Peter Honig

Changes in the pharmacokinetics and electrocardiographic pharmacodynamics of terfenadine with concomitant administration of erythromycin

Terfenadine is a nonsedating H1‐antagonist that when overdosed, used with hepatic compromise, or when given with ketoconazole results in accumulation of parent terfenadine, prolongation of the QT interval, and torsades de pointes in susceptible patients. Nine subjects were given the recommended dose of terfenadine (60 mg every 12 hours) for 7 days before initiation of oral erythromycin (500 mg every 8 hours). All subjects increased metabolite concentrations after the addition of erythromycin for 1 week. The maximum concentration of metabolite increased by a mean of 107% and the mean metabolite area under the concentration‐time curve increased by 170%. Three subjects accumulated unmetabolized terfenadine after administration of erythromycin for 1 week. Electrocardiographic data revealed changes in QT intervals and ST‐U complexes in a subset of subjects who accumulated terfenadine. We conclude that erythromycin alters the metabolism of terfenadine, leading to accumulation of terfenadine in certain individuals that is associated with altered cardiac repolarization.

From Adaptive Licensing to Adaptive Pathways: Delivering a Flexible Life-Span Approach to Bring New Drugs to Patients

The concept of adaptive licensing (AL) has met with considerable interest. Yet some remain skeptical about its feasibility. Others argue that the focus and name of AL should be broadened. Against this background of ongoing debate, we examine the environmental changes that will likely make adaptive pathways the preferred approach in the future. The key drivers include: growing patient demand for timely access to promising therapies, emerging science leading to fragmentation of treatment populations, rising payer influence on product accessibility, and pressure on pharma/investors to ensure sustainability of drug development. We also discuss a number of environmental changes that will enable an adaptive paradigm. A life‐span approach to bringing innovation to patients is expected to help address the perceived access vs. evidence trade‐off, help de‐risk drug development, and lead to better outcomes for patients.

Drug interactions with herbal products and grapefruit juice: A conference report

Shiew-Mei Huang, PhD, Stephen D. Hall, PhD, Paul Watkins, MD, Lori A. Love, MD, PhD, Cosette Serabjit-Singh, PhD, Joseph M. Betz, PhD, Freddie Ann Hoffman, MD, Peter Honig, MD, Paul M. Coates, PhD, Jonca Bull, MD, Shaw T. Chen, MD, PhD, Gregory L. Kearns, PharmD, PhD, and Michael D. Murray, PharmD, MPH Rockville and Bethesda, Md, Indianapolis, Ind, Chapel Hill and Research Triangle Park, NC, Morris Plains, NJ, West Point, Pa, and Kansas City, Mo

Comparison of the Effect of the Macrolide Antibiotics Erythromycin, Clarithromycin and Azithromycin on Terfenadine Steady-State Pharmacokinetics and Electrocardiographic Parameters

SummaryTerfenadine is a nonsedating histamine H1-antagonist that, when given with ketoconazole, results in accumulation of parent terfenadine and altered cardiac repolarisation in susceptible individuals. This prospective cohort study, designed to assess macrolide effects on terfenadine pharmacokinetics and electrocardiogram (ECG) parameters, evaluated 18 healthy male and female volunteers who received terfenadine to steady-state. Equal numbers (6) were randomised to receive either erythromycin, clarithromycin or azithromycin at recommended doses while continuing terfenadine. Macrolide monotherapy effects on the ECG were also investigated. Pharmacokinetic profiles for terfenadine were performed before and after the addition of macrolide therapy, and ECGs were obtained at baseline and predose on days of blood sampling.Erythromycin and clarithromycin significantly affected the pharmacokinetics of terfenadine. Three of 6 volunteers receiving erythromycin and 4 of 6 receiving clarithromycin demonstrated accumulation of quantifiable unmetabolised terfenadine that was associated with altered cardiac repolarisation. Azithromycin had no effect on terfenadine pharmacokinetics or cardiac pharmacodynamics.

The effect of fluconazole on the steady-state pharmacokinetics and electrocardiographic pharmacodynamics of terfenadine in humans.

Terfenadine is rapidly and nearly completely biotransformed during a first pass to an active acid metabolite. Accumulation of unmetabolized terfenadine has been associated with altered cardiac repolarization. Drug‐drug interactions resulting in the accumulation of terfenadine have been reported for ketoconazole and erythromycin. Six subjects were given the recommended dose of terfenadine (60 mg every 12 hours) for 7 days before initiation of oral fluconazole (200 mg once daily). The mean metabolite area under the concentration‐time curve increased by 34% and the time to maximum concentration of the metabolite was delayed from 2.3 to 4 hours by concurrent fluconazole. Unmetabolized terfenadine was not present in any subject, and cardiac repolarization was not significantly changed from baseline during any phase of the study. We conclude that a pharmacokinetic interaction between terfenadine and fluconazole exists; however, the absence of accumulation of parent terfenadine in plasma suggests that a clinically significant interaction is unlikely.

