Drug Interactions Of Clinical Significance Research Articles

Outpatient prescription drug interactions at a city-affiliated healthcare center in Vietnam

Context: Adverse drug interactions increase the risk of hospitalization, treatment costs, unfavorable treatment outcomes, and prolonged hospital stays. However, there are a limited number of studies conducted in city-affiliated healthcare settings in Vietnam. Aims: To identify drug interactions in outpatient treatment prescriptions at a city-based healthcare center in the southern region of Vietnam. Methods: A cross-sectional descriptive study was conducted on outpatient treatment prescriptions stored in the outpatient department of a city-affiliated healthcare center from January to June, 2023. The study used two databases for drug interaction checking: the Drug Interactions Checker and Medscape Interactions Checker. Univariate and multivariate regression analyses were used to identify predictors of clinically significant drug interactions. Results: Among 1203 surveyed prescriptions, 36.7% contained at least one clinically-significant drug interaction, with 3% of prescriptions having severe interactions. The highest frequency of drug interactions involved amlodipine and metformin (9.9%). Patients with five or more prescribed medications (OR = 3.305; 95% CI: 2.320-4.708), hypertension (OR = 7.142; 95% CI: 4.658-10.950), dyslipidemia (OR = 2.242; 95% CI: 1.665-3.020), and non-insulin-dependent diabetes (OR = 2.447; 95% CI: 1.817-3.295) had a higher likelihood of experiencing clinically significant drug interactions. Conclusions: This study revealed that over one-third of outpatient prescriptions were associated with clinically-significant drug interactions. This study highlights the importance of clinical pharmacists screening prescriptions to detect and reduce interactions, as well as the application of computerized alert systems with intelligent screening software to minimize drug interactions.

Clinically significant drug interactions between antiretroviral and co-prescribed drugs in HIV infected patients: retrospective cohort study.

IntroductionThere are limited data on human immunodeficiency viruses (HIV) infected people in the UAE and the Gulf region. This study aimed at assessing the prevalence and risk factors for potential clinically significant drug interactions (CSDIs) in a cohort of 181 HIV infected people in Dubai.MethodsA retrospective study was conducted at the outpatient infectious diseases clinic of Rashid hospital. Consecutive HIV seropositive people on anti-retroviral therapy (ART) were included. All potential CSDIs were analyzed and classified using Liverpool HIV drug interactions database.ResultsNucleoside reverse transcriptase inhibitors (NRTIs) and integrase strand transfer inhibitors (INSTIs) were the most frequently used antiretroviral agents (ARVs), while the most common (non-ARV) were cardiovascular medication followed by antilipidemic statins. A total of 140 potential CSDIs were found in nearly half (n=86, 47.5%) of the 181 included HIV persons. Of the 140 potential CSDIs, 27 (19%) were of weak clinical relevance, 108 (77%) were of potential clinical relevance, and 5 (4%) were of contraindicated clinical relevance interactions. Moreover, 52 (37.14%) of CSDIs were between two ARVs and 88 (62.85%) were between ARV and non-ARV drugs. In the univariate analysis, age, dyslipidemia, number of medications, analgesics use, statin use, supplement intake, time since diagnosis of HIV, number of ART, and use of a protease inhibitor (PI) were significant. In the logistic regression, factors independently associated with CSDIs were the number of medications (odds ratio [OR] 1.165, 95% CI 1.021–1.329, P = 0.023) and the time since diagnosis of HIV (OR 1.156, 95% CI 1.008–1.327, P = 0.038).ConclusionThe frequency of CSDIs between ART and co-medications is high in HIV seropositive people. Awareness of the risk factors may assist clinicians to recognize and manage CSDIs.

Implementation of Pharmacogenomics and Artificial Intelligence Tools for Chronic Disease Management in Primary Care Setting.

