1. It’s a trust issue: discuss strategies for pharma and payer to achieve greater levels of partnership and decrease perceptions of data bias
2. Europe’s GDPR tremor: is a shift in US privacy regulation around the corner? Discuss the impact new EU regulations are already having and how they might alter the US system
3. Real-time patient insights: explore how to overcome issues with data quality and trust from the new era of digital devices
4. Predict outcomes: learn how to work with payers to model patient populations
5. Social media as a source of RWE: discuss how emerging technologies such as Natural Language Processing (NLP) are being used to find new patient insights
6. The use of RWE in clinical trials: debate how to best incorporate big data insights into the development process, keeping high data relevance and quality
7. Agree on outcomes: discuss experience and best practices on effective communication with payers and agreeing on desired outcomes
8. The pragmatic solution: explore different approaches to defining the right question for pragmatic studies
9. One standard to rule them all: learn about developments in data standardization techniques and discuss whether a standardized model is the best approach to harmonizing data silos
10. Put your house in order first: discuss difficulties and different approaches on how best to place internal RWE expertise for the most effective knowledge dissemination
11. Real-world patients: how can pharma engage with patients regarding ownership and data use?
12. Learning healthcare systems: harmonized HEOR - but how feasible are these systems and what’s a realistic timeframe for their development?

• Implementation of the 21st Century Cures Act
• FDA real-world demonstration projects – Exploring the future

• Essential briefing on how employers view the changing access landscape
• How do employers view value and where do they differ from payers?
• Can pharma contract directly with employers? Is this the next frontier for value-based contracting?

• Why early engagement makes increasing sense
• Tackle bias with transparent and collaborative models
• Walk through an example of mutual data sharing in oncology
• Set your third-party strategy: how to balance external party evidence generation against higher costs and complexity

• Understand the critical differences required in your approach to traditional payers relative to ACOs
• Examine ACO development priorities and opportunities for collaboration

• What lessons can we learn from failure of previous attempts at VBC?
• Case Study: How Aetna and Merck created their VBC for Januvia
• Create incentives to align partners and scale the adoption of VBC

• Collaboratively define VBC driven endpoints with payers and strategize the burden of evidence
• Integrate provider perspectives to drive VBC adoptions and support for evidence generation
• Set patient at the center of VBC strategy and generate a payer-patient value chain

• Understand the differences between ACO and traditional payer perspectives on VBC
• What additional support do you need to give to providers and ACOs in order to implement VBC?
• Hear from the provider: This is pharma’s do list to scale VBC

• Discuss recent FDA final guidance on use of Health Economic Information
• Update on the status of existing and new safe harbors impacting value based contracting
• Understand compliant use of dynamic data modeling and RWE when working with payers and providers 
• Best practices in contracting for use of digital health platforms and data when designing value based offers 

• Determine when to deploy co-pay programs to boost patient access
• How to boost wellness by supporting patients with outcome data
• Is VBC truly patient-centric?

• Where do VBC models need to adapt vs. traditional payer collaborations
• Can pharma form direct partnerships with health systems?
• Where do hospital systems require support to overcome data-driven difficulties?

Speakers TBA

• The story behind AstraZeneca's platform to enrol patients from >35 countries in a global study of diabetes treatment and outcomes
• Identification of the drivers of diabetes care across the world
• How to pull through best practices for multi-country real-world studies

• Build trust in RWE amongst regulators and payers by aligning data standards with competitors
• Work directly with IDNs and providers to fix gaps and align efforts towards a unified data capture strategy & breaking data silos
• Explore the industry actions required to reshape public perception of data sharing and ownership

• Address current gaps in real world data generation
• Find the right data for your study with automated data source mapping
• Create new cost efficiencies in data generation with the use of novel technologies

• How to map patient sub-populations to determine if your target population is sufficiently heterogeneous
• Assess benefit risk across in sub-populations to determine validity of RWE
• Shift from evidence to cost-effectiveness, and measure value across populations

• Inform phase 3 trial design by enabling clinical colleagues to define endpoints and inclusion criteria more accurately
• See how Lilly adapted traditional FDA submission standards to incorporate new levels of patient/population understanding from RWE sources

• How to create collaborative partnerships between R&D and HEOR
• Case study: extracting value from untapped data
• Repurpose data to discover payer endpoints in time for incorporation into Phase II trials

• Discuss the impact of blockchain on data ownership and the breaking down of data silos
• Explore use case examples of blockchain technology in patient registries and genomic matching
• Build industry trust in blockchain through the reputation systems: KYC – Know Your Customer, Collaborator, Clinician

• Your briefing on the essential NLP innovations to unlock hidden value in your data (Linguamatics)
• Create your vision to build internal capacity to accept new technology through training and partnerships
• How to take advantage of new capabilities to combine, use and extract data while staying compliant