Monday, September 29
3:00-4:00 Conference Registration
4:00-4:10 Welcoming Remarks from Conference Director
Julia Boguslavsky, Cambridge Healthtech Institute
Establishing Biomarker Utility
4:10-4:15 Chairperson’s Opening Remarks
4:15-4:40 Five Characteristics of a Biomarker to be Useful for Personalizing Medicine
Felix Frueh, Ph.D., Vice President, Research & Development, Personalized Medicine, Medco Health Solutions, Inc.
4:40-5:05 Biomarkers for What? Diagnostic, Prognostic or Predictive?
Sudhir Srivastava, Ph.D., Chief, Cancer Biomarkers Research Group, NIH National Cancer Institute
Biomarkers have been touted as a next frontier in the realm of personalized medicine. However, one has to be specific and clear about its intended use: Diagnostic, Prognostic, or Predictive? Each type has a different purpose. Each has to meet certain criteria to be fit for the purpose. Therefore, when discussing biomarkers, one must clearly state its targeted goal and population.
5:05-5:30 Building a Biomarker Information Pipeline and Enabling Translational and Personalized Medicine: Leveraging Industry Standards to Bring Omics Closer to Medicine
Martin D. Leach, Ph.D., Executive Director, Basic Research & Biomarker IT, Merck & Co., Inc.
5:30-6:30 Opening Reception in the Exhibit Hall
Tuesday, September 30
Genomic Biomarkers | Protein Biomarkers | Metabolic Biomarkers | Biomarker Data Analysis
7:00 Registration Open
7:30-8:15 Morning Coffee or Technology Workshops
(Sponsorship Available. Contact Ilana Schwartz at 781-972-5457 or firstname.lastname@example.org.)
7:30 Breakfast Workshop
Biological Variation Based Data Interpretation. Why Can This be of Value?
Gordon F. Kapke, Ph.D., Senior Director of Biomarker Services, Covance Central Laboratory Services
With the emphasis on biomarkers to improve drug development the question arises as how to interpret the data. The traditional clinical laboratory methodology for interpreting data involves the identification of the expected values (the normal range) and from this range defining the probably of disease or no disease (sensitivity and specificity). The challenge in drug development is in monitoring the patient overtime while identifying if important changes have occurred in the biomarker values that indicate inappropriate toxicity or demonstrate appropriate efficacy. The use of the reference interval as a means of identifying toxicity or efficacy will be challenged and an alternative approached based embracing biological variation will be proposed.
Gene Expression Profiling of Health and Disease:
Bridging Statistics and Biology
(Shared session between Genomic Biomarkers and Biomarker Data Analysis)
8:30-8:35 Chairperson’s Opening Remarks
8:35-9:00 Biomarkers: Understanding the Disease Process
Michael N. Liebman, Ph.D., Senior Institute Fellow, Windber Research Institute; and Managing Director, Strategic Medicine, Inc.
Measurement of gene expression data presents an opportunity to further classify patients and their disease using biological specimens, robust experimental methods and statistical analysis to enhance clinical decision making. It is critical, however, to appropriately evaluate this perspective on patient and/or disease stratification in terms of the complexity of the disease process and clinical need, rather than solely on the concept of a disease state. This presentation will describe both the conceptual framework for understanding the relationship between biomarkers and the disease process and results from its application in breast cancer.
9:00-9:25 NextBio - Searching Large Scale Biological Data for Metabolic Syndrome X Biomarkers
James Flynn, Ph.D., Field Application Scientist, NextBio
NextBio presents a powerful research tool to analyze Metabolic Syndrome X, one of the most complex and pervasive medical conditions that combines several disorders into one. Patients with Metabolic Syndrome X exhibit clinical signs of diabetes, obesity, dyslipidemia, hypertension and heart disease. This fact underscores the complexity involved in the study of this disorder and highlights the value of NextBio, which enables researchers to look at the interplay of various disease pathways. In this talk, we will demonstrate diverse search strategies for the discovery and validation of Metabolic Syndrome X biomarkers and drug toxicities through NextBio. NextBio’s collection of public experimental data will be used to explore mechanisms of potentially applicable compounds, discover tissue specific expression profiles associated with the disease and drill into the interplay of relevant pathways (such as lipid metabolism, glucose metabolism and inflammation).
