Making a Breakthrough in Drug Discovery with AI

The discovery of drugs is a long and often an arduous process with the typical marketing time of 14 years, and the cost of the drug is billions. AI offers a way of accelerating development and reducing costs. The development of drugs depends in part on biomedical data. Such data are always highly complex, and the interactions between hundreds of biological entities are also complex.

Today, research at the cutting edge of cancer research involves billions of permutations which could occur. Some cancers grow every two seconds and never die; some grow 16 times every second and die every five days, and some grow every five days, never die. Each calls for a different approach, therapy, or management method.

Science and technology strive to understand the discovery of drugs. It is necessary to know how it works, how to control it, and how to avoid further imbalance in a patient.

Open source software is not available for the required analytical types, and proprietary algorithms are required. BioSymetrics uses AI to process raw phenotypes, imaging, drugs, and genomic data sets and enables researchers to integrate rapid analytics and machine learning capabilities into existing business processes to improve care, improve discoveries, gain business insight, and enable fast data-driven decision-making.

Cambridge Cancer Genomics, a U.S. research foundation, predicts cancer progression from tumor DNA in blood samples using AI technology. The technology allows researchers to determine earlier treatment response and relapse and to use Bayesian adaptive clinical trial design to increase the success of late-stage studies.

CytoReason, an Israel-based bioinformatics company, uses AI to organize and standardize immune-related gene, protein, cell, and microbiome data into a single cell-level, machine-readable immune system view. Company researchers can gain new insights into disease mechanisms, clinical markers, and drug discovery and validation.

Standigm uses state-of-the-art AI technologies to detect and develop drugs, understand how drug compounds interact with people in the real world. The current focus of the company is to forecast new indications for existing medicines. In EU, there is a legislative proposal for new regulations on medical devices, which offers software for medical devices with the purpose of prediction and prognosis.