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Drug interactions are always a major concern in medicine and within the pharmaceutical industry. Fatal drug interactions have been reported, and several prominent drugs have been withdrawn from the market because of serious adverse reactions related to drug interactions. Therefore, drug interactions represent not only a medical problem for clinicians, but also an economic loss for pharmaceutical companies. Today, many pharmaceutical companies are predicting potential interactions of new drug candidates in an attempt to minimize such losses and to more effectively safeguard the welfare of patients. Can in vivo drug interactions be predicted accurately from in vitro metabolic studies? Should the prediction be qualitative or quantitative? These are the fundamental questions that industrial drug metabolism scientists must confront daily. Prediction of in vivo drug interactions from in vitro metabolic data is highly controversial, because of the complexities of factors that are involved in drug interactions. Some scientists believe that quantitative prediction of drug interaction is possible, whereas others are less optimistic, and believe that quantitative prediction is extremely difficult, if not impossible. The purpose of this review is to present and discuss the technical problems inherent in estimating in vitro Ki values and in measuring inhibitor concentration at the active-site of enzymes. Theoretic considerations are briefly reviewed, and representative examples are drawn from literature to illustrate the sense and nonsense in predicting in vivo drug interactions.
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Drug interactions are important causes of both unexpected toxic and therapeutic effects. Adverse reactions due to drug interaction are proportional to the number of drugs given and the duration of administration. Although drug interactions may be beneficial, they are most often recognized when they increase mortality or morbidity. The frequency of adverse drug interactions in clinical practice makes it mandatory for physicians to know the drugs and mechanisms involved.A drug may potentiate or antagonize the effects of another drug by direct chemical or physical combination, by altering gastrointestinal absorption, by influencing metabolism, transport, or renal clearance, by changing the activity of a drug at its receptor site, or by modifying the patient's response to the drug by a variety of means. This article stresses the importance of avoiding multible drug therapy. When such treatment is unavoidable, patients must be carefully observed for evidence of intensified or diminished drug effect. Only this permits the detection and prevention of untoward drug interactions.
Drug interactions have been implicated in approximately 7 percent of all reported adverse drug reactions. Although many drug interactions are not clinically significant, the potential for an interaction increases from 5.6 percent in patients receiving two drugs to 100 percent in patients receiving eight or more drugs. Drug interactions can involve alterations in the pharmacokinetic parameters of absorption, distribution, metabolism and excretion, or can result from cumulative or antagonistic effects.
Drug therapy for rheumatoid arthritis (RA) often requires the use of more than one drug, thus drug-drug interactions are very likely in this patient population. We discuss the pharmacokinetic and pharmacodynamic mechanisms involved in drug-drug interactions. Our review focuses on selected examples involving drugs used to treat RA and other antirheumatic drugs [e.g., methotrexate and nonsteroidal antiinflammatory drugs (NSAID)] or with other therapeutic classes of drugs (e.g., NSAID and warfarin). Studies and case reports of drug-drug interactions with antirheumatic drugs are critically evaluated and the potential clinical implications are discussed.
Drug interactions may be responsible for certain changes in therapeutic response and toxicity of cardiac drugs. Interactions occur at the sites of drug absorption and elimination as well as at the receptor sites in the pacemaker cells, specialized conducting tissue, and myocardium. Studies of the kinetics of cardiac drugs are being applied clinically in an effort to reduce the danger of adverse drug interactions in heart patients.
Drug interactions are a major concern for health care professionals, the pharmaceutical manufacturing industry, the FDA, and the general public. Today we know that one of the primary causes of drug interactions is the cytochrome P450 enzymes. However, our knowledge about the complexities of these drug-metabolizing enzymes and the part they play in drug interactions is often limited. The actions and effects of P450 enzymes will be addressed in this article. Examples of induction and inhibition of P450 enzymes will illustrate how these enzymes can, in some instances, render a drug less potent and at other times more toxic. By understanding the unique actions of these enzymes, health care professionals may better anticipate, identify, explain, and manage individual responses to pharmacotherapeutic regimens.
Drug interactions are one of several outcomes (typically adverse) associated with drug therapy. The bulk of the clinical literature that has been published about drug interactions has focused either on the mechanisms, pharmacokinetic studies, or cases observed by clinicians. However, when it comes to the true risk of a drug interaction, or the probability of such an interaction occurring in a given population, a dearth of information is available. This area is opportune for the application of epidemiological and outcomes-based studies.
