Revvity Collaborates with Lilly to Expand Access to AI Drug Discovery Models

Key Terms

federated learning technical

A method of building artificial intelligence where many devices or locations train the same model using their own private data and only share the model updates, not the raw data—like many cooks each stirring their own pot and sending a note about what worked. It matters to investors because it lets companies improve products and personalization while lowering data-transfer costs and privacy risk, affecting regulatory compliance, customer trust, and the scalability and competitive value of AI-based offerings.

AI/ML technical

AI/ML stands for artificial intelligence and machine learning, software systems that identify patterns in data and make predictions or automate decisions, improving performance as they process more information. Investors care because these technologies can boost revenue, cut costs and create competitive advantages — like a factory that learns to produce goods faster and with fewer mistakes — while also introducing execution, ethical and regulatory risks that can affect a company’s value.

Models-as‑a‑Service technical

Models-as-a-service is a business model where companies host predictive algorithms (such as machine‑learning or statistical models) in the cloud and deliver them on demand via an interface so customers can use advanced analytics without building or running the software and hardware themselves. For investors, it’s like renting a specialized tool that can generate steady, recurring revenue and scale quickly, while also creating exposure to model accuracy, data privacy, and regulatory risks.

wet-lab technical

A wet-lab is a physical laboratory where scientists perform hands-on experiments using liquids, biological samples, chemicals, or live cells—think of it as a kitchen where recipes are mixed and tested rather than simulated on a computer. For investors, wet-lab work signals real-world experimental progress, tangible costs for equipment and materials, and potential regulatory or safety hurdles that can affect timelines, capital needs, and the credibility of scientific claims.

CROs technical

Contract research organizations (CROs) are independent firms hired by drug and medical-device companies to run research tasks such as clinical trials, patient recruitment, lab testing, data management, and regulatory filings. For investors they matter because CROs act like contractors turning a sponsor’s plans into finished work—so their capacity, timelines, costs and quality directly affect how quickly and cheaply a drug or device can move toward approval and revenue.

Collaboration funds participating biotechs to access Lilly predictive models through the Revvity Signals Xynthetica offering

WALTHAM, Mass.--(BUSINESS WIRE)-- Revvity, Inc. (NYSE: RVTY) today announced a collaboration with Eli Lilly and Company (Lilly) that expands access to Lilly’s high-quality predictive models by making Lilly TuneLab available through the Revvity Signals platform. The collaboration builds on Revvity’s recently introduced Signals Xynthetica^TM offering, creating a scalable, federated framework designed to accelerate AI-enabled drug discovery.

Lilly TuneLab was established to make advanced AI/ML models, trained on decades of Lilly research data, available to the broader biotech community in exchange for data contributions that improve model performance through federated learning. The Signals Xynthetica platform operationalizes the delivery of the Lilly TuneLab models directly within the Signals platform, where experimental data is already captured, curated, and analyzed by thousands of discovery teams worldwide.

“Federated learning represents one of the most powerful paths forward for AI in drug discovery, but it requires the right platform to succeed,” said Kevin Willoe, president of Revvity Signals Software. “By providing access to Lilly’s worldclass predictive models through the Signals Xynthetica platform, we are creating a practical, secure way for organizations of all sizes to contribute to, and benefit from, collective intelligence.”

Through Revvity’s Models-as‑a‑Service framework and its Signals Xynthetica offering, participating organizations will be able to apply Lilly’s predictive models to their own discovery programs while keeping proprietary data private and secure. This approach amplifies the value of contributions from small and midsized‑biotechs, whose diverse experimental data can significantly enhance collective predictive performance.

The Signals platform provides critical infrastructure to enable organizations to access the Lilly TuneLab models, including scientific data management, analytics, and collaboration across internal and external partners. Revvity’s Signals One^TM offering already supports wet-lab data capture and orchestration across experiments, and its Signals Synergy^TM module enables secure data exchange with CROs, academic collaborators, and partners, capabilities that are essential for scalable federated learning networks.

As part of the collaboration, Lilly and Revvity will jointly fund access for selected participants, including access to Signals One and Signals Xynthetica software offerings and modeling credits. This co-funded model underscores both companies’ commitment to lowering barriers to AI adoption and accelerating innovation across the biotech ecosystem.

About Revvity
At Revvity, “impossible” is inspiration, and “can’t be done” is a call to action. Revvity provides health science solutions, technologies, expertise and services that deliver complete workflows from discovery to development, and diagnosis to cure. Revvity is revolutionizing what’s possible in healthcare, with specialized focus areas in translational multi-omics technologies, biomarker identification, imaging, prediction, screening, detection and diagnosis, informatics and more.

With 2024 revenue of more than $2.7 billion and approximately 11,000 employees, Revvity serves customers across pharmaceutical and biotech, diagnostic labs, academia and governments. It is part of the S&P 500 index and has customers in more than 160 countries.

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Investor Relations:

Steve Willoughby

steve.willoughby@revvity.com

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Chet Murray

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chet.murray@revvity.com

Source: Revvity