Literature DB >> 31312407

Creating a Virtual Assistant for Medicinal Chemistry.

Lewis R Vidler1, Matthew P Baumgartner2.   

Abstract

The virtual assistant concept is one that many technology companies have taken on despite having other well-developed and popular user interfaces. We wondered whether it would be possible to create an effective virtual assistant for a medicinal chemistry organization, the key being delivering the information the user would want to see, directly to them, at the right time. We introduce Kernel, an early prototype virtual assistant created at Lilly, and a number of examples of the scenarios that have been implemented to try to demonstrate the concept. A biochemical assay summary email is described that brings together new results and some basic analysis, delivered within an hour of new data appearing for that assay, and an email delivering new compound design ideas directly to the original submitter of a compound shortly after their compound was tested for the first time. We conclude with a high level description of the first example of a Design-Make-Test-Analyze cycle completed in the absence of any human intellectual input at Lilly. We believe that this concept has much potential in changing the way that computational results and analysis are delivered and consumed within a medicinal chemistry group, and we hope to inspire others to implement their own similar solutions.

Entities:  

Year:  2019        PMID: 31312407      PMCID: PMC6627723          DOI: 10.1021/acsmedchemlett.9b00151

Source DB:  PubMed          Journal:  ACS Med Chem Lett        ISSN: 1948-5875            Impact factor:   4.345


  12 in total

Review 1.  Making medicinal chemistry more effective--application of Lean Sigma to improve processes, speed and quality.

Authors:  Shalini Andersson; Alan Armstrong; Annika Björe; Sue Bowker; Steve Chapman; Rob Davies; Craig Donald; Bryan Egner; Thomas Elebring; Sara Holmqvist; Tord Inghardt; Petra Johannesson; Magnus Johansson; Craig Johnstone; Paul Kemmitt; Jan Kihlberg; Pernilla Korsgren; Malin Lemurell; Jane Moore; Jonas A Pettersson; Helen Pointon; Fritiof Pontén; Paul Schofield; Nidhal Selmi; Paul Whittamore
Journal:  Drug Discov Today       Date:  2009-03-11       Impact factor: 7.851

2.  Kinase inhibitor data modeling and de novo inhibitor design with fragment approaches.

Authors:  Michal Vieth; Jon Erickson; Jibo Wang; Yue Webster; Mary Mader; Richard Higgs; Ian Watson
Journal:  J Med Chem       Date:  2009-10-22       Impact factor: 7.446

3.  Integrated Platform for Expedited Synthesis-Purification-Testing of Small Molecule Libraries.

Authors:  Aleksandra Baranczak; Noah P Tu; Jasmina Marjanovic; Philip A Searle; Anil Vasudevan; Stevan W Djuric
Journal:  ACS Med Chem Lett       Date:  2017-03-28       Impact factor: 4.345

4.  Organic synthesis in a modular robotic system driven by a chemical programming language.

Authors:  Sebastian Steiner; Jakob Wolf; Stefan Glatzel; Anna Andreou; Jarosław M Granda; Graham Keenan; Trevor Hinkley; Gerardo Aragon-Camarasa; Philip J Kitson; Davide Angelone; Leroy Cronin
Journal:  Science       Date:  2018-11-29       Impact factor: 47.728

5.  A remote-controlled adaptive medchem lab: an innovative approach to enable drug discovery in the 21st Century.

Authors:  Alexander G Godfrey; Thierry Masquelin; Horst Hemmerle
Journal:  Drug Discov Today       Date:  2013-03-21       Impact factor: 7.851

6.  D3R Grand Challenge 2: blind prediction of protein-ligand poses, affinity rankings, and relative binding free energies.

Authors:  Zied Gaieb; Shuai Liu; Symon Gathiaka; Michael Chiu; Huanwang Yang; Chenghua Shao; Victoria A Feher; W Patrick Walters; Bernd Kuhn; Markus G Rudolph; Stephen K Burley; Michael K Gilson; Rommie E Amaro
Journal:  J Comput Aided Mol Des       Date:  2017-12-04       Impact factor: 3.686

7.  Lessons learned in induced fit docking and metadynamics in the Drug Design Data Resource Grand Challenge 2.

Authors:  Matthew P Baumgartner; David A Evans
Journal:  J Comput Aided Mol Des       Date:  2017-11-10       Impact factor: 3.686

Review 8.  Automating drug discovery.

Authors:  Gisbert Schneider
Journal:  Nat Rev Drug Discov       Date:  2017-12-15       Impact factor: 84.694

9.  Rapid assessment of a novel series of selective CB(2) agonists using parallel synthesis protocols: A Lipophilic Efficiency (LipE) analysis.

Authors:  Thomas Ryckmans; Martin P Edwards; Val A Horne; Ana Monica Correia; Dafydd R Owen; Lisa R Thompson; Isabelle Tran; Michelle F Tutt; Tim Young
Journal:  Bioorg Med Chem Lett       Date:  2009-05-21       Impact factor: 2.823

10.  Integration of in silico and in vitro tools for scaffold optimization during drug discovery: predicting P-glycoprotein efflux.

Authors:  Prashant V Desai; Geri A Sawada; Ian A Watson; Thomas J Raub
Journal:  Mol Pharm       Date:  2013-03-01       Impact factor: 4.939

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  2 in total

Review 1.  Artificial Intelligence for Autonomous Molecular Design: A Perspective.

Authors:  Rajendra P Joshi; Neeraj Kumar
Journal:  Molecules       Date:  2021-11-09       Impact factor: 4.411

2.  Current and Future Roles of Artificial Intelligence in Medicinal Chemistry Synthesis.

Authors:  Thomas J Struble; Juan C Alvarez; Scott P Brown; Milan Chytil; Justin Cisar; Renee L DesJarlais; Ola Engkvist; Scott A Frank; Daniel R Greve; Daniel J Griffin; Xinjun Hou; Jeffrey W Johannes; Constantine Kreatsoulas; Brian Lahue; Miriam Mathea; Georg Mogk; Christos A Nicolaou; Andrew D Palmer; Daniel J Price; Richard I Robinson; Sebastian Salentin; Li Xing; Tommi Jaakkola; William H Green; Regina Barzilay; Connor W Coley; Klavs F Jensen
Journal:  J Med Chem       Date:  2020-04-14       Impact factor: 7.446

  2 in total

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