Chronic disease management often requires use of multiple drug regimens that lead to polypharmacy challenges and suboptimal utilization of healthcare services. While the rising costs and healthcare utilization associated with polypharmacy and drug interactions have been well documented, effective tools to address these challenges remain elusive. Emerging evidence that proactive medication management, combined with pharmacogenomic testing, can lead to improved health outcomes and reduced cost burdens may help to address such gaps. In this report, we describe informatic and bioanalytic methodologies that integrate weak signals in symptoms and chief complaints with pharmacogenomic analysis of ~90 single nucleotide polymorphic variants, CYP2D6 copy number, and clinical pharmacokinetic profiles to monitor drug–gene pairs and drug–drug interactions for medications with significant pharmacogenomic profiles. The utility of the approach was validated in a virtual patient case showing detection of significant drug–gene and drug–drug interactions of clinical significance. This effort is being used to establish proof-of-concept for the creation of a regional database to track clinical outcomes in patients enrolled in a bioanalytically-informed medication management program. Our integrated informatic and bioanalytic platform can provide facile clinical decision support to inform and augment medication management in the primary care setting.

Pharmacokinetic enhancers (cobicistat/ritonavir) and the potential for drug-drug interactions.

The potential for clinically significant drug interactions (CSDIs) for patients taking ritonavir and cobicistat is high because of their powerful pharmacokinetic effect on the cytochrome P450 (CYP) enzyme system, most notably their inhibitory effect on CYP3A4. An audit was conducted to measure and correct for patients exposed to potentially dangerous drug interactions. Two hundred individuals attending a regional specialist human immunodeficiency virus (HIV) clinic between June and September 2014 who were receiving the pharmacokinetic enhancers ritonavir or cobicistat were interviewed to determine a medication history including medications prescribed by their general practitioner (GP), over-the-counter (OTC) medicines, herbal remedies and recreational drugs. Of the 200 patients interviewed, patients were aged 23-76 years (median age was 41.5), 64% were female and 173 reported taking a co-medication. Sixty-six (33%) were taking a medication or medications which had no significant drug interaction associated with them. One hundred andseven (54%) were taking one or more medications with a CSDI which could require a dose adjustment, close monitoring or an absolute contraindication. Only 27% of these co-medications were identified in the normal course of an outpatient visit outside of the audit. A detailed medication history is often lacking at routine HIV follow-up visits. There is a significant risk of CSDIs in this cohort. Awareness of physicians and pharmacists needs to be raised. Implementation of several innovative strategies to capture the most accurate medication histories and avoid drug toxicities now employed in this cohort is also discussed here.

CLINICALLY SIGNIFICANT DRUG-DRUG INTERACTION IN A LARGE ANTIRETROVIRAL TREATMENT CENTRE IN LAGOS, NIGERIA

Background: An important cause of treatment failure to antiretroviral therapy (ART) is the potential interaction between the antiretroviral (ARV) drugs and co-prescribed drugs used concomitantly for the treatment of opportunistic infections and co-morbid ailments in HIV-infected patients. Objectives: The study evaluated potential clinically significant drug interactions (CSDIs) occurring between recommended ART regimens and their co-prescribed non-antiretroviral drugs (CPD) Method: This study was carried out in a large HIV treatment centre (APIN clinic) in a Nigerian teaching hospital, in Lagos Nigeria, caring for over 20,000 registered patients. Electronic Medical Records (EMR) of 500 patients who received treatment between 2005 and 2015, were selected using systematic random sampling, reviewed retrospectively, and evaluated for potential CSDIs using Liverpool HIV Pharmacology Database and other similar databases. Results: Majority of patients, 421 (84%) were at risk of CSDIs, of which 410, (82%) were moderate and frequently involved co-trimoxazole + zidovudine (or stavudine) /lamivudine (386, 77.2%) and NNRTIs or PIs + artemisinin-based combination therapies (ACTs) [296, 59.2%]. Age (p=0.131), sex (p=0.316) and baseline CD4+ cell counts (p>0.05) were not significantly associated with CSDIs. The interactions, however, were significantly associated with the development of antiretroviral treatment failure (p <0.001) which occurred in nearly a third (139; 27.8%) of the patients. Conclusion: There is a high prevalence of CSDIs between ART and CPDs most of which were categorized as moderate. Further studies are required to evaluate the pharmacokinetic and clinical relevance of these interactions.

