How AI & Automation help Target Identification & Validation in Drug Discovery

An Intelligent OMICS & Arctoris Partnership

The ability of Artificial Intelligence (AI) to transform drug discovery is widely seen as one of the biggest disruptors within the biotech and pharma industry. Our partnership with Intelligent OMICS demonstrates a powerful example of how AI and automation enable faster and better target identification and validation for drug discovery.

Target Identification & AI

Target identification has previously relied upon manually combing through scientific literature to identify potential candidates for disease-drivers and druggable targets. The growth of relevant literature together with the development of high-throughput technologies, such as single-cell RNA sequencing, means there is a vast amount of information waiting to be analyzed. The sheer amount of data makes it practically impossible for humans to derive any insights, with computational (bioinformatics) approaches being the answer. AI builds upon these existing approaches by not only providing faster, more efficient analysis, but by unveiling patterns normally hidden from human observation. 

Indeed, Intelligent OMICS’ project to identify suitable drugs for lung cancer began by deploying their patented machine learning approach to analyze and integrate different types of biomedical datasets. This approach was able to not only identify novel targets, but also the biology underlying them by using explainable AI.

Target Validation & Automation

Once the in silico derived targets had been identified, they needed to be validated experimentally to ensure they are relevant to the disease. This is where Arctoris comes in, as a trusted partner to many of the world’s leading and emerging AI drug discovery companies. We partnered up with Intelligent OMICS to provide them with access to our sophisticated robotics platform, Ulysses, and our experienced scientists to design a target validation project to rapidly and reliably validate the targets. Data and insights generated during this project also informed the choice of drug candidates that were then also profiled in cell-based assay systems using Ulysses. 

This partnership demonstrated clearly that  by combining AI and automated experimentation, it is possible to  identify and validate 6 potential drugs for lung cancer in just 6 weeks. 

Read more about our partnership with Intelligent OMICS by downloading our case study here.

Image thanks to Tara Winstead over on Pexels.