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

   by Andrii Buvailo    5508

(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:  

[Interview] Adoption of AI-driven Tools By The Life Sciences Professionals: What Is Coming In 2018?

   by Andrii Buvailo    1406
[Interview] Adoption of AI-driven Tools By The Life Sciences Professionals: What Is Coming In 2018?

The previous year was rich in discussions and events one way or another related to potential applications of artificial intelligence (AI) advances for the benefit of drug discovery and development.

(Note: For the sake of simplicity, the term “AI” will be applied herein interchangeably with terms like “machine learning” (ML), “deep learning” (DL), “neural networks” (NN) etc., although conceptually, those terms are quite different in meaning. The term AI describes a field of computer science studying how to make a computer intelligent at doing something, while terms like ”machine learning”, “deep learning”, and “neural networks” relate to algorithms and methods by which it can be achieved.).

[Interview] The Current Status Of AI In Drug Discovery And Looking Forward Into 2018

   by Andrii Buvailo    3312
[Interview] The Current Status Of AI In Drug Discovery And Looking Forward Into 2018

Without a doubt, the area of artificial intelligence (AI) has been a sensation lately -- judging by the amount of hype around this topic. But the hype is not a guarantee of a real breakthrough, which is defined by facts and measurable achievements, not just loud statements.

The fact is, however, AI-driven systems managed to learn chess at a champion level in just 4 hours, and beat human champions in Jeopardy, and Go -- we all know that. And Facebook can recognize faces in a blurry photo where you are hanging out with a bunch of friends -- not worse than you (human) can do. You can try and see it for yourself anytime -- it works!

Three Insights For Immuno-oncology Drug Discovery

   by Alfred Ajami    5130

Immunotherapies are hot property. Immuno-oncology is the crown jewel. But the road to riches, and more importantly cancer cures, is now crowded and full of potholes. Drug hunters need to look ahead, beyond the discovery process itself, to the reality of the many impediments that will confront drug candidates as they proceed towards the clinic in today's landscape. Here, I present three insights from current events, the third one taking a contrarian position.