Daiichi Sankyo Expanded Turbine ADC Partnership
The pharmaceutical company is utilizing AI simulation technology to accelerate the discovery of new drug therapies.
Updated on Sept. 24, 2026 in Biotech
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Daiichi Sankyo has broadened its collaboration with Turbine to deploy the vLab platform for antibody-drug conjugate (ADC) discovery. This partnership integrates in silico simulation into the drug research process.
Why it matters
The growing complexity of ADC development, including payload and biomarker selection, has made the drug discovery process more difficult. This expansion aims to reduce the reliance on wet-lab experiments by using simulations to guide research.
The vLab platform models biological responses across millions of conditions using data from cell lines and patient-derived xenograft models. This lab-in-the-loop workflow uses simulated experiments to guide data generation for future drug candidates.
The players
Daiichi Sankyo
This is a global pharmaceutical company focused on developing innovative medicines with a major research pipeline in antibody-drug conjugates.
Turbine
This biotechnology firm specializes in cell-based simulations and AI-driven drug discovery platforms.
AstraZeneca
This multinational pharmaceutical company collaborates with various technology firms to advance its cancer research and drug development efforts.
The details
The collaboration applies this AI-driven approach to Daiichi Sankyo's proprietary ADC pipeline, which includes candidates like trastuzumab deruxtecan and datopotamab deruxtecan. By feeding simulation results back into the models, the companies aim to make in silico experimentation a standard prerequisite for wet-lab research.
Timeline
2025: Turbine announced an ADC discovery collaboration with AstraZeneca.
July 2026: Daiichi Sankyo maintained a pipeline including multiple deruxtecan candidates.
August 2026: The DS1025 CD25-directed ADC entered clinical development.
September 24, 2026: The collaboration expansion was officially announced.
The Tech Race
This move represents a shift toward making AI-driven in silico experimentation a necessary component of the pharmaceutical discovery cycle. It positions the technology as a complement to traditional lab work as the industry attempts to solve increasingly complex drug development challenges.
For the medical community, the integration of simulation technology could eventually accelerate the time required to bring new cancer therapies to clinical trials. Patients may benefit from faster development cycles of specialized treatments, though adoption timelines remain dependent on successful research outcomes.
The takeaway
The move highlights a growing trend where major pharmaceutical companies are offloading high-complexity modeling tasks to specialized simulation firms. This shift is expected to change the standard operating procedure for drug labs by prioritizing data-backed simulations before physical testing begins.
Further reading
For more information on the evolving landscape of drug research, visit the Biotech section.
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