Ginkgo Datapoints: Can AI Drug Discovery Move Faster When the Data Comes From Robots, Not Spreadsheets?

Overview: How Ginkgo Datapoints’ AI-Driven Automated Design and Closed-Loop Laboratory Platform Transforms Drug Discovery R&D

Ginkgo Datapoints is an automated, lab-in-the-loop data-generation platform for drug discovery that combines high-throughput experimental services with AI/ML-ready biological datasets. It addresses a frequent bottleneck in AI-enabled R&D: predictive models and discovery teams require consistent, information-rich experimental data, but conventional laboratory workflows can be slow, fragmented, and difficult to reuse across screening, modelling, and lead-optimisation activities. The platform provides automated antibody-developability testing, perturbation-response profiling, specialised high-throughput screening, and small-molecule ADME services, producing structured outputs intended for computational analysis and iterative discovery programmes.

Its approach connects automated assays, laboratory instrumentation, sample and compound workflows, and structured data returns with AI-supported modelling and prioritisation. For example, its ADME-One service combines automated Tier 1 ADME testing with compound-management support from Tangible Scientific and AI-driven human pharmacokinetic projection from Inductive Bio; other services use Cell Painting, DRUG-seq, high-content imaging, and biophysical antibody assays to generate multimodal experimental datasets. The resulting data can support target and hit prioritisation, mechanism-of-action analysis, developability assessment, lead optimisation, and model training, while retaining experimental evidence as a decision input rather than relying on prediction alone.

For biopharma R&D workflows, Ginkgo Datapoints can consolidate the path from assay design and compound submission to experimental profiling and machine-learning-ready results, reducing manual data reformatting and helping teams compare larger candidate sets earlier in discovery. Its antibody-developability service states that it can screen more than 2,400 designs in parallel across over 10 biophysical assays, while its perturbation-profiling workflows support library-scale transcriptomic and morphological studies; the practical impact will depend on assay design, data quality, programme biology, and how results are incorporated into downstream decisions.

Last checked on September 30, 2026: Ginkgo Datapoints remains active and most recently announced an agreement with Lilly TuneLab to supply ADME and antibody-developability data for AI/ML drug-discovery workflows.

What is Ginkgo Datapoints?

Ginkgo Datapoints is an automated experimental-data platform for drug discovery that provides antibody-developability testing, perturbation-response profiling, specialised high-throughput screening, and small-molecule ADME services. Pharmaceutical, biotech, TechBio, technology, academic, and non-profit research organisations use it to generate structured biological data for target identification, hit and lead evaluation, developability assessment, and model development. Its technical approach combines automated laboratory workflows with ML-ready data outputs; its ADME-One service integrates Tier 1 ADME assays with Inductive Bio’s AI-driven human pharmacokinetic projection and Tangible Scientific’s compound-management workflow.

Intended Use and Limitations

• Ginkgo Datapoints is an offering of Ginkgo Bioworks, a publicly traded biotechnology company listed on the NYSE under the ticker DNA.

• In September 2026, Ginkgo Datapoints entered an agreement with Lilly TuneLab, Eli Lilly’s collaborative AI/ML drug-discovery platform, to provide small-molecule ADME and antibody-developability data-generation services.

• The Lilly TuneLab agreement uses standardised assay protocols and enables participating companies to submit Ginkgo Datapoints-generated data to access additional TuneLab model benefits.

• Ginkgo Datapoints partnered with Tangible Scientific and Inductive Bio to create a lab-in-the-loop drug-discovery workflow connecting automated experimental testing, compound logistics, and AI-driven pharmacokinetic prediction.

• The partners launched ADME-One in May 2026, combining high-throughput Tier 1 ADME testing, compound management, and AI-driven human pharmacokinetic projection.

• Ginkgo Datapoints states that its data-generation services are automated, reproducible, and delivered in machine-learning-ready formats, covering antibody developability, perturbation-response profiling, specialised high-throughput screening, and small-molecule ADME.

• The platform publishes selected open datasets, including 2026 DRUG-seq and antibody-developability datasets, through Hugging Face for research access and model-development use.

• Ginkgo Bioworks completed the divestiture of its biosecurity business in May 2026 and stated that it was continuing to scale its autonomous-laboratory business; this was a parent-company portfolio change rather than a reported ownership change for Datapoints.