HPC for Cancer Drug Accuracy
Presentation of the problem and objective of the experiment
Many cancer patients fail to respond to their drug treatment, resulting in heavy human and economic loss. This lack of efficacy is mainly attributed to host/tumour variations at the genetic and molecular level, which clinical practice still struggles to integrate. The experiment we propose aims to deliver a tangible solution for boosting the development of the personalized response prediction tool Allied Intelligence for Drug Accuracy AÏDA. This tool will consist in an intelligent diagnostic platform able to analyse the molecular profiles of cancer patients and identify the drugs most likely to achieve high effectiveness.
Short description of the experiment
This experiment is based on an extensive analysis of a huge volume of publicly available chemosensitivity and omics data, by using a state-of-the-art AI platform, namely JADBio, developed by one of the partners of the consortium and specialized in automatic machine learning. HPC will play a vital role in the experiment, allowing the execution of experiments that would require a prohibitive amount of time on less performing computational architectures.