Gene/Protein Disease Symptom Drug Enzyme Compound
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Query: UMLS:C0268596 (EMA)
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Intra- and/or inter-individual variability in drug response is mainly a result of either subtherapeutic or supratherapeutic plasma levels of the active drugs and their metabolites, with this variability mainly being influenced by differences in the rate of drug metabolism. Indeed, drug metabolism is largely determined by genetic polymorphism in the CYP enzymes, which are responsible for approximately 85% of the drug metabolism process. However, this genetic heterogeneity can accurately predict actual drug metabolizing capacity (oxidation phenotype) for some individuals: poor metabolizers (PMs), who cannot produce the drug metabolizing enzymes, and 20% of ultra-rapid metabolizers. According to EMA recommendations, phenotyping procedures for drug interaction studies and clinical research are therefore required to obtain actual data on the main CYP enzymes. With this purpose, cocktail phenotyping approaches give information on the activity of different CYPs in just one experiment. In this review, the issues related to the phenotyping of the main CYP enzymes are reviewed, and the current in vivo phenotyping cocktails are analysed: the sampling procedures, probe drugs utilized, analytical techniques and main applications are also discussed. Based on this analysis, a fully validated cocktail approach to measure the metabolic activity of the main CYP enzymes and drug transporters is still required. This novel approach should fulfil certain conditions: a faster and simpler analytical methodology to obtain information on several CYPs in one experiment, minimal sample amounts, and minimal doses of optimal probe drugs.
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PMID:Simultaneous Determination of Cytochrome P450 Oxidation Capacity in Humans: A Review on the Phenotyping Cocktail Approach. 2767 73

We present g-Nomic, a pharmacogenetics interpretation software that analyzes globally a prescribed medication taking into account the personal background genetics, drug-drug interactions, lifestyle, nutritional supplements, inhibitors, inducers, and other risks to analyze primary or secondary metabolism pathways. G-Nomic provides a set of recommendations describing the suitability of a given combination of drugs for each patient according to their genes and polymedication. G-Nomic is updated monthly including data from the new drugs to be included, their known interactions, and the relevant pharmacokinetic biomarkers. For the interactions, the list is curated manually, only keeping those with clinical relevance. For each drug, their FDA and EMA drug labels are accessed, to check for relevant enzymes and transport proteins that influence its pharmacokinetics, and for their ability to induce or inhibit other enzymes, particularly the CYP-450 system. When this information is not available, a PubMed search is made to look for these characteristics. In addition, a distinction is made between drugs and prodrugs. A query on the g-Nomic software begins with entering the medication by either their common or commercial name. Non-pharmacological substances can be also added or selected under "lifestyle habits". The lifestyle list is dynamic, showing only the substances known to interact with the drugs that are currently selected, and includes herb compounds, such as St. John's wort, as well as proper lifestyle substances such as grapefruit or cigarette smoking. The software provides a list of the genes classified as primary biomarkers as candidates for genetic testing, and a list of the interactions that have been detected. If genetic information is available then, or is made available at a later point, these results can also be entered and the software returns pharmacogenetics recommendations regarding specific genotypes. g-Nomic takes all the above-mentioned parameters in an easy and user-friendly tool making prescription safer.
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PMID:g-Nomic: a new pharmacogenetics interpretation software. 3123 53

Translational and ADME Sciences Leadership Group (TALG) Induction Working Group (IWG) presents an analysis on the time-course for cytochrome P450 induction in primary human hepatocytes. Induction of CYP1A2, CYP2B6, and CYP3A4 was evaluated by seven IWG laboratories following incubation with prototypical inducers (omeprazole, phenobarbital, rifampicin, and efavirenz) for 6 to 72 hours. The effect of incubation duration and model-fitting approaches on induction parameters (Emax and EC50) and drug-drug interaction (DDI) risk assessment was determined. Despite variability in induction response across hepatocyte donors, the following recommendations are proposed: i) 48 hours should be the primary time point for in vitro assessment of induction, based on mRNA level or activity, with no further benefit from 72 hours, ii) when using mRNA, 24 hour incubations provide reliable assessment of induction and DDI risk, iii) if validated using prototypical inducers (>10-fold induction), 12-hour incubations may provide an estimate of induction potential including characterization as negative if < 2-fold induction of mRNA and no concentration-dependence, iv) atypical dose-response ('bell-shaped') curves can be addressed by removing points outside an established confidence interval and %CV, v) when maximum fold induction is well-defined, the choice of non-linear regression model has limited impact on estimated induction parameters, vi) when the maximum-fold induction is not well-defined, conservative DDI risk assessment can be obtained using sigmoidal-3-parameter fit or constraining logistic 3/4 parameter fits to the maximum observed fold induction, vii) preliminary data suggest initial slope of the fold induction curve can be used to estimate Emax/EC50 and for induction risk assessment. Significance Statement Regulatory agencies have provided inconsistent guidance on the optimum length of time to evaluate CYP induction in human hepatocytes, with the EMA recommending 72 h and the FDA suggesting 48 to 72 h. The IWG analyzed a large dataset generated by 7 member companies and determined that induction response and drug-drug risk assessment determined after 48 h incubations was representative of 72 h incubations. Additional recommendations are provided on model-fitting techniques for induction parameter estimation and addressing atypical concentration-response curves.
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PMID:Considerations from the Innovation and Quality Induction Working Group in Response to Drug-Drug Interaction Guidance from Regulatory Agencies: Guidelines on Model Fitting and Recommendations on Time Course for In Vitro CYP Induction Studies Including Impact on Drug Interaction Risk Assessment. 3313 60