Case Studies Accelerating Synthetic Biology with Fully Unified Informatics
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Accelerating Synthetic Biology with Fully Unified Informatics

Platform as a Service (PaaS) - Data Management Platforms
Healthcare & Hospitals
Life Sciences
Product Research & Development
Predictive Quality Analytics
Regulatory Compliance Monitoring
Data Science Services
Synlogic, a company developing microbe-based therapeutics, faced several challenges in their operations. Their complex workflows were being sketched out step-by-step on paper, which hindered collaboration and reproducibility. Without a workflow system linked to a registration system, it was difficult for Synlogic to trace the lineages of their candidates. Additionally, placing requests, uploading results from instruments, and collating data across experiments were cumbersome and unreliable without unified, intelligent systems.
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Synlogic is a pioneering company in the field of synthetic biology, developing microbe-based therapeutics to treat a wide array of diseases. These diseases range from cancer to genetic inborn errors of metabolism. The company's innovative approach to therapeutics involves leveraging the natural capabilities of microbes to produce and deliver therapeutics in the body. However, the complexity of their work and the need for precise tracking and data management presented significant challenges.
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To address these challenges, Synlogic turned to Benchling, a unified informatics platform. Benchling developed a custom data model that maps to Synlogic’s unique workflows, enabling real-time experiment tracking and automating lineage tracking. This solution provided a much-needed structure to Synlogic's complex workflows and made it easier to trace the lineages of their candidates. Additionally, Benchling integrated Synlogic's instruments with the informatics requests system and bioreactors. This integration streamlined the process of placing requests and automatically associated results data with samples. As a result, Synlogic was able to streamline their IND filing process by using Benchling links in IND filings to provide full experimental history.
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Improved collaboration and reproducibility through the use of a unified informatics platform.
Enhanced traceability of candidate lineages through automated lineage tracking.
Streamlined request placement and data collation through integrated systems.
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