High Risk of Drug-drug interactions among Hospitalized Patients with kidney Diseases at a Nigerian Teaching Hospital: A Call for Action.

Background:Potential drug–drug interactions (DDIs) are increasingly common in clinical practice, especially among individuals with chronic conditions, such as chronic kidney dysfunction. However, data relating to DDIs among chronically ill patients are limited in Nigeria. We, therefore, investigated the prevalence and pattern of DDIs among patients with kidney diseases on admission at a tertiary hospital in Lagos, Nigeria.Materials and Methods:This was a prospective observational study involving 61 adults with kidney diseases and on admission in medical wards of the study center, over a 3-month period. Data extractions were with a purposefully designed pro forma to extract relevant data on demographic, clinical, and dosing regimens of the prescribed drugs for individual patients. Potential DDIs were identified, and their severity was rated using the MICROMEDEX® software database (IBM® Watson–Truven Health Analytics), which is available online with limited access.Results:Of the 61 patients evaluated, majority were males (34; 55.7%), were elderly (26; 42.6%), and had chronic kidney disease Stage 3 (40; 65.5%). The most common cause of kidney disease was hypertension (20; 32.8%). Out of the 542 prescriptions received by the patients, potential DDI was observed in 508 (93.7%) prescriptions. Clinically significant drug interactions (CSDIs) were detected in 486 (85.7%) prescriptions. Pharmacodynamic DDIs (466; 91.7%) were the most common. Pill burden exceeding 25 pills/day was present in nine (14.8%) patients. The severities of the potential DDIs were major (135; 24.9%), moderate (333; 61.4%), and minor (38; 7.1%). Only two different potential DDIs were rated X (contraindicated).Conclusion:Exposure to drugs with potential DDIs was very common among patients with kidney diseases. Most of the CSDIs observed were of major severity. The use of DDI checker before prescribing drugs for individuals with kidney diseases could avert clinically significant interactions.

4 powody, dla których warto zastosować lewetyracetam

Levetiracetam belongs to a group of new antiepileptic drugs with a complex mechanism of action. Introduced to the pharmaceutical market in the 1980s, to date it has established its position of an effective and a safe drug. This is supported by the predictable pharmacokinetics of the drug, the lack of drug interactions of clinical significance, the low risk of drug resistance as well as the lack of depressant effect on the central nervous system.

Clinically Significant Drug Interactions Among Human Immunodeficiency Virus–Positive Patients on Antiretroviral Therapy in an Outpatient Setting

Abstract Human immunodeficiency virus (HIV) treatment is complicated by antiretrovirals prone to clinically significant drug interactions (CSDIs). Objectives were to examine relationships of patient and medication characteristics and provider training level with CSDIs in an outpatient HIV clinic. A clinical pharmacist reviewed medication lists of randomly selected adult HIV-positive patients on antiretrovirals for accuracy and presence of a CSDI, defined as grade C, D, or X using Lexicomp software. Characteristics were compared between patients with and without CSDIs by χ2 tests for categorical variables and t tests for continuous variables. Associations between these parameters and CSDIs (presence vs absence) were evaluated by logistic regression. Associations between provider type (infectious disease physician [IDMD], infectious disease fellow [Fellow], and nurse practitioner [NP]) and number of CSDIs per patient, and provider response to being informed of a CSDI were analyzed by χ2 tests. Of 107 records reviewed, 405 CSDIs were identified in 83 (76%) patient records. Clinically significant drug interaction presence was associated with older age, increased medications, protease inhibitor-based regimen, and medication list inaccuracies. Patients with and without CSDIs did not differ in sex, race, HIV viral load, or nonnucleoside reverse-transcriptase inhibitor regimen. Older age (odds ratio [95% confidence interval], 3.53 [1.21–11.64]) and a protease inhibitor-based regimen (odds ratio [95% confidence interval], 8.49 [2.18–46.07]) were associated with having a CSDI. Fellows were more likely to report being unaware of CSDIs than IDMDs and NPs and to request additional information versus IDMDs and NPs. These findings suggest that providers may benefit from involving a pharmacist to identify and educate about CSDIs.

