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Clinical Trial Designs for Personalized Therapy


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Wednesday, September 19

» Opening Plenary Session 

2:00-3:00 Main Conference Registration

3:00-3:10 Welcoming Remarks from Conference Director

Julia Boguslavsky, Executive Director, Conferences, Cambridge Healthtech Institute

Strategies to Accelerate Development and Advance Personalized Therapy (ADAPT) 

3:10-3:15 Chairperson's Opening Remarks

3:15-3:45 Rules, Tools and Data Pools: The Critical Path's Recipe for Speeding Drug Development

Carolyn ComptonCarolyn Compton, M.D., Ph.D., President & CEO, Critical Path Institute

Both regulatory agencies and the medical products industry recognize the need for new biomarkers and methods to speed the development and delivery of effective, safe medicines to patients. However, developing consensus on the utility of new biomarkers and establishing a process for putting them into routine practice in medical product development and regulatory decision making is a complex undertaking. In 2009 and 2010, respectively, the European Medicines Agency and the FDA released guidance that describes a voluntary pathway for "qualification" of novel drug development tools or methods. Determining the relative advantages/disadvantages and evidentiary standards required for regulatory "qualification," applying a novel biomarker on a specific drug development program, or submitting an application for a diagnostic device are challenging tasks. The Critical Path Institute (C-Path) acts as a trusted third party to lead six pre-competitive global consortia that, with the cooperation of the FDA, develop and qualify molecular and imaging biomarkers as well as patient-reported outcomes instruments for specific contexts of use in medical product development. Several C-Path consortia use Clinical Data Interchange Standards Consortium disease area data standards in constructing clinical trial databases from which disease progression models and virtual clinical trial simulations are developed. Specific examples from these consortia will be utilized to illustrate the power of pre-competitive collaboration in the generation and qualification of drug development tools.

3:45-4:15 Technology Transformation at FDA: Driving Efficiency and Unleashing Innovation

Eric-PerakslisEric D. Perakslis, Ph.D., Chief Information Officer and Chief Scientist, Informatics, U.S. Food and Drug Administration

The U.S. Food and Drug Administration has recently taken significant steps to modernize and improve its information technology and informatics capabilities.  The resulting infrastructure, architecture, innovation pathways and data sharing initiatives are intended to ease regulatory burden on innovators while maintaining the highest quality standards. In this talk, Eric Perakslis, Ph.D., the Chief Information Officer and Chief Scientist for Informatics at FDA, will discuss these initiatives in detail and will provide success examples, recent progress and future directions.

4:15-4:45 Turning an Active Compound into a Personalized Medicine: Do Biomarkers Help or Hinder?

Geert-KolvenbagGeert Kolvenbag, M.D., Ph.D., Global Product Vice President, AstraZeneca

The co-development of drug and biomarker has several inherent risk and challenges. In addition the expectations and demands of the oncology community have increased over the last years. These challenges will be illustrated by a case study of a very active compound destined for a fast development program as a personalized medicine, but running into scientific, diagnostic and development challenges. This experience creates questions for development of drugs and diagnostics today and in the future.

4:45-5:15 Strategies to De-Risk Drug Development Utilizing Biomarkers in Early Clinical Trials

Scott-KennedyScott Kennedy, Ph.D., Global Head, Biomarker Development, Novartis Institutes for BioMedical Research, Inc.

Other than recent examples in oncology, the emerging field of personalized medicine has yet to live up to its promise of enabling more rapid, efficient drug development and providing customized therapies to patients. This presentation will exemplify and discuss how leveraging biomarkers which inform a biological understanding of targeted and disease pathways can increase the success of early clinical development.  These biologically relevant markers can also enable the identification and treatment of parallel disease populations and serve as stratification or response markers for later stage development. This presentation will also discuss several of the challenges that this paradigm presents.

5:15-5:45 Implementing a Personalized Medicine Strategy: Is There Light at the End of the Tunnel?

