News
June 30, 2026
Inductive Bio joins Anthropic’s Connector Ecosystem for Life Sciences, Surfacing State-of-the-Art ADMET Prediction to Drug Discovery Scientists through Claude
NEW YORK, June 30, 2026 /PRNewswire/ — Inductive Bio, an AI drug discovery partner developing virtual chemistry labs, today announced that it has joined Anthropic’s life sciences ecosystem and launched a Model Context Protocol (MCP) connector that makes its ADMET (Absorption, Distribution, Metabolism, Excretion, & Toxicity) prediction models accessible directly within Claude. Any scientist can now reason about key drug properties for any chemical structure in natural language directly from Claude’s interface.
The connector gives Claude and Claude Science, Anthropic’s AI workbench for scientists, users on-demand access to predictions for ADMET properties, bringing trusted insights into the same place that scientists are already thinking through key questions about their discovery project. Drug discovery scientists can work with Claude to explore chemical structures, get predictions of ADMET properties, and reason about those predictions alongside the rest of their compound design rationale.
ADMET represents one of the most persistent bottlenecks in small molecule drug discovery: balancing a molecule's potency against a multitude of competing properties that drive how the molecule behaves in the body is essential for a drug’s success yet consumes an enormous amount of time and resources. Inductive Bio's ADMET models are independently validated as state-of-the-art, having placed first among more than 370 entries from large pharma and AI companies in the OpenADMET-ExpansionRx blind challenge. By making these models available to AI assistants, the new connector democratizes access to those capabilities, helping scientists design higher quality drug hypotheses.
“Scientists are increasingly reasoning through their work with Claude, and predictive ADMET models are the perfect complement to add to their toolkit,” said Ben Birnbaum, Inductive’s Co-Founder & CTO. “Any drug discovery scientist can now make use of Inductive’s ADMET predictions in their conversation and immediately reason about what it means for their compound designs and program hypotheses. It’s a step change in access to the state of the art in small molecule drug discovery, and a powerful taste of what our models can do.”
The connector is designed around Inductive Bio’s commitment to protecting scientists’ data: chemical structures submitted through Claude are not retained or used to train Inductive’s models.
Scientists and teams interested in Inductive Bio's full suite of ADMET and pharmacokinetic (PK) models - as well as models fine-tuned to their own chemical space - are encouraged to reach out to the Inductive team.
About Inductive Bio
Inductive builds virtual chemistry labs that help drug hunters design higher quality molecules, faster. Inductive’s virtual labs are designed to scale proven scientific best practices across medicinal chemistry, computational chemistry, DMPK, and safety, enabling teams to make higher-quality decisions consistently throughout discovery. Inside these virtual labs, AI chemistry assistants, predictive ADMET and PK models, and human-relevant digital organ technologies work together to help scientists evaluate more hypotheses in silico and surface key risks earlier. The most promising molecules move from the virtual lab to the wet lab in a tight feedback loop that accelerates the advancement of high-quality molecules. Inductive already powers dozens of active discovery programs, including collaborations with leading biopharma partners. For more information, please visit www.inductive.bio.
INDUCTIVE BIO MEDIA CONTACT: media@inductive.bio
SOURCE: Inductive Bio
- QC analytical reports (1H/13C/19F/2D NMR, chiral SFC)
- Propose, visualize, and triage forward and retrosyntheses
- Monitor the synthesis queue and flag stalled targets
- QC assay data as it lands and flag suspicious results
- Prioritize repeats and nominate compounds for downstream assays
- Analyze SAR and identify data gaps
- Evaluate IVIVC and suggest diagnostic experiments
- Design, enumerate, and triage analogs
- Launch and analyze physics-based workflows like docking and FEP
- Project human PK and efficacious dose
- Answer questions about a program’s history (what was learned and when)
- Track team progress against the target candidate profile
- Get new scientists up to speed on a program
- Make meeting-ready slides and figures
Prompt: I’m attaching two files with activity data, one with new data from today and one with historical data. Can you look through the new data and identify any QC issues that I should be aware of? Create a csv where every compound + assay run pair is labeled with any relevant issues.
Prompt: Do a nitrogen walk around the core of this molecule: O=C(NCC1=CC=C(C)C(F)=C1)C2=CC=C3C=C(N4[C@H](C)CCCC4)C=CN32
Prompt: Do an OH walk around this whole molecule: O=C(NCC1=CC=C(C)C(F)=C1)C2=CC=C3C=C(N4[C@H](C)CCCC4)C=CN32
Prompt: Replace the core of this molecule with this set of 5,6-ring systems (file attached): O=C(NCC1=CC=C(C)C(F)=C1)C2=CC=C3C=C(N4[C@H](C)CCCC4)C=CN32
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