Executive Summary

Collaborative Drug Discovery’s agreement with Eli Lilly and Company to integrate Lilly TuneLab into CDD Vault marks an important step in the practical adoption of AI and machine learning across biotech drug discovery.

Announced on 20 May 2026, the partnership will make select Lilly AI/ML predictive models available to biotech companies using CDD Vault. For senior biotech and pharma leaders, the significance goes beyond platform integration. It reflects a broader shift: AI is moving from specialist computational environments into the secure scientific workflows where discovery decisions are already made.

Why It Matters for Biotech and Pharma Leaders

AI in drug discovery is now directly linked to operational readiness, portfolio efficiency, data governance, and competitive advantage.

Access to predictive models trained on decades of Lilly’s proprietary research data could help participating biotech companies strengthen early decision-making, particularly in compound prioritisation, ADMET assessment, and discovery-stage risk reduction.

For emerging and mid-sized biotech companies, this could be especially valuable. Many organisations lack the data depth, infrastructure, or model development scale of large pharmaceutical companies. By embedding Lilly TuneLab within CDD Vault, the partnership gives companies access to advanced model intelligence without requiring them to build those AI capabilities internally or log into another system.

Embedded AI, Not Standalone AI

One of the most important aspects of the announcement is where the AI will sit. -> The key question is not just what the AI can do, but how it fits into the scientist’s workflow.

Rather than requiring scientists to move into a separate platform, Lilly TuneLab will be integrated into CDD Vault, a secure hosted environment used to manage biological and chemical research data, including SAR, assays, ELN, inventory, activity visualisation, AI, and automation.

This matters because AI predictions are most useful when connected to the scientific context behind decisions: compound structures, assay results, experimental history, SAR trends, and programme objectives. Without this context, even advanced models can remain underutilised.

ADMET Prediction as a Strategic Lever

The press release highlights TuneLab’s ADMET models as a key fit for CDD Vault’s secure software environment.

ADMET properties (absorption, distribution, metabolism, excretion, and toxicity), often determine whether a promising compound progresses or fails. Potency alone is not enough if a molecule faces barriers around exposure, metabolism, safety, or tolerability.

Earlier access to predictive ADMET insights may help discovery teams identify liabilities sooner, prioritise compounds more effectively, and reduce unnecessary experimental spend. For C-suite leaders, this has implications for programme selection, capital allocation, timeline compression, and probability of technical success.

Collaboration as Competitive Advantage

The next phase of AI-enabled drug discovery will not be defined by algorithms alone. It will be shaped by how effectively companies combine secure data environments, trusted models, collaborative workflows, and human judgement.

CDD’s founding vision has long centred on web-based collaboration in drug discovery. Integrating Lilly TuneLab into CDD Vault extends that concept into AI-enabled prediction and model-supported discovery.

For biotech and pharma executives, collaboration is increasingly becoming infrastructure-led. Competitive advantage may depend on how well companies connect internal data, external models, ecosystem partners, and scientific teams in secure, scalable environments.

A Broader AI Discovery Ecosystem

CDD has positioned the partnership as part of a broader discovery informatics ecosystem, alongside capabilities such as Zero Click Models, Generative Bioisosteres, deep learning similarity search, novelty assessment, catalogue exploration, SAR analysis, and structured experimental data management.

The strategic value is not in any single AI feature. It is in creating a more connected decision environment across discovery.

Questions for Executive Teams:

The CDD-Lilly TuneLab partnership raises important strategic questions for biotech and pharma leaders:

How mature is our internal discovery data infrastructure?

Can scientists access predictive tools within their existing workflows?

Are our AI investments connected to measurable portfolio decisions?

How do we govern external model use while protecting data privacy and IP?

Where can predictive modelling reduce avoidable experimental cycles or early-stage attrition?

How do we ensure AI supports scientific judgement rather than creating a disconnected layer of automated output?

These questions are now central to AI strategy. Adoption is no longer about whether companies should explore machine learning. It is about how they integrate it responsibly, securely, and productively into the discovery engine.

Spotlight: AI in Drug Discovery Xchange – San Francisco 2026

The strategic questions raised by this partnership will be central to discussions at the AI in Drug Discovery Xchange – San Francisco 2026.

Taking place on Wednesday, 9 September 2026, at the DoubleTree by Hilton San Francisco Airport Hotel, the event will bring together senior-level scientists, biotech executives, pharma leaders, technology innovators, and data strategy decision-makers to examine how AI is being applied across the drug discovery value chain.

Key themes include:

Data Quality | Target Identification | Lead Generation & Optimization | Drug Response Prediction | Drug Design & Modeling

Across expert-led roundtables, structured 1:1 meetings, technical presentations, and networking, participants will explore how AI can move from technical promise to practical discovery impact.

For C-suite leaders, the Xchange provides a focused setting to benchmark AI strategy, assess emerging collaboration models, and engage with peers facing similar challenges around infrastructure, governance, scientific validation, and portfolio impact.

Want to find out more? Attend in person with complimentary registration. View the agenda and reserve your seat. 

The Strategic Takeaway

The CDD-Lilly TuneLab partnership is more than a technology integration. It signals where AI-enabled drug discovery is heading.

The future will favour organisations that can connect secure data management, collaborative workflows, high-quality predictive models, and scientific decision-making.

For biotech and pharma executives, AI adoption is becoming an operational priority, not just a research initiative. Companies that bring models, data, workflows, and people together will be better positioned to improve discovery productivity, reduce avoidable risk, and accelerate progress toward meaningful therapies.

Bibliography

Collaborative Drug Discovery. (2026, May 20). Collaborative Drug Discovery partners with Lilly TuneLab to make Lilly AI/ML models available in CDD Vault. Collaborative Drug Discovery. https://www.collaborativedrug.com/hubfs/CDD%20Vault%20Lilly%20Tunelab%20Press%20Release-1.pdf

Collaborative Drug Discovery. (n.d.). AI drug discovery. Collaborative Drug Discovery. https://www.collaborativedrug.com/ai-drug-discovery

Collaborative Drug Discovery. (n.d.). CDD Vault: Hosted biological and chemical data management. Collaborative Drug Discovery. https://www.collaborativedrug.com/cdd-vault

Eli Lilly and Company. (2025, September 9). Lilly launches TuneLab platform to give biotechnology companies access to AI/ML drug discovery models. Lilly Investor Relations. https://investor.lilly.com/news-releases/news-release-details/lilly-launches-tunelab-platform-give-biotechnology-companies

Eli Lilly and Company. (n.d.). Lilly TuneLab. https://tunelab.lilly.com

Reuters. (2025, September 9). Eli Lilly launches platform for AI-enabled drug discovery. Reuters. https://www.reuters.com/business/healthcare-pharmaceuticals/eli-lilly-launches-platform-ai-enabled-drug-discovery-2025-09-09/

Reuters. (2025, October 28). Lilly partners with Nvidia on AI supercomputer to speed up drug development. Reuters. https://www.reuters.com/business/healthcare-pharmaceuticals/lilly-partners-with-nvidia-ai-supercomputer-speed-up-drug-development-2025-10-28/

Reuters. (2026, January 9). Schrödinger to offer Eli Lilly’s AI drug discovery platform on its software. Reuters. https://www.reuters.com/business/healthcare-pharmaceuticals/schrodinger-offer-eli-lillys-ai-drug-discovery-platform-its-software-2026-01-09/

U.S. Food and Drug Administration. (2025, January 7). FDA releases draft guidance on alternatives to animal testing in drug development. FDA. https://www.fda.gov/news-events/press-announcements/fda-releases-draft-guidance-alternatives-animal-testing-drug-development