Jeremy BartonJeremy Barton, M.D., Vice President, Head of Oncology Clinical Research, Pfizer

Personalized medicine, the practice of tailoring treatment to individual characteristics of the patient, has emerged as a major force in oncology in the last decade with the expectation of significant improvement in safety and efficacy of therapeutics. The ultimate success of this paradigm is dependent on a variety of factors. The choice of drug target, selection of patients by companion diagnostic, regulatory authority acceptance of novel trial designs which best serve this strategy, improved health care information technology, insurance coverage and reimbursement are just a few of the important variables in the equation. This presentation will provide an overview of the current situation and discuss factors which will impact future progress in the field.

5:45-6:45 Welcome Reception in the Exhibit Hall with Poster Viewing

Thursday, September 20

7:30-8:15 am Morning Coffee or Sponsored Breakfast Presentation (Opportunity Available)

Contact Ilana Quigley at or 781-972-5457


Innovation in Oncology Clinical Trial Design 

8:30-8:55 Cancer Clinical Trials in the Genomic Era

Richard M. Simon, Ph.D., Chief, Biometric Research Branch, National Cancer Institute

Developments in cancer biology and biotechnology provide unprecedented opportunities for the development of effective therapeutics and for utilizing them in a predictive manner. Taking advantage of these opportunities requires the development of new designs for clinical trials and re-evaluation of some existing paradigms for analysis strategies. This talk will review some of these issues, provide some examples of new designs and identify some of the opportunities and challenges for drug developers and computational scientists in 21st century medicine.

8:55-9:20 Methodology of Clinical Trials in Oncology—From Theory to Practice

Jarl Ulf Jungnelius, M.D., Vice President, Oncology CR&D; Therapeutic Area Lead, Tumor CR&D, Celgene

Development of new drugs in cancer is becoming more and more challenging, and clinical trials with so-called targeted agents are adding a new dimension. Several considerations have to be taken into the equation, especially the indication, clinical stage and type of response, but also the number of patients to be enrolled, more stringent statistics (parametrics vs. non-parametrics tests), patient selection and biomarker approach. The only answer to these challenges is innovation: new or alternative clinical trial design, choice of surrogate endpoints and creative strategies based on the physiology. There is also a need to effectively and efficiently apply the new tools such as pharmacogenomics, proteomics and imaging techniques. We will review and discuss some of our experiences in dealing with these challenges and through examples of development strategy of recent oncology agents we will analyze the theory versus the reality.

9:20-9:45 Clinical Development of XALKORI®: A Statistical Perspective on Opportunities and Challenges

Paulina Selaru, M.S., M.S.P.H., Director, Xalkori Statistical Lead, Oncology Business Unit, Pfizer

Crizotinib (XALKORI®) has received accelerated approval from the U.S. FDA (August 2011) for treatment of ALK-positive non-small cell lung cancer (NSCLC) based on data from 2 phase 1/2 single arm studies. Remarkable anti-tumor activity was observed early on during development of crizotinib and consistently over time. As a first-in-class and first-on-target agent in a prospectively identified, molecularly enriched population, development of crizotinib posed some unique opportunities and challenges. Different methods and analyses employed to put the crizotinib data into perspective of a “quasi-randomized” manner relative to historical data from NSCLC patients, will be presented.

9:45-10:45 Coffee Break in the Exhibit Hall with Poster Viewing

10:45-11:10 Strategies for Integrating Biomarkers into Clinical Trials of New Therapies in Cancer

Maria Koehler, M.D., Ph.D., Vice President, Tumor Strategy; Clinical Development and Medical Affairs, Oncology Business Unit, Pfizer

Increasing understanding of the molecular basis for cancer development and ever-growing subclassification of cancers based on molecular abnormalities found in tissues is proven to help many patients with identified abnormalities. These discoveries, while helpful, create mounting challenges in design and execution of clinical trials in oncology. Sustainable, clinically useful drug development depends on increasing efficacy, limiting toxicity and reducing development costs/decreasing attrition. Biomarkers have the potential to stratify patients thus optimizing response rates, identify patients at risk for severe toxicity and allow for smaller, shorter clinical trials. In this talk you will hear a few examples of clinical trials with successful and unsuccessful use of biomarkers prior to Phase III design.

