Abstract
The evolution of AI has reached a point at which first commoditized analytical tools can be integrated into real-world workflows for assisting human practitioners in the health and life sciences sector by making better and faster decisions. Pharma is embracing this development by exploring the use of AI technology not only for increasing the efficiency and capabilities of drug discovery, design, and development but also for addressing new markets and adopting new business models in digital health. Since 2018 several big pharma enterprises have built substantial in-house capabilities in data science, AI/ML research and development, struck partnerships with big tech, EMR, cloud and analytics vendors, and expanded their data and AI footprint through acquisitions of innovative start- and scale-ups. We shed a light on market and technology drivers for these developments by explaining selected high-impact use cases of AI for the drug development cycle: discovery of new drug targets, custom-design of novel drug compounds, design and execution of more efficient clinical trials, as well as automation and optimization of drug manufacturing, distribution, and marketing channels. Transporting these applications into the digital health sector, we describe why and how pharma explores the use of AI, data, and cloud technology to bring new diagnostic, prognostic, personalized treatment, and prevention schemes for health, disease, and wellness management to patients and caregivers. Focus is given to the following topics: digital therapeutics, digital diagnostics and pathology, telehealth and virtual care, patient monitoring, and interoperable and securely linked electronic health data management platforms. Technology and market trends affecting the near and long-term future of the role of AI as driver of the digital transformation of pharma are provided accompanied by a comprehensive list of technical and strategic articles and market research analyses.
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