551 25

Acalabrutinib, a selective, covalent Bruton tyrosine kinase inhibitor, is a CYP3A substrate and weak CYP3A/CYP2C8 inhibitor. A physiologically-based pharmacokinetic (PBPK) model was developed for acalabrutinib and its active metabolite ACP-5862 to predict potential drug-drug interactions (DDIs). The model indicated acalabrutinib would not perpetrate a CYP2C8 or CYP3A DDI with the sensitive CYP substrates rosiglitazone or midazolam, respectively. The model reasonably predicted clinically observed acalabrutinib DDI with the CYP3A perpetrators itraconazole (4.80-fold vs. 5.21-fold observed) and rifampicin (0.21-fold vs. 0.23-fold observed). An increase of two to threefold acalabrutinib area under the curve was predicted for coadministration with moderate CYP3A inhibitors. When both the parent drug and active metabolite (total active components) were considered, the magnitude of the CYP3A DDI was much less significant. PBPK dosing recommendations for DDIs should consider the magnitude of the parent drug excursion, relative to safe parent drug exposures, along with the excursion of total active components to best enable safe and adequate pharmacodynamic coverage.
CPT Pharmacometrics Syst Pharmacol 2019 07
PMID:Evaluation of the Drug-Drug Interaction Potential of Acalabrutinib and Its Active Metabolite, ACP-5862, Using a Physiologically-Based Pharmacokinetic Modeling Approach. 3104 21