Combining Data-Rich Experimentation with Modeling to Drive Productivity
Programa
- Case studies from key industry players
- Recent work with data-rich experimentation and kinetic modeling
- Live Q&A with industry experts
This free online event is for chemists and engineers who are interested in obtaining a deeper understanding of their processes at every scale to deliver increasingly complex processes under compressed timelines.
Topics include:
- Use of automation to increase the information density of every experiment
- Innovative problem-solving tools to avoid "trial and error experimentation", which carries a significant risk of failure
- The use of predictive process modeling that can be built quickly and allows users to remain focused on process goals
Past Presentations
Using ReactIR for In Situ Tracking and Quantification of an Unstable Intermediate
Eoghan Delany - Senior Process Development Chemistry, APC Ltd
2007-2011 BSc, Chemistry (Trinity College Dublin)
2011-2015 