The Clinical Pharmacokinetics of Amphetamines Utilized in the Treatment of Attention-Deficit/Hyperactivity Disorder.

Amphetamine (AMP), an indirectly acting psychostimulant approved for the treatment of attention-deficit/hyperactivity disorder (ADHD) in children, adolescents, and adults, is among the most long-standing therapeutic agents in all of clinical psychopharmacology. This review focuses on AMP absorption, metabolism, and elimination brought to bear on comparative pharmacokinetics in its various formulations. A comprehensive search of the published literature was conducted using MEDLINE (PubMed) and Google Scholar databases through April 2017 to retrieve all pertinent in vitro and human studies for review and synthesis. Additionally, Food and Drug Administration (FDA) databases were accessed for otherwise unavailable data when possible. Initially available as racemic (dl)-AMP, this drug was later supplanted by enantiopure (d)-AMPH or enantioenriched (75:25 dl)-AMP formulations; although racemic AMP returned as an approved drug to treat ADHD in 2014. Presently, there are several immediate-release (IR) formulations available, including d-AMP, dl-AMP, and mixed amphetamine salts, which are neither racemic nor the pure d-enantiomer (i.e., a 3:1 mixture of d-AMP and l-AMP). Furthermore, new modified-release AMP formulations, including an oral suspension and an orally disintegrating tablet, are now available. A lysine-bonded prodrug form of d-AMP also serves as a treatment option. Oral AMP is rapidly absorbed, with high absolute bioavailability, followed by extensive metabolism involving multiple enzymes. Some metabolic pathways exhibit stereoselective biotransformations favoring the l-isomer substrate. Drug exposure exhibits dose-proportional pharmacokinetics. Body weight is a fundamental determinant of differences in observed AMP plasma concentrations. IR formulations typically provide a Tmax from 2 to 3 hours. In replicated studies, children exhibit a shorter plasma T1/2 (∼7 hours) relative to adults (∼10 to 12 hours). There are few documented pharmacokinetic drug interactions of clinical significance beyond influences of drug-induced alteration of urinary pH. The array of AMP formulations addressed in this review offer flexibility in dosing, drug onset, and offset to assist in individualized pharmacotherapy of ADHD.

Recognition of possible risk factors for clinically significant drug-drug interactions among Indian people living with HIV receiving highly active antiretroviral therapy and concomitant medications.

Greatest challenges for clinician is to recognize risk factors for clinically significant drug interactions (CSDIs). There is a lack of awareness about CSDIs among healthcare professionals in India. To recognize all possible risk factors for drug-drug interactions (DDIs) and to identify clinically significant drug interactions (CSDIs), the prevalence, pattern of occurrence of DDIs in People Living with HIV (PLW-HIV) receiving highly active antiretroviral therapy (HAART) and concomitant medications. A retrospective medical record review was carried out by clinical pharmacist with ethics committee approval. Case files of HIV patients receiving HAART with concomitant medications were analyzed for CSDIs using University of Liverpool drug interaction database and CSDIs were classified based on red flag indication (RFI) or contraindicated drug-drug interaction (XDDIs) and orange flag indication (OFI) or DDIs that needs close monitoring. Patients with DDIs (cases) and patients without DDIs (controls) were compared with Chi-square tests. P value <0.05 was considered as statistically significant. A total of 240 HIV patients' cases were screened. Out of which 267 DDIs were reported in 107 patients. Prevalence of DDIs was higher in male 71 (66.4%) compared to female 36 (33.6%). On zero-inflated poisson regression analysis, factors of polypharmacy, opportunistic infections, comorbid condition like Ischemic heart disease, respiratory tract infections, and psychiatric disorder were found to be predictors of high risk factors for DDIs to HAART. Fourteen XDDIs with RFI and two hundred fifty three DDIs with OFI were reported. XDDIs were atazanavir with fluconazole 4(28.6%), ritonavir with fluconazole 4(28.6%), nevirapine with rifampicin 2(14.4%), ritonavir with quetiapine, atazanavir with pantoprazole. Pharmacokinetic DDIs were highest 238(89.1%). Sixteen DDIs were reported in a single patient. The majority 97(90.6%) patients had developed ≤5 DDIs, 8(7.5%) developed six to eleven DDIs. The highest DDIs were reported with efavirenz 49(18.4%) and zidovudine 44(16.5%) based HAART regimen. In India, with the increasing access to HAART usage, Clinician must focus to pay attention to recognize possible risk factors for CSDIs associated with HAART regimen and strictly to avoid "Red Flag Indication combinations" while prescribing so as to prevent CSDIs.

