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Thursday, March 30
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7:30 - 8:15 Breakfast Technology Workshop
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Sponsored by |
Effect of
Genetic Polymorphisms on Clinical Pharmacology
Dr. Peter Schultz-Knappe, CSO, Digilab BioVision GmgH |
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Effect of Genetic Polymorphisms on Clinical Pharmacology
8:30 – 9:00 Design Considerations for Pharmacogenomic Studies
Dr. Keith Johnson, Senior Director, Research and Development, Pfizer Inc.
Pharmacogenomics encompasses both pharmacogenetic studies and the measurement of transcriptional changes as a result of drug response or disease progression. Most pharmacogenetic studies to date have focused on the determination of the effect of polymorphisms in drug metabolizing enzymes or drug transporters. A few key examples of variation in drug response based on genotypes of the drug target, or pathway components have been reported and these are predicted to increase in number in the next few years as the widespread application of pharmacogenetics across the industry reads out. There are minimum standards, in terms of subject numbers per study group, required to be confident of genotype influence on pharmacokinetics that will be presented, as well as recent laboratory approaches to measure the contribution of genotype to variability of CYP and UGT enzyme activities using a human liver bank. In addition, recent reports of variation in drug response based on ethnicity will be discussed with relation to moving the argument onto a scientific rather than a sociological basis using genotyping and not ethnicity to predict response.
9:00 – 9:30 Pharmacogenomics of Drug Transporters
Prof. Wolfgang Sadee, Chair, Pharmacology, Ohio State University
Membrane transporters are encoded by several hundred genes. We have established a chemogenomics approach for identifying drug-transporter relationships, with particular application to cancer chemotherapy. This leads to identification of transporters involved in chemo-resistance and sensitivity. Moreover, we have established a screen for finding functional polymorphisms affecting gene regulation and mRNA processing, main factors in inter-individual variability.
9:30 – 10:00 Pharmacogenomics, Arrhythmias, and the QT Interval
Dr. Dan Roden, Director, Oates Institute for Experimental Therapeutics, Vanderbilt University School of Medicine
Prolongation of the QT interval, the electrocardiographic representation of the duration of cardiac
repolarization, occurs as a rare congenital syndrome and in association with many drugs. Exaggerated drug-induced QT interval prolongation can lead to a potentially fatal arrhythmia, and this rare adverse drug reaction has been a leading cause of removal or relabeling of marketed drugs and is an increasing focus in drug development. Clinical predictors and cellular mechanisms in drug-induced QT prolongation have been described, and a role for subclinical congenital long QT syndrome has been identified in 5-10% of subjects. Approaches to identify more general genomic predictors of this adverse drug effect may serve as a model for applying these methods to the study of rare adverse drug effects.
10:00 -11:00 Coffee Break in the Exhibit Hall with Poster Viewing
11:00 – 11:30 Pharmacogenetics and the Prediction of Drug Interactions
Dr. Anne Nafziger, ORI Drug Development Center, Ordway Research Institute
Genetic polymorphisms are one of the factors that contribute to drug interactions. In so far as pharmacogenetic information is available for a given individual, and metabolism information is available for concurrently administered drugs, it may be possible to predict the level of risk for drug interactions and the severity of the interactions. Knowledge of the phenotype, and not solely genotype, may be required to make such assessments. Application of pharmacogenetic principles may allow drug dosing to be tailored to the individual and thereby modify drug response when adequate pharmacogenetic information is available for an individual patient. The issues involved in application of pharmacogenetic principles to the prediction of drug interactions will be discussed.
11:30 – 12:00 Impact of Pharmacogenetics on Drug Interactions
Dr. Rene H. Levy, Professor & Chair, Pharmaceutics & Neurological Surgery, University of Washington
Drugs metabolized by polymorphic enzymes (CYP2D6, CYP2C19) exhibit variable drug exposure and the exposure of poor metabolizers must be ascertained. Particular concern arises when poor metabolizers are treated with an inhibitor of the
non-polymorphic pathway because exposures can be 10 to 30 fold higher than in extensive
metabolizers. An approach to the prediction of maximum exposure in poor metabolizers will be presented.
Luncheon Technology Showcase
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12:15 – 12:30
Pathway Analysis in Renal Cell Carcinoma: Implications for Drug Development
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Dr. Catherine Tribouley, Gene Logic
Identification of pathways essential for tumor development is key to successful therapeutic intervention, can be performed using microarray technologies and integrated into the drug development process. Gene Logic’s BioExpress® System contains extensive clinical and pathology information for each collected tissue sample as well as a set of tools for rapid quality assessment, gene expression and pathway analysis in humans and animal models of disease. In this presentation, we will demonstrate how gene expression profiling and pathway analysis of clear cell renal cell carcinoma specimens can help identify the most appropriate target for drug discovery and potentially the most efficacious drug combinations.
