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

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Andrii Buvailo

Co-founder and Editor-in-Chief

Andrii Buvailo is a pharmaceutical industry analyst and writer, focusing on emerging companies (startups), technologies and trends in drug discovery, as well as R&D outsourcing. His articles were published on Forbes.com, and market research reports were referenced by some of the leading life science organizations.

Andrii is a Director of Ecommerce at Enamine Ltd -- a global supplier of fine chemicals and contract research services for the pharmaceutical industry. In this role he is involved in IT-management (ecommerce applications and systems), sales management and marketing activities, related to supporting drug discovery organizations across the globe with innovative chemicals and research services. Apart from his role at Enamine, he oversees BiopharmaTrend.com, and industry analytics consultancy.

He received a master's degree in Inorganic Chemistry and a PhD in Physical Chemistry from Kyiv National Taras Shevchenko University. He spent a year at Prof. Eric Borguet Group at Temple University Department of Chemistry developing gas sensor and biosensor systems, He also participated in numerous scientific projects in Ukraine, Belgium, and Germany (DAAD, Horizon 2020, NATO, CRDF grants), and published in high-impact research journals. Andrii has hands-on experience in structural and coordination chemistry, surface science, physical chemistry, nanomaterials and gas sensors, as well as bioinorganic chemistry. He received extensive theoretical training in molecular biology, medicinal chemistry, and computer-aided drug discovery.

   

Selected posts from Editor

Pharma R&D Outsourcing Is On The Rise

Pharmaceutical companies are increasingly outsourcing research activities to academic and private contract research organizations (CROs) as a strategy to stay competitive and flexible in a world of exponentially growing knowledge, increasingly sophisticated technologies and an unstable economic environment.  

The R&D tasks that firms choose to outsource include a wide spectrum of activities from basic research to late-stage development: genetic engineering, target validation, assay development, hit exploration and lead optimization (hit candidates-as-a-service), safety and efficacy tests in animal models, and clinical trials involving humans.

According to a report by Clearwater International (autumn 2019), the global CRO market will potentially rise to a $45 billion industry by 2022, as compared to an estimated $30 billion valuation (by Objective Capital Partners), exhibiting the current rate of market growth of around 10% CAGR with projected acceleration up to 12%. This is in line with Vantage’s alliance benchmarking study, revealing that over 80% of bio-pharma respondents reported increased alliance activity compared to previous periods. Getting ideas and expertise from external sources is a well-established practice in the pharmaceutical industry with about one-third of all drugs in the pipelines of the top ten pharmaceutical companies initially developed elsewhere, according to a 2014 WSJ article by Jonathan D. Rockoff.  

Top 7 Trends In Pharmaceutical Research In 2018

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.

How Big Pharma Adopts AI To Boost Drug Discovery

(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.  

Top AI in Pharma and Healthcare Conferences in 2020 You Can’t Miss

Artificial intelligence (machine learning and deep learning, to be more specific) has become widely discussed topics in the area of life sciences and healthcare over the last several years and the excitement keeps growing. While a lot of pharmaceutical companies and healthcare organizations express considerable interest in possible new opportunities, associated with the use of artificial intelligence for early drug discovery, clinical trial optimization, and business intelligence, a considerable gap still exists when it comes to understanding new technologies by pharmaceutical professionals and leaders. The key questions here are these:

  • What machine learning / AI can and can’t do for the pharmaceutical industry

  • What should be done to harness practical and measurable value out of machine learning / AI?

  • How it should be done and what are the timelines for getting returns on investments? 

19 Marketplaces for the Life Sciences Industry

(Last updated: 12.05.2020)

Online marketplaces are websites with a “many-to-many” business logic. They can host multiple suppliers trading with multiple buyers via different e-commerce tools available as a part of a website functionality.

Why are online marketplaces great?

Online marketplaces can provide a substantial added value to its users. For example, buyers can quickly compare and select better offerings without the need to research multiple websites and surf online for price comparisons or product specifications. Additionally, marketplaces bring more transparency, trust, and standardization to the whole process of sourcing.

Will Biologics Surpass Small Molecules In The Pharma Race?

The first biologics drug, humanized insulin (5.8 kDa), became available in 1982 following the advent of biotechnology, and it marked a new era in pharmaceutical industry. Modern advances in biotechnology permit large-scale syntheses of biologics in a more or less cost-effective manner. Having once started with large peptides and recombinant proteins, biologics nowadays include a wide range of other entities, such as antibodies, monoclonal antibodies, and more recently, nanobodies and related objects, soluble receptors, recombinant DNA, antibody-drug conjugates (ADCs), fusion proteins, immunotherapeutics, and synthetic vaccines.  

18 Startups Using Quantum Theory To Accelerate Drug Discovery

Molecular mechanics (MM) is a traditional computational approach when it comes to modeling in synthetic organic chemistry, medicinal chemistry and versatile aspects of drug design. However, MM methods have significant limitations, for example, when used to study electron-based properties within the drug-receptor microenvironment. Quantum mechanical (QM) methods allow to substantially increase the accuracy of predictions and provide much more relevant models of chemical and biological objects and their interactions, but QM methods are extremely (often prohibitively) computationally costly.

However, a series of advancements over recent years allowed to expand horizons in this direction, for example, the emergence of density functional theory (DFT), the overall increase in the computation power and the emergence of distributed cloud-based computational infrastructures.

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.

 

Pharma Companies Join Forces to Train AI for Drug Discovery Using Blockchain

The newly organized research project “MELLODDY” (Machine Learning Ledger Orchestration for Drug Discovery), involving ten large pharma companies and seven technology providers, is that kind of deals which can catalyze a transition of the pharmaceutical industry to a new level -- a “paradigm shift”, as one might refer to it in terms of Thomas Kuhn’s “The Structure of Scientific Revolutions”.

The project aims at developing a state-of-the-art platform for collaboration, based on Owkin’s blockchain architecture technology, which would allow collective training of artificial intelligence (AI) algorithms using data from multiple direct pharmaceutical competitors, without exposing their internal know-hows and compromising their intellectual property -- for the collective benefit of everyone involved.