TechBio Discovering Inhibitors of Previously Undruggable Targets to Treat Cancer

Industry: Drug-Discovery

No. of employees:


Cancer cells use transcription factors to give themselves the superpowers they need to grow and spread. So it makes sense to block transcription factors to treat cancer. This approach has been successful with hormone receptors—estrogen and progesterone receptors are well known targets for breast cancer drugs. But most transcription factors are considered undruggable because they are unstable outside of the nucleus and they don’t have well-defined binding pockets for small molecule drugs.

Seattle-based digital biotech company Talus Bio has found a new way to study transcription factors. Instead of taking the proteins out of cells for drug studies, Talus monitors their activity in live cells in response to treatment. The company’s MARMOT drug discovery platform uses live cells, automated cell processing, and next-generation functional proteomics to identify compounds that target previously undruggable gene regulatory proteins, like transcription factors.

“We measure if a drug affects the binding of a transcription factor to DNA, and if it's inhibiting and degrading that transcription factor.”  Lindsay Pino, Co-Founder & CTO at Talus Bio.

The Challenge: Integrating and Sharing Big Data

Talus Bio uses very large proteomics sample sets and their experiments generate huge data sets. They needed an integrated solution to manage their proteomics samples, data, and metadata. Their wet-lab and dry-lab teams needed to be able to seamlessly share data and metadata. 

The Solution: A Bespoke Proteomics Sample Manager

So Talus Bio used Scispot to build a personalized proteomics sample manager, which they now use to design experiment templates and workflows, as well as store all of their result data and metadata. Scispot’s unified OS helps Talus Bio to connect various aspects of their experiment metadata. As a result, they can track the complete experiment metadata journey for their proteomics workflow. 

Lindsay Pino, Co-founder and CTO, Talus Bio, and the Talus Bio team, used Scispot to build a personalized proteomics sample manager.

Scispot has built-in connections between various databases (called Labsheets) that help track aliquots, derivatives, and their relationships with the parent sample. This offers comprehensive sample tracking and management linked with Scispot notebook. Here is an example knowledge graph that scientists can create from experiment metadata:

Example knowledge graph created from metadata that was automatically collected and integrated by Scispot.

With Scispot, Talus Bio can be sure that their data and metadata are all in one spot and available for all team members to work on. They can standardize workflows and automate data collection, saving time and ensuring data is never lost. 

“We are a growing TechBio company so we need flexible solutions to manage our data and metadata. With Scispot, we could build our proteomics sample manager to do exactly what we need.”  Lindsay Pino, Co-Founder & CTO at Talus Bio.
To learn more about how you can centralize company-wide data, templatize routine research, and automate non-scientific tasks with Scispot,
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