Preliminary Agenda


Pre-Conference Summit - June 19, 2018


7:30 AM – 8:30 AM

Workshop Registration and Morning Coffee

Pre-Conference Summit- Building a COE 101


8:30 AM – 12:00 PM

WORKSHOP: How to Build a Center of Excellence 101

Centers of excellence (COE) are created for two main reasons: to help manage workload and to support problem solving leading to improved commercial quality. A real world data center of excellence serves both project management and innovation interests among various therapeutic areas within an organization. To bridge these functions and effectively meet the needs of all stakeholders a model where interests are connected to the CoE can achieve the organizations goals. As real world evidence becomes more applicable for both clinical and commercial projects, respective teams have the opportunity to efficiently partner on joint-data projects in order to share information and resources. Within this workshop discuss how to build a long term CoE model to solve short term problems.

  • Discuss the necessary building blocks that must be in place to successfully build a center of excellence
  • Recruit, train & develop a high performing sustainable CoE team to achieve your business goals
  • Partner with the right third party to provide your CoE Function with the infrastructure & tools to thrive
  • Build a CoE with a limited budget: navigating internal hurdles
12:00 PM - 1:00 PM

Lunch for Pre-Conference Attendees


Day One - June 19, 2018


12:00 PM – 1:00 PM

Summit Registration and Morning Coffee

1:00 PM – 1:15 PM

Chairperson’s Welcome and Opening Remarks

Shared Plenary Sessions


1:15 PM - 1:45 PM

FDA Guidance on Real World Data Regulatory Decision Making Post Passage of 21st Century Cures Act

A major area of focus for the FDA the past few years has been to expand the use of real world data. With the regulatory landscape evolving to allow for increased use of real world data, the life science industry must be informed on specific guidelines, benchmarks and intent of new policies in order to appropriately develop new products.

  • Learn how the FDA is implementing the 21st Century Cures Act requirements into the regulatory framework
  • Analyze both policies and their impacts on clinical, commercial and medical use of real world data as well as opportunities for new drug development
  • Discuss the regulatory hurdles to increase the use of real world data sources
1:45 PM - 2:30 PM

KEYNOTE PANEL DISCUSSION: Optimize Business Insights and Enhance R&D Through Real World Data and Advanced Analytics

As actionable insights and opportunities for both clinical and commercial uses are gathered from the expanded access to, and acceptance of real world data, so is the presence of challenges in data quality and threats of patient privacy hacks. The life science industry must find a balance in capitalizing on the utilization of real world data.

  • Gain insight from a leadership perspective on how expanded real world data capabilities have altered biopharmaceutical development and commercialization
  • Understand how RWE is being used to meet the Post Marketing Study (PMS) commitment for FDA
  • Learn how RWE is used throughout the life cycle of a molecule starting from first human dose
  • Learn how to perform data oversight and quality control when acquiring and accessing data from third-party vendors
2:30 PM - 3:15 PM

PANEL DISCUSSION: Artificial Intelligence: Pharma’s Path to Adopting AI and Other Emerging Technologies

Emerging technologies are dominating the conversation across the pharmaceutical industry. Artificial intelligence and machine learning have pushed many industries toward a highly powerful state. Many pharmaceutical companies are beginning projects involving some elements of AI and ML. AI has the potential to increase research productivity exponentially. Through this panel discussion learn how the industry is moving from aspiration to adoption of using these technologies.

  • Explore where machine learning and artificial intelligence will help in the product development process
  • Utilize the digital transformation to drive performance and connect data
3:15 PM - 3:45 PM

Afternoon Refreshments Break

Centers of Excellence Track Case Study Segment


3:45 PM - 4:30 PM

CASE STUDY: Building a Centralized Big Data CoE to be the Bedrock for Establishing a Data Driven Company

While adoption of analytics is still at a nascent stage in the pharmaceutical industry, leading organizations are anticipating (if they have not already) taking a step ahead of their competitors with the implementation of data analytics into their management systems. Hear first-hand from an organization that has built and sustained a successful CoE. This session will shed light on the lessons learnt, best practices and common pitfalls, when building & managing a CoE. A few of the common misconceptions on longevity of the CoE function will be addressed.

