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Discovering Optimal Reaction Conditions via High-Throughput Experimentation

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  March 7, 2019

  8:00 a.m. PST / 11:00 a.m. EST / 16:00 GMT / 17:00 CET

 

Overview

 

High throughput experimentation (HTE) is an indispensable tool for the discovery and optimization of chemical reactions. The integration of automated technologies with expert knowledge and data science allows for scientists to maximize experimental efficiency for the rapid identification of critical class variables through HTE. Namely, the class variables represent the discrete entities of a reaction such as the type of catalyst or reagent, additives, and solvent that are critical to reaction performance. The prompt identification of key class variables accelerates the deployment of newly discovered reactions and subsequent optimization. In this webinar, our speaker Jason Stevens from Bristol-Myers Squibb will discuss several examples for the design, execution and analysis of class variable studies through the use of laboratory automation.

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Key Learning Objectives

  • Learn how to apply lab automation to high throughput experimentation
  • Integrate data science into reaction discovery and optimization
  • Optimize reaction conditions by efficiently studying discrete reaction entities.

Who Should Attend

  • Researchers / R&D Managers
  • Laboratory Managers / Directors / Supervisors
  • Laboratory Technicians / Operators
 

Speaker

Jason Stevens,
Senior Research Investigator,
Bristol-Myers Squibb
 

Moderator

Samantha H. Jones, Ph.D.,
Assistant editor,
C&EN
 

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