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Final Agenda

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7:00 am Registration and Morning Coffee

Plenary Keynote Session: Rethinking the Clinical Trial Paradigm 

8:00 Organizer’s Welcome and Chairperson’s Remarks

Lee Yuan, Associate Conference Producer, Cambridge Healthtech Institute

Katherine Vandebelt, Senior Director, Clinical Development Innovation, Eli Lilly and Company

8:10 Transforming Clinical Trials with Big Data and New Technology

BarbaraTardiffBarbara Tardiff, M.D., Vice President, Development Operations; Global Head, Clinical Innovation and Informatics, Worldwide Research & Development, Pfizer

Personalized Medicine is based on digital data and Precision Medicine is enabled by big data. Advances in technology along with new data sources and channels are changing the drug development paradigm, and collaborations between non-traditional partners will drive further innovations. We must learn to manage and be successful at understanding new types of data and evidence, in order to realize the power of new types of data and evidence.

8:40 Opening up Clinical Study Design to the Long Tail

TomaszSablinskiTomasz Sablinski, M.D., Ph.D., Founder and CEO, Transparency Life Sciences

Clinical research is in a crisis of existential proportions. Failure rates are unchanged from, or worse than, in prior decades while costs have skyrocketed. We are implementing, a systemic solution to this problem in the form of a new kind of drug development company, Transparency Life Sciences LLC (TLS). Using the TLS approach, the design of a clinical trial is crowdsourced via our transparent web-based Protocol Builder®, which invites participation of a broad range of researchers, patients, health care providers, etc. Clinical studies are conducted in a patientfriendly manner, with collection of data largely managed remotely with the use of digital technology through video visits, and/or telemonitoring devices.

9:10 Leveraging Data from One of the Largest Pharmacy Chains in the World in Order to Achieve Efficient, Cost-Effective Patient Recruitment for Clinical Research

HowardGolubHoward L. Golub M.D., Ph.D., Vice President, Clinical Research, Walgreen Company

The creation of Walgreens Boots Alliance (a recent merger between Walgreen Co., and Alliance Boots Ltd.) establishes the first global pharmacy-led health and wellbeing enterprise. Together, Walgreens Boots Alliance spans more than 25 countries, with over 12,800 stores. In addition, there are primary-care clinics located in over 425 U.S. stores that can be used for subject study visits. In the U.S. alone, 40M people visit our 8200 stores a week. The prescription database contains over 70M active customers at any one time. In addition, Walgreens U.S. has one of the largest specialty drug support services in the country. Use of our customer data uniquely facilitates the contacting of potential study patients in order to determine if they would like to opt-in for any of the studies which we are currently recruiting.

9:40 Coffee Break with Exhibit Viewing

10:30 PANEL DISCUSSION: Rethinking the Clinical Trial Paradigm: What is on the Horizon for Clinical Trials?

Moderator: Katherine Vandebelt, Senior Director, Clinical Development Innovation, Eli Lilly and Company
Barbara Tardiff, MD, Vice President, Development Operations; Global Head, Clinical Innovation and Informatics, Worldwide Research & Development, Pfizer
Howard L. Golub M.D., Ph.D., Vice President, Clinical Research, Walgreen Company
Tomasz Sablinski, Founder and CEO, Transparency Life Sciences

A Look at What’s Next for Clinical Trials 

11:00 Mining Big Data for Translational & Clinical Insights

Anastasia-ChristiansonAnastasia Christianson, Head, Translational R&D IT, Bristol-Myers Squibb

The emergence of new technologies and continued exponential growth of data and information generated daily in the clinic and in laboratories have led to a surge in translational research opportunities for new clinical insights and treatment paradigms. Pharma, Biotech, academic and medical research centers are all facing the arduous task of finding and mining overwhelming quantities of efficacy, safety, biomarker, and outcomes data accumulated from decades of preclinical studies and clinical trials. Despite years of focusing on information management and integration strategies, we still have less than optimal technical solutions for mining our data. Our current strategy is to utilize expert data, information science, and analytics skills, alongside scientific, medical, and technical experts to work together as a team in defining questions, finding relevant data, analyzing, and interpreting results into sustainable short term and long term solutions. Examples of how this approach is enabling translational research will be presented, as will opportunities for cross-functional and cross-organizational collaboration.

