Lawrence J. Lesko

Impact of Pharmacometric Analyses on New Drug Approval and Labelling Decisions

Pharmacometric analyses have become an increasingly important component of New Drug Application (NDA) and Biological License Application (BLA) submissions to the US FDA to support drug approval, labelling and trial design decisions. Pharmacometrics is defined as a science that quantifies drug, disease and trial information to aid drug development, therapeutic decisions and/or regulatory decisions. In this report, we present the results of a survey evaluating the impact of pharmacometric analyses on regulatory decisions for 198 submissions during the period from 2000 to 2008. Pharmacometric review of NDAs included independent, quantitative analyses by FDA pharmacometricians, even when such analysis was not conducted by the sponsor, as well as evaluation of the sponsor’s report. During 2000–2008, the number of reviews with pharmacometric analyses increased dramatically and the number of reviews with an impact on approval and labelling also increased in a similar fashion. We also present the impact of pharmacometric analyses on selection of paediatric dosing regimens, approval of regimens that had not been directly studied in clinical trials and provision of evidence of effectiveness to support a single pivotal trial. Case studies are presented to better illustrate the role of pharmacometric analyses in regulatory decision making.

Personalized Medicine and Genomics: Challenges and Opportunities in Assessing Effectiveness, Cost-Effectiveness, and Future Research Priorities

Personalized medicine is health care that tailors interventions to individual variation in risk and treatment response. Although medicine has long strived to achieve this goal, advances in genomics promise to facilitate this process. Relevant to present-day practice is the use of genomic information to classify individuals according to disease susceptibility or expected responsiveness to a pharmacologic treatment and to provide targeted interventions. A symposium at the annual meeting of the Society for Medical Decision Making on 23 October 2007 highlighted the challenges and opportunities posed in translating advances in molecular medicine into clinical practice. A panel of US experts in medical practice, regulatory policy, technology assessment, and the financing and organization of medical innovation was asked to discuss the current state of practice and research on personalized medicine as it relates to their own field. This article reports on the issues raised, discusses potential approaches to meet these challenges, and proposes directions for future work. The case of genetic testing to inform dosing with warfarin, an anticoagulant, is used to illustrate differing perspectives on evidence and decision making for personalized medicine.

Paving the Critical Path: How can Clinical Pharmacology Help Achieve the Vision?

It has been almost 3 years since the launch of the FDA critical path initiative following the publication of the paper “Innovation or Stagnation: Challenges and Opportunities on the Critical Path of New Medical Product Development.” The initiative was intended to create an urgency with the drug development enterprise to address the so‐called “productivity problem” in modern drug development. Clinical pharmacologists are strategically aligned with solutions designed to reduce late phase clinical trial failures to show adequate efficacy and/or safety. This article reviews some of the ways that clinical pharmacologists can lead and implement change in the drug development process. It includes a discussion of model‐based, semi‐mechanistic drug development, drug/disease models that facilitate informed clinical trial designs and optimal dosing, the qualification process and criteria for new biomarkers and surrogate endpoints, approaches to streamlining clinical trials and new types of interaction between industry and FDA such as the end‐of‐phase 2A and voluntary genomic data submission meetings respectively.

Evaluation of exposure change of nonrenally eliminated drugs in patients with chronic kidney disease using physiologically based pharmacokinetic modeling and simulation.

Chronic kidney disease, or renal impairment (RI) can increase plasma levels for drugs that are primarily renally cleared and for some drugs whose renal elimination is not a major pathway. We constructed physiologically based pharmacokinetic (PBPK) models for 3 nonrenally eliminated drugs (sildenafil, repaglinide, and telithromycin). These models integrate drugdependent parameters derived from in vitro, in silico, and in vivo data, and system‐dependent parameters that are independent of the test drugs. Plasma pharmacokinetic profiles of test drugs were simulated in subjects with severe RI and normal renal function, respectively. The simulated versus observed areas under the concentration versus time curve changes (AUCR, severe RI/normal) were comparable for sildenafil (2.2 vs 2.0) and telithromycin (1.6 vs 1.9). For repaglinide, the initial, simulated AUCR was lower than that observed (1.2 vs 3.0). The underestimation was corrected once the estimated changes in transporter activity were incorporated into the model. The simulated AUCR values were confirmed using a static, clearance concept model. The PBPK models were further used to evaluate the changes in pharmacokinetic profiles of sildenafil metabolite by RI and of telithromycin by RI and co‐administration with ketoconazole. The simulations demonstrate the utility and challenges of the PBPK approach in evaluating the pharmacokinetics of nonrenally cleared drugs in subjects with RI.

