Big investments in artificial intelligence (AI) do not guarantee success in drug development, according to Niven R. Narain, CEO of BPGbio. He compares AI's role to that of a star soccer player, like Lionel Messi, who may still fail to score despite immense talent.
Narain emphasizes that the key issue lies in how companies utilize AI and the quality of the data they input. He likens AI to coaching and teamwork, which are essential for maximizing drug development efforts.
Many AI companies are competing in drug discovery, but they must effectively advance their potential drugs through preclinical studies and clinical trials to earn regulatory approvals and bring therapies to market.
Notable AI-driven companies include:
Anima Biotech: Partnering with major pharmaceutical firms to develop mRNA modulators for oncology and immunology.
Atomwise: Collaborating with industry leaders to identify drug targets using its AtomNet technology.
BPGbio: Focused on a drug-lipid conjugate aimed at cancer, collaborating with prestigious institutions.
Generate Biomedicines: Exploring protein therapeutics with significant funding since its launch.
Insilico Medicine: Expanding its pipeline after positive early trial results for idiopathic pulmonary fibrosis.
Model Medicines: Developing a large pipeline of candidates targeting viral infections and cancer.
Nimbus Therapeutics: Partnering with Eli Lilly to develop metabolic treatments.
Recursion Pharmaceuticals: Aiming for significant pipeline growth with candidates in late-stage trials.
Relay Therapeutics: Planning pivotal trials for a breast cancer drug based on encouraging data.
Schrödinger: Focusing on predicting drug toxicity in early discovery phases with support from the Gates Foundation.
These companies highlight the potential of AI in drug development but stress the necessity of quality data and strategic applications of AI technologies for impactful outcomes.