9:25-9:50 Ingenuity Pathways Analysis: Prioritization of Biomarker Candidates from Omics Data Based on Phenotypic Association
Deborah Riley, Ph.D., Senior Application Scientist, Ingenuity Systems
As gene expression profiling has matured to become a common component of biomarker discovery programs, the challenge has shifted to translating large scale datasets into biomarkers that can be used to diagnose disease and predict patient response to treatment. Prioritization of biomarker candidates requires – at a very practical level - an understanding of candidates’ expression patterns in bodily fluids and target tissues and - at the mechanistic level – identification of biologically plausible paths between candidate markers and the physiological responses, cellular phenotypes, or disease processes of interest. In this session we will present a case study in which the biomarker discovery tool IPA was used to prioritize biomarker candidates and elucidate the molecular mechanisms connecting those markers to disease phenotypes and pathways.
9:50-10:15 Defining Health at the Molecular Level
Martin Grigorov, Ph.D., Head of Bioinformatics, Nestlé Research Center
The challenge for the Life Sciences in the new century resides in promoting health and in preventing disease. In order to meet this challenge, knowledge should be built to define and better understand the function of the molecular markers which define the healthy status of a biological system. The aim of the present study was to generate a map of gene expression patterns along the human healthy adult gastrointestinal tract in order to use such sets of biomarkers as references when screening for pathological deviations. Nearly 150 marker genes were found to perfectly discriminate the five major GI regions considered. Fourteen had never been described in the GI tract, and six were novel genes. This work offers a perspective on nutrition-specific biomarkers discovery programs. It shows such studies to be complementary to typical drug development programs focusing on disease-specific biomarkers, rather than on the molecular signatures of health.
10:15-11:10 Networking Coffee Break with Poster and Exhibit Viewing
Molecular Diagnostics: Translation to the Clinic
11:10-11:35 Lost in Translation: Factors Affecting the Clinical Uptake of Molecular Diagnostics
Judd Staples, Director, Translational Initiatives, Corporate and Venture Development, Institute for Genome Sciences & Policy, Duke University
This presentation will explore the barriers to translating new molecular diagnostic discoveries into clinical practice. We will provide a framework to assist researchers in critically evaluating the potential applications of their discoveries and suggest an approach to maximizing the chances that their invention ultimately has an effect in the management of patient care. Topics that will be covered will include assessment of the value of the technology from the perspective of the patient, the healthcare provider, the investor/strategic partner, regulators, and payers.
11:35-12:00 Title to be Announced
Alberto Gutierrez, Ph.D., Deputy Director, New Product Evaluation, Office of In Vitro Diagnostic Device Evaluation and Safety, Center for Devices and Radiological Health, U.S. Food and Drug Administration
12:00-1:40 Luncheon Technology Showcases
An Automated and Streamlined Solution to Increase Productivity and Confidence in Microarray Studies
Jean-Francois Olivier, Ph.D., Affymetrix
This case study highlights the increase in productivity and confidence in microarray results for whole genome expression analysis using a microplate-based high throughput platform. The platform includes automated target preparation, an array processing instrument and complementary reagents that minimize hands-on time. Applications in drug discovery and development will be discussed.
Cancer DSA™ - Disease Focused Microarrays: A Platform for Biomarker Discovery and Validation, Optimised for Use with FFPE Tissue
Austin Tanney, Ph.D., Scientific Liaison Manager, Almac Diagnostics
WideScreen™ Assays for the Multiplex Detection and Quantitation of Cell Signaling Proteins and Serum Biomarkers
Laura Juckem, Ph.D., R&D Senior Scientist, Multiplex Assays, EMD Chemicals, Novagen
Bead-based immunoassays allow multiplex analysis of 5-20 protein analytes from a single sample. This session will discuss select WideScreen™ Assays and their use in the characterization of cell signaling events and in the analysis of serum biomarkers. These assays include:
·Multiplex assays to analyze the expression and tyrosine phosphorylation status of several key receptor tyrosine kinases, enabling the profiling of protein kinase inhibitors in a cellular context.