11:30 The Greatest Threats Opportunities to the Clinical Trial Industry: A Look at What’s Next

Leonard-DAvolioLeonard D'Avolio, Director, Informatics, Ariadne Labs; Assistant Professor, Harvard Medical School

A perfect storm of change is washing over the pharmaceutical industry thanks to payment reform, low-cost high-throughput sequencing, and an explosion of digital healthcare data. Combine enormously expensive trials with high failure rates and rampant under-enrollment, and it becomes clear that change is coming. While some are battening down the hatches, the real winners will be those that refuse to let a crisis go to waste. We’ll explore who are those opportunists, what are they doing, and what does it mean for the clinical trial industry.

12:00 pm Session Break

Content Analyst Company Logo12:10 Luncheon Presentation: Diving Down the Wormhole of Unstructured Clinical Trial Data: Going from “How” and “Why” to “Eureka!” in 60 Seconds

Melissa Chapman, Principal, The Riverhead Group

John Felahi, Chief Strategy Officer, Content Analyst Company

Understanding, analyzing and visualizing critical relationships across massive amounts of unstructured proteomic and metabolite data, gene pathway data, mechanisms of action and adverse event data can be key to driving your development pipeline with reduced risk and lower costs. But navigating these large repositories of unstructured content can be a nightmare. Learn how recent advancements in web-based machine learning technology now make it possible to discover breakthrough insights buried within vast, disparate collections of unstructured content at speeds never possible before.

12:55 Session Break

Focused Breakout Session: Tech Innovation in Clinical Trials: New Tools and Analytics to Advance Clinical Research

Leveraging Technology to Bring Patient Centricity to Clinical Trials 

1:40 Chairperson’s Remarks

Devin Trejo, Director, Oncology Feasibility Lead, Development Operations, Pfizer

1:45 Clinical Trials: Responsive and Considerate Care for Patients 

Katherin-VandebeltKatherine Vandebelt, Senior Director, Clinical Development Innovation, Eli Lilly and Company

Imagine being diagnosed with a new illness or chronic condition after a lifetime of perfect health...would you feel embarrassed? What if existing treatments failed to help you effectively treat your illness…would you feel vulnerable? What if your condition prevented you from doing what you wanted to do, from living life to the fullest?...would you be frustrated, even angry? Now, imagine consulting with your doctor to determine a clinical trial to be your best course of treatment…could you imagine that? Lilly Clinical Innovation believes that you should. Join us to learn more about our vision for making responsive and considerate clinical research a reality for vulnerable and embarrassed patients - like all of us - who need them.

2:15 Bringing Science to Patient Centricity

Sally-OkunSally Okun, RN, MMHS, Vice President, Advocacy, Policy & Patient Safety, PatientsLikeMe 

Patient engagement in research has been increasing in recent years, enabled in part by attention to patient-focused drug development, online patient communities and rapidly emerging technologies. Patients are no longer just subjects in trials but partners in all phases of the process. This session explores insights from PatientsLikeMe about patient preferences, motivations, barriers, and concerns for participation in clinical trials. The resulting data can be used to inform clinical development program decisions most consistent with patient perspectives and study objectives.

Waife2:45 Before and After the Honeymoon: The Criticality of Process Implementation Design to the Success of Innovation

Waife_RonaldRonald S. Waife, MS, President and Founder, Waife & Associates, Inc.

Innovation in Clinical Informatics is dependent on many factors coming together successfully, and the technical component is only one of them. Besides vision, creativity, energy and timing, successful execution of Informatics innovation in clinical research requires understanding the existing and desired operational context of new technologies, even if the goal is to disrupt it. Barriers to clinical research innovation are not necessarily typical to those in other industries. In our experience innovation fails because of the gap between ideas and execution – not execution of the technical solution but execution by the intended users for the intended advantage. This presentation covers common unanticipated barriers and how to overcome them.

3:15 Refreshment Break with Exhibit Viewing


Innovating Existing Clinical Trial Processes and Systems via New Tech Approaches 

3:50 Re-Use of Electronic Health Records: The IMI EHR4CR Project

Johann-ProveJohann Proeve, Ph.D., Global Strategy and Development Advisor, Bayer Healthcare, Leverkusen, Germany

The EHR4CR (electronic health records for clinical research) as part of the Innovative Medicines Initiative in Europe looks into the re-use of electronic health records for protocol feasibility, patient recruitment and eventually study conduct. A consortium of 10 university clinics across Europe, 11 pharma companies and several small businesses worked together for the past 4 years to a.) improve clinical trial protocol design by accessing the electronic health records b.) support study investigators in identifying suitable patients and c.) identify the most common data items used in clinical trials and check those vs the data available in the electronic health records of the participating hospitals. The presentation will provide an insight into the challenges, the accomplishments and the next steps of this 5 year program.