Cytel 11:10-11:35 Analyzing Software Solutions to Control and Facilitate Interim Analysis Data Access, Reporting, and Communications Between Sponsors and Data Monitoring CommitteesEric Silva, Enterprise & Hosted Solutions, Cytel Inc.• Review international regulatory requirements for DMCs
• Addressing increased responsibilities for sponsors of adaptive design trials
• Identifying methods for building firewalls to protect sensitive data
• Automating generation of supporting documentation for interim analysis and safety monitoring
• Using online systems to better secure clinical data and build regulatory trust


Aptiv Solutions11:35-11:50  A Software Tool to Evaluate the Impact of a Biomarker on the Cost and Complexity of an Oncology Trial

Philip Dehazya, Ph.D., Program Director, Oncology Business Unit, Aptiv SolutionsIncorporation of biomarkers into clinical trial design is a necessity in the development of new oncology drugs.  The impact of biomarkers on aspects of clinical trial planning (cost, sample size, patient accrual) can be modeled with appropriate software tools. This presentation will discuss a hypothetical oncology trial and present the results obtained when a biomarker is used to help select a patient population for treatment.

11:50 am-12:05 Sponsored Presentation (Opportunity Available) Contact Ilana Quigley at or 781-972-5457

12:05-1:30 Enjoy Lunch on Your Own

Adaptive Trial Designs for Personalized Therapy

1:30-1:35 Chairperson’s Opening Remarks

1:35-2:00 Adaptive Biomarker Trial Designs: I-SPY 2 and Beyond

Donald Berry, Ph.D., Professor and Head, Quantitative Sciences, MD Anderson Cancer Center

Modern approaches to clinical trial design use outcomes of patients in the trial to determine the trial’s course. One adaptation is learning about which types of patients benefit from which therapies, and shifting to emphasize those patients. Learning is possible about the way treatments interact with each other as well as with biomarkers. Prospective confirmation is essential. To enhance efficiency, early markers of therapeutic effect (longitudinal biomarkers, measurements of tumor burden, etc.) could be correlated with long-term clinical outcome. I will give an example (called I-SPY 2) of an adaptive biomarker-driven trial in neoadjuvant breast cancer. The goal is to efficiently identify biomarker signatures for a variety of treatments being considered simultaneously. 

2:00-2:25 ADAPT-IT—Adaptive Designs Accelerating Promising Trials into Treatments

William Barsan, M.D., Principal Investigator, NETT Clinical Coordinating Center, Neurologic Emergencies Treatment Trials Network

The ADAPT-IT project is designed to illustrate and explore how best to use adaptive clinical trial designs to improve the evaluation of drugs and medical devices and to use mixed methods to characterize and understand the beliefs, opinions, and concerns of key stakeholders during and after the development process. Since its inception in 2010, we have designed four confirmatory phase adaptive trials in the area of neurological emergencies. Three of these projects will be submitted for funding to be performed in the NINDS funded Neurological Emergencies Treatment Trials (NETT) network. We have also conducted a number of focus groups, surveys, and key stakeholder interviews from clinical trialists, biostatisticians, clinicians, FDA personnel and study section members about the acceptance, design and implementation of adaptive trial designs. 

2:25-2:50 Adaptive Clinical Trial Design in the Era of High-Density Data Analysis

Yu Shyr, Ph.D., Director, Vanderbilt Center for Quantitative Sciences; Ingram Distinguished Professor of Cancer Research; Associate Director, Vanderbilt-Ingram Cancer Center; Professor, Biostatistics, Biomedical Informatics, Cancer Biology and Preventive Medicine, Vanderbilt University School of Medicine

As high-density data (“-omics”) technologies and understanding of cancer biology continue to advance at a rapid pace, the cancer research community dedicates increasing resources to the translation of such advances to the development of personalized medicine approaches based on novel adaptive trial design. Personalized medicine requires knowledge of (1) differential tumor molecular profiles, based on targeted sequencing of known cancer-related genes or, increasingly, on biomarker discovery and validation through high-throughput assays, as well as understanding of (2) how such profiles correlate with responsiveness to particular treatment regimens, based on pre-clinical and clinical studies of approved or investigational agents, in cell lines or patients, stratified by molecular profile. In this talk, I will discuss the opportunities and challenges of the adaptive trial design associated with the development of such knowledge, from the laboratory bench to the bedside, with appropriate statistical and bioinformatic techniques guiding the interpretation of data at each step.