·An assay that uses EpiTag™ Technology (Epitome Biosystems) for the simultaneous, multiplex quantitation of total and phosphorylated ERK pathway proteins in a single well.
·Highly validated and functionally defined serum biomarker panels developed in partnership with Rules Based Medicine.
Personalized Medicine: Translation to Clinical Practice
1:40-1:45 Chairperson’s Opening Remarks
1:45-2:10 Personalized Healthcare – Where Are We Now?
Ruth E. March, Ph.D., Director, Personalized Healthcare Science and Technology; Lead, Personalized Healthcare Team, AstraZeneca
This talk will examine what Personalized Healthcare (PHC) is, its current state and its main beneficiaries. We will then examine what makes for successful PHC development and what are the main challenges. This will be illustrated by case studies including Iressa®, Exanta™ and products from AstraZeneca’s early development pipeline. The talk will demonstrate that PHC is at an exciting time and depends on all those involved working together to realise the benefits.
2:10-2:35 Novel Computational Tools for Translating Genomic Biomarkers into Clinical Practice: Case for Warfarin
Saeed A. Jortani, Ph.D., Director, Toxicology, University of Louisville Hospital Laboratory; Associate Professor, Pathology and Laboratory Medicine, University of Louisville School of Medicine
There is a combination of clinical, scientific, and regulatory evidence supporting the adoption of pharmacogenetic-guided dosing for warfarin (Coumadin). This drug is the most commonly used oral anticoagulant medication, currently taken by four million people in the US who are at risk for blood clots and strokes. Because the proper warfarin dose per patient is difficult to assess, most physicians take an educated, ballpark guess, and follow up with a blood test to ensure the medicine is working properly. Confounding this is the fact that therapeutic warfarin doses vary significantly from patient to patient, so that even a “standard dose” can cause life-threatening hemorrhaging. Despite the evidence supporting adoption of pharmacogenetic testing for warfarin dosing, it is not yet clear how clinicians will incorporate this new discipline into their clinical decision making. We have developed a computational decision support module for translating pharmacogenetics laboratory test results into clinical action.
2:35-3:00 Genomic Biomarkers: Examples for Discovery, Utility, and Implementation
Andrew Grupe, Ph.D., Senior Director, Pharmacogenomics and Director, CNS Research, Celera
Results from studies across several disease indications suggest that prognostic genetic markers represent excellent candidates for predictive biomarkers. A specific example for a genetic risk factor of cardiovascular disease that also predicts the reduction of cardiac events after statin treatment will be presented. Furthermore, the impact of genomic biomarkers on clinical trial design and the timeframe for developing and implementing a molecular diagnostic test will be discussed.
3:00-4:00 Networking Refreshment Break with Poster and Exhibit Viewing
4:00-4:25 Pharmacogenomics Data: Transmission and Submission
Joyce Hernandez, Ph.D., Manager, Global Data and Information Standards, Merck Research Labs; and Philip M. Pochon, Ph.D., Enterprise Information Architect, Covance Inc.
The emerging use of pharmacogenomic drug metabolism and disease markers in drug development research has sparked considerable interest in the transmission and reporting of pharmacogenomic data. The FDA has recently issued a final guidance on the voluntary submission of pharmacogenomic data, and CDISC and HL7 teams have been actively developing models and vocabularies for this data. This presentation provides an overview of the proposed CDISC/HL7 pharmacogenomic data standards, which include a pharmacogenomic extension to the CDISC/HL7 LAB message, and three new domains within the CDISC SDTM. Example data sets are used to show how the detailed data of the CDISC/HL7LAB operational standard populates the SDTM biospecimen, pharmacogenomic specimen and pharmacogenomic result domains. Example of sequence based and gene expression based analyses are shown. A final section discusses proposed pilot projects using the models to submit data under the FDA Voluntary Genomics Data Submission program.
