Client success story
Automating DMTA Cycle to Accelerate Drug Discovery
Business Value: Increase Lead Identification Throughput & Increased Company Partnerships
Summary: Automation of DMTA Cycle Significantly Increases Screening Rate
A clinical-stage therapeutics company has validated a powerful platform for identifying lead candidates across multiple indications, but their existing screening process was becoming a barrier to growth. Partnering with bPrescient, they designed a modular, AI-enabled automation platform that will transform their DMTA cycle by dramatically reducing cycle time, improving hit quality, and scaling discovery throughput. The first installation of the platform will more than double the company’s screening throughput capability. The result is a competitive edge that attracted new partnership opportunities and positioned the company to broaden their therapeutic approach.
Challenge: Screening Process Was Manual and Data was Fragmented
Despite a proven and effective screening methodology, the client recognized that their manual workflows were a strategic liability. Capacity constraints made it difficult to meet growing demand from research partners, and the inability to scale quickly was putting future opportunities at risk. Compounding this, their data infrastructure was built on legacy systems that didn’t model the underlying data optimally and created downstream inefficiencies. Early internal efforts to automate analytical workflows were limited, as data processing and upload steps continued to require significant manual intervention.
Solution: A Fully Automated, AI-Driven DMTA Platform
bPrescient assembled a cross-functional team that included experts in AI, lab automation and laboratory informatics. The team undertook a ground-up redesign of the DMTA workflow and conducted a rigorous evaluation of integrated automation platforms, LIMS solutions, and analytics tools. This led to the technology selections and design of a modular platform engineered for efficiency and long-term scalability. The resulting system integrates robotics, high-density storage, advanced liquid handling, and multiple binding and functional assays. Central to the architecture is an agentic AI model that orchestrates operations end-to-end, enabling continuous, autonomous execution of the screening pipeline around the clock.
Outcome: Continuous 24/7 Screening
The client is building a new AI-driven platform that streamlines their proven screening methodology. The integrated data infrastructure now captures and organizes information across all discovery platforms, creating a unified foundation for decision-making and reporting. The system allows for continuous learning and leverages AI tools to automate all phases of the DMTA cycle. Most significantly, the platform’s newfound scale and reliability has opened doors to new partnerships, enabling the client to pursue additional therapeutic indications and expand their drug discovery pipeline.
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