A Landscape of Artificial Intelligence (AI) In Pharmaceutical R&D

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Biopharma Insights


The Overview of AI in Drug Discovery in 2019: The “Proof-of-concept Year”

   by Andrii Buvailo    6461
The Overview of AI in Drug Discovery in 2019: The “Proof-of-concept Year”

The race for adopting new machine learning (ML), deep learning (DL) and related technologies (for simplicity -- “artificial intelligence”/”AI”) keeps rapidly unfolding in the pharmaceutical industry, albeit with varying rate of progress across different use cases

Let’s review retrospectively some of the key developments in the drug discovery area in 2019 and see how they characterize the current state of AI in the pharmaceutical industry (“hype vs reality”). Note, that I do not cover the healthcare sector in this post (diagnostics, medical applications of AI, digital health etc) -- those will be discussed in one of the future posts.

 

Becoming Pharma 4.0: How Digital Transformation Is Reshaping Pharmaceuticals

   by Tim Sandle    8473
Becoming Pharma 4.0: How Digital Transformation Is Reshaping Pharmaceuticals

The digital transformation of biopharmaceutical manufacturing is continuing at a rapid pace as companies attempt to mine the sources of data available. Innovations include predictive analytics, big data analytics, and creating the digital plant. Digital transformation offers a mechanism to revise its business model, to improve production processes, to design new drugs faster by using artificial intelligence to screen compounds and to increase responsiveness to customers. Furthermore, the volume of data processed by pharmaceutical firms shows no sign of slowing down. This means pharmaceutical companies must act quickly in terms of building core internal digital capabilities and moving beyond their traditional IT functions to all areas of the business.

 

The Growth Imperative: Why The Next Big Pharma Competitor Could Be Google Or Apple

   by Jacob LaPorte    864
The Growth Imperative: Why The Next Big Pharma Competitor Could Be Google Or Apple

In a seminal work published by McKinsey & Company – The Granularity of Growth, a detailed study of the performance of the 100 largest US corporations over the two most recent business cycles – a key finding emerged: top-line growth is vital for survival.

To dig a bit deeper, the study found that a company whose revenue increased slower than the growth of U.S. GDP was five times more likely to falter in the next cycle than a company that expanded more rapidly. Companies have a “Growth Imperative,” which is to either “grow or go,” the authors concluded; in other words, companies must grow faster than their peers or else be left behind.

Toronto AI Startups Aim High in Drug Discovery Space

   by Andrii Buvailo    3486
Toronto AI Startups Aim High in Drug Discovery Space

According to a report by the Advisory Council on Artificial Intelligence of Canada, this country is home to more than eight hundred artificial intelligence (AI) companies, and the number of AI startups is growing by about 28% each year.

This is due to quite favorable conditions, that Canada offers to local and foreign AI-focused talent and organizations. Not only the country is a strong global leader in artificial intelligence research, with some of the most cited academics working here (Yoshua Bengio and Geoffrey Hinton -- pioneers of modern AI), but also the government is quite active in pushing Pan-Canadian Artificial Intelligence Strategy, aiming at supporting AI research and talent attraction and retention in Canada.