How AI is Helping Discover New Drugs

The uses for artificial intelligence (AI) are increasing everyday. One of the latest developments is the use of AI for the creation of new pharmaceutical drugs.

Biovia, a bioscience research company has developed a system for discovering molecular compounds which may be good drug candidates. This means therapeutics (even for rare diseases) could be developed faster, less expensively and with higher rates of success.

Their method of AI assisted pharmaceutical development is accomplished using a critical combination of both virtual and real experimentation cycles which feed into one another.

AI is able to generate ideas for new compounds which are virtually tested, scored and pruned so that only viable candidates are suggested for real testing, analysis, design and creation. Then physical lab tests are done and fed back into the machine learning.

Combining AI generated ideas with physical lab testing methods can increase drug discovery speed as much as 50% by minimizing the number of experiments and shortening the required testing time. It's an ever improving cycle of human and machine learning feeding into eachother.

These AI advancements are enabling scientists to test massive chemistry data sets for viable pharmaceutical solutions at a scale never before possible. Until recently, this quantity of experimentation has been too costly and essentially unimaginable at this scale.

Virtual molecule testing means physical testing is more targeted, which means drugs can be discovered faster and less expensively. Safety for human trials is also increased with this extra addition of machine learning.

Biovia also streamlines the physical testing with software to improve with the process of creating, organizing and tracking utilization of samples, lab materials and more.

More and more companies are utilizing AI for generating healthcare solutions. There is a good chance that diseases, disorders and ailments of all kinds which were once thought to be incurable could, in fact, be cured with the increased productivity of AI-powered research.

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