Achieving excellence with R&D data will enable the life sciences industry to increase the speed and quality of innovation and is thus a major source of competitive advantage. Whether researchers and informaticians deal with “big data,” “deep data” or just put their data to smarter use, it is clear that the future of R&D is dependent on both smart technologies and clever researchers. The rapid progress of innovation in software and powerful hardware now allows human researchers to interpret masses of raw data in unique ways and is redefining the R&D business model. The benefits range from discovery and “omics” research, through to clinical trials and to real patients in the real-world. However, it is major technical, financial, and operational challenge is to turn “messy” data into structured data, that can be used for advanced analytics that can spot opportunities and achieve true insights. Some of the most promising areas of technological innovation making rapid progress include, for example, artificial intelligence, machine learning, cloud computing and the blockchain (distributed ledgers). There is also huge potential for efficient collaborations between the life science industry, technology companies, academic researchers, health systems, physicians, and health insurers to remove data silos. A deeper convergence between key stakeholders and advanced technologies will facilitate the discovery and development of powerful therapies, devices and advanced diagnostics to benefit patients.
The “R&D Data Intel Leaders Forum” is the must attend event for those senior decision-makers, researchers, data scientists and technologists, looking to make the shift towards an integrated R&D and data strategy and for those looking to improve their implementation of data-driven approaches to enhance R&D specific decision-making and intelligence.
Who will Benefit:
Senior R&D executives: Scientific Officers, Chief Information Officers, Chief Technology Officers, Knowledge & Data Management (Discovery, Clinical & Real-World Data), R&D Analytics, Informatics, R&D Innovation, External Alliances & Innovation, R&D Strategy.
Drug Discovery: Drug Discovery, R&D, Lead Identification & Target Validation, Screening, Translational R&D, Genomics & Proteomics, Biomarker R&D, Senior Scientist, Biostatistics, Biometric, Precision Medicine, Personalised Medicine, Computational Biology
External Innovation: Business Development, Strategic Collaborations, Alliances, External Innovation, Consortia, Partnerships
R&D Analytics & AI: Data Analyst, Data Scientist, Bioinformatician, Bioinformatics, CIO, AI, Machine Learning