Identification of potential clinically significant drug interactions in HIV-infected patients: a comprehensive therapeutic approach.

The aim of the study was to determine the prevalence of potential clinically significant drug interactions (CSDIs) in HIV-positive individuals and to identify associated risk factors. A cross-sectional study was conducted including all HIV-infected out-patients attending the Pharmacy Service of a regional reference hospital in Murcia, south-eastern Spain. The complete treatment was screened for possible CSDIs using the Spanish College of Pharmacists' online software resource, bot. Additionally, the severity level of the CSDIs involving antiretroviral (ARV) drugs was compared with that established in the specific antiretroviral database InteraccionesHIV.com. Multivariate logistic regression was used to identify associated risk factors. Two hundred and sixty-eight patients were included in the study. A total of 292 potential drug interactions were identified, of which 102 (34.9%) were CSDIs, of which 52.9% involved ARV drugs. Seven therapeutic drug classes were involved in 75% of CSDIs (protease inhibitors, benzodiazepines, nonsteroidal anti-inflammatory drugs, nonnucleoside reverse transcriptase inhibitors, corticosteroids, antithrombotics and proton pump inhibitors). Factors independently associated with CSDIs were treatment with more than five drugs [odds ratio (OR) 15.1; 95% confidence interval (CI) 6.3-36.2], and treatment with a protease inhibitor (OR 5.3; 95% CI 2.4-11.74). The findings of this study suggest that the prevalence of clinically relevant drug-drug interactions is high in HIV-infected patients, and could represent a major health problem. Awareness, recognition and management of drug interactions are important in optimizing the pharmaceutical care of HIV-infected patients and helping to prevent adverse events and/or loss of efficacy of the drugs administered.

Potential drug&amp;ndash;drug interactions in HIV-infected children on antiretroviral therapy in Lagos, Nigeria

BackgroundMulti-therapy is common in HIV-infected children, and the risk for clinically significant drug interactions (CSDIs) is high. We investigated the prevalence of CSDIs between antiretroviral (ARV) and co-prescribed drugs for children attending a large HIV clinic in Lagos, Nigeria.MethodsThe case files of pediatric patients receiving treatment at the HIV clinic of the Lagos University Teaching Hospital (LUTH), Idi-Araba, between January 2005 and December 2010 were reviewed. The ARV and co-prescribed drug pairs were evaluated for potential interactions using the Liverpool HIV Pharmacology Group website. The potential interactions were rated as A (no known interaction), B (minor/no action needed), C (moderate/monitor therapy), D (major/therapy modification), and X (contraindicated/avoid combination).ResultsOf the 310 cases reviewed, 208 (67.1%) patients were at risk of CSDIs. Artemisinin-based combination therapy was prescribed for over one-half of the patients, accounting for 40% of the CSDIs. Excluding this drug class, the prevalence of CSDIs reduced from 67.1% to 18.7% in 58 patients. Most of the CSDIs (579; 97.2%) were moderately significant and frequently involved nevirapine and fluconazole (58; 9.7%), zidovudine and fluconazole (55; 9.2%), zidovudine and rifampicin (35; 5.9%), and nevirapine and prednisolone (31; 5.2%). Age (P=0.392), sex (P=0.783), and moderate (P=0.632) or severe (P=0.755) malnutrition were not associated with risk for CSDIs.ConclusionThere is a tendency for CSDIs between ARV and co-prescribed drugs among the group of children evaluated in this study. Measures are necessary to prevent important drug interactions and to manage those that are unavoidable.

