Eliminating Drug Discovery Bottlenecks

By: Katana Graph

March 07, 2022

Eliminating Drug Discovery Bottlenecks

The volume of biological data available to the pharmaceutical industry now threatens the capacity of conventional data analysis methods. The common cheminformatics task of generating drug hypotheses, for example, always involves complex pipelines operating on multiple platforms in multiple environments. This process often includes sifting through historical literature, public databases, and previous research findings.

Drug Discovery Process

Most firms in the industry have invested in proprietary software for managing such data but have not been able to successfully integrate this software with other sources. For researchers trying to correlate results, the traditional tools, techniques, and resources available to them often combine into a convoluted process that is sometimes too time-consuming to justify the research. This problem isn’t limited to drug research, though; it applies to other aspects of the life sciences that rely on unstructured raw data—supply chain management, factory operations, market analysis, and more.

To reduce drug discovery time, life science researchers are now moving from cheminformatics pipelines based on disparate traditional relational data stores to massive, heterogeneous, fully integrated, graph-based solutions.

How Katana Graph™ is Helping

A platform that can quickly locate, identify, organize, and distill meaningful information from large volumes of data can bring new efficiencies from clinical trials to drug discovery.

To this end, Katana Graph developed an integrated graph-RDKit cheminformatics platform that allows complex cheminformatics workflows to be streamlined across large, heterogeneous, biomedical knowledge graphs. This allows cheminformatics researchers to run a drug-disease association query to extract a subset of simplified molecular-input line-entry system (SMILES) representation of compounds. These researchers can then conduct specialized searches to identify similar chemical compounds that are in current clinical trials.

By ensuring that relevant biological knowledge can be more easily and rapidly obtained from networks of data pertinent to each specific disease, Katana Graph is pioneering the application of graph intelligence technology in the life sciences industry. Katana Graph’s graph intelligence platform is elegantly designed for seamless mining, analysis, AI integration, and query.

For more information check out our Life Science Data Sheets:

Industry Overview: Health & Life Sciences

RDKit Integration

Get to Know Katana Graph

We thrive on testing new and diverse ideas.

Katana Graph was born of cutting-edge research and scientific rigor, and these beginnings have a powerful effect on who we are to this day. We’re devoted to problem solving, and are relentless in our pursuit of more effective and more efficient solutions to real-world challenges. Continuous improvement is the very foundation of our success.

Whether structured or unstructured data, Katana Graph can greatly improve the insights and opportunities uncovered from your organization’s data. Click to schedule a meeting.

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