Life Sciences Companies Can Achieve 10x More Efficient Insight Discovery And 4x Faster Information Retrieval With Ontotext’s New AI-Powered Target Discovery Solution

Target Discovery, an AI-powered platform that accelerates the search for new, effective medication candidates, is now immediately available from Ontotext, a long-time valued partner of the top 10 pharmaceutical firms, biotech startups, and healthcare organisations. Target Discovery enables life science organisations to combine knowledge from all pertinent sources, including public and proprietary data, with AI-derived data from scientific publications, patents, and clinical trials. It is already in use at leading pharmaceutical companies, biotech startups, and healthcare enterprises.

According to studies, it takes more than 10–15 years and costs an average of over $1–2 billion for each new drug to be licenced for clinical usage. Drug research and development is also a time-consuming, expensive, and risky process. Target Discovery enables researchers, scientists, translational biologists, and bioinformaticians to compile all the knowledge they have about biological entities like genes, proteins, and chemicals into a single knowledge graph. The system then makes it easier for anybody to find insights by providing robust search capabilities, data visualisation, and open analytics to support data-driven decision-making. With visibility into the algorithms, Ontotext’s Target Discovery enables biomedical experts to use strong AI-based analytics for target selection and identification.

Benefits of target discovery in particular include:

AI-derived insights from clinical trials, patents, and scholarly publications:
Target Discovery helps customers stay abreast of new discoveries by automatically extracting knowledge from more than 80 million documents, including patents and clinical trials. They can also gain fresh insights, analyse data graphically or using strong algorithms, and draw on a wide knowledge network to make better decisions.
Providing target selection with cutting-edge, customizable analytics:
Regardless of the data format or source, users can rapidly get an overview of a specific condition or goal thanks to fully customizable dashboards and visual analytics.
Impactful innovation through the invention and assessment of fresh hypotheses:
Target Discovery uses sophisticated graph algorithms to find hidden associations from a network of over 5 billion facts, enabling users to quickly construct strong, highly confident biological hypotheses. Without any prior technical knowledge, biomedical experts may utilise all analytics, including AI-powered ones.
Realising transparent evidence and insight provenance: It increases trust in important decision-making processes by establishing openness over the data and the analytics that come from it. Target Discovery helps organisations better accomplish fact traceability and display evidence at various levels, enabling users to put their trust in their data rather than depending on possibly flawed “gut” decisions.
According to Todor Primov, Head of Life Sciences Product and Solutions at Ontotext, “developing new treatments requires a complex understanding of disease mechanisms and the capacity to identify the relationships between molecular and genetic factors in the context of a specific disease.”

“However, because this knowledge is spread across numerous dissimilar sources and consists of various modalities, it is difficult to develop a comprehensive understanding of a particular condition. Organisations may dramatically reduce the cost of bringing new pharmaceuticals to market and reduce the time for fresh insight discovery from integrated data by utilising Target Discovery’s built-in knowledge graph technology.