4:25-4:50 DNA-Guided Medicine in the Management of Cardiovascular and Psychotropic Drugs
Richard L. Seip, Ph.D., Senior Physiologist, Genomas, Inc.
Genomas is a biomedical company advancing DNA-Guided medicine with PhyzioType™ systems for personalized healthcare. A PhyzioType System has 3 components: an ensemble of inherited, stable genetic markers (single nucleotide polymorphisms, SNPs) from various genes, a biostatistical algorithm validated in clinical studies for ascertaining the clinical significance of a patient’s SNPs, and a portal for doctors to select drugs based on an individual’s risk of developing side effects. By comparing side effect risks of drugs in a therapeutic class for each patient and by forewarning doctors of adverse responses that will complicate treatment, PhyzioType systems substantially enhance patient safety. PhyzioType systems in development for statins, atypical antipsychotics, and glitazones will be described.
5:15 Close of Day
Wednesday, October 1
7:00 Registration Open
7:30-8:15 Breakfast Presentation
An Integrated Quantitiative Mass Spectrometric Workflow for the Discovery and Validation of Protein Biomarkers Using Tandem Mass Tags (TMT®)
Dr. Rainer Voegeli, Commercial Director, Proteome Sciences plc.
The establishment of highly specific and sensitive validation assays is a key task to transfer candidate biomarkers from discovery into validation studies. In response to the limited availability of ELISA’s, single and multiple reaction monitoring (SRM, MRM) is emerging as a highly selective and sensitive approach for the quantitation of proteins. Here we present an integrated workflow for discovery, assay development and validation studies which utilises chemical labelling by Tandem Mass Tags (TMT). In discovery mode up to six samples are labelled with different colours of TMT, mixed and subsequently analysed by Tandem Mass Spectrometry in a single assay run. From individual samples generally >1,000 peptides and proteins are analysed. Peptides and proteins are selected as candidates for validation if they appear differentially regulated, and meet appropriate biostatistical properties across an adequately powered discovery study. Assay development is then performed using peptides unique to the candidate biomarkers. By combining MRM with peptide labelling by Tandem Mass Tags TMTzero (label mass: 224 Da) and sample labelling by TMTsixplex (label mass: 229 Da), peptide pairs are generated which exhibit perfect co-elution and show a mass difference of 5 Da per added Tag. Quantitation against a reference labelled with TMTzero is so made possible whilst maintaining the selectivity/specificity of MRM combined with the superior sensitivity of Triple Quadrupole instrumentation. This approach allows the very fast transfer of discovery candidates into high quality assays and alleviates the need for immunoassay development or the synthesis of heavy-isotope labelled peptides (as routinely used in MRM’s).
- Seamless transition from discovery to high quality, high sensitivity assay development will shorten validation time
- Multiplex Assay Capability is in-line with the expected multitude of biomarkers to be validated
- No need to invest into lengthy immunoassay-development prior to validation of the marker itself
- Quick translation from pre-clinical to human trials
Genomic Biomarkers in Clinical Pharmacology
8:30-8:35 Chairperson’s Opening Remarks
8:35-9:00 Discovery of Gene Expression-Based Pharmacodynamic Biomarkers in Tumor Immunotherapies
Zenta Tsuchihashi, Ph.D., Group Leader, Oncology Clinical Biomarker, Discovery Medicine and Clinical Pharmacology, Bristol-Myers Squibb Co.
Gene expression profile analysis in ‘clinically available’ tissue samples such as tumor biopsy and peripheral blood provides a powerful tool in discovering novel pharmacodynamic biomarkers. This approach is especially useful in the immunology area, as these tissues samples do contain immune cells that are the targets of the drug action. These biomarkers are useful in both understanding the key mechanism of action, as well as optimizing the use of these drugs. A gene expression based ‘hypothesis-free’ approach complements the more traditional ‘hypothesis-driven’ biomarker analyses in immunology including flow cytometry and immunohistochemistry, and is especially useful when the detail of the drug action is not well understood.
9:00-9:25 Noninvasive Safety Biomarkers of Germinal Center Atrophy and Infection
Eric R. Fedyk, Ph.D., Head, Inflammation Biology & Immunotoxicology, Non-Clinical Development Sciences, Millennium Pharmaceuticals, Inc.
