Name: How AI disease modeling can support precision medicine for glioma/other cancers
Start: 2021-06-10T14:00:00Z
End: 2021-06-10T14:00:59.000Z
Location: BrightTALK
Rating: 4

Realize the potential of data-driven drug discovery and development with solutions that help you increase research efficiency and ensure a thriving R&D pipeline.

Looking to universally turn code into reliable chemistry and materials processes?

Discover this new approach that maps into a universal programming language for chemistry that is accessible to ALL synthetic chemists and will work on ALL robotic systems (subject to suitable specification), thus capable of universally turning code into reliable chemistry and materials processes.

Today it is possible to design and synthesize many of the physically allowed molecules and materials conceivable if practical, yet paradoxically it is not possible to reproduce or rerun these successful procedures with high reliability. This is because many of the conditions devised for the manual or semi-manual synthesis are not uniformly recorded and there is no standard way of recording reaction informatics. 

Join Lee Cronin, Professor, Center for Digital Chemistry, School of Chemistry, University of Glasgow for this webinar that will show how his group works on solving this problem by devising a universal approach to recording reaction informatics and chemical synthesis that allows them to translate all procedures, manual or automatic, to a new standard language for exploring chemical reactions and synthesis. 
 
Part of the Big Data in Chemistry webinar series
Showcasing the work of top class chemistry researchers who have used Elsevier’s reaction and substance data from Reaxys database as input to their current research programs for algorithm development, predictive analytics and/or data visualisation for delivering actionable insights to accelerate synthesis workflows.

A Universal Approach to Reaction Informatics

Along its evolution, chemistry has left a historical record of substances and chemical reactions that today are stored in large electronic databases such as Reaxys.  

In this webinar Professor Guillermo Restrepo, from Leipzig University will show that this large corpus of historical chemical information constitutes more than a source of data.  It can shed light on the evolution of chemistry and its knowledge through a computational approach posing new challenges and opportunities for the field of chemistry.  In this setting chemical knowledge is modelled as an emergent property of the material, social and semiotic systems of chemistry.  It is our claim that this approach not only illuminates on the past of chemistry but on its present and future.  

He will cover the sources of data and the available mathematical and computational methods to carry out computational studies of the history of chemistry.  As a case study recent results on the computational study of the evolution of the chemical space will show how World Wars and scientific theories have affected the annual production of new chemicals.

Part of the Big Data in Chemistry webinar series
Showcasing the work of top class chemistry researchers who have used Elsevier’s reaction and substance data from Reaxys database as input to their current research programs for algorithm development, predictive analytics and/or data visualisation for delivering actionable insights to accelerate synthesis workflows.

Understanding the history of chemical space through big data

DNA-encoded libraries (DELs) are a powerful technology for target-based small molecule screening. DEL design raises the question of chemical reaction selection for accessing chemical and especially structural diversity. However, chemical reaction space is vast, thus computer-assisted tools for reaction database mining are needed to support and enhance the efforts of medicinal and synthetic organic chemists. 

In this webinar Dr Andreas Brunschweiger, Professor at Chemistry and Chemical Biology of TU Dortmund  expands on this research topic and shows how we can develop a computational tool allowing for filtering relevant reactions from the vast reaction space and organizing the still impressive number of potentially useful reactions by clustering. This tool and the mentioned approach shall support decision-making for DNA encoded library design to aid acceleration of Lead Identification workflows.

Part of the Big Data in Chemistry webinar series
Showcasing the work of top class chemistry researchers who have used Elsevier’s reaction and substance data from Reaxys database as input to their current research programs for algorithm development, predictive analytics and/or data visualisation for delivering actionable insights to accelerate synthesis workflows.

Charting the chemical reaction space for DNA-encoded library design

The novel Medication Safety Risk Score quantifies clinically and economically meaningful polypharmacy adverse effects based on pharmacokinetics, pharmacodynamics, chronopharmacology, and pharmacogenomics factors.  The Medication Risk Score is unique in its ability to compute aggregated and simultaneous anticholinergic cognitive burden (ACB), sedative burden (S.B.), drug-induced Long QT Syndrome (LQTS) burden, and competitive inhibition (CYP450) burden (CIB) risks from a patient’s medication, OTC & supplement regimen.  The presentation will include sharing several recently published case studies based on the results of a CMS Center for Medicare & Medicaid Innovation Part D Enhanced Medication Therapy Management Innovation Model, and an in silico clinical trial study to determine medication-induced premature death.

New Medication Risk Score for Polypharmacy-induced Drug-Drug Interactions

Do you find it a challenge selecting optimal reaction conditions in the development of a synthesis strategy, or are you developing different approaches such as neural network based methods for building predictors to aid reaction condition optimization? 

