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Turbine expands virtual biology collaboration on antibody-drug conjugate discovery

Turbine, a virtual biology company, has expanded its collaboration with Daiichi Sankyo after completing an initial feasibility programme that evaluated its predictive modelling capabilities for antibody-drug conjugate (ADC) development.

Turbine Daiichi

Feasibility work leads to wider collaboration

Turbine reported that the feasibility programme demonstrated its ability to generate insights relevant to ADC research and development, which gave both parties the confidence to proceed. Its virtual biology platform, vLab™, will now be applied to Daiichi Sankyo’s proprietary ADC programmes. The aim is to explore complex biology and support data-driven decision-making across discovery.

Simulating experiments at scale

The work centres on Virtual Assays, which are computational experiments that simulate biological responses across large numbers of conditions. Turbine noted that, as ADC pipelines grow, selecting the optimal payload, combination, indication and biomarker strategies has become a significant challenge in oncology R&D, particularly as novel payload classes add complexity. Conventional experimental approaches can address only a fraction of the biological search space needed to optimise these decisions.

According to the company, vLab allows scientists to simulate experiments at computational scale, identify hypotheses supported by mechanistic evidence and prioritise the most promising candidates for experimental validation. Turbine describes the platform as a “lab without limits”: a no-code system with collaborative workflows and interactive visualisations. The resulting in silico data packages can be integrated into existing R&D processes.

Iterative learning between simulation and bench

The collaboration also sets up a lab-in-the-loop approach. Simulated experiments guide efficient data generation, and experimental validation then feeds back into the computational models. Turbine said each cycle sharpens the Virtual Assays further, creating a compounding learning effect as new experimental data strengthens the knowledge base that informs later predictions and decisions.

Szabolcs Nagy, Chief Executive Officer and Co-Founder of Turbine, said: “Virtual Assays offer near infinite search space and greatly reduce the number of wet lab experiments needed.” He added: “We believe in silico experimentation will become the prerequisite for wet lab work and the accelerant across R&D pipelines, transforming R&D productivity.”

Nagy noted that Turbine has already used vLab with partners including AstraZeneca and MSD (Merck & Co.) to generate mechanistic insights and prioritise targets and biomarkers in defined patient populations. He commented: “This collaboration reflects Turbine and Daiichi Sankyo’s shared commitment to applying innovation to improve decision-making across ADC discovery.”

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