Big Techs and startups in pharmaceutical R&D – A 2020 perspective on artificial intelligence. Issue 10 (October 2021)

• Record Type: Journal Article
• Authors: Schuhmacher, Alexander; Gatto, Alexander; Kuss, Michael; Gassmann, Oliver; Hinder, Markus
• Is Part Of: Drug discovery today. Volume 26:Issue 10(2021)
• Page Start: 2226
• Page End: 2231
• Publication Date: 2021-10
• Subjects: Artificial intelligence -- AI -- research and development (R&D) -- Pharma -- Big tech -- Startup -- Machine learning -- Deep learning; Drugs -- Design -- Periodicals; Drugs -- Research -- Periodicals; 615.1
• DOI: 10.1016/j.drudis.2021.04.028
• Languages: English
• ISSNs: 1359-6446

Abstract

Highlights: To understand the AI technologies that are used in pharmaceutical research and development (R&D), we analyzed 271 AI-related publications from the top 20 pharmaceutical companies (published 2014 to Q3 of 2019). To understand the AI activities of the Big Tech companies Alphabet, Amazon, Apple, IBM, and Microsoft in pharmaceutical R&D, we analyzed their scientific publications. To understand the competencies of 398 AI startups in pharmaceutical R&D, we investigated their (1) determination, as illustrated by information from corporate communication; (2) knowledge, as proven by scientific publications and/or patent applications; and (3) ability to execute with respect to AI, as documented by collaborations with pharmaceutical companies and Big Techs. Abstract : We investigated what kind of artificial intelligence (AI) technologies are utilized in pharmaceutical research and development (R&D) and which sources of AI-related competencies can be leveraged by pharmaceutical companies. First, we found that machine learning (ML) is the dominating AI technology currently used in pharmaceutical R&D. Second, both Big Techs and AI startups are competent knowledge bases for AI applications. Big Techs have long-lasting experience in the digital field and offer more general IT solutions to support pharmaceutical companies in cloud computing, health monitoring, diagnostics or clinical trial management, whereas startups can provide more specific AI services to address special issues in the drug-discovery space.