4:20 Case Study: Merging EDC and CTMS without a Traditional Data Warehouse 

Kesha Rodgers, Associate Director, Clinical Systems, BioMarin

When conducting and managing trials, the information in EDC systems and the operational data in CTMS are critical to making fast, accurate decisions. Blending the data, though, is typically either highly manual or requires expensive data warehouse solutions. This talk follows BioMarin’s experience finding alternative ways to merge CTMS and EDC data for reporting purposes.

4:50 Maximizing Utilization of Claims/EHR during Clinical Development

Devin Trejo, Director, Oncology Feasibility Lead, Development Operations, Pfizer

Opportunity exists to maximize the use of real-world patient data in order to incorporate into the clinical development process. Valuable insight can be gained by application of these data sets in order to realize cost and time savings while conducting quality clinical research. Successful utilization of these data sets have been used to optimize protocol design, minimize downstream amendments, improve the site identification process and enhance patient recruitment. This presentation will highlight case studies and discuss novel combinations of unique data sets in order to apply fact-based data to improve predictability, reduce time to reach clinical endpoints and target the correct patient population.

Focused Breakout Session: Big Data for Clinical Trials: Harnessing & Unlocking the Potential of Existing Data Sources 

Establishing & Using a Big Data Strategy for Clinical Trial Insights 

1:40 Chairperson’s Remarks

Anastasia Christianson, Head, Translational R&D IT, Bristol-Myers Squibb

1:45 Clinical Research Continuum: Big Data FOR and FROM Clinical Trials

Alex-ShermanAlexander Sherman, Director, Strategic Development and Systems, Neurological Clinical Research Institute at MGH, Massachusetts General Hospital

In the world of Big Data in clinical research, there are bidirectional flows of information: data from clinical trials may be aggregated and analyzed to better our understanding of the disease, while information from the “bedside” combined with data from clinical research helps companies to make better decisions on disease progression models, outcomes selection, eligibility criteria tuning and patient recruitment. In rare diseases such information may bring us to personalized intervention tracking, with so-called “virtual lead-in” modeling.

2:15 Considerations in Building a Data Hub to Support Clinical Trial Development

Francis-KendallFrancis Kendall, Global Head, Statistical Programming and Analysis, Roche

This talk will give an overview of how Roche is developing a Process and Systems framework to store and manage Clinical Trial Data and Real World data and how the Biometrics organization is changing to maximize the potential of these data sources. Part of the talk will focus on the Data Hub Team who are the curators of the data and how this team was formed and its current remit. The final part of the talk will look at several ways we intend to use the Data Hub to support our Portfolio.

Tamr2:45 Talk Title to be Announced
Ted Snyder, Senior Solution Architect, Tamr, Inc. 

3:15 Refreshment Break with Exhibit Viewing

3:50 Clinical Trial Planning: Strategy, CER and Real World Patients

Michael Liebman, Managing Director & Co-Founder, IPQ Analytics LLC

Clinical trials are considered the gatekeeper for attaining regulatory approval for therapeutics and diagnostics, but the actual goal of commercial success (and improved patient outcomes) may not be adequately addressed because of the gap between clinical trials and real world patients and medicine. Examples of how to objectively evaluate the gaps to provide decision support early in the process will be presented in several disease areas.

4:20 Deriving Insight and Value from Clinical Data Using Large-Scale Analytics

Nirmal-KeshavaNirmal Keshava, Ph.D., Senior Principal Informatics Scientist, Research & Development Information, AstraZeneca PLC

Clinical data, whether derived from EHRs or actual clinical trials, provides a valuable resource to analyze the outcomes and efficacy of clinical treatments and therapeutic interventions. Classification and prediction algorithms can benefit from novel representations of large populations of clinical data. In this talk we address the challenge of deriving value from clinical data using analytics that can benefit many parts of the drug development process. The ability to scale analyses to increasingly large populations will also be discussed.

4:50 Using Watson to Improve Clinical Trials: A Mayo Clinic-IBM Initiative

Nick-LaRussoNicholas LaRusso, M.D., Director, Center for Innovation, Mayo Clinic

Combining the functionality of IBM Watson and leveraging the expertise of Mayo clinicians, the Watson Clinical Trials Matching solution uses natural language processing, machine learning and probabilistic computing to compare individual patient attributes to complex eligibility criteria for multiple clinical trials. Supporting clinician decisions at the point of care, it quickly provides a list of trials that are mostly likely matched to the patient’s needs and an analysis of how well the patient matches the criteria for those trials. Initial experience with three cancers has been positive.