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12:30-12:45
Comprehensive Serum Biomarker Screening for Clinical Trial Participant Classification: How Healthy is Your Volunteer?
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Dr. Ralph McDade, Strategic Development Officer, R&D, Rules-Based Medicine
We applied comprehensive serum biomarker screening to 250 healthy, asymptomatic individuals that measured over 250 serum analytes in each. Serious health conditions were detected in 7% of the individuals and moderate health situations were identified in an additional 15% of the group. These data indicate that 1 in 5 members of any cohort may have an underlying disease/condition that could provide confounding trial data.
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12:45-1:00 OGAP® A Healthcare Data Integration Solution for Proteomic & Genomic Biomarkers
Dr Christian Rohlff, CEO, Oxford Genome Sciences
• Successful implementation of biomarkers facilitate faster and
more accurate drug development programmes.
• To establish an effective biomarker panel for phase II clinical
trials requires a shorter transition from biomarker discovery to
validation
• OGAP® is a new integrated bioinformatics platform that
contains one million experimentally derived peptide sequences
from 50 human tissues and diseases integrated with eight
million SNPs and haplotypes.
• OGAP can me queried from a molecular, pathological, clinical,
drug treatment and disease outcome perspective to evaluate
and prioritize protein biomarker candidates and design optimal
analytes for clinical biomarkers assays.
• OGeS is using a MS peptide array platform for a transition of
newly discovered biomarker candidates into a clinical reference multiplex assay format in six to twelve month
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1:00 – 1:45 Technology Short Talks
(Additional Sponsorship Available. Please contact Arnold Wolfson at
awolfson@healthtech.com
or 781-972-5431.)
PK/PD Biomarkers and Modeling
2:00 – 2:30 PK/PD Modeling of Early Biomarker Data: Impact on Study Design
Dr. Jean-Michel Gries, US Site Head, Clinical Pharmacology (PDMP), F. Hoffmann-La Roche Inc.
2:30 – 3:00 Application of Biomarkers in Early (Phase I) Clinical Development
Dr. Michael-Friedrich Boettcher, Global Clinical
Pharmacological Project Leader, Bayer HealthCare AG
Selecting, evaluating and applying biomarkers in early clinical (phase I) drug development can substantially shorten the time to reach a critical decision point. The use of biomarkers in phase I studies helps to determine whether the drug is reaching the molecular target in humans or affecting a meaningful measurable endpoint that predicts desired or undesired clinical effects. Critical decisions such as candidate selection, early proof of mechanism or proof of concept, and dose ranging can be based on measurement of appropriate biomarkers. Linking pharmacodynamic to pharmacokinetic information may help to predict drug response and to assess safety risks. Preclinical and phase I development plans should be focused to support an early sd or md biomarker study in healthy volunteers or mildly diseased patients, thus saving both resources and time. Examples of using biomarkers in early clinical development are given.
3:00 – 4:00 Refreshment Break in the Exhibit Hall with Poster Viewing
4:00 - 4:30 Integrating Novel PD Assays into Early Stage Clinical Trials
Dr. Dan Fitzpatrick, Associate Director, Molecular Sciences, Amgen Inc.
The ability to incorporate PD analyses early in the clinical development of a therapeutic agent opens a window into the functional complement to
PK, enabling more objective and rational determinations of dosage in subsequent stages of drug administration. Using data from several early stage Amgen trials where PD assays have been integrated we will present both the advantages as well as caveats of these approaches.
4:30 – 5:00 Biomarkers as Prerequisite for PK/PD Modeling and Model-Based Drug Development
Dr. Bernd Meibohm, Associate Professor of Pharmaceutical Sciences, College of Pharmacy, University of Tennessee Health Science Center
Model-based drug development including exposure/response assessments in form of
pharmacokinetic/pharmacodynamic (PK/PD) modeling has recently been strongly promoted by industry, academia and regulatory agencies. One of the major prerequisites for the successful application of
PK/PD-modeling, however, is the availability of response measures such as biomarkers that provide an immediately accessible link between pharmacotherapeutic intervention and clinical outcome and allow to easily assess variations in desired and/or undesired drug effects in response to changes in dose, dosage regimen, dosage formulation, administration pathway, or external factors affecting drug response. Although analytically more challenging,
PK/PD-based response assessments generally provide a substantially improved predictive power compared to traditional exposure/response assessments and allow for consideration of the temporal aspects in effect intensity. Rigorous implementation of biomarker-based
PK/PD modeling in drug product development provides a rationale, scientifically-based framework for efficient decision making regarding the selection of potential drug candidates, for maximum information gain from the performed preclinical experiments and clinical studies, and for conducting fewer, more focused clinical trials with improved efficiency and cost-effectiveness. Thus, biomarker-based
PK/PD modeling is a valuable tool for a scientifically driven, evidence-based, and thus streamlined drug development process.
5:00 – 6:30 Cocktail Reception in the Exhibit Hall with Poster Viewing
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