Outpatient Prescribing of Antiarrhythmic Drugs from 1995 to 2000

There is growing evidence that some class III antiarrhythmic drugs, unlike class I agents, are not associated with an increased risk of death in patients with prior myocardial infarction and left ventricular dysfunction. 1‐14 For this reason, we evaluated the extent to which the current prescribing of antiarrhythmic medications complies with the evidence that supports the use of class III rather than class I agents. Using pharmaceutical marketing research data, we reviewed outpatient antiarrhythmic drug prescriptions in the United States from 1995 through the third quarter of 2000, to characterize the prescribing of these drugs and to examine drug use trends over this period. ••• Data on antiarrhythmic drug prescribing were derived from 2 audits owned by IMS Health (Plymouth Meeting, Pennsylvania): the National Prescription Audit (NPA) Plus and the National Disease and Therapeutic Index (NDTI). The NPA Plus audit measures the retail outflow of prescriptions in the United States. This includes prescriptions dispensed by retail pharmacies and mailorder pharmacies. The NDTI audit contains data on drug mentions associated with a diagnosis during a specific clinic visit. These data are collected by a continuing survey of 343,655 physicians in officebased practices in the United States. An NDTI panel of physicians, a subset of 343,655, is selected every 2 weeks to provide demographic information, diagnoses, and recommended drugs for each diagnosis on all patients encountered. This is then projected to the national level. The NPA Plus audit was queried for all class I and class III antiarrhythmic drugs for which an oral dosage form was marketed and sold in the United States between January 1995 and September 2000. The numbers presented for the year 2000 represent a 9-month period. Class I agents included the class IA agents quinidine, procainamide, and disopyramide, the class IB agents mexiletine and tocainide, and the class IC agents flecainide, propafenone, and moricizine. Class III agents included amiodarone and sotalol. We limited this analysis to class I and III antiarrhythmic drugs because it would be difficult to determine whether blockers (class II antiarrhythmic agents) and calcium channel blockers (class IV antiarrhythmic agents) were prescribed solely for an arrhythmic indication. The NDTI audit was queried for all oral class I and class III antiarrhythmic agents strati fied by physician specialty and diagnoses for which the agent(s) was used. Trends in antiarrhythmic drug prescriptions were evaluated based on physician specialty and the diagnosis for which each agent or class of agents was reported to be prescribed.

A Proposal for Integrated Efficacy-to-Effectiveness (E2E) Clinical Trials

We propose an “efficacy‐to‐effectiveness” (E2E) clinical trial design, in which an effectiveness trial would commence seamlessly upon completion of the efficacy trial. Efficacy trials use inclusion/exclusion criteria to produce relatively homogeneous samples of participants with the target condition, conducted in settings that foster adherence to rigorous clinical protocols. Effectiveness trials use inclusion/exclusion criteria that generate heterogeneous samples that are more similar to the general patient spectrum, conducted in more varied settings, with protocols that approximate typical clinical care. In E2E trials, results from the efficacy trial component would be used to design the effectiveness trial component, to confirm and/or discern associations between clinical characteristics and treatment effects in typical care, and potentially to test new hypotheses. An E2E approach may improve the evidentiary basis for selecting treatments, expand understanding of the effectiveness of treatments in subgroups with particular clinical features, and foster incorporation of effectiveness information into regulatory processes.

The effectiveness of antihistamines in reducing the severity of runny nose and sneezing: A meta-analysis

Clinical Pharmacology & Therapeutics (1998) 64, 579–596; doi:

Centers for Education and Research on Therapeutics report: Survey of medication errors education during undergraduate and graduate medical education in the United States

Clinical Pharmacology & Therapeutics (2002) 71, 4–10; doi: 10.1067/mcp.2002.120676

“Threshold‐crossing”: A Useful Way to Establish the Counterfactual in Clinical Trials?

A central question in the assessment of benefit/harm of new treatments is: how does the average outcome on the new treatment (the factual) compare to the average outcome had patients received no treatment or a different treatment known to be effective (the counterfactual)? Randomized controlled trials (RCTs) are the standard for comparing the factual with the counterfactual. Recent developments necessitate and enable a new way of determining the counterfactual for some new medicines. For select situations, we propose a new framework for evidence generation, which we call “threshold‐crossing.” This framework leverages the wealth of information that is becoming available from completed RCTs and from real world data sources. Relying on formalized procedures, information gleaned from these data is used to estimate the counterfactual, enabling efficacy assessment of new drugs. We propose future (research) activities to enable “threshold‐crossing” for carefully selected products and indications in which RCTs are not feasible.