The pathology of autoimmune disease is characterized by recurrent chronic inflammation. Successful therapeutic intervention requires immunosuppression, however not of a magnitude that predisposes subjects to infection, a current safety risk, particularly in outpatient settings (ex. rheumatoid arthritis). Dosing patients for “efficacy without infection” is an elusive endeavor with contemporary therapeutics, largely due to inherent heterogeneity among subjects. Recent development of noninvasive, antecedent biomarkers of immunosuppression and infection, in genetically heterogeneous primate models, has the potential to improve dosing of subjects in clinical trials and patients in clinical practice.
9:25-9:50 Genomic Biomarkers for Early Screens for Non-Genotoxic Carcinogenicity
Nandini Raghavan, Ph.D., Principal Biostatistician, Non-Clinical Biostatistics, Johnson & Johnson Pharmaceutical Research & Development
Genomic drug safety screens will accelerate the process for developing safer drugs and limit the failure of drugs in late stage development due to toxicity issues, by identifying potential toxicity issues early in the development process. As a result, there is now heightened interest in developing biomarkers for predictive toxicology and risk assessment using toxicogenomic technologies from pharmaceutical companies as well as from governmental agencies worldwide. In this talk we describe the development of a gene-expression based signature to predict non-genotoxic carcinogenicity with high accuracy, using 24 hour microarray experiments on rats. This is especially critical, since short-term assays for non-genotoxic carcinogenicity, which is commonly observed in long-term rodent studies, have proven difficult to develop. We also discuss the need for validating and standardizing gene signatures, to make them portable across platforms, technologies and experimental protocols and eventually applicable for regulatory use.
Development Considerations for Single-Analyte Markers, Panels, and Profiles
10:50-11:15 Optimal Biomarker Approach: Data Analysis Considerations of Individual, Panel or Profile
Stephen Naylor, Ph.D., Chief Executive Officer & Chairman, PPM, Inc.
The advent of relatively high throughput and broad analyte coverage analysis in “omic” measurements has reignited a debate about what constitutes the optimal biomarker solution. Is it a single analyte per biological event, or a panel (3-10 analytes) or even a profile (>20 analytes)? This will be discussed in the context of statistical and data analysis as well as data mining characteristics.
11:15-11:40 Panel Discussion
11:40-1:10 Luncheon Technology Workshop
Enabling Drug Development Through Multiplexed Assays
Monica Erico, Ph.D., Scientific Services, Meso Scale Discovery
Meso Scale Discovery (MSD) has an electrochemiluminescence platform that is fast (1-3 minutes per plate independent of plate density), robust (non-fluidics instrument), radioactive free, sensitive (detection limits near 10 attomoles) and has a wide dynamic range (5 logs) with multiplexing capabilities. The performance (sensitivity, reproducibility, and ease of use) of multiplexing cytokines, cell signaling pathways, and multiplexed toxicology biomarkers assays will be presented. Development of multiplex panels for complex matrices is challenging because of varying levels of biomarkers, interfering substances in the sample, and interactions between proteins measured. The platform allows for simple assay development that can greatly reduce the amount of time to develop novel assays. The combined properties of the system provide both a cost and time savings with a highly quantitative assay format while improving productivity.
11:40-1:10 Luncheon Technology Workshop
Multiplexed Biomarker Assay Development
Michael Pisano, Ph.D., President and CEO, NextGen Sciences
Biomarkerexpress™ is a suite of mass spectrometry-based biomarker services that utilize proprietary methods to significantly decrease timelines and increase the success rates traditionally associated with biomarker development. The services include discovery of protein biomarkers, development of protein biomarker assays, testing biological samples utilizing the assays to determine levels of protein biomarkers.
