Why Big AI Investments in Pharma Don’t Always Ensure Success: Insights from Niven Narain

Big investments in artificial intelligence (AI) do not guarantee success in drug development. Niven R. Narain, CEO of BPGbio, highlighted this in an editorial for Forbes. He compared the use of AI in drug development to a soccer team with a star player like Lionel Messi, who may still fail to score despite their talent.

Narain pointed out that the key issue lies in how companies use AI and the quality of data they input. He likened AI to coaching and teamwork, essential for maximizing the potential of drug development efforts.

Currently, many AI companies aim to dominate drug discovery. However, they must effectively advance their potential drugs through various stages, from preclinical studies to clinical trials, to earn regulatory approvals and bring therapies to market.

Some notable AI-driven companies include:

Anima Biotech: Founded in 2018, Anima has partnered with major pharmaceutical companies to develop mRNA modulators for oncology and immunology. They utilize their Lightning.AI platform to differentiate between healthy and diseased cells, focusing on uncovering new treatment targets.

Atomwise: This company, which gained recognition since 2020, collaborates with industry leaders like Sanofi. Atomwise utilizes its AtomNet technology to identify drug targets and has proven effective in screening studies.

BPGbio: Focused on BPM31510, a drug-lipid conjugate aimed at targeting cancer energy, BPGbio has multiple ongoing programs. The company collaborates with prestigious institutions to validate and enhance its data.

Generate Biomedicines: With a focus on protein therapeutics, this company initiated collaborations with Novartis and Amgen to explore treatments across various disease areas. Generate gained significant funding since its launch in 2020.

Insilico Medicine: Insilico’s lead candidate for idiopathic pulmonary fibrosis showed positive results in early trials. The company is expanding its pipeline and platforms through significant funding and relocations to tap into talent and partnerships.

Model Medicines: This company boasts a large pipeline of drug candidates developed via its GALILEO platform, which analyzes protein structures. They have promising candidates targeting viral infections and cancer.

Nimbus Therapeutics: Gilead Sciences invested heavily in Nimbus for its pioneering drug and has since partnered with Eli Lilly to develop metabolic treatments.

Recursion Pharmaceuticals: The company aims to develop a substantial number of drug candidates quickly. It has already advanced candidates into late-stage trials, aiming for significant pipeline growth.

Relay Therapeutics: The company plans pivotal trials for its breast cancer drug based on encouraging data. Relay maintains a healthy cash reserve to support its research initiatives.

Schrödinger: With a grant from the Gates Foundation, Schrödinger is focusing on predicting drug toxicity in early discovery phases. They are developing multiple therapeutic programs through partnerships with major pharmaceutical companies.

These companies illustrate the potential of AI in drug development but underscore the necessity for quality data and strategic application of AI technologies to achieve impactful outcomes.