4:30 PM - 5:15 PM

Digital Innovation & Data Analytics in Consumer & Patient Care

While Machine Learning and Artificial Intelligence have been around for some time, in Healthcare, what do recent advances like Driverless Car technology, Sensors, and Deep Learning and Analytics today mean for the experiences of Consumers and Patients tomorrow? And, what role can Real World Evidence and Social Data play in advancing the experiences of others even further? We will seek to explore these questions and conclude with answers than may help drive our Industries and Businesses.

5:15 PM - 6:15 PM

Cocktail and Networking Reception


Day Two - June 20, 2018


8:30 AM - 8:45 AM

Morning Coffee

8:45 AM -9:00 AM

Chairperson’s Welcome and Review of Day One

9:00 AM - 9:45 AM

Future of COE/RWE Panel: Where is the industry going?

Over the past several years new real world evidence analytic platforms have emerged. Real world evidence is essential at every stage of a product lifecycle from understanding a products value to gaining market access. As the need for real world evidence increases, RWE organizations with strong capabilities will have significant competitive advantage over their peers. This session will shed light on:

  • Uses of electronic health records and databases containing other health-related data (claims, pharmacy) can support observational studies and pragmatic clinical trials, both of which can be important sources of real-world evidence now and in the future
  • Creating richer, more robust datasets in the future than any one source alone can yield. Combining data from different sources is currently a labor-intensive process due to challenges with data standardization and interoperability.
  • Patients and consumers have a significant role to play in the collection of real-world data and generation of real-world evidence, but to be effective, patient and consumer engagement approaches would include considering them partners and capturing outcomes that are important to them.
9:45 AM - 10:30 AM

Case study: Generating RWD through a Learning Health System

RWD are typically obtained from existing data sources, such as administrative claims or EMRs, or from observational studies. Existing data sources may not systematically capture important outcomes whereas observational studies are limited by resource requirements and low participation. Innovative solutions are needed to capture RWD from patients within the healthcare setting. A “Learning Health System” (LHS), as advocated by the Institute of Medicine, captures outcomes from routine care. We will describe a collaborative network of 10 healthcare institutions in the US and EU, designed as an LHS that is focused on Multiple Sclerosis (MS). During routine care, patients use an iPad-based assessment tool, called the Multiple Sclerosis Performance Test (MSPT), to complete a standardized MS history; the Neuro-QoL instrument, and electronic adaptations of the Multiple Sclerosis Functional Composite (MSFC), a validated measure of neuro-performance in MS. Over 11,000 MS patients have agreed to participate. In this session, we will discuss:

  • Practical details of implementing an LHS as a collaborative network
  • The benefits and drawbacks of generating RWD via an LHS compared with existing data sources or clinical research studies
  • Initial analytic results with regard to patient characteristics, validation studies and benchmark analyses
10:30 AM - 11:00 AM

Networking and Refreshment Break

11:00 AM - 11:45 AM

Metrics and Measurements to Quantify Value- Convey a Clear Value Proposition by Setting Clear-Cut Benchmarks

The time has come to put metrics and measurements in place that allow pharma companies to align their strategies around the push for greater profitability putting them on the right track for growth. Senior management across the industry have looked to the traditional metrics, which are no longer sufficient to ensure a profitable brand. It is important to set in place the right benchmarks, metrics and measurements to set your center of excellence up for success.

  • Discuss the most effective parameters to judge the success and value a CoE brings to an organization
  • Define common set of best practices and work standards to be followed, and provide direct guidance and support to assist plans in implementing these standards
  • Set clear priorities and goals in place to better assess success
11:45 AM - 12:30 PM

Closing Keynote
CASE STUDY: CancerLinQ and FDA Collaboration on Real World Impacts of Precision Medicine Therapies

This year, ASCO and the FDA entered into a partnership to examine the real-world use of newly-approved cancer treatments. CancerLinQ, ASCO’s big data initiative, will harness analytics to help inform regulatory decision-making.

  • Learn about the methodology used to collect data and well as understanding the information flow from patient to platform to regulatory bodies
  • Explore the goals of the collaboration, as well as breakthroughs in data leveraging, patient reported outcomes, real world evidence, and development of checkpoint inhibitors
  • Discuss how insights gained through data leveraging will further impact both drug development and regulatory decision-making
12:30 PM

Close of Summit