BiopharmaTrend.com

A fresh viewpoint on drug discovery, pharma, and biotech

Subscribe | Become an author | Author LogIn

Topic: ‘Machine Learning’


2018: AI Is Surging In Drug Discovery Market

   by Andrii Buvailo    6426
2018: AI Is Surging In Drug Discovery Market

Updated: 14.12.2018. Newly added content is marked in the text with "Update" sign.

The idea of using artificial intelligence (AI) to accelerate drug discovery process and boost a success rate of pharmaceutical research programs has inspired a surge of activity in this area over the last several years. In 2018, things are getting even “hotter” with the increase in the amount of partnerships, investments and other important events, summarized and grouped below into “mini-trends”.

How Big Pharma Adopts AI To Boost Drug Discovery

   by Andrii Buvailo    16185

(Last updated 08.10.2018)

The type of artificial intelligence (AI) which scares some of the greatest minds, like Elon Musk and Stephen Hawking, is called “general artificial intelligence” -- the one which can “think” pretty much like humans do, and which can quickly evolve into a dangerous “superintelligence”. There is a notion that it might be invented in the nearest decades, but today we are definitely not there yet. The AI which is making headlines these days is a “narrow artificial intelligence”, a limited type of machine “intelligence” able to solve only a specific task or a group of tasks. It can’t go anywhere beyond specifics of the problem for which it is designed, so apparently, it will not hurt anyone in the nearest time. But already now it can provide meaningful practical results on those narrow tasks, like natural language processing, image recognition, controlling self-driving cars, and helping develop new drugs more efficiently. With the ability to find hidden and unintuitive patterns in vast amounts of data in ways that no human can do, AI represents a considerable promise to transform many industries, including pharma and biotech.  

Pharma and Healthcare AI Vendors Join Forces To Accelerate Progress In Drug Discovery

   by Andrii Buvailo    1274
Pharma and Healthcare AI Vendors Join Forces To Accelerate Progress In Drug Discovery

Today Basel is crowded with some of the top business and research leaders representing a young and rapidly growing industry of artificial intelligence (AI) in healthcare and pharmaceutical research. They come together to announce mission and launch activities of a global Alliance for Artificial Intelligence in Healthcare (AAIH), which is to become a leading international organization for advancing artificial intelligence innovations in Drug Discovery, Clinical Research, Diagnostics, Precision Medicine and other key areas of pharmaceutical research and healthcare. The newly formed alliance will be a voice of the industry in matters of education, lobbying for policies and regulations, facilitating investment, and promoting AI-innovations among top drug makers and healthcare institutions.

The “Why”, “How” and “When” of AI in Pharmaceutical Innovation

   by Andrii Buvailo    1635

(Edited version of this post originally appeared in Forbes)

“It is not the strongest of the species that survives, nor the most intelligent, but the one most adaptable to change” -- Leon C. Megginson

Last year brought about new hope and even more hype around the idea of applying artificial intelligence (AI) for “revolutionizing” drug discovery research -- via machines being able to “learn” chemistry and biology from vast amounts of experimental data to propose potent drug candidates, accurately predict their properties and possible toxicity risks. It is supposed to dramatically minimize failures in clinical trials -- saving R&D budgets, time, and most importantly, lives of patients.

How AI Is Applied To Metabolomics To Identify New Targets And Drugs

   by Andrii Buvailo    1763

The team at MIT created the most comprehensive database of metabolites, their interactions with proteins, protein-protein interactions, drug-protein interactions, and associations of metabolites with diseases. They then use the obtained interactions map to make inferences about the disease mechanisms and novel targets. With this new technology, the team launched a biotech startup ReviveMed in 2016 having raised $1.5M of funding so far.