Artificial intelligence in human genomics and biomedicine

Reinhard Heil,Harald König,Nils B Heyen,Bärbel Hüsing,Ulrich Schmoch,Daniel Bachlechner,Martina Baumann

doi:10.14512/tatup.30.3.30

Abstract

The increasing availability of extensive and complex data has made human genomics and its applications in (bio)medicine an at tractive domain for artificial intelligence (AI) in the form of advanced machine learning (ML) methods. These methods are linked not only to the hope of improving diagnosis and drug development. Rather, they may also advance key issues in biomedicine, e. g. understanding how individual differences in the human genome may cause specific traits or diseases. We analyze the increasing convergence of AI and genomics, the emergence of a corresponding innovation system, and how these associative AI methods relate to the need for causal knowledge in biomedical research and development (R&D) and in medical practice. Finally, we look at the opportunities and challenges for clinical practice and the implications for governance issues arising from this convergence.

Highlights

The increasing availability of extensive and complex data has made human genomics and its application areas inmedicine an attractive domain for artificial intelligence (AI) in the form of advanced machine learning (ML) methods (Wainberg et al 2018)
We analyze the increasing convergence of AI and genom ics, the emergence of a corresponding innovation system, and how these associative AI methods relate to the need for causal knowledge in biomedical research and development (R&D) and in medical prac tice
Martina Baumann, Bärbel Hüsing, Daniel Bachlechner, Ulrich Schmoch, Harald König human genomics and biomedicine is associated with the hope of obtaining answers to a key question in these domains, namely how individual differences or mutations in the genome cause specific traits or diseases

Summary

Introduction

The increasing availability of extensive and complex data has made human genomics and its application areas in (bio)medicine an attractive domain for artificial intelligence (AI) in the form of advanced machine learning (ML) methods (Wainberg et al 2018). The focus of interest is on sequence data of the human genome as well as on data of genes that are read (transcribed) or proteins that are produced in various body cells and organs. Human genomics and biomedicine is associated with the hope of obtaining answers to a key question in these domains, namely how individual differences or mutations in the genome cause specific traits or diseases. This would allow predictions about functional consequences of genetic differences, diagnoses, prognoses about therapy options or the development of new drugs at an unprecedented pace and scope

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