ACS Fall 2020 Virtual Meeting & Expo
Moving Chemistry from Bench to Market
In this extraordinary year, the ACS Fall 2020 National Meeting & Expo takes place virtually, providing access to myriad of talks, sessions, and Q&A panels to chemists around the world. Our new open access journals, recent books and chemical research solutions provide fundamental resources for your research needs. Elsevier is proud to continue supporting and empowering researchers in the chemical sciences.
We’re delighted to congratulate Professor Peter Schultz, the recipient of the 2019 Tetrahedron Prize for Creativity in Organic Chemistry.
Tetrahedron Special Issue in Honor of Peter Schultz
This Bioorganic and Medicinal Chemistry Special Issue celebrates the research and career of Peter Schultz of Scripps Research, the recipient of the 2019 Tetrahedron Prize for Creativity in Organic Chemistry.
Join us for a full program of speaker sessions as part of the Tetrahedron Prize Symposium
Join Elsevier experts, Dr. Friedrich Kroll, Dr. Jürgen Swienty-Busch, Dr. Camilo Thorne, Dr. Frederik van den Broek and Dr. Matthew Clark, in their presentations at ACS Fall 2020 Virtual Meeting, as they discuss chemistry databases, cheminformatics, research workflows, AI, and much more.
1. Combining artificial intelligence with structured high-quality data in chemistry – delivering outstanding predictive chemistry application
Dr. Jürgen Swienty-Busch, Director Product Management, ElsevierRead the abstract
Reaxys and its predecessors Beilstein, Gmelin and Patent Chemistry have served the chemistry community well with scrutinized, high quality chemical information over the last 150 years. Reaxys is typically used by bench chemists whose focus is on synthetic chemistry, however, Reaxys Medicinal Chemistry, a companion of Reaxys, is also becoming an essential tool for medicinal chemists in drug discovery workflows. With advancements in machine learning technologies and improvements in computing power, new applications are envisioned, and some are already in place, which leverage the vast amount of Reaxys chemistry data readily available in a structured machine-readable format. This talk will discuss new ways on how to provide developers, data scientists and computational chemists with access to this huge knowledge base and presents Reaxys Retrosynthesis Engine (Pending AI) as application in the field of predictive retrosynthesis with examples and recent developments.
2. Predicting reaction sequences: Deep neural networks & the Reaxys database
Wednesday, August 19, 2020 - 10:00 AM – 12:00 PM (PDT)
Dr. Friedrich Kroll, Senior Manager Scientific Affairs, ElsevierRead the abstract
This presentation will discuss how to discover new chemistries and the automated predictions of most feasible synthesis routes employing the Reaxys database. It will show case how deep neuronal networks predict new paths to known and unknown molecules successfully. Effective synthetic organic chemistry is based on several principal skills: i) envisioning all feasible synthetic steps and selecting the most suited ii) finding applicable procedures iii) mastering instruments and equipment iv) analyzing and drawing the right conclusions from reaction outcomes.  The complexity of such tasks explains why it takes several years to educate and enable chemists in this discipline successfully. Even then, non-yielding synthesis steps are part of the reasons why the amount of time to be invested is considerable higher than often expected - particularly in cases of complex molecules.
Reaxys is a software tool that contains well curated FAIR (Findable, Accessible, Interoperable, Reusable) scientific information and teaches chemists how to find and apply the right literature for chemical transformations, identify analytical information and most importantly educates, how to develop retrosynthesis schemes swiftly. The possibilities to evaluate and compare different routes, yields and conditions to molecules are exceptional and allow educators to illustrate retrosynthesis in organic chemistry classes on a day to day basis. 
Furthermore, computer-aided retrosynthesis tools, which can predict reactions to novel molecules correctly, are part of Reaxys. The ‘deep learning’, neuronal networks produce schemes of sequences of reactions needed to create the much-needed compounds. This novel AI tool has processed nearly every reaction ever published (> 15 million) and has the potential to transform the way organic chemists work in the future. In an assessment, various synthesis routes generated were tested in a double-blinded trial with 45 organic chemists from two institutes in China and Germany and the routes have proven to be scientifically sound and robust. This novel approach will lead to an increase of the success rate in synthetic organic chemistry and should have an enormous benefit in terms of discovering sustainable chemical solutions and minimizing expenditure. 
