87520Evaluation of an In silico pipeline for drug discovery – a sustainable alternative model to laboratory based – drug discovery without borders.ClosedCollaborative R&DInnovate UKDrug discovery is an expensive, time consuming, and unsustainable process requiring large teams, significant use of animal models, and extensive physical laboratory resources. The process is also prone to failure because many of the methods used are unrepresentative of the disease state or organism being targetted. Despite the significant investment of biological, technical, and financial resources into the High Throughput Screening (THS) process, the drop off rate is high with few contenders even reaching trials in human subjects. This resource requirement has meant that drug discovery has been significantly impacted by the COVID-19 pandemic and subsequent lockdown of laboratory staff. We believe there is an alternative to this process using computer-based artificial intelligence-driven approaches here termed biologically driven In silico high throughput screening and drug discovery. With the MDC we are constructing a drug discovery pipeline based on existing artificial Intelligence in silico (computer-based) tools. These will be utilised in this project to identify alternative druggable targets for the KRas related pathway in lung cancer. This will be achieved through the application of the pipeline to high dimensional molecular data (transcriptomic) for lung cancer held in public repositories. We aim to identify a number of druggable contenders and associated small molecule-based compounds that can target these. We also will seek to validate the biological relevance of these through rapid automated cell line validation. The validation of this process will provide an alternative cost-effective sustainable approach to drug discovery which can be used with minimal resource constraints, reduced environmental impact, reduced costs, reduced use of animals, and human disease targetting. Thus we will circumvent many of the limitations of current HTS approaches. This will open up further opportunities for new cost-effective drug discovery allowing drugs to be developed in areas where there has traditionally been a lack of investment, such as rare or orphaned diseases.