Drug interactions evaluation: An integrated part of risk assessment of therapeutics
ABSTRACT Pharmacokinetic drug interactions can lead to serious adverse events or decreased drug efficacy. The evaluation of a new molecular entity's (NME's) drug-drug interaction potential is an integral part of risk assessment during drug development and regulatory review. Alteration of activities of enzymes or transporters involved in the absorption, distribution, metabolism, or excretion of a new molecular entity by concomitant drugs may alter drug exposure, which can impact response (safety or efficacy). The recent Food and Drug Administration (FDA) draft drug interaction guidance (http://www.fda.gov/downloads/Drugs/GuidanceComplianceRegulatoryInformation/Guidances/ucm072101.pdf) highlights the methodologies and criteria that may be used to guide drug interaction evaluation by industry and regulatory agencies and to construct informative labeling for health practitioner and patients. In addition, the Food and Drug Administration established a "Drug Development and Drug Interactions" website to provide up-to-date information regarding evaluation of drug interactions (http://www.fda.gov/Drugs/DevelopmentApprovalProcess/DevelopmentResources/DrugInteractionsLabeling/ucm080499.htm). This review summarizes key elements in the FDA drug interaction guidance and new scientific developments that can guide the evaluation of drug-drug interactions during the drug development process.
- SourceAvailable from: Endalkachew Admassie
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- "A pharmacokinetic interaction occurs when a drug alters the pharmacokinetic processes such as absorption, distribution, metabolism (most often due to interaction with the cytochrome P450 hepatic enzymes), and/or excretion of another medication. A pharmaceutical interaction occurs when mixing chemically incompatible drugs outside the body, as for example, incompatibility of Phenobarbital with opioid analgesics when mixed in the same syringe, resulting in inactivation of one or both drugs. "
ABSTRACT: The aim of this study was to assess the extent of poly-pharmacy, occurrence, and associated factors for the occurrence of drug–drug interaction (DDI) and potential adverse drug reaction (ADR) in Gondar University Teaching Referral Hospital. Institutional-based retrospective cross-sectional study. This study was conducted on prescriptions of both in and out-patients for a period of 3 months at Gondar University Hospital. Both bivariate analysis and multivariate logistic regression were used to identify risk factors for the occurrence of DDI and possible ADRs. All the statistical calculations were performed using SPSS® software. A total of 12,334 prescriptions were dispensed during the study period of which, 2,180 prescriptions were containing two or more drugs per prescription. A total of 21,210 drugs were prescribed and the average number of drugs per prescription was 1.72. Occurrences of DDI of all categories (Major, Moderate, and Minor) were analyzed and DDI were detected in 711 (32.6%) prescriptions. Sex was not found to be a risk factor for the occurrence of DDI and ADR, while age and number of medications per prescription were found to be significant risk factors for the occurrence of DDI and ADR. The mean number of drugs per prescription was 1.72 and hence with regard to the WHO limit of drugs per prescription, Gondar hospital was able to maintain the limit and prescriptions containing multiple drugs supposed to be taken systemically. Numbers of drugs per prescription as well as older age were found to be predisposing factors for the occurrence of DDI and potential ADRs while sex was not a risk factor.Journal of Advanced Pharmaceutical Technology & Research 11/2013; 4(4):183-9. DOI:10.4103/2231-4040.121412
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- "We also do not know whether chimeric mice can be used to prospectively evaluate the potential for a drug-drug interaction (DDI) involving a candidate therapeutic to occur in human subjects. Because more than 30% of the US population over 57 years of age take five or more prescription drugs at a given time, DDIs have created major problems for patients and for regulatory authorities (Zhang et al., 2010). However, with use of available in vitro or in vivo animal models, it has been difficult to predict many of the clinically important DDIs, which only became apparent after drug development was completed (Bode, 2010). "
ABSTRACT: Inter-species differences in drug metabolism have made it difficult to use pre-clinical animal testing data to predict the drug metabolites or potential drug-drug interactions (DDI) that will occur in humans. Although chimeric mice with humanized livers can produce known human metabolites for test substrates, we do not know whether chimeric mice can be used to prospectively predict human drug metabolism or a possible DDI. Therefore, we investigated whether they could provide a more predictive assessment for clemizole, a drug in clinical development for the treatment of hepatitis C virus (HCV) infection. Our results demonstrate, for the first time, that analyses performed in chimeric mice can correctly identify the predominant human drug metabolite prior to human testing. The differences in the rodent and human pathways for clemizole metabolism were of importance, since the predominant human metabolite was found to have synergistic anti-HCV activity. Moreover, studies in chimeric mice also correctly predicted that a DDI would occur in humans when clemizole was co-administered with a CYP3A4 inhibitor. These results demonstrate that using chimeric mice can improve the quality of pre-clinical drug assessment.Journal of Pharmacology and Experimental Therapeutics 11/2012; 344(2). DOI:10.1124/jpet.112.198697 · 3.86 Impact Factor
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- "The ever-increasing popularity of certain foods and dietary supplements as a means to decrease health care costs via self-diagnosis and treatment is due in part to the widely held view that these products are safer, " natural " alternatives to prescription, as well as non-prescription, drugs  . Evaluation of drug interaction liability of new drug candidates is strictly defined  , whereas that for foods and supplements is not. Consequently, robust guidelines on the evaluation of potential drug-dietary substance interactions are essentially non-existent. "
ABSTRACT: Successful delivery of promising new chemical entities via the oral route is rife with challenges, some of which cannot be explained or foreseen during drug development. Further complicating an already multifaceted problem is the obvious, yet often overlooked, effect of dietary substances on drug disposition and response. Some dietary substances, particularly fruit juices, have been shown to inhibit biochemical processes in the intestine, leading to altered pharmacokinetic (PK), and potentially pharmacodynamic (PD), outcomes. Inhibition of intestinal CYP3Amediated metabolism is the major mechanism by which fruit juices, including grapefruit juice, enhances systemic exposure to new and already marketed drugs. Inhibition of intestinal non-CYP3A enzymes and apically-located transport proteins represent recently identified mechanisms that can alter PK and PD. Several fruit juices have been shown to inhibit these processes in vitro, but some interactions have not translated to the clinic. The lack of in vitroin vivo concordance is due largely to a lack of rigorous methods to elucidate causative ingredients prior to clinical testing. Identification of specific components and underlying mechanisms is challenging, as dietary substances frequently contain multiple, often unknown, bioactive ingredients that vary in composition and bioactivity. A translational research approach, combining expertise from clinical pharmacologists and natural products chemists, is needed to develop robust models describing PK/PD relationships between a given dietary substance and drug of interest. Validation of these models through well-designed clinical trials would facilitate development of common practice guidelines for managing drug-dietary substance interactions appropriately.Current Drug Metabolism 11/2010; 11(9):778-92. DOI:10.2174/138920010794328869 · 3.49 Impact Factor