Case Study 1: Discovery and Assay Development for Putative Biomarkers of Lung Cancer Progression
Case Study 2: Assay Development for a Panel of 30 Biomarkers for Alzheimer’s Disease
Bridging Silos: Integrating Omic Data
1:10-1:15 Chairperson’s Opening Remarks
1:15-1:40 Integration of Metabolic and Transcriptomic Profiling for Understanding of Diabetes and Obesity Mechanisms
Christopher B. Newgard, Ph.D., Director, Sarah W. Stedman Nutrition and Metabolism Center, Duke University Medical Center
Type 2 diabetes is a disease that occurs as a result of metabolic dysfunction in multiple tissues, including most prominently liver, skeletal muscle, and the pancreatic islets of Langerhans. An understanding of the transcriptional and metabolic networks that control normal functions in these tissues, and identification of the network elements that are perturbed during development of type 2 diabetes, are essential steps in the development of new therapies for the disease. The value of targeted mass spectrometry-based profiling of key clusters of intermediary metabolites for identifying specific network perturbations will be highlighted, as will recent examples of integration of metabolomic and transcriptomic profiling for identifying heretofore unrecognized regulatory pathways.
1:40-2:05 Integrating Gene and Protein Expression Biomarkers in a Systems Biology Approach to Colon Cancer
Mark R. Chance, Ph.D., Director, Case Center for Proteomics; Director, Center for Synchrotron Biosciences; Professor, Department of Physiology & Biophysics, Case Western Reserve University
Protein interaction networks are at the heart of functional control of human disease. Network and pathway modeling driven by Omics based approaches are increasingly important to our understanding of disease progression and drug responses. However, deriving and validating network models are complex research problems requiring integra tion of multiple types of high-throughput data. We have recently employed a systems biology approach to find small networks of proteins discriminative of late stage human colorectal cancer (CRC). Expression proteomics studies were initially used to identify proteins differentially regulated when comparing normal and late stage tumor tissues obtained from adequately sized cohorts of human patients. Proteins identified by these experiments were used to seed a search for protein-protein interaction networks selective for biological relevance to the human colon. We chose four significant networks returned by this search and illustrated using measures of mutual information, calculated using gene expression data, that certain protein “signatures” within each network are highly discriminative of late stage cancer versus control. These signatures would not have been discovered using only proteomic data, or by merely clustering the gene expression data. Expanding these signatures by a single hop generated four sub-networks, which were analyzed for biological relevance to human CRC. A number of the proteins in these sub-networks have been shown to be critically involved in the progression of CRC. Others have been recently identified as potential markers of CRC, and still others merit follow-on experimental validation for biological significance in this disease. This general approach can be applied to network modeling for a number of diseases.
2:05-2:30 A Systems Biology Approach to Biomarker Discovery
Karin Rodland, Ph.D., Science Lead for NIH Programs, Pacific Northwest National Laboratory
Efforts to identify biomarkers for early diagnosis or prognosis of cancer and other disease have often focused on a singular molecular species, with preference given to mRNA, microRNA, proteins, autoantibodies or metabolites based on available technologies and model systems. Each one of these measurements provides a snapshot of cell function, but a dynamic understanding of disease processes really requires the integration of all these modalities to the extent possible. Particularly in the context of using biomarkers to guide therapeutic interventions, it is necessary to understand the relationship between changes in expression, and changes in function. One aspect of systems biology is the integration of heterogeneous datasets to define relationships that predict function. This talk will describe the application of this approach to models of chronic obstructive pulmonary disease.
2:30-2:55 Connecting the Biomarker Dots in Cancer and Neurodegenerative Diseases
Ira L. Goldknopf, Ph.D., Director, Proteomics, Power3 Medical Products, Inc.
The application of fundamental principles to Omic integration to address unmet clinical needs will be illustrated with examples from cancer and neurodegenerative diseases. The integrations relate analytical with clinical validation across different analytical processes and platforms; clinical diagnostics with assessment of severity, disease progression, and efficacy; and data analysis integrating proteomic and genomic biomarkers, post-translational modifications, and protein isoforms. The clinical applications cover testing of blood serum for early detection of breast cancer as well as for early differential diagnosis and monitoring of the neurodegenerative diseases. The attainment of biological significance in terms of monitoring mechanisms of disease through blood testing as well as practical clinical diagnostic applications of such testing will also be discussed.
3:00 Close of Conference