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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.”

Nvidia-Backed SandboxAQ Generates Synthetic Data to Accelerate Drug Discovery

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Artificial intelligence startup SandboxAQ, spun out of Alphabet’s Google and backed by Nvidia, unveiled a large synthetic dataset designed to speed up drug discovery by improving predictions of how drugs bind to proteins. This crucial step helps scientists determine whether a drug candidate will effectively target biological processes involved in diseases.

Although the dataset is rooted in real-world experimental science, SandboxAQ created it computationally using Nvidia’s powerful chips rather than through lab experiments. By combining traditional scientific computing with advanced AI, the startup generated approximately 5.2 million new three-dimensional molecular structures that have not been observed naturally but are scientifically plausible based on existing data.

This synthetic data is being released publicly to train AI models capable of rapidly and accurately predicting drug-protein interactions, a process that would otherwise take far longer to compute manually—even on the fastest computers. SandboxAQ plans to monetize its own AI models developed using this data, offering a faster, cost-effective alternative to lab experiments.

Nadia Harhen, SandboxAQ’s general manager of AI simulation, explained the breakthrough: “This is a long-standing problem in biology that the industry has been trying to solve. Our synthetic data is tagged with ground-truth experimental results, enabling models trained on this data to achieve unprecedented accuracy.”

The approach represents a promising intersection of scientific computation and AI, potentially accelerating the development of new medicines and improving outcomes in pharmaceutical research.