2:50-3:15 Adaptive Clinical Trial Designs with Pharmacogenomic Biomarkers for Targeted Therapies

Jens C. Eickhoff, Ph.D., Senior Scientist, Biostatistics and Medical Informatics, University of Wisconsin-Madison

Targeted therapies are becoming increasingly important for the treatment of various diseases. Pharmacogenomic biomarkers are a critical component in both the discovery and development of targeted therapy as they can be used to identify patients who are more likely to benefit from a treatment. New study designs and re-defining the traditional pathway may be required to accommodate emerging pharmacogenomic biomarker information into the drug development process of targeted therapies. Adaptive designs provide a particularly useful tool for incorporating biomarker information into a decision-making process. We describe the use and implementation of adaptive designs for the early efficacy evaluation of targeted therapies.

3:15-4:15 Refreshment Break in the Exhibit Hall with Poster Viewing

Integrating Genomics into Personalized Therapy Development 

4:15-4:20 Chairperson’s Opening Remarks

4:20-4:45 Genetic Signatures and Their Use for Personalized Therapy

Paola Sebastiani, Ph.D., Professor, Biostatistics, Boston University

Genome-wide association studies have shown that the genetic basis of many diseases is complex, and this complexity has raised questions about the utility of genetic data for personalized therapy. I will describe an approach that can help dissect the genetic basis of complex traits. The method builds genetic risk profiles with large numbers of genetic variants, and uses cluster analysis to group them into genetic signatures. By examining the association between genetic signatures and sub-phenotypes of a trait, the method can identify genetic signatures linked to specific response to treatment. I will show examples from genetic traits with different heritability.

4:45-5:10 Next-Generation Sequencing in Drug Discovery

Joseph D. Szustakowski, Ph.D., Senior Group Head, Translational Medicine, Biomarker Development, and Bioinformatics, Novartis Institutes for Biomedical Research

Next-generation sequencing technologies and applications have seen rapid uptake in all facets of drug discovery. The inclusion of NGS platforms in our experimental armamentarium is enabling a host of experiments that were previously not tractable. Several NGS case studies will be reviewed with an emphasis on understanding and predicting how NGS will impact our clinical biomarker efforts.

5:10-5:35 Personalized Medicine: An Update on 1,985 Patients with Advanced Cancer at MD Anderson Cancer Center

Apostolia-Maria Tsimberidou, M.D., Ph.D., Associate Professor, Investigational Cancer Therapeutics, University of Texas, MD Anderson Cancer Center

We hypothesized that in Phase I clinical trials, use of targeted agents matched with tumor molecular aberrations would improve treatment outcomes. A targeted therapy was considered to be “matched” to a patient if at least one drug in the regimen was known to inhibit the functional activity of at least one of the patient’s mutations. In a 5-year period, 50% of patients who underwent tumor molecular profiling had a molecular aberration. Rates of response, time to treatment failure, and survival were higher in patients treated with matched Phase I therapy compared to those of patients treated with non-matched Phase I therapy. In patients treated with matched Phase I therapy, time to treatment failure was longer than on prior systemic therapy. These results continue to support use of a personalized molecular approach for patients with cancer. Complete molecular profiling to understand resistance mechanisms and new targeted agents are needed.

5:35-6:00 GliomaPredict – Translation from Transcriptomic Subtypes to Patient Bed

Aiguo Li, Ph.D., Senior Bioinformatician, NOB, National Cancer Institute, National Institutes of Health

We developed GliomaPredict, a tool that allows the fast and reliable assignment of glioma patients into one of six previously stratified subtypes based on sets of extensively validated classifiers. Our tool utilizes a principle component analysis (PCA)-based approach to generate a visual representation of the analyses, quantifies the confidence of the underlying subtype assessment and presents results as a printable PDF file. The GliomaPredict tool is implemented as a plugin application for the GenePattern framework. GliomaPredict provides a user-friendly, clinically applicable novel platform for instantly assigning transcriptomic subtype in patients with gliomas thereby aiding in clinical trial design and therapeutic decision making.

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