This algorithm aims at unifying and generalizing the algorithm for detecting all types of documented drug interactions such as drug-drug interactions, drug-disease interactions, drug-patient interactions (drug allergy) from patient profile information and drug-laboratory test interactions in real-time prescribing system. Ideally, the system should conform to the following criteria: (1) data independence; (2) software interconnectability; (3) knowledge expandability; (4) flexibility; and (5) computation resource efficiency. We propose a robust Structured Query Language (SQL) algorithm to detect drug interactions and drug allergy according to such criteria. We believe that this is the first public domain algorithm in SQL that could be easily implemented into most open-system prescribing software which support SQL language. The algorithm comprises two major stages: 'expand' and 'extract'. The former expands all information in the prescription with their synonyms, groups, or components. The latter extracts the documented interactions by inner-joining knowledge-base with two independent copies of the expanded prescription list simultaneously. Simulation study for speed performance indicates that this algorithm is well behaved, for the speed of computation does not grow faster than the growth in prescription size.
Drug interactions are a common and serious problem arising from polypharmacy. Strategies to reduce the likelihood of the co-prescription of hazardous drug combinations are likely to enhance the quality of care provided for patients requiring polypharmacotherapy. Drugs for which patient-oriented information strategies may decrease the likelihood of drug interactions tend to be those of low therapeutic index. and have interaction potential with other drugs commonly prescribed or available without prescription.
Drug interactions are often the result of complex biochemical, physical, and kinetic factors and may not often be easily predicted or even recognized. Although this article has attempted to point out the more common mechanisms and results of drug interactions, the few interactions that have been documented in small animals are undoubtedly only the tip of the iceberg. For the safety of patients and for the highest quality of veterinary care, it is essential that the practitioner become thoroughly familiar with the actions and interactions of drugs used in his or her practice and realize the possible consequences of multiple drug therapies before adding another drug to a therapeutic regimen. From a therapeutics standpoint, the temptation to polypharmacy is great, but the adage "an ounce of prevention is worth a pound of cure" is especially appropriate when discussing drug therapy. The rational decision to use as few drugs as possible in any given situation is the route to safe and successful drug therapy.
Drugs labeled with stable isotopes have been successfully used in pharmacokinetic drug interaction studies. This technique provides precise information on the mechanisms responsible for drug interactions, e.g., changes in clearance due to induction or inhibition of drug metabolism, bioavailability, and volume of distribution. It offers the advantage that detailed studies on the pharmacokinetics and metabolism of a drug can be conducted in a clinical setting during steady-state conditions, thus avoiding problems in patient management that can arise from studies in which drug is withdrawn.
Drug interactions may lead to adverse drug effects or therapeutic failure. Many clinically relevant unwanted interactions are caused by a change in the activity of cytochrome P450 isoenzymes or the activity of active drug transport systems (e.g. p-glycoprotein). Most drug interactions may be anticipated and prevented by dose modification or using alternative drugs.
Drug level at receptor site dictates the intensity of the pharmacological response. The level which is achieved depends upon several factors such as gastrointestinal absorption, protein binding, distribution, biotransformations and excretion. Modification of anyone of these processes can influence drug level at the site of action and thus the therapeutic effect of the drug. Physiological and pathological states or drug interactions can influence pharmacokinetics of benzodiazepines and thus modification of dosage regimen may be necessary. The influence of aging, liver disease, drug interactions such as alcohol, antidepressants... is of importance. Consequences of these modifications are discussed.
Management of warfarin drug interactions is often complicated by lack of information regarding interactions with new drugs and with herbal medicinals. The pharmaceutical industry has increased both the number and quality of drug interaction studies prior to marketing new agents. Interactions may still occur in patients, however, despite negative pre-marketing studies in healthy volunteers. The clinical significance and intensity of warfarin interactions with prescription drugs (e.g., celecoxib, proton pump inhibitors, and selective serotonin reuptake inhibitors) can often be predicted on the basis of known metabolic characteristics of the drugs and warfarin enantiomers. Drug interactions with herbal medicinals are much more difficult to characterize and predict because of the lack of federal regulations regarding safety, efficacy, and manufacturing standards. Published case reports of interactions between warfarin and even the most widely used herbal medicinals are limited. Practitioners are encouraged to report such interactions through the FDA MedWatch program.
As a biological phenomenon the interaction between drugs may be viewed in ;explanatory' or ;empirical' terms. In clinical psychopharmacology the former is rarely possible: two examples are cited, one concerning amphetamine and reserpine, the other desmethyl-imipramine and tetrabenazine. Among centrally acting substances, empirical studies of the interaction between alcohol and the barbiturates have been pursued intensively by several methods in clinic and laboratory. Both general considerations and recent work on the effects of amphetamine-barbiturate combinations suggest caution in the medical use of mixtures of psychotropic drugs. Adverse reactions caused by interaction between psychotropic drugs and other substances have still to be studied systematically as a potential hazard.