Ontotext’s New AI-powered Target Discovery Solution Enables Life Sciences Companies to Achieve 10x More Efficient Insight Discovery and 4x faster Information Retrieval

Ontotext, a trusted partner for many years for top 10 pharmaceutical companies, biotech startups and healthcare enterprises, announces the immediate availability of Target Discovery, an AI- powered platform that speeds the process of discovering new safe & efficient drug candidates. Already in place at leading top 10 pharmaceutical companies, biotech startups, and healthcare enterprises, Target Discovery empowers life science organizations to combine knowledge from all relevant sources, including public and proprietary data with AI-derived data from scientific publications, patents, and clinical trials.

Read More: The Practical Applications of AI in Workplace

Drug discovery and development is a long, costly, and high-risk process that takes over 10–15 years with an average cost of over $1–2 billion for each new drug to be approved for clinical use according to reports. With Target Discovery, scientists and researchers, translational biology professionals and bioinformaticians can bring together all the knowledge about biomedical entities, such as genes, proteins, compounds, into a centralized Knowledge Graph. The system then democratizes insight discovery through powerful search tools, data visualization and provides transparent analytics to aid data-driven decision making. Ontotext’s Target Discovery helps biomedical experts without any technical skills utilize powerful AI-based analytics for both target identification and selection with visibility over the algorithms.

Specific benefits of Target Discovery include:

• Generating AI-derived insights from scientific literature, patents and clinical trials
  By automatically extracting knowledge from more than 80 million documents, including patents and clinical trials, Target Discovery allows users to stay up-to-date with the latest discoveries. It also allows them to realize new insights, analyze data visually or with powerful algorithms, and leverage a vast network of knowledge for improved decision-making.

• Providing advanced and customizable analytics for target selection
  With customizable visual analytics and fully configurable dashboards, users can quickly gain an overview of a particular disease or target regardless of data type or source.

• Achieving impactful innovation through novel hypothesis generation and evaluation
  With advanced graph algorithms, Target Discovery helps identify hidden relationships from a network of over 5 billion facts so users can build sound highly confident biological hypotheses in minutes. Biomedical experts can leverage all analytics, including AI-powered ones, without any prior technical skills.

• Realizing transparent insight provenance and evidence — Improves confidence in critical decision-making processes by creating transparency over information and resulting analytics. With Target Discovery, organizations can achieve fact traceability better and present evidence on different levels, so users can trust their data instead of relying on potentially faulty ‘gut’ decision making.

AiThority: How AI Can Improve Public Safety

“Developing new treatments requires a complex understanding of disease mechanisms and the ability to identify the relationships between molecular and genetic factors in the context of a specific disease,” said Todor Primov, Head of Life Sciences Product and Solutions at Ontotext.

“However, this knowledge resides across multiple disparate sources and consists of different modalities which makes building a holistic view for a specific disease challenging. Leveraging Target Discovery’s built in knowledge graph technology, organizations can significantly lower the cost of bringing new drugs to market and shorten the time for novel insight discovery from integrated data.”

Latest Insights: What Techniques Will Deliver for Measuring Attention in 2023?

[To share your insights with us, please write to sghosh@martechseries.com]