If yes, then join us on October 7 for a 45 minute webinar that will cover the workflow that starts with input of raw data from Reaxys database and ends up with the model that suggests several possible reaction conditions for desired synthesis outcomes. 

The workflow implies a reaction data curation procedure that includes reaction structure curation as well as standardization of reaction condition information. 

Timur Madzhidov , Associate Professor & Chair of Organic Chemistry at Kazan Federal University, will discuss:
• The nearest neighbor and neural network-based approaches applied for reaction condition prediction in small and quite homogeneous hydrogenation reactions subset. 
• The problems of scaling of mentioned approaches to a larger and more diverse dataset 
• AI-based approaches that can be applied to a diverse database of reactions. The approaches are validated in retrospective and prospective scenarios and show quality superior to existing ones.

Part of the Big Data in Chemistry webinar series:
Showcasing the work of top class chemistry researchers who have used Elsevier’s reaction and substance data from Reaxys database as input to their current research programs for algorithm development, predictive analytics and/or data visualisation for delivering actionable insights to accelerate synthesis workflows.

Reaction condition prediction using Reaxys: from raw data to best-in-class model

Are you trying to break silos and show the value of a well-organized information center? 
Join this webinar where Teresa Silveira, Affiliate Professor at Engineering Faculty, Oporto University will show how integrated management of information resources can speed up business development and boost innovation.
Innovation happens when powerful information meets clearly defined goals and a will to change. The application of the information mapping technique is based on the evaluation of the nature,  need, potential usability, coverage, impact and return on investment (ROI). The enhancement of information resources is a strategic action that helps companies take full advantage of their intellectual capital and more easily achieve their business goals.

First in Knowledge Culture Webinar series

The secret power of information resources: Information mapping and ROI

Rapid navigation of increasingly complex druggable chemical space is critical for innovative drug design. However, chemical synthesis and route design is still a significant challenge. In this session, we will discuss recent development in predictive retrosynthesis. Also, we explore how Reaxys collaborated with Pending.AI, a startup led by Prof. Mark Waller, to develop a ‘deep learning’ solution that predicts new synthesis routes with high accuracy for creating small organic compounds. The webinar will focus on:
1. Science behind AI powered predictive retrosynthesis
2.	Reaxys predictive retrosynthesis overview
3.	Discussion on benefits, limitation of technology and future roadmap

AI-enabled predictive retrosynthesis tool to advance drug discovery

- データ活用によるR&Dの加速
- 現状と課題
-フルテキストから得られる情報
- グローバルにおける事例

※所属機関のメールアドレスよりお申込みください。

「R&Dにおけるデジタルトランスフォーメーション~Scientific dataの活用~」

This webinar will focus on trends in artificial intelligence and explore knowledge graphs and data extraction and deep dive into how they are currently used across industries, focusing on the following topics:

•	Health Markets tech overview 
•	H-Graph/H-Search 
•	Knowledge extraction

Join us on August 12 and hear Elsevier's Rhett Alden - Chief Technology Officer of Health Markets, Kaushik Raha – Vice-President Data Science, Health Content Operations and Mevan Samarasinghe - Vice-President and Technical Fellow give their expert opinions on this topic and ask them any questions you may have.

Knowledge graphs and data extraction – Current trends

Reaxysの初心者から中級者まで使えるMarvin JSでの構造描画テクニックについてご紹介。ノイズが出てしまう原因を解説し、いかにノイズを解消するかをデモンストレーション致します。また、検索結果を得た後に絞り込むためのフィルター機能の活用の仕方も併せて解説します。

※所属機関のメールアドレスよりお申込みください。

Reaxys基礎編「なぜあなたの反応・化合物検索ではノイズが多いのか？～ノイズを減らす構造描画とフィルター機能のノウハウ～」

Rapid navigation of increasingly complex druggable chemical space is critical for innovative drug design. However, chemical synthesis and route design is still a significant challenge. In this session, we will discuss recent development in predictive retrosynthesis. Also, we explore how Reaxys collaborated with Pending.AI, a startup led by Prof. Mark Waller, to develop a ‘deep learning’ solution that predicts new synthesis routes with high accuracy for creating small organic compounds. The presentation will focus on:

1.	Science behind AI powered predictive retrosynthesis 
2.	Reaxys predictive retrosynthesis overview and demo
3.	Discussion on benefits, limitation of technology and future roadmap

Speaker bios:
Mandar Bodas, Solution Sales Manager - Life Sciences, Elsevier (https://www.linkedin.com/in/mandar-bodas-b360314/)
Abhinav Kumar, Head of Strategy and Business Development - Chemistry Solutions, Elsevier (https://www.linkedin.com/in/abhinavkumar8/)
Juergen Swienty-Busch, Director of Product Management - Chemistry Solutions, Elsevier (https://www.linkedin.com/in/jsb2018/)

Next generation synthesis planning using AI for chemists

This is our second webinar in continuation to share more insights on patent content expansion in Reaxys. In previouswebinar, we have shared the Reaxys patent content road map which helps to build a more competitive intelligence for your research projects.
In this segment we will be sharing more insights on finding the chemical compound information hidden in patents directly from our speakers where Mr Honmute will be sharing his knowledge & experience on the challenges & importance of patent data in chemistry research and Dr Rane will showcase how this data can be easily discoverable in Reaxys with the new patent content coverage expansion.

