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Case Studies > Accelerating the discovery of multidomain proteins for next-generation cell and gene therapies

Accelerating the discovery of multidomain proteins for next-generation cell and gene therapies

Technology Category
  • Analytics & Modeling - Machine Learning
  • Platform as a Service (PaaS) - Data Management Platforms
Applicable Industries
  • Healthcare & Hospitals
  • Life Sciences
Applicable Functions
  • Product Research & Development
Use Cases
  • Machine Condition Monitoring
  • Predictive Maintenance
Services
  • Cloud Planning, Design & Implementation Services
  • Data Science Services
The Challenge
Serotiny, a therapeutic discovery company, was facing challenges in managing their research data and processes. They were using a collection of Microsoft products to keep track of protocols, experiments, samples, and results. However, these tools were not designed for biotech R&D, making it difficult to organize and find past samples or results. The lack of easy-to-use templates meant that teams often had to write new protocols from scratch, taking precious time away from research. Additionally, their legacy molecular biology tools were clunky and did not integrate with their other systems, leading to tedious, slow, and error-prone copy/paste actions.
About The Customer
Serotiny is a therapeutic discovery company that designs new genes for next-generation cell and gene therapies. Their goal is to design new treatments for cancers and genetic disorders. To do so, they have developed proprietary technology to create high-throughput, multi-domain proteins with novel functionalities. The company is based in South San Francisco, CA, and has between 11 to 50 employees. They operate in the biotechnology research industry.
The Solution
Serotiny implemented Benchling, a modern, centralized cloud solution designed for biotech R&D. This unified suite of applications connects sequence design & analysis, sample management, and experimental record keeping in the same platform, accessible by API. Benchling's global search feature surfaces all previous experiments, results, biological entities, and their physical locations in the lab, leading to more efficient, informed decisions. The platform also allows Serotiny to collaborate in real-time within the platform and unlocks the ability to search and interact with data across teams and experiments, driving optimization across scientific workflows.
Operational Impact
  • Improved data quality through standardization and centralization of all research data in one platform.
  • Access to scientific and operational insights drive faster and better decision-making.
  • Real-time collaboration within the platform, allowing interaction with data across teams and experiments.

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