Accelerating the discovery of multidomain proteins for next-generation cell and gene therapies
公司规模
11-200
地区
- America
国家
- United States
产品
- Benchling
技术栈
- Cloud Computing
- Machine Learning
- API
实施规模
- Enterprise-wide Deployment
影响指标
- Innovation Output
- Productivity Improvements
技术
- 分析与建模 - 机器学习
- 平台即服务 (PaaS) - 数据管理平台
适用行业
- 医疗保健和医院
- 生命科学
适用功能
- 产品研发
用例
- 机器状态监测
- 预测性维护
服务
- 云规划/设计/实施服务
- 数据科学服务
关于客户
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.
挑战
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.
解决方案
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.
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