KEY POINTS

  • TPC Marketing Research releases study on AI drug discovery strategies across pharmaceutical companies, AI ventures and big technology groups
  • AI use in drug discovery expands from target discovery and screening to molecular design, ADMET prediction, preclinical research and clinical development
  • Survey covers May to August 2026 and includes AstraZeneca, Roche, Takeda, Recursion, NVIDIA, Amazon, Google and Microsoft
TPC Marketing Research releases 2026 AI drug discovery strategy survey

TPC Marketing Research said on August 26 it had released the results of a study on business strategies in AI-driven drug discovery, as pharmaceutical companies seek to improve research productivity and raise the low success rate of bringing candidate compounds to market.

The Osaka-based market research firm said new drug development requires long timelines and large research and development spending, while the probability that candidate compounds reach commercialization remains low. In that environment, AI drug discovery has drawn attention as a tool to improve productivity in drug research by rapidly analyzing large volumes of gene, disease and compound data, identifying promising drug targets and candidate compounds, and predicting efficacy and safety.

Advances in AI and machine learning have broadened the use of AI in drug discovery from target identification and compound screening to molecular design, ADMET prediction and preclinical and clinical development, according to the release. ADMET refers to the absorption, distribution, metabolism, excretion and toxicity properties used to assess drug candidates. The emergence of generative AI, foundation models and multimodal AI has also accelerated drug research using large-scale biological and chemical data.

The study said cases are emerging in which drug candidates created or designed with AI have progressed into clinical development, indicating that AI drug discovery is moving from a technology verification stage toward practical application and commercialization.

Looking at strategies among major players, TPC Marketing Research said pharmaceutical companies, AI ventures and big technology companies are each pursuing approaches based on their respective strengths. Those directions include wider implementation of AI in pharmaceutical research and development processes, development and deployment of AI drug discovery platforms by AI ventures alongside the creation and development of drug candidates, and the provision by big technology companies of research infrastructure such as AI models, cloud services and GPU and high-performance computing resources.

The company said pharmaceutical companies are increasingly moving to incorporate external AI technologies, data and computing infrastructure through partnerships with AI ventures and big technology companies. It added that competition in AI drug discovery is increasingly seen as depending on strategies that combine technology, data, pipelines and external collaboration to improve R&D efficiency, generate new drug candidates and support commercialization.

The survey, titled "2026 Business Strategy Survey on AI Drug Discovery," was published on August 24 and covered research conducted from May to August 2026. Companies included in the study included AstraZeneca, Sanofi, Roche (Chugai Pharmaceutical), Novartis, Eli Lilly and Company, Merck & Co., Takeda Pharmaceutical, Astellas Pharma, Daiichi Sankyo, Eisai, Ono Pharmaceutical, Recursion Pharmaceuticals, Schrödinger, Insilico Medicine, BenevolentAI, Iambic Therapeutics, XtalPi, Relation Therapeutics, FRONTEO, MOLCURE, Elix, NVIDIA, Amazon.com, Google and Microsoft.

TPC Marketing Research, established in August 1991, is based in Nishi Ward, Osaka.

Originally published on jp.ibtimes.com