5:20 Welcome Reception with Exhibit Viewing

6:20 End of Day

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7:30 am Morning Coffee

Case Studies: Using Existing Data Sources for Advancing Clinical Trials 

8:00 Chairperson’s Remarks

Catherine Marshall, Director, Information Strategy & Analytics, Clinical Informatics and Innovations, Pfizer

8:05 Banking Biospecimens for Exploratory Research

Catherine-MarshallCatherine Marshall, Director, Information Strategy & Analytics, Clinical Informatics and Innovations, Pfizer

Many pharmaceutical companies have established processes for collecting, banking, and using clinical trial biospecimens consented for research purposes. Until recently, the decision to collect these specimens has generally been made at the level of the individual clinical teams. As the value of biospecimen-derived research data is increasingly realized, it is important to take a more proactive and strategic approach to routinely collecting and banking of biospecimens from our clinical trials. This talk highlights the strategic imperative as well as some examples of key research needs as well as the key challenges we face around cost, patient consent, as well as linkage back to clinical phenotypic data will also be explored.

8:35 ImmPort: Open-Access Individual-Level Clinical Trials Data-Sharing, Dissemination and Meta-Trial Analyses 

Sanchita-BhattacharyaSanchita Bhattacharya, Scientific Project Lead, ImmPort; Senior Bioinformatics Research Specialist, Division of Systems Medicine, Stanford University School of Medicine

Broad public access to individual-level clinical trials data is on the rise. In this presentation, we will discuss the reasons and various ways of effective data sharing including issues surrounding it. Few case studies on data re-use, reproducibility and cross-trial meta-analyses for gaining insight to the multiple clinical studies will be presented.

9:05 Open Source National Network Facilitating Healthcare and Resource Data Sharing

Doug Macfadden, Chief Informatics Officer, Harvard Catalyst

Bhanu Bahl, Director of Informatics, Harvard Catalyst

In the era of personalized medicine there is an ever increasing need to match patients with clinical trials specific to their indications. In the absence of a common way to describe, organize and query the data, the information is silo-ed and fractured across healthcare providers and hospitals. Recognizing this gap, Accrual to Clinical trials (ACT) project supported by NCATS was launched with the goal of creating a network of 60 Clinical Translational Science Center Award (CTSA) sites. The network will facilitate investigators to query EHR data across all these sites for cohort exploration and subsequently engage and enroll identified patients into clinical trials. SHRINE (Shared Health Research Information Network) is a system developed by Harvard Catalyst for enabling clinical researchers to query across distributed hospital electronic medical record systems. SHRINE is built on top of i2b2 a widely used and robust platform for clinical research. In the immediate future for the ACT project the plan is to scale SHRINE functionality to establish a national network of CTSA sites, to facilitate more sophisticated querying and allow users to trigger detailed review of potential trial subjects at each site. Biomedical researchers spend lot of time and money finding necessary resources for their research. There is a need for a common way to describe and publish resource information which will allow search of all published resources. Some of the resources maybe created by small-labs in remote locations and thus hidden from the research community. The goal of eagle-i project is to make all aspects of research resources as transparent as possible, putting all information into the public domain and enabling scientists to easily find and obtain resources from the groups that make them. Launched as a consortium of 9 universities in 2010 funded by NIH grant, today eagle-i network spans 40 sites nationwide and publishes resources for reagents, antibodies, bio-specimens, stem cell lines, mice etc.

9:35 Coffee Break with Exhibit Viewing

Cross-Industry Data Sharing to Advance Clinical Trials & Data Privacy Issues 

10:30 Co-Presentation: De-Mystifying Data De-Identification (the Why and the How)

Muzafar Mirza, Director, Information Strategy and Analytics, Clinical Informatics and Innovation, Pfizer, Inc.
Stuart Pearce, Director, Information Strategy and Analytics, Development Operations, Worldwide Research & Development, Pfizer, Inc.

With the increased value of sharing clinical data for secondary discovery and novel analyses the question of informed consent and patient privacy is being debated and discussed at length. There are different schools of thought as to whether data should be de-identified, and when and also if this practice should be used for certain data applications. This talk seeks to de-mystify some of the confusion, offer up some suggestions as well as provoke discussion about the issue.

11:30 The Yale Open Data Access (YODA) Project -- An Academic-Industry Partnership towards Data Transparency

Nihar Desai, M.D., MPH, Assistant Professor of Medicine, Cardiology, Yale School of Medicine

The talk will offer an overview of the push for data transparency broadly as well as the Yale Open Data Access Project specifically, which is an academic-industry partnership aimed at improving access to clinical trial data. The presentation will review results of the initial collaboration with Medtronic, Inc. as well as the recent announcements of partnerships with Johnson & Johnson/Janssen.

12:00pm Close of Conference

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