Measures of Exposure versus Measures of Rate and Extent of Absorption

Regulatory assessment of bioavailability and bioequivalence in the US frequently relies on measures of rate and extent of absorption. Rate of absorption is not only difficult to measure but also bears little clinical relevance. This paper proposes that measures of bioavailability and bioequivalence for drugs that achieve their therapeutic effects after entry into the systemic circulation are best expressed in terms of early [partial area under the concentration-time curve (AUC)], peak plasma or serum drug concentration and total AUC exposure for a plasma or serum concentration-time profile. With suitable documentation, these systemic exposure measures can be related to efficacy and tolerability outcomes. The early measure is recommended for an immediate release drug product where a better control of drug absorption is needed, for example to ensure rapid onset of a therapeutic effect or to avoid an adverse reaction from a fast input rate. The 3 systemic exposure measures for bioavailability and bioequivalence studies can provide critical links between product quality and clinical outcome and thereby reduce the current emphasis on rate of absorption.

A prototypical process for creating evidentiary standards for biomarkers and diagnostics.

A framework for developing evidentiary standards for qualification of biomarkers is a key need identified in the Food and Drug Administrations Critical Path Initiative. 1 This article describes a systematic framework that was developed by Pharmaceutical Research and Manufacturers of America (PhRMA) committees and tested at a workshop in collaboration with the Food and Drug Administration and academia. With some necessary refinements, this could be applied to create an appropriately individualized evidentiary standard for any biomarker purpose.

Human Intestinal Permeability of Piroxicam, Propranolol, Phenylalanine, and PEG 400 Determined by Jejunal Perfusion

AbstractPurpose. To determine the human jejunal permeabilities of compounds utilizing different transport mechanisms using a regional perfusion approach and to establish a standard procedure for determining drug permeability class to be used for the establishment of drug product bioequivalence standards. Methods. Six healthy male volunteers participated in this study. A multi-lumen perfusion tube was inserted orally and positioned in the proximal region of the jejunum. A solution containing piroxicam, phenylalanine, propranolol, PEG 400 and PEG 4000 was perfused through the intestinal segment at a rate of 3.0 ml/min. Perfusate samples were quantitatively collected every 10 minutes for two 100 minute periods with an intermediate wash out period to determine intra and intersubject variation. Results. The mean Peff (±SD) of piroxicam, phenylalanine, propranolol, and PEG 400 were 10.40 ± 5.93, 6.67 ± 3.42, 3.59 ± 1.60, 0.80 ± 0.46 × 10−4 cm/sec, respectively. The coefficient of variation for the intersubject variability, first and second perfusion periods were: piroxicam, 60.5% and 57.1%; phenylalanine, 52.8% and 57.8%: propranolol, 62.1 % and 44.6%; and PEG 400, 81.7% and 42.3%, indicating a slightly lower CV for the second perfusion period in the same subject. The intrasubject CVs between the two perfusion periods were: 19.4%, 21.3%, 23.6% and 41.0% respectively, indicating a smaller intraindividual variation for all compounds studied. Conclusions. Piroxicam, a nonpolar drug exhibited the highest permeability of the compounds studied. The intrasubject CV was lower than the intersubject CV, indicating consistent permeability estimation within subjects. The methodology is useful for permeability estimation regardless of absorption mechanism and can be used to establish a consistent data base of human permeabilities for estimation of human drug absorption and for establishing the biopharmaceutic permeability class of drugs.

