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

7-Ethyl-10[4-(1-piperidino)-1-piperidino] carbonyloxy-camptothecin (CPT-11), a DNA topoisomerase I inhibitor, undergoes several metabolic pathways to generate conjugated and unconjugated derivatives that could be excreted from the body. The objective of this study was to determine the oxidative metabolites of CPT-11 recovered in human urine samples and to identify cytochrome P450 (CYP) involved in their formation. In addition to the already known metabolites of CPT-11 [SN-38, SN-38-G, 7-ethyl-10-[4-N-(5-aminopentanoic acid)-1-piperidino]carbonyloxycamptothecin (APC), and 7-ethyl-10-(4-amino-1-piperidino) carbonyloxycamptothecin (NPC)], we isolated three oxidized metabolites from the urine of two children and two adults given CPT-11. M1 and M2 (molecular weight, 602) were hydroxylated, respectively, on the CPT moiety and on the terminal piperidine ring of CPT-11. M3 had a molecular mass of 602, but its urine concentration in patients was too low to establish its chemical structure by liquid chromatography/mass spectrometry. In vitro incubations with cells expressing CYP2C8, CYP2C9, CYP1A1, CYP1A2, or CYP3A7 did not produce any detectable metabolites. Only CYP3A4 produced both APC and NPC, resulting from the oxidation of the piperidinylpiperidine side chain of CPT-11 along with metabolite M2. The metabolism of CPT-11 by CYP3A5 was markedly different because neither APC or NPC nor M2 was produced, whereas only one new metabolite, M4 (molecular weight, 558), was generated by de-ethylation of the CPT moiety. No previous study has reported the presence of the M4 metabolite. Production of APC, NPC, M2, and M4 was prevented by ketoconazole, a specific CYP3A inhibitor. The parameters of CPT-11 biotransformation into M2 and M4 were examined using cell lines expressing, respectively, with CYP3A4 and CYP3A5, indicating that CPT-11 is preferentially metabolized by CYP3A4. In conclusion, CYP3A plays a major role in the metabolism of CPT-11, with some differences of the metabolic profile exhibited by 3A4 and 3A5.
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PMID:Metabolism of irinotecan (CPT-11) by CYP3A4 and CYP3A5 in humans. 1081 27

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

This study describes the maturation of sirolimus clearance in a cohort of very young pediatric patients with vascular anomalies. The relationship between allometrically scaled in vivo clearance and age was described by the Emax model in patients aged 1 month to 2 years. Consistent with the observed increase, in vitro intrinsic clearance of sirolimus using pediatric liver microsomes showed a similar age-dependent increase. In children older than 2 years, allometrically scaled sirolimus clearance did not show further maturation. Simulated clearance estimates with a sirolimus physiologically based pharmacokinetic model that included CYP3A4/5/7 and CYP2C8 maturation profiles were in close agreement with observed in vivo clearance values. In addition, physiologically based pharmacokinetic model-simulated sirolimus pharmacokinetic profiles predicted the actual observations well. These results demonstrate the utility of a physiologically based pharmacokinetic modeling approach for the prediction of the developmental trajectory of sirolimus metabolic activity and its effects on total body clearance in neonates and infants.
CPT Pharmacometrics Syst Pharmacol 2015 Feb
PMID:Development of a Pediatric Physiologically Based Pharmacokinetic Model for Sirolimus: Applying Principles of Growth and Maturation in Neonates and Infants. 2622 30

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

As rifampicin can cause the induction and inhibition of multiple metabolizing enzymes and transporters, it has been challenging to accurately predict the complex drug-drug interactions (DDIs). We previously constructed a physiologically-based pharmacokinetic (PBPK) model of rifampicin accounting for the components for the induction of cytochrome P450 (CYP) 3A/CYP2C9 and the inhibition of organic anion transporting polypeptide 1B (OATP1B). This study aimed to expand and verify the PBPK model for rifampicin by incorporating additional components for the induction of OATP1B and CYP2C8 and the inhibition of multidrug resistance protein 2. The established PBPK model was capable of accurately predicting complex rifampicin-induced alterations in the profiles of glibenclamide, repaglinide, and coproporphyrin I (an endogenous biomarker of OATP1B activities) with various dosing regimens. Our comprehensive rifampicin PBPK model may enable quantitative prediction of DDIs across diverse potential victim drugs and endogenous biomarkers handled by multiple metabolizing enzymes and transporters.
CPT Pharmacometrics Syst Pharmacol 2019 11
PMID:Expanded Physiologically-Based Pharmacokinetic Model of Rifampicin for Predicting Interactions With Drugs and an Endogenous Biomarker via Complex Mechanisms Including Organic Anion Transporting Polypeptide 1B Induction. 3142 Sep 41