With the cost of developing a drug doubling every 9 years, the pharma business model will soon become largely unsustainable. Yet we are in the middle of a data revolution. The availability and analysis of biodata to improve drug R&D represents the biggest opportunity for pharma to arrest the slide in productivity, cut costs, increase ROI and deliver for (and reconnect with) patients.
But how do you use data to drive efficiencies and optimize ROI in drug discovery and development?
We’ve worked with contributors from Pfizer, GSK, AstraZeneca, Roche, Biogen, Novartis, Regeneron and Lantern Pharma to bring you this definitive guide for pharma to optimize the impact of data-driven approaches in R&D, and on the bottom line. It provides unique insights to help pharma companies stay ahead of the curve.
This report is for both scientific and technical people within biopharma companies – those building data capabilities and infrastructure, and those using new tools and applications to enhance drug discovery and development.
This report will help you to:
- Optimise your data lifecycle to support R&D.
- Make a strong business case for investing in data and supporting infrastructure/tools.
- Explore new applications using actual case studies and real data.
- Generate better ROI with AI/ML.
- Understand how to cleanse data and optimize the principles of FAIR for the best outcome.
- Better resource data scientists within pharma companies.
- Integrate multi-omic data more effectively.
- Use data to reduce costs and increase success rates in clinical trials.
A big thank you to our contributors:
- Pankaj Agarwal, Senior Fellow, Computational Biology, Functional Genomics, GSK
- Peter Henstock, Senior Data Scientist, Pfizer
- Kristin Haraldsdottir, Clinical & Research Collaborations Manager, Lantern Pharma
- Bino John, Associate Director, AstraZeneca
- Charles Paulding, Director of Pharmacogenomics, Regeneron
- Michelle Penny, Director, Computational Biology and Genomics, Biogen
- Tom Plasterer, Director of Bioinformatics, Data Science & AI, Biopharmaceuticals R&D, AstraZeneca
- Martin Romacker, Principle Scientist Data and Information Architect, Pharma Early Development Informatics, Scientific Solution Engineering and Architecture, Roche Innovation Center Basel
- Nuray Yurt, Data Science Lead for US Oncology, Novartis