Cancer Pharmacogenomics and Pharmacoepidemiology: Setting a Research Agenda to Accelerate Translation

Recent advances in genomic research have demonstrated a substantial role for genomic factors in predicting response to cancer therapies. Researchers in the fields of cancer pharmacogenomics and pharmacoepidemiology seek to understand why individuals respond differently to drug therapy, in terms of both adverse effects and treatment efficacy. To identify research priorities as well as the resources and infrastructure needed to advance these fields, the National Cancer Institute (NCI) sponsored a workshop titled “Cancer Pharmacogenomics: Setting a Research Agenda to Accelerate Translation” on July 21, 2009, in Bethesda, MD. In this commentary, we summarize and discuss five science-based recommendations and four infrastructure-based recommendations that were identified as a result of discussions held during this workshop. Key recommendations include 1) supporting the routine collection of germline and tumor biospecimens in NCI-sponsored clinical trials and in some observational and population-based studies; 2) incorporating pharmacogenomic markers into clinical trials; 3) addressing the ethical, legal, social, and biospecimen- and data-sharing implications of pharmacogenomic and pharmacoepidemiologic research; and 4) establishing partnerships across NCI, with other federal agencies, and with industry. Together, these recommendations will facilitate the discovery and validation of clinical, sociodemographic, lifestyle, and genomic markers related to cancer treatment response and adverse events, and they will improve both the speed and efficiency by which new pharmacogenomic and pharmacoepidemiologic information is translated into clinical practice.

Variability in cimetidine absorption and plasma double peaks following oral administration in the fasted state in humans: correlation with antral gastric motility

The role of gastrointestinal motility and pH in determining cimetidine bioavailability as well as double peaks in plasma profiles following oral administration, in the quiescent or active phase of antral motility, to humans in the fasted state was examined. Plasma cimetidine-time curves did not show the presence of double peaks in any subject following intravenous administration. The incidence of double peaks was 73% following oral administration and was independent of antral migrating motility complex phase. Further, it was found that oral administration of cimetidine in the quiescent phase resulted in significantly higher bioavailability and in other pharmacokinetic parameters compared to that obtained following administration in the active phase. Excellent linearity in plots of motility peaks vs. plasma peaks with slopes close to unity were evident for both quiescent (r(2)=0.93) and active phase (r(2)=0.97) administration. A total of 14 peaks out of 22 (10 subjects, 64%) and 20 out of 27 peaks (11 subjects, 74%), were accounted for in quiescent and active phase oral administration, respectively. The proximal occurrence of plasma peaks to antral motility peaks typical of phase III contractions strongly implies that motility patterns may be responsible for secondary maxima following oral cimetidine administration in the fasted state.

Predicting Drug Interaction Potential With a Physiologically Based Pharmacokinetic Model: A Case Study of Telithromycin, a Time‐Dependent CYP3A Inhibitor

Telithromycin is a substrate and an inhibitor of cytochrome P450 3A (CYP3A4), with dose‐ and time‐dependent nonlinear pharmacokinetics (PK). We hypothesized that the time‐dependent inhibition (TDI) of CYP3A4 was responsible for the nonlinear PK of telithromycin and then used physiologically based PK (PBPK) modeling and simulation to verify this mechanism. Telithromycin PBPK models integrating in vitro, in silico, and in vivo PK data ruled out the contribution of enzyme/transporter saturation and suggested that TDI is a plausible mechanism for PK nonlinearity. The model successfully predicted the clinical interaction with the CYP3A4 substrate midazolam, as verified by external data not used for the model‐building (intravenous (i.v.) and oral (p.o.) midazolam area under the concentration–time curve (AUC) ratio with/without concurrent telithromycin administration: 3.26 and 6.72 predicted vs. 2.20 and 6.11 observed, respectively). Models assuming reversible inhibition failed to predict such strong CYP3A4 inhibition. In the absence of in vitro TDI data, a PBPK model can be used to incorporate TDI mechanisms based on nonlinear PK data to predict clinical drug–drug interactions.