Finalist
Big Data for in Silico R&D: Visualizing label expansion opportunities
Summary of work
Manual identification of potential new indications for licensed medicines is challenging, time-consuming and expensive. In response to this, following multiple workshops with our client, we built the IN-SIGHT virtual R&D platform, an in silico drug discovery tool that integrates over 20 data sources, leveraging artificial intelligence (AI) to derive meaningful analytics efficiently. IN-SIGHT allows our client to scope new label extension opportunities for existing products, identify portfolio gaps and assess the competitive landscape. IN-SIGHT has the potential to transform the way existing drug product portfolios are assessed.
One component of the platform, IO-MAP (Interactive Overlapping Mechanisms of Action Plot), integrates multiple data sets in a novel interactive data visualization. More than a visualization, the tool allows users to interrogate the underlying database and, based on overlapping drug mechanisms of action, surface potential repurposing opportunities and explore the underlying evidence for a specific drug or a mechanism of action in the potential new indication. In this way, IO-MAP is able to uncover hidden opportunities and provides a unique drug differentiation method, allowing a global panel of experts to screen potential new indications rapidly and effectively.
Judges’ comments
This entry demonstrated clear purpose, goals and approach that delivered an innovative AI-based tech solution and a tangible product. An impressive entry and a really interesting idea - well constructed and impactful.