Potential drug‐drug interactions in HIV‐infected children on highly active antiretroviral therapy in Lagos, Nigeria

ObjectiveMultiple therapies are common in HIV‐infected children on highly active antiretroviral therapy (HAART). These children are at risk for clinically significant drug interactions (CSDIs). While CSDIs are under‐recognized in developed countries, data are lacking for developing African countries. We aimed to investigate the prevalence of CSDIs between antiretrovirals (ARVs) and co‐prescribed drugs for children attending a large HIV clinic in Lagos, Nigeria.MethodsWe retrospectively assessed the risk for clinically significant drug interactions in children on HAART. Of the 417 patients enrolled for treatment, 80 were eligible for inclusion. We defined CSDIs as ‘major’ (capable of causing severe or permanent damage, contraindicated, avoid or not recommended by the manufacturer, or requiring dose modification) or ‘moderate’ (manufacturers advise caution, or close monitoring, or capable of causing clinical deterioration).ResultsA total of 60 (75%) patients were at risk for a CSDI resulting in major interactions in 13 (16.3%) patients and could potentially lower the plasma concentration of antiretroviral drugs in 9 (15%) patients. Major interactions most frequently involved rifampicin in 9 (11.3%) patients and artemisinin combination therapies (ACTs) in 8 (10%) patients whereas moderate interactions frequently involved ACTs (48.8%), fluconazole (36.3%), and rifampicin (11.3%). Age (p = 0.392), gender (p = 0.813), and moderate (p = 0.692) or severe (p = 0.788) malnourished state of the children were not associated with risk for CSDIs.ConclusionsThree‐quarters of children receiving ARV drugs are at risk for CSDIs. Strategies are needed to be put in place to prevent important drug interactions and to manage unavoidable interactions.

Oral Antibiotic Drug Interactions of Clinical Significance to Dermatologists

Oral antibiotics are commonly prescribed by dermatologists in clinical practice. When prescribing an oral antibiotic, as with other systemic medications, it is important to consider potential interactions with other drugs, including over-the-counter medications. The most common drug interaction mechanisms that may lead to clinically significant sequelae are inhibition of GI drug absorption and alterations in drug metabolism. Tetracycline and quinolones undergo chelation interactions with many metal ions found in antacids and mineral supplements. Some macrolides, such as erythromycin, inhibit the hepatic metabolism of many other drugs, increasing the risk for toxicity. Rifampin increases the metabolism of many other drugs, thus predisposing to treatment failure. Drug interactions can only be averted if their potential is understood and recognized in advance.

Prevalence and Risk Factors for Clinically Significant Drug Interactions with Antiretroviral Therapy

To identify the prevalence and types of clinically significant drug interactions (CSDIs) in the drug regimens of patients with human immunodeficiency virus (HIV) infection who were receiving antiretroviral therapy, and to explore risk factors for these CSDIs. Retrospective medical record review. Academic HIV specialty clinic. One hundred fifty-three randomly selected patients with HIV infection who were receiving antiretroviral therapy from May 1-September 30, 2006. Data were collected on patient demographics, date of HIV diagnosis, most recent viral load and CD4(+) count, Centers for Disease Control and Prevention HIV classification, and comorbid conditions. Patients' drug regimens were analyzed for total and clinically significant antiretroviral drug interactions using three resources. Logistic regression and classification and regression tree analysis were used to identify independent CSDI predictors. Clinically significant drug interactions were defined as drug interactions that required a dosage adjustment or consisted of a drug combination that is contraindicated due to its high potential for clinical adverse effects. Of the 153 patients, at least one CSDI was found in 41.2% of their regimens: 34.6% with at least one drug interaction that required a dosage adjustment, 2.0% with at least one contraindicated drug combination, and 4.6% with at least one of each of these CSDIs. In the logistic regression model, risk factors independently associated with CSDIs were age older than 42 years (odds ratio [OR] 2.9, 95% CI 1.2-7.1), more than three comorbid conditions (OR 3.0, 95% CI 1.4-6.6), treatment with more than three antiretroviral agents (OR 2.4, 95% CI 1.0-5.8), and treatment with a protease inhibitor (OR 11.5, 95% CI 4.2-31.2). When directly compared, CSDIs were more prevalent among protease inhibitor-based than nonnucleoside reverse transcriptase inhibitor-based regimens (p<0.001). Clinically significant drug interactions are highly prevalent among HIV-infected patients receiving antiretroviral therapy. Knowledge of the risk factors for CSDIs may help clinicians recognize and manage CSDIs.