 Hoffmann R. W., Elemente der Syntheseplanung, 2006, ISBN-13: 978-3-8274-1725 https://doi.org/10.1007/978-3-662-59893-1
 Segler M.H.S.; Preuss M.; Waller M.P., Planning chemical syntheses with deep neural networks and symbolic AI. Nature. 2018 555(7698), 604-610. 10.1038/nature25978
3. ChEMU shared task: chemical entity recognition and event extraction of chemical reactions from patents
Dr. Camilo Thorne, NLP Scientist, ElsevierRead the abstract
We introduce a new chemical information extraction shared task, named ChEMU, part of the 11th Conference and Labs of the Evaluation Forum (CLEF-2020). ChEMU proposes two key information extraction tasks over chemical reactions from patents. Task 1 --- named entity recognition (NER) --- is to identify specific types of chemical compounds, i.e. to assign the label of a chemical compound according to the role for which the chemical compound plays within a chemical reaction. Task 2 --- event extraction over chemical reactions (EE) --- involves on the other hand event trigger detection and argument recognition. We will publicly release reaction-specific gold standards --- that we describe in this presentation --- derived from patent literature and annotated by chemists (for NER and EE, resp.) in early 2020. Thereafter academic or industrial teams working in the field will be encouraged to participate in a shared evaluation campaign, by developing and contributing NER and EE models. The models will be then evaluated (by measuring their recall, precision and F1 scores), compared and jointly discussed at CLEF-2020.
4. Data preparation for reaction prediction: the quest for “AI-ready” data
Dr Frederik van den Broek, Consultant, R&D Solutions, ElsevierRead the abstract
Many believe that Artificial Intelligence has the potential to revolutionize not only life sciences and healthcare, but also chemistry and chemical synthesis, which is why there has recently been a great increase in applying Machine Learning and Big Data-handling techniques to chemical synthesis.
Data preparation for synthesis routes’ predictions is often tedious and time-consuming due to variations in how the reactions data is stored in electronic laboratory notebooks or extracted from scientific literature, how reactions are annotated, stored and transformed to be usable for the modelling exercise.
This talk will give an overview of the data preparation, normalization and de-duplication challenges cheminformaticians and data scientists often face when preparing the AI/ML models. It will also focus on how one could prepare the ever-sought-after “AI-ready” data sets, using the right tools, conventions and chemical rule-sets.
5. Use of conditional generative adversarial networks (cGAN) with molecular orbital fields to study chlorination sites
Dr. Matthew Clark, Senior Director, Consulting, ElsevierRead the abstract
We have been studying use of 3D molecular orbitals of products and reactants as input to conditional generative adversarial networks (cGAN) to model organic chlorinations. Our previous work with electron densities has been extended to include nuclear density. The resulting cGAN then takes a 3D computed density and generates an image of the electronic structure and nuclear positions of the chlorinated product. The current status, successes, and limitations will be discussed.
Reaxys PhD Prize
Now celebrating its 10th anniversary, the Reaxys PhD Prize recognizes accomplished young chemists for their innovative and rigorous research. Join us for the first virtual Reaxys PhD Prize Symposium from Sept 30 – Oct 2, where we will celebrate the 2020 finalists of this prestigious competition. This special gathering includes talks from our short-listed speakers, a keynote address with Prof. Bruce Lipshutz, guest lectures from Reaxys Prize Club members as well as virtual poster presentations from all 45 finalists. Join us for special event and network with the future leaders in chemistry! Registration is free and is available here
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Current Research in Green & Sustainable Chemistry
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Current Research in Chemical Biology
As part of the CO+RE journal suite, this new primary research, gold open access journal publishes research on all aspects of chemical biology and related areas.
Journal of Photochemistry and Photobiology
JPAP focuses on results of fundamental studies covering all aspects of chemical phenomena induced by interactions between light and molecules/matter; as well as papers relating to investigations of the interaction of light with biological systems.
Journal of Magnetic Resonance Open
Sharing the same mission as its parent journal, Journal of Magnetic Resonance, JMRO provides an open access option for articles covering Magnetic Resonance Spectroscopy and Magnetic Resonance Imaging.
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