Gather Data, Evidence and Case Studies to Transform Data-Driven Drug Development
Pioneering Speakers Include
Lead Bioinformatician in Neuroscience and Principal Research Scientist
Director of Discovery Data Strategy, R&D
Global Chief Data Scientist
Director, Global Head of Integrated Data Science
Principal Scientist, pREDi, Data Information Architecture in Technical Solution Delivery, Roche Pharma Research and Early Development
Director, Health Informatics
Global Head of Digital, Medical and RWE Solutions
Global Head of Statistical Programming & Analysis
Senior Bioinformatics Data Scientist
Programme Lead, Merck Research Labs UK
Abel Archundia Pineda
Global Head of IT, BP
Chief Data Officer
Data, Evidence, Case Studies
Air-headed, conceptual talks that dominate other data events are banned. At D4, every talk is a data/evidence-driven case designed to provoke and expand the possibilities of your own research and development.
Pioneering Speaker Faculty
Hear from the most impressive pharma-focused speaker line-up ever assembled for an event on this topic, on a diverse array of subjects tackling THE critical problems in drug development.
Senior, Intimate Networking
This is a small, senior meeting with expansive networking sessions and time to connect with other attendees, initiate conversations and build lasting relationships among peers.
D4 has been designed to impact the bottom line, tackling crucial problems and prioritizing near-term solutions that will positively impact R&D efficiency and effectiveness in the short-term.
Built by Pharma, for Pharma
Talks and speakers have been carefully curated by a close-knit network representing every one of the top 25 pharma companies. Agenda sessions are the result of pain-staking research and prioritization.
Two Worlds Collide
D4 brings together biopharma technical/IT professionals (“enablers”) who build biodata capabilities with scientists (“doers”) who are using new data-driven systems to solve problems in drug development.
D4 Features Data/Evidence Driven Case Studies in the Following Areas:
Getting the Most Out of Biodata:
FAIR, achieving ROI and making the business-case for investment
Harnessing complex data sets
Applying AI/ML/ANN approaches
Automated knowledge management and building/leveraging knowledge graphs
Transforming data into knowledge
How to build a biopharma company from scratch in a new data-driven era
The Healthcare Data Ecosystem
Leveraging healthcare data from the many siloes that exist
Planning for the growing role of the patient.
Predicting patient response using machine learning techniques
Market access and convincing payors
Driving new insights and treatments for cancer
Target Discovery and Validation
Omics data-driven target discovery
Leveraging genetic-driven insights
The role of AI/ML in target ID
Enhancing Drug Discovery and Development
How to ‘surf on the data lake’
Data flows, FAIRness and integration in the context of drug discovery
Enhancing the progression from compounds into hits/leads
Using advanced analytics and AI
Re-thinking drug design via AI
Phenotypic approaches to accelerate discovery
Filling Gaps in Translational Research
Interpretation of Real-World Data
Data-driven problem solving
Using Artificial Neural Networks to gain clinically actionable insights