Blog

Aug 26, 2023

The company landscape for artificial intelligence in large

McKinsey & Company, London, UK. You can also search for this author in PubMed Google Scholar McKinsey & Company, Lyon, France. You can also search for this author in PubMed Google Scholar McKinsey &

McKinsey & Company, London, UK.

You can also search for this author in PubMed Google Scholar

McKinsey & Company, Lyon, France.

You can also search for this author in PubMed Google Scholar

McKinsey & Company, Zürich, Switzerland.

You can also search for this author in PubMed Google Scholar

McKinsey & Company, London, UK.

You can also search for this author in PubMed Google Scholar

McKinsey & Company, London, UK.

You can also search for this author in PubMed Google Scholar

McKinsey & Company, London, UK.

You can also search for this author in PubMed Google Scholar

Artificial intelligence (AI) techniques such as machine learning are transforming drug research and development (R&D), enabled by ever-increasing amounts of data and computational power. Historically, small molecules have been at the forefront of AI applications in drug discovery, including modelling small-molecule–target interactions, lead candidate optimization and safety prediction. However, AI tools are increasingly being applied to large-molecule modalities, including antibodies, gene therapies and RNA-based therapies. Such therapies represent an important share of the biopharma industry’s current portfolio — around 40% of new molecules approved in 2022 — and of its future commercial potential. For example, in oncology, large molecules are forecast to represent ~50% of the market by revenue in 2030, of which more than 80% is expected to be derived from antibodies.

Access Nature and 54 other Nature Portfolio journals

Get Nature+, our best-value online-access subscription

$29.99 / 30 days

cancel any time

Subscribe to this journal

Receive 12 print issues and online access

$189.00 per year

only $15.75 per issue

Rent or buy this article

Prices vary by article type

from$1.95

to$39.95

Prices may be subject to local taxes which are calculated during checkout

doi: https://doi.org/10.1038/d41573-023-00139-0

Acknowledgements

The authors wish to thank Jeffrey Algazy, Joachim Bleys, Sam White, Ester Friedlaenderova, Thomas Devenyns, Rachel Moss, Michael Steinmann and Chris Anagnostopoulos for their contributions to this article.

The authors of this article are employees of McKinsey & Company, a management consultancy that works with the world’s leading biopharmaceutical and biotechnology companies. The research for this specific article was funded by McKinsey’s Life Sciences practice.

Postdoc and postgrad positions open in Dr. Renato Polimanti’s group at the Yale University School of Medicine.

New Haven, Connecticut

Yale University School of Medicine

Biostatistics and Bioinformatics at Moffitt Cancer Center is seeking a faculty member on a tenure track position.

Tampa, Florida

H. Lee Moffitt Cancer Center & Research Institute

Tampa, Florida

University of South Florida (USF)

Biostatistics and Bioinformatics at Moffitt Cancer Center is seeking a faculty member on a tenure track position.

Tampa, Florida

H. Lee Moffitt Cancer Center & Research Institute

Looking for talented data scientists to work on ground breaking transplant genomic &omic projects including human-to-human & pig-to-human studies

New York City, New York (US) (or Palo Alto, Philadelphia or remote location work also possible)

Division of Transplantation, New York University