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Schrodinger to Integrate Eli Lilly’s AI Drug Discovery Platform TuneLab

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Biotech software company Schrodinger said on Friday it is collaborating with pharmaceutical giant Eli Lilly to offer Lilly’s artificial intelligence–based drug discovery platform, TuneLab, through its software.

Under the collaboration, Lilly’s TuneLab platform will be integrated into Schrodinger’s cloud-based drug design software LiveDesign, giving biotechnology companies direct access to AI tools designed to accelerate drug discovery and development. Schrodinger said the integration will help researchers move more quickly from early-stage molecule design to viable drug candidates.

LiveDesign is used by chemists to design compounds and predict key properties such as absorption and distribution, helping developers understand how experimental drugs are likely to behave in the body. The addition of TuneLab is expected to further enhance these capabilities by applying AI and machine learning models trained on years of pharmaceutical research data.

Drugmakers and biotech firms have been increasingly adopting AI tools to speed up discovery and safety testing, aiming to reduce costs and development timelines. The trend aligns with efforts by regulators such as the U.S. Food and Drug Administration to encourage alternatives to animal testing in the coming years.

Schrodinger Chief Strategy Officer Karen Akinsanya said existing LiveDesign customers will gain access to TuneLab in the first quarter of this year, while new users will be able to use the AI platform starting in the second quarter.

Eli Lilly launched TuneLab last year to allow external biotech companies to tap into its AI and machine learning models trained on proprietary research data. Lilly has already announced multiple partnerships using the platform to support drug development efforts.

“More biotechs using the models means more diverse training data,” said Aliza Apple, global head of Lilly TuneLab. “Ultimately, this is about moving molecules through discovery faster for the patients who are waiting.”

Metagenomi Uses Amazon’s AI Chips to Power Next-Gen Gene Editing

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Biotech company Metagenomi (MGX.O) has begun using Amazon Web Services’ custom AI chips to accelerate the discovery of new gene-editing technologies, marking one of the first major biotech applications of Amazon’s in-house silicon beyond large language models and chatbots.

The Emeryville, California-based firm, which is developing tools to deliver gene therapies directly into human cells, said AWS Inferentia chips have given it a major cost advantage over Nvidia’s AI hardware, cutting computational expenses by about half while maintaining comparable performance.

Metagenomi’s approach relies heavily on artificial intelligence to design and test enzymes capable of safely editing DNA. The company scans nature for rare proteins that might serve as effective delivery vehicles for genetic material and then uses AI to generate millions of variants in search of the most effective designs.

“We generated over a million different proteins from a rare class of enzymes used in gene editing,” said Chris Brown, Metagenomi’s head of discovery. “It was a clear cost advantage to use the Inferentia platform. Unless you cast a broad enough net early, you risk missing key breakthroughs entirely.”

Amazon’s Inferentia chips, first introduced in 2019 to enhance the AI capabilities of its Alexa virtual assistant, are now being used by other industries beyond software — with biotechnology emerging as a new frontier for AI-driven hardware.

By applying cloud-based AI to the complex problem of gene delivery and editing, Metagenomi hopes to make treatments for genetic disorders faster and more affordable, while demonstrating how custom AI infrastructure can accelerate scientific discovery.

Nabla Bio and Takeda deepen AI-powered drug discovery partnership

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U.S. biotech startup Nabla Bio has expanded its collaboration with Japanese pharmaceutical giant Takeda, signing a new multi-year agreement to further integrate artificial intelligence (AI) into the drug discovery process.

The partnership, building on an initial 2022 deal, includes upfront and research payments in the double-digit millions, with Nabla eligible for success-based milestones exceeding $1 billion. The companies will use Nabla’s proprietary Joint Atomic Model (JAM) platform to design next-generation protein-based therapeutics, including multi-specific drugs targeting hard-to-treat diseases.

Nabla CEO Surge Biswas described JAM as a system that “responds to molecular queries the way ChatGPT answers text questions,” generating custom antibody designs that meet specific biological targets. The company says its technology offers one of the fastest feedback loops in the biotech sector — only three to four weeks from computational design to laboratory testing.

Takeda’s renewed focus on scalable, AI-driven drug types follows its decision to exit cell therapy research earlier this year. The Japanese firm also recently joined a consortium with Bristol Myers Squibb to develop AI models using shared pharmaceutical data.

Nabla expects to deliver first-in-human data from its AI-designed therapeutics within one to two years, marking another milestone in the industry’s growing reliance on AI to cut development timelines and boost innovation.