Reaxys Patent Expansion: Uncovering chemical compounds hidden in patents

Reaxys is growing. The leading knowledge solution for small molecule design and synthesis has exponentially augmented its patent content to bring you competitive intelligence for biological target validation. 

With AI-powered extraction, primary target indexing, and quality control through domain experts and data scientists, the rapidly growing content of Reaxys grants insights into risks in a rapidly evolving patent landscape.

Keep your finger on the pulse of the market:
•	Access newly published patents, covering 105 offices and 170 IPC classes
•	Use the only solution that translates non-English language abstracts and claims
•	Capture comprehensive results with indexed primary targets and synonyms
•	Do competitive deep-dives with advanced searches for patent assignee
•	Get alerts on the latest patents, available just 5 days after publication

Reaxys Patent Expansion 2021: An improved Competitive Intelligence

Join John McConnell, Editor-in-Chief of The Lancet Infectious Diseases to update yourself on the latest scientific viewpoints regarding the workings of the COVID-19 vaccines. In this professional webinar, John will cover areas such as: 
• Effectiveness of vaccines in preventing disease, including variant viruses 
• Vaccine safety – reactogenicity, anaphylaxis, clotting disorders, Bell’s palsy 
• What vaccines are available and their mechanisms of action 
• The path to making vaccines available worldwide 
• How has the pandemic affected the research landscape 
Moreover, you will get the opportunity to secure answers to your own pressing questions. You won’t want to miss this valuable webinar.

About the presenter: 
John McConnell studied clinical microbiology and parasitology at the University of East London, before spending 6 years researching septic-shock-related topics at the Royal Postgraduate Medical School, Hammersmith Hospital, London (now part of Imperial College London). He joined The Lancet in 1990 as a peer-review editor before becoming the first Web Editor in 1996. In 2001, John was the founding editor of The Lancet Infectious Diseases. He has appeared as an expert commentator on BBC, ITV, Channel 4, Sky News, Al Jazeera, CNBC, CNN, and CCTV America. In the past year, The Lancet Infectious Diseases has published some of the most impactful research on COVID-19.

COVID-19 Vaccines: An Update on Research & Global Availability

Organizations produce data and ingest externally generated data at a rapid pace. Holistic views of multiple data sources allow for inferences to be made that would otherwise remain unseen. In order to take holistic views of this data, it is critical that they are aligned to standards and that intuitive data structures are utilized to enable complex querying of the integrated dataset.

In this short webinar our Lead Technical Consultant Joe Mullen will explain how SciBite’s semantic enrichment technology is being used to facilitate the production of Knowledge Graphs.

We will explain how the SciBite stack can be used for the extraction of semantic triples from literature as well as the harmonization and integration of these with data from both external and internal structured data sources.

For more upcoming SciBite webinars visit our website: https://www.scibite.com/events/

Creating Knowledge Graphs from Literature, 29 April 2020

• Information that can be retrieved through patent information provided by Reaxys
• Patent update process
• Use case: How to search patents using Biological Targets

Join biological modeling expert Dr. Anton Yuryev for an exclusive look at disease modeling that informed precision medicine decisions. 

In this project, OMICs data for patients with the brain cancer diffuse intrinsic pontine glioma (DIPG) was analyzed using an Elsevier biology knowledge graph and complementary software to develop a molecular disease model. This model was then leveraged to find FDA-approved drugs inhibiting the disease mechanism.

In this webinar, you’ll see:
-	The workflow for importing patient OMICs data, projecting onto an Elsevier biology knowledge graph, and building a unified consensus disease model
-	The workflow for finding and ranking drugs that could inhibit the disease mechanism, and how this drug selection was refined 
-	The mutations found in all DIPG patients and how common these are in other cancer types

The webinar includes a Q&A session with Dr. Yuryev.

How AI disease modeling can support precision medicine for glioma/other cancers

disease modeling

precision medicine

biology knowledge graph

glioma

DIPG

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How AI disease modeling can support precision medicine for glioma/other cancers

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Elsevier's Life Science Solutions