Drug interactions of clinical significance for the dermatologist: recognition and avoidance.

While it would be impossible for any dermatologist to remember all potential drug interactions, knowledge of the mechanisms of drug interactions can help reduce the risk of serious adverse outcomes. Most drugs are associated with interactions but the majority do not produce significant outcomes. Dealing with drug interactions is a challenge in all clinical practice, including dermatology. New information continues to appear, and dermatologists need to know about the drugs they use.This article focuses on the mechanisms of drug interactions. In particular, the life of a drug in terms of absorption, distribution, metabolism and excretion are reviewed with the focus on points of importance and relevance to drug interactions. The most clinically important drug interactions in dermatological practice are caused by alterations in drug metabolism. The contributions of P-glycoprotein, pharmacogenetic variation and genetic polymorphisms to drug interactions are highlighted, and the best evidence for drug interactions involving drug classes relevant to the dermatologist is presented. Since the initial evidence for clinically relevant drug interactions comes from case reports, prescribing physicians can have a major role in collating information on interactions. By understanding the mechanisms behind drug interactions and staying alert for toxicities, we can help make drug therapy safer and reduce the fear of drug interactions.

Drug trials in children: problems and the way forward.

The drug-licensing system was introduced with the Medicines Act of 1968, following the thalidomide disaster, with the aim of ensuring that medicines are safe, effective and of high quality. There is increasing concern from the pharmaceutical industry, paediatricians, paediatric pharmacists and the Government that many medicines routinely used in children have not been formally evaluated by this system. Such use is therefore not supported by the assurances that the process brings. A joint report was produced in 1996 by the British Paediatric Association (now the Royal College of Paediatrics and Child Health) and the Association of the British Pharmaceutical Industry. This described in detail the current unsatisfactory situation and made specific recommendations for a way forward [1]. Since then several studies have documented the extent of unlicensed and off-label drug use in critically ill children, paediatric medical and surgical inpatients and neonates [2–4]. These studies all show that unlicensed and off-label drug use is a frequent occurrence for children in hospital with up to 90% of newborn infants in intensive care receiving either unlicensed or off-label treatment. Unlicensed medicines may be those compounded in a hospital pharmacy department or by a ‘specials’ manufacturer due to a lack of licensed alternatives. These medicines may not necessarily undergo the rigorous quality testing procedures that a licensed preparation must, and their quality may be variable. The term off-label refers to the use of a medicine outside the specifications of the product licence [5]. This covers medicines used at a different dosage to that recommended, in different age groups, by a different route or for a different indication. These off-label uses may be based on reliable published data, in which case prescribers can feel confident in using medicines in an off-label manner since this practice would be supported by peer review. In other instances they may rely more on the experience of the paediatrician or pharmacist, or drug information resources such as those of DIAL (Drug Information Advisory Line, Alder Hey Children’s Hospital, Liverpool). They are less likely to be supported by extensive clinical trial information, as would the manufacturer’s recommended uses of a licensed preparation.

Antiarrhythmic agents: drug interactions of clinical significance.

