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Topic: ‘Machine Learning’


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

   by Andrii Buvailo    361

(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.

Top 7 Trends In Pharmaceutical Research In 2018

   by Andrii Buvailo, Alfred Ajami    2664

Being under ever-increasing pressure to compete in a challenging economic and technological environment, pharmaceutical and biotech companies must continually innovate in their R&D programmes to stay ahead of the game.

External innovations come in different forms and originate in different places -- from university labs, to privately held venture capital-backed startups and contract research organizations (CROs). Let’s get to reviewing some of the most influential research trends which will be “hot” in 2018 and beyond, and summarize some of the key players driving innovations.

Applying Artificial Intelligence And Bioinformatics To Create “Instagram” Of Immune System

   by Andrii Buvailo    1064

Nowadays, the brightest innovations usually happen at the intersection of different disciplines and technologies. A recent scientific achievement by Dr. Carsten Krieg, a researcher at Hollings Cancer Center (HCC), Medical University of South Carolina, is not an exception to this observation.
With an ambitious goal in mind to advance the field of cancer immunotherapy, Dr. Krieg combines a very powerful analytical technique -- mass cytometry, with artificial intelligence (AI), machine learning and bioinformatics tools to visualize the obtained experimental data and have a bird’s-eye view of the immune system.

2018 Brings A Surge Of Activity In The “AI For Drug Discovery” Space

   by Andrii Buvailo    3391

(Last updated: 15.03.2018)

The idea of using artificial intelligence (AI) to accelerate drug discovery process and boost a success rate of pharmaceutical research programs has inspired a notable amount of activity over the last several years with a considerable number of initiated research collaborations between AI-driven R&D vendors and top pharmaceutical companies in 2016-2017.

(For a detailed review of the topic, read Biopharma’s Hunt For Artificial Intelligence: Who Does What?).

A busy beginning of 2018 shows that the area is getting even “hotter” and things start unfolding faster in the emerging “AI for drug discovery” space. Below is a brief summary of some of the most notable events of this year so far: