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invoX Pharma and Insilico Medicine partner to enhance R&D using AI

24 April 2024 | News

To utilise Insilico’s target discovery engine, PandaOmics, in conjunction with invoX’s own drug research and development expertise

image credit- shutterstock

image credit- shutterstock

invoX Pharma, a UK-based research-driven global biopharmaceutical company with an advancing pipeline of innovative products, and Insilico Medicine, a China and US-based clinical stage artificial intelligence (AI)-driven drug discovery company, have entered a new strategic collaboration to combine Insilico’s computational services and AI with invoX’s drug discovery, development and data science capabilities.

The aim of the collaboration is to enhance research and development (R&D) activities for invoX by identifying potential novel indications for pipeline assets in oncology. 

The collaboration will utilise Insilico’s target discovery engine, PandaOmics, in conjunction with invoX’s own drug research and development expertise, to identify new potential indications of interest for existing assets in invoX’s pipeline. These potential indications will then undergo further investigation.

Insilico’s PandaOmics is an AI-driven target discovery platform that applies deep learning models to identify therapeutic targets associated with a given disease. The system draws from millions of data points to identify the most promising indications and potential drug combinations. It further refines its selection through analysis of attention metrics, discovery trends, relevant data from Key Opinion Leaders, and chemistry databases. invoX will leverage this technology platform for its target discovery activities.

AI models arising from the collaboration will be applied to a range of use cases of which the first two are in execution. The companies are taking a platform approach to AI where a set of large models are trained for multiple tasks. This will allow new projects and use cases to be initiated on a continuous basis throughout the multi-year collaboration between the companies.

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