Inductive Bio Launches ADMET Prediction Connector for Anthropic's Claude, Democratizing AI-Powered Drug Discovery
Key Insights
Inductive Bio (search) has joined Anthropic (search)'s life sciences connector ecosystem, making its state-of-the-art ADMET prediction models directly accessible within Claude's interface.
The Model Context Protocol (MCP) connector allows drug discovery scientists to explore chemical structures and reason about ADMET properties using natural language in their existing workflow.
Inductive Bio (search)'s ADMET models were independently validated as best-in-class, placing first among over 370 entries from large pharma and AI companies in the OpenADMET-ExpansionRx blind challenge.
Inductive Bio (search), an AI drug discovery company developing virtual chemistry labs, announced on June 30, 2026 that it has joined Anthropic (search)'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. The integration enables any drug discovery scientist working with Claude to access state-of-the-art predictive models directly in their existing workflow, reasoning about key drug properties for any chemical structure in natural language.
The connector gives Claude and Claude Science — Anthropic (search)'s AI workbench for scientists — on-demand access to predictions for ADMET properties, bringing trusted insights into the same environment where scientists are already evaluating critical questions about their discovery projects. Drug discovery scientists can now work with Claude to explore chemical structures, obtain predictions of ADMET properties, and reason about those predictions alongside the rest of their compound design rationale.
Addressing a Persistent Bottleneck in Small Molecule Discovery
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 (search)'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."
Data Privacy and Enterprise Capabilities
The connector is designed around Inductive Bio (search)'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 for broader collaboration.
Inductive Bio (search) builds virtual chemistry labs that help drug hunters design higher quality molecules, faster. The company'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. Inductive already powers dozens of active discovery programs, including collaborations with leading biopharma partners.