Startup unifies lab management to pave the way for Big Data analytics
公司规模
11-200
地区
- America
国家
- United States
产品
- Benchling Notebook
- Benchling Registry
- Benchling Inventory
技术栈
- Big Data Analytics
- CRISPR/Cas9
- Data Harmonization
实施规模
- Enterprise-wide Deployment
影响指标
- Innovation Output
- Productivity Improvements
技术
- 分析与建模 - 大数据分析
- 应用基础设施与中间件 - 数据交换与集成
适用行业
- 医疗保健和医院
- 生命科学
适用功能
- 产品研发
- 质量保证
用例
- 库存管理
- 预测性维护
服务
- 数据科学服务
- 系统集成
关于客户
Spotlight Therapeutics is a pioneering company in the field of cell-targeted in vivo CRISPR gene editing. They are creating a new class of programmable ribonucleoproteins called Targeted Active Gene Editors (TAGE). These modular biologic constructs are engineered to overcome the current limitations of viral and nanoparticle delivery. The company is an early adopter of Benchling, initially using just Benchling Notebook to record experiments. As they’ve grown and matured their technology, they’ve expanded their Benchling usage to eliminate manual inventory management, enable big data queries, and increase the speed of collaboration. The company is based in Hayward, CA and has between 11 to 50 employees.
挑战
Spotlight Therapeutics faced several challenges in their lab management. Their inventory management system was prone to human error and created bottlenecks as it was managed by a single person using spreadsheets. This was inefficient and led to errors. Additionally, they lacked a data infrastructure that would allow them to run big data analysis, which was crucial for their discovery platform. Their data lacked the structure and standardization necessary for big data analytics. Furthermore, their unconnected note-taking, lab management, and data interpretation systems encouraged siloed work rather than collaborative work.
解决方案
Spotlight Therapeutics implemented Benchling Registry and Inventory to automate their manual inventory management process. This empowered the team to track usage and availability of common reagents, reducing administrative time and freeing up time for scientific progress. They also unified naming conventions and established standard fields for data capture. With uniform data fields, the team could quickly query across all affinity experiments to find patterns and trends. This set up a clear structure for their data, opening up a world of interesting questions that Spotlight could now explore. The standardized data also had benefits beyond data analysis. It provided a reliable framework to store and share data, which was key to tracking continuous scientific progress, crucial for attracting future investors. Standardized data capture, coupled with custom tools built on Benchling’s APIs, also saved scientists time both for uploading new data and gathering insights.
运营影响
数量效益
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