Join and Learn from Pharma Leaders on How to Build and Execute a Comprehensive Pharma R&D Data Strategy
Bleeding edge or leading edge? That’s an important decision for senior pharma executives thinking about making major investments (time, resources, money) in upgrading R&D data capabilities and truly innovating their way to transformative success that is meaningful for patients.
This meeting will put you in the room with 80-100 senior pharma leaders from both the computational/data and R&D sides, so that you can:
Learn from other pharma to distinguish between bleeding and leading-edge technology.
Build and execute a scalable, sustainable and future-resistant R&D strategy.
Build a business case for meaningful change, alongside an executive team.
Understand how to value specific data sets, activity related to making data FAIR and associated technologies.
Get the latest on how pharma is incorporating machine learning/AI approaches into specific aspects of drug development.
Abel Archundia-Pineda, Global Head of IT, Bayer Pharma, Bayer
Martin Romacker, Principal Scientist, Roche
Peter Speyer, Global Head of Digital, Medical and Real World Data Solutions, NovartiS
Paul Agapow, Director, Health Informatics, AstraZeneca
Previous D4 Events
The first D4 event took place in Cambridge, MA in March 2019.
92% of attendees were senior-level e.g. C-level, Director, VP, Head, Senior, Principle.
85% of attendees are from pharma. The remaining were mostly academia (e.g. Stanford and Harvard) and FDA.
95% of attendees said they would strongly recommend this event to a colleague or someone in their wider network.
A sample of the companies who were represented at D4 USA:
DAY 1: Strategy
What’s required to fully embrace and drive data-driven decision making at executive level?
Top level strategies for implementing and improving data-driven approaches.
A critique of the existing data life cycle and a vision for the immediate and long-term future.
How to secure budget and executive support.
How to assess the true value of bio-data within pharma, and understanding what to do (and what not to do) about making data FAIR
DAY 2: Practical and Tactical
Pharma case studies focusing on effectiveness in discoverability, integration/interoperability, analysis and interpretation of bio-data.
A crash-course for AI in big pharma/large biotech leadership teams.
Understanding where pharma is on integrating machine learning approaches into R&D activities – specific case studies and activities – moving from ‘sexy’ to ‘applicable’.
Moving from the vision/concept, through initial integration to successful execution.
Leveraging genomics data in an integrative context.
Applying new data approaches to improve clinical success.
Conversations are intimate, open and with exactly the right people around the table.
The agenda moves beyond the sexy ‘what might be possible’ to ‘exactly how do I do it’
There is a focus on innovation, and helping pharma to make the difference between bleeding and leading edge.
The hype is stripped away and there is a focus on practical implementation and timing of investment.
This event focuses as much on cultural aspects such as the difficulties of managing change, managing upwards and winning the internal investment case.
It will help senior pharma leaders understand how to get the balance right between the scaled approach favoured by computational/data/IT leaders, and the bespoke approach favoured among R&D leaders.
The agenda for this meeting was carefully crafted from research conducted at 8 invite-only industry meetings involving 100+ senior-level business and scientific leaders from 60+ organisations.
The reports from those meetings are packed full of first-hand intelligence on the challenges, priorities and solutions for pharma/biotech and the wider precision medicine community.
To receive these reports, email Richard Lumb here.