The recipients of the additional funding, according to Laboratory News, are the software company Optibrium, artificial intelligence firm Intellegens, and the healthcare organization Medicines Discovery Catapult. The three bodies have been issued with grant from Innovate UK to fund a £1 million ($1.3 million) scheme designed to tap into the power of artificial intelligence.
The funding will be used to run a project whereby the consortium set to learn from complex data patterns and use the analysis as a roadmap for scientists in the design and testing of potential new medicines.
According to Matthew Segall, who is the Chief Executive Officer of Optibrium: “We will apply cutting edge deep learning methods and new data to address important challenges in drug optimisation. The funding from Innovate UK is important validation of our project team’s expertise and the impact it will have on the industry’s efficiency and productivity.”
Innovate U.K. is part of the U.K.’s innovation agency ‘U.K Research and Innovation’, which is a non-departmental public body funded by a grant-in-aid from the U.K. government. The remit includes, as the government agency self-defines: “We connect businesses to the partners, customers and investors that can help them turn ideas into commercially successful products and services and business growth…We fund business and research collaborations to accelerate innovation and drive business investment into research and development.”
With the new funding to the three companies, the intention is to apply artificial intelligence so that researchers can more easily shift through complex chemical data in the quest to develop new medicines more quickly. The drug development process is complex and time consuming, even before any candidate products are considered for clinical trial.
The three organizations are hoping to develop a process for providing more meaningful insights into how a medicine interacts with the human body. From this they hope to improve the efficiency and productivity of drug discovery.
The first project will deploy deep learning methods to design a next generation platform that should better predict the absorption, distribution, metabolism, excretion and toxicity (ADMET) of new drug candidates. ADMET describes the disposition of a pharmaceutical compound within an organism. The four criteria all influence the drug levels and kinetics of drug exposure to the tissues and hence influence the performance and pharmacological activity of the compound as a drug.