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Upcoming Symposium Applies Big Data methods to Cheminformatics and Retrosynthetic analysis

Posted on July 27th, 2018 by

Pharma R&D

Although the fields of cheminformatics and retrosynthetic analysis have been well established for a number of decades, there has recently been a large increase in applying methods from the world of Big Data and Predictive Analytics to the field of chemical reactions.

A symposium, led by Dr. Frederik van den Broek of Elsevier, will be devoted to these topics at the ACS National Meeting in Boston this August.  A series of global experts from industry and academia will discuss the latest developments in the field of chemical reaction analytics, whether by proposing novel synthetic routs, predicting optimal reaction conditions, or potential dead ends in a synthetic route. Also covered will be the topics of normalizing, mapping and joining reaction data from different sources, often essential precursors for reaction analytics.

The Reaction Analytics Symposium will be held in two sessions:

Session 1: Wednesday 22 August 2018, 1:30pm – 4:35pm EDT

Session 2: Thursday 23 August 2018, 08:30am -11:55am EDT

Location: Lewis Room, Westin Boston Waterfront Hotel

Please register for the ACS National Meeting to join this informative symposium.

Here is the current overview of the program:

Date Time Abstract Title Presenting Author Presenting Author Institution
22-Aug 13:30 Introductory Remarks
22-Aug 13:35 A brief history of Reaction Analytics Frederik van den Broek Elsevier, Amsterdam, Netherlands
22-Aug 14:00 Automatic discovery and enumeration of new tactical combinations Sara Szymkuc Institute of Organic Chemistry PAS, Warsaw, Poland
22-Aug 14:25 Intermission
22-Aug 14:40 Retrosynthetic software for practicing chemists: Novel and efficient in silico pathway design validated at the bench Lindsey Rickershauser Cheminformatics Technologies, MilliporeSigma, Chelmsford, MA, United States
22-Aug 15:00 Learning to Plan Chemical Syntheses Mark Waller Shanghai University, Shanghai, China
22-Aug 15:30 Intermission
22-Aug 15:45 Powerful algorithms in CASD systems: How important is the quality of the underlying data? Overview of results obtained with a transform library approach Valentina Eigner Pitto InfoChem GmbH, Munchen, Germany
22-Aug 16:10 Exploring the use of conditional generative adversarial networks (cGAN) to analyze chemical reactions via electron density fields Matthew Clark Elsevier, Philadelphia, PA, United States
22-Aug 16:35 Session close
23-Aug 08:30 Machine Learning and Continuous Flow: Detection and Correction of Flow-Incompatible Reaction Conditions Pieter Plehiers Laboratory for Chemical Technology, Ghent University, Ghent, Belgium
23-Aug 08:55 Predicting reaction conditions for computer-generated SAVI reactions by machine learning from reaction databases Victorien Delannée Natl Inst Health NCI Ft Detrick, Frederick, MD, United States
23-Aug 09:20 Intermission
23-Aug 09:35 Using Machine Learning to Recommend Suitable Conditions for Organic Reactions Hanyu Gao Chemical Engineering, MIT, Cambridge, MA, United States
23-Aug 10:00 Analysing Matched Molecular Pair Transformations in Drug Discovery Projects as a Function of Time and Molecular Environment Andreas Bender Chemistry Department, University of Cambridge, Cambridge, United Kingdom
23-Aug 10:25 Intermission
23-Aug 10:40 Regioselectivity: An Application of Expert Systems and Ontologies to Chemical (Named) Reaction Analysis Roger Sayle NextMove Software, Cambridge, United Kingdom
23-Aug 11:05 Representing organic reactions through InChI differences Martin Walker | John Paliakkara SUNY Potsdam, Potsdam, NY, United States
23-Aug 11:30 Automatically finding and fixing mistakes in detailed kinetic models of combustion Nathan Harms Department of Chemical Engineering, Northeastern University, Boston, MA, United States
23-Aug 11:55 Session Close

 

AI Can Work Wonders, But Can It Create Miracle Cures?

Posted on June 19th, 2018 by

Pharma R&D

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Modern technology seems downright magical at times. There are so many things that it can do for us at the push of a button, whether it’s our personal devices instantly retrieving information or massive industrial machines Continue reading “AI Can Work Wonders, But Can It Create Miracle Cures?” »

The Future of Chemistry R&D Will Depend on Deep Learning

Posted on June 7th, 2018 by

Pharma R&D

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A recent survey of chemists, carried out by Elsevier’s Reaxys team, showed that only 13% identified a familiarity with machine learning (or similar technologies) as being important for future chemists. Continue reading “The Future of Chemistry R&D Will Depend on Deep Learning” »

Cancer-killing combo: Viagra and the flu vaccine

Posted on June 6th, 2018 by

Pharma R&D

Cancer injection

“Strange bedfellows” doesn’t even begin to describe the drug combination that a new study published in OncoImmunology suggests may actually work together to combat cancer. Continue reading “Cancer-killing combo: Viagra and the flu vaccine” »

When Looking to Accelerate the Pace of Research, Having the Right Multidisciplinary Tools Matters

Posted on May 18th, 2018 by

Pharma R&D

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Have you ever heard the term “stay in your lane”? While it may be applicable in some workplaces, where people are expected to keep their focus narrow, these days it isn’t something you’ll hear much in pharmaceutical-related industries. Continue reading “When Looking to Accelerate the Pace of Research, Having the Right Multidisciplinary Tools Matters” »

Big Talks on Big Data are Coming to Bio IT World

Posted on May 9th, 2018 by

Pharma R&D

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At next week’s Bio IT World conference and expo (Boston, May 15-17), Elsevier will be giving four talks on the implications of AI and machine learning on life science research, a statistical analysis of concordance between animal toxicities and human adverse events, strategies for increasing data sharing and the latest technologies being used to integrate multiple data sources. Continue reading “Big Talks on Big Data are Coming to Bio IT World” »

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About this Blog

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The Elsevier Pharma R&D blog provides insight and opinion on topics related to pharmaceutical research and development, namely: big data, target identification, new drug discovery, drug safety monitoring, risk mitigation and regulatory compliance. We serve the community of chemists, scientists, drug safety specialists, educators and students interested in pharmaceutical R&D.

Editor’s note: The views and opinions expressed are those of the author and do not necessarily reflect the views of Elsevier,  its affiliates and sponsors or its parent company, Reed Elsevier.