实例探究 > Unlocking Pivotal R&D Answers While Ensuring Data Integrity

Unlocking Pivotal R&D Answers While Ensuring Data Integrity

公司规模
11-200
地区
  • America
国家
  • United States
产品
  • Benchling’s Bioregistry
技术栈
  • Data Management
  • Sample Tracking
实施规模
  • Enterprise-wide Deployment
影响指标
  • Digital Expertise
  • Productivity Improvements
技术
  • 平台即服务 (PaaS) - 数据管理平台
适用行业
  • 生命科学
适用功能
  • 产品研发
服务
  • 数据科学服务
关于客户
Obsidian Therapeutics is a biotechnology company that is developing a suite of technologies that allow for control of protein activity within cells to power therapeutics. The company is focused on creating transformative treatments for cancer and other serious diseases. Their work involves extensive research and development, and they rely heavily on data management and tracking systems to ensure the integrity and reliability of their experimental records.
挑战
Obsidian Therapeutics was facing several challenges with their previous Electronic Lab Notebook (ELN). The system was clunky and didn't allow for linkages to registered samples, which hindered adoption and experimental detail. Without a formal registration system, Obsidian scientists couldn't draw connections between results data and upstream entities. Their legacy sample tracking system was unintuitive and saw low scientist usage, leading to data loss and compliance concerns.
解决方案
Obsidian Therapeutics implemented Benchling’s Bioregistry, a unified informatics solution that integrated sample tracking and note-taking. This system generated strong user adoption and improved the quality and reliability of experimental records. With a centralized registration system, Obsidian can now trace from downstream results to identify effective upstream entities. This allows them to answer questions like, 'Why does this lentivirus work well? Is it related to a specific batch of constructs?' The robust Bioregistry also ensures that the constructs, parts, and other entities they’re tracking will hold up in a court of law.
运营影响
  • Improved user adoption of the data management system
  • Enhanced quality and reliability of experimental records
  • Ability to trace from downstream results to identify effective upstream entities
  • Increased confidence in the integrity of tracked data

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