Takeda

Two Agentforce agents: SEIMEI condenses clinical literature and field conversation notes into insights, and AIMI drafts cited answers to healthcare professionals' medical questions for staff to review.

Partners: Salesforce

A field platform that gives sales reps AI-generated views of each doctor's patient population, prescribing patterns and access barriers. It was an award finalist write-up, not a Takeda release.

Takeda chose Salesforce's AI-enabled Life Sciences Cloud to give commercial teams embedded insights for engaging healthcare professionals.

Partners: Salesforce

Takeda is deploying Weave Bio's AI regulatory-writing platform across 14 programs. Use started with IND drafting and has grown to health-authority question responses.

Partners: Weave Bio

Takeda's medical writing team built a generative AI prototype to speed compilation of regulatory dossiers by automating analysis of clinical study data. It was being tested on a CSR efficacy section.

A collaboration using Insilico's generative AI Pharma.AI platform to find drug candidates across Takeda's therapeutic areas.

Partners: Insilico Medicine

Atinary's machine-learning experiment optimizer is being built into Takeda discovery workflows to speed up reaction and process optimization.

Partners: Atinary, AWS

A multi-year partnership that gives Takeda access to Iambic's AI discovery tools, including the NeuralPLexer protein-ligand model, initially for oncology and GI/inflammation programs.

Partners: Iambic Therapeutics

A second multi-year deal applying Nabla Bio's generative Joint Atomic Model to design antibodies and other protein drugs for Takeda's early programs.

Partners: Nabla Bio

Takeda joined a federated effort to fine-tune the OpenFold3 structure-prediction model on proprietary protein-ligand data without sharing the data itself.

Partners: Apheris, AlQuraishi Lab (Columbia)

An enterprise platform on Databricks that lets over 10,000 employees build, deploy and run AI agents under central governance, including a control tower, policy-enforcement agent and agent marketplace.

Partners: Databricks

Takeda is the founding partner in TetraScience's program to re-platform scientific data for AI use in R&D and CMC.

Partners: TetraScience

A Takeda R&D Quality lead described a multi-agent AI system for preparing CDMO audit briefings. It was shown as a validation-feasibility study on synthetic data, not a production deployment.

AI agents watch real-time equipment data to catch early signs of degradation and prevent unplanned downtime. More than 170 agents run across 45 systems at the Lessines site.

An AI assistant trained on Takeda's internal investigation standard that helps staff write more consistent deviation investigation reports.

A manufacturing digital transformation program using AI, digital twins and big-data analytics across Takeda plants, including cloud anomaly detection to prevent equipment failures.

Takeda programmers presented a framework that uses an LLM through Amazon Bedrock to review ADaM specifications and generate SAS code.

Partners: AWS

Takeda's Japan manufacturing and supply unit brought in an AI demand-forecasting model for production planning. It replaces a mostly history-and-expert approach.

Takeda's in-house generative AI assistant for summarizing, drafting and analysis. It only sees data that users put into their prompts.

A research alliance using nference machine-learning models on de-identified health records to find IBD patients who could benefit from advanced therapies.

Partners: nference