The management of cardiac arrhythmias has grown more complex in recent years. Despite the recent focus on nonpharmacological therapy, most clinical arrhythmias are treated with existing antiarrhythmics. Because of the narrow therapeutic index of antiarrhythmic agents, potential drug interactions with other medications are of major clinical importance. As most antiarrhythmics are metabolised via the cytochrome P450 enzyme system, pharmacokinetic interactions constitute the majority of clinically significant interactions seen with these agents. Antiarrhythmics may be substrates, inducers or inhibitors of cytochrome P450 enzymes, and many of these metabolic interactions have been characterised. However, many potential interactions have not, and knowledge of how antiarrhythmic agents are metabolised by the cytochrome P450 enzyme system may allow clinicians to predict potential interactions. Drug interactions with Vaughn-Williams Class II (beta-blockers) and Class IV (calcium antagonists) agents have previously been reviewed and are not discussed here. Class I agents, which primarily block fast sodium channels and slow conduction velocity, include quinidine, procainamide, disopyramide, lidocaine (lignocaine), mexiletine, flecainide and propafenone. All of these agents except procainamide are metabolised via the cytochrome P450 system and are involved in a number of drug-drug interactions, including over 20 different interactions with quinidine. Quinidine has been observed to inhibit the metabolism of digoxin, tricyclic antidepressants and codeine. Furthermore, cimetidine, azole antifungals and calcium antagonists can significantly inhibit the metabolism of quinidine. Procainamide is excreted via active tubular secretion, which may be inhibited by cimetidine and trimethoprim. Other Class I agents may affect the disposition of warfarin, theophylline and tricyclic antidepressants. Many of these interactions can significantly affect efficacy and/or toxicity. Of the Class III antiarrhythmics, amiodarone is involved in a significant number of interactions since it is a potent inhibitor of several cytochrome P450 enzymes. It can significantly impair the metabolism of digoxin, theophylline and warfarin. Dosages of digoxin and warfarin should empirically be decreased by one-half when amiodarone therapy is added. In addition to pharmacokinetic interactions, many reports describe the use of antiarrhythmic drug combinations for the treatment of arrhythmias. By combining antiarrhythmic drugs and utilising additive electrophysiological/pharmacodynamic effects, antiarrhythmic efficacy may be improved and toxicity reduced. As medication regimens grow more complex with the aging population, knowledge of existing and potential drug-drug interactions becomes vital for clinicians to optimise drug therapy for every patient.

Clinically significant pharmacokinetic drug interactions between antiepileptic drugs.

Pharmacokinetic interactions between antiepileptics represent a major potential complication of epilepsy treatment because drug combinations are common. This review discusses pharmacokinetic drug interactions of clinical significance involving antiepileptics and cytochrome P450 (CYP). Most commonly used antiepileptics are eliminated through hepatic metabolism, catalysed by the enzymes CYP2C9, CYP2C19 and CYP3A4 and uridine diphosphate glucuronosyltransferase (UDGPT). Antiepileptics are associated with a wide range of drug interactions, including hepatic enzyme induction and inhibition. Phenytoin, phenobarbiral, primidone and carbamazepine induce CYP and UDPGT enzymes while valproic acid inhibits them. Avoidance of unnecessary polypharmacy, selection of alternative agents with lower interaction potential and careful dosage adjustments based on serum drug concentration monitoring and clinical observation are the main methods for reducing the risks associated with these interactions.

Modification of the pharmacokinetics of cyclosporine a and metabolites by the concomitant use of neoral and diltiazem or ketoconazol in stable adult kidney transplants

THE CLINICALLY significant drug interactions with cyclosporine A (CyA) were recently updated. The interaction between CyA and diltiazem or ketoconazole is well documented in a large number of patients, and, while based mainly on the use of the liquid solution or gel capsule of CyA, it is well accepted fact that the interactions allow for a lower dosage of CyA. Furthermore, in the specific case of the calcium channel blocker (CCB) diltiazem, there is further evidence that a kidney protective action by this agent is operating, supporting this cotreatment scheme. However, the available literature is rather scarce on the interactions with the novel galenical microemulsionated formulation of CyA (Neoral) (Sandoz). Recently a further effect of the diltiazem cotreatment with Neoral has been reported indicating an increase in specific metabolites significantly higher in female patients. This presentation refers to a critical analysis of CyA pharmacokinetics as Neoral in cotreatment with diltiazem or ketoconazole in chronic stable adult kidney transplanted patients.