TetraScience
Centralize Scientific Data, Enhance Research Efficiency

"We have observed a new mindset in drug development called the ‘digital biotech;' whether it’s a big pharma company or a small biotech company, these organizations are adopting new approachs which emphasize being data driven, agile, and collaborative,” begins Alok Tayi, PhD CEO of TetraScience. However, in the life sciences industry, data is scattered over numerous places, from instrumentation inside laboratories to software databases to external collaborators such as CROs and CMOs. "In such a complex and heterogeneous scenario, there are a multitude of business problems that need to be resolved.” While finding and analyzing data from numerous sources is a daunting task, entering data manually from one system to another hinders the overall research and drug development process. At a higher level, it leads to difficulty in learning from historical data, tracking projects and in using the data for mission-critical projects like NDA filings for the FDA.

As a true innovator in the life sciences industry, TetraScience provides a cloud-based Data Integration Platform that centralizes data from disparate sources inside an organization into a single repository. Common data sources integrated include chromatography systems, ELN/LIMS, and file-based instruments. "We believe that data is the lifeblood of the life sciences industry as it’s essential for making scientific and organizational decisions. We are empowering companies to effectively use their data," says Tayi. Eliminating the problems of siloed applications, TetraScience enables pharma and biotech companies to be more productive, compliant, and consistent by giving them the ability to monitor, track, and interact with data. APIs at the back end of the Platform facilitate movement of data from instruments and labs to users and management, allowing visualization and analysis of data through a single dashboard in real time, from anywhere.

As data is collected, TetraScience’s Lab Monitoring solution allows monitoring of clients’ instruments such as incubators and freezers. Using integrated sensors, the company enables clients to keep an eye on all their instruments in real time with an intelligent dashboard and alerting system. Clients can also gain insights into the usage of capital instrumentation and the way their labs are operating through TetraScience’s Instrument Utilization.

We want to help life sciences companies drive their enterprise data strategy by automating the collection and analysis of scientific and operational data

The solution provides meaningful reporting and analytics on instrument usage and helps save money on unused equipment and service contracts. “We leverage the power of our Data Integration Platform not only to connect data from various sources, but also to deliver specific value to customers as they continue with drug development,” remarks Tayi.

Serving numerous top-tier customers from the pharma and biotech field, TetraScience is a preferred solution provider when it comes to Data Integration services. One such happy client is a biotech company publicly traded at 150 billion dollars. They faced challenges around collecting and entering data in a timely and compliant fashion to perform analytics for manufacturing drugs. With the TetraScience Data Integration Platform, the client was able to extract data from their instrumentation in real time, standardize it, and automatically enter the data into their electronic lab notebook. “We helped them reduce the time from hours to minutes, ensure compliance with data accuracy, and make the best decisions around manufacturing processes. With our solution, the client was able to benefit from a 5x ROI.”

TetraScience is well aligned with the data strategy of for life sciences companies by enabling data collection and centralization. The company also works with customers to drive innovation in machine learning and artificial intelligence and apply it to the drug development process. “We want to help life sciences companies drive their enterprise data strategy by automating the collection and analysis of scientific and operational data,” concludes Tayi.