Harnessing AI to create next-generation medicines
公司规模
51-200
地区
- America
国家
- United States
产品
- Absci Integrated Drug Creation™ Platform
- Benchling
技术栈
- Deep Learning AI
- Synthetic Biology
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
- 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
- 质量预测分析
服务
- 数据科学服务
关于客户
Absci is a drug and target discovery company that harnesses deep learning AI and synthetic biology to expand the therapeutic potential of proteins. Through its Integrated Drug Creation™ Platform, Absci is able to identify novel drug targets, discover optimal biotherapeutic candidates, and generate the cell lines to manufacture them in a single efficient process. Biotech and pharma innovators partner with Absci to create the next generation of protein-based drugs. The company is based in Vancouver, Washington, US, and has between 51 to 250 employees. They operate in the Biotechnology Research industry.
挑战
Absci, a drug and target discovery company, was facing several challenges in its operations. The success of their work heavily relied on coordination across teams. However, they were managing sample handoffs in spreadsheets, which not only had the risk of error but also lacked sophisticated collaboration features, making it difficult to share and reference data. Additionally, the performance of their AI models depended on the quality of the training data. They occasionally experienced data-related deviations such as duplicate or incomplete datasets and risked copy/paste errors. Lastly, they lacked a universally accessible tool for data connectivity, making it difficult for stakeholders to drive organizational and scientific decisions.
解决方案
Absci adopted Benchling to address their challenges. Benchling provided a formal request handoff data model that tracks sample handoffs and makes it possible to manage data in a way that is machine readable. This resulted in substantially improved operational efficiency in the laboratory. Benchling’s unique data model flexibility, API, and data warehouse capabilities allowed Absci to develop critical applications in the Benchling platform that enabled seamless integration with its distributed data model and application ecosystem. Absci uses Benchling’s custom registry schema to connect disparate data types, manage metadata associations, store experiment outcomes, and link to large quantities of raw data that they use to train AI models.
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