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

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MedChem


Enamine Ltd. Released Coronavirus Library to Support COVID-19 Research Programs

   by Yuliia Bakanovych    85
Enamine Ltd. Released Coronavirus Library to Support COVID-19 Research Programs

A preplated library of 16800 compounds designed for the discovery of new SARS-CoV-2 and pan-Coronavirus antivirals

KIEV, Ukraine -- Enamine Ltd., a leading chemical research organization and producer of the world’s largest collections of novel building blocks (225,000+) and screening compound libraries (2,740,000+), today announced the release of the Coronavirus Library. The new screening library capitalizes on Enamine’s decades of chemical R&D, advanced library design expertise, and experience with creating focused antiviral libraries. Enamine is a participant of a global Open Science initiative “COVID Moonshot”, aimed at discovering novel therapeutics against SARS-CoV-2.

Chemspace collaborates with ChemAlive

   by Kateryna Shtereverya    289
Chemspace collaborates  with ChemAlive

Chemspace and ChemAlive (the largest repository of quantum chemical data, a Contract Research Company that develops software products to obtain accurate and reliable data on molecular properties, synthetic reactions, verification of molecules using quantum chemistry), announced the launch of the collaboration to provide accurate molecular structural information about commercial small molecules.

How Latest Drug Candidates Were Discovered? (Retrospective Review, 2016-2017)

   by Andrii Buvailo    4038
How Latest Drug Candidates Were Discovered? (Retrospective Review, 2016-2017)

Recently D.G.Brown and J.Boström of AstraZeneca published an insightful analysis, where they reviewed lead generation research strategies behind 66 small molecule clinical candidates published over 2016-2017 in Journal of Medicinal Chemistry.  

Below is a brief summary of some key statistics and ideas outlined in the work (I encourage reading the original paper, it contains a ton of valuable insights and a strong list of references).

A Clear Example of AI Value For Drug Discovery Has Arrived

   by Andrii Buvailo    4901
A Clear Example of AI Value For Drug Discovery Has Arrived

With all the hot discussions (for instance, here, here, here and here) going on right now among medicinal chemists, pharmaceutical researchers, and data scientists as to what artificial intelligence (AI) means for the future of drug discovery, the life science world has divided into “AI-believers”, “AI-atheists”, and “AI-agnostics”.

It is useless to repeat what has been many times said about successes of AI in areas like natural language processing, image processing, pattern recognition and self-driving cars (here is the summary), but few of us knew if those sort of results (or any meaningful results at all) could possibly be achieved with such complex systems as biological organisms… Finally, however, a hint of hope arrived.   

A Brief Guide To Assay Technology For Efficient Drug Discovery -- Part 1

   by Alfred Ajami    3417
A Brief Guide To Assay Technology For Efficient Drug Discovery -- Part 1

Effective drug discovery begins with the right assay, but the definition of "right" will shift as technology advances. More often than not, "right" is the product of tribal knowledge, namely the traditions of one's close peer group, study lineage and corporate culture. Instead, the right assay should be a fit-for-purpose application born of  a broader, continuously updated, and unbiased consensus. As Steve Hamilton, aka The Lab Man, at the Society for Laboratory Automation  and Screening (SLAS) has often stated in his blog posts, "developing assays – properly – is the cornerstone for life sciences R&D."