Teaming up with a trailblazer to develop next-gen drug discovery
公司规模
Startup
地区
- America
国家
- United States
产品
- Benchling
技术栈
- DNA encoded library (DEL) technology
- Machine Learning
- Next-gen sequencing (NGS)
实施规模
- Enterprise-wide Deployment
影响指标
- Productivity Improvements
- Innovation Output
技术
- 分析与建模 - 机器学习
- 应用基础设施与中间件 - 数据交换与集成
适用行业
- 药品
- 医疗保健和医院
适用功能
- 产品研发
- 质量保证
用例
- 质量预测分析
- 预测性维护
服务
- 数据科学服务
关于客户
Anagenex is a drug discovery company that combines DNA encoded library (DEL) technology with machine learning (ML) to achieve their vision of finding a drug candidate for every disease cheaply and quickly. Their goal is to radically accelerate the traditionally time- and labor-intensive portion of drug discovery with a fast and powerful approach based on combinatorial chemistry, machine learning and rapid, large scale iteration. They’ve relied on Benchling from day one, capturing every intermediate data point to ensure that their computational systems get a complete picture of lab processes. The company is based in the Bay Area, CA and has between 1-10 employees.
挑战
Anagenex, a drug discovery company, is combining DNA encoded library (DEL) technology with machine learning (ML) to accelerate the traditionally time- and labor-intensive portion of drug discovery. However, they faced several challenges. Treating DNA sequencing readouts as an intermediary step to understanding the molecule of interest is an indirect use case, creating an additional layer of complexity. Each experiment can introduce batch effects that mask the biologically relevant effects and confuse the machine learning process. Anagenex needed a robust solution that could start tracking from the very first experiments and scale quickly as the company grows.
解决方案
Anagenex chose Benchling to make sure they would have a digital lab solution that could keep up with its team’s fast pace and cutting edge science. Benchling allowed Anagenex to create a custom data schema in their Benchling Registry that mapped the parent-child relationships between DELs, the DNA tags identifying the building blocks of each DEL, and the pools each DEL was added to. This helped them decode DNA sequencing readouts. Anagenex also used templatized registration in Benchling to lower friction to data entry, keeping scientist compliance up and data records clean and complete. This standardized data entry sped up their ML workflows despite high volumes of data because no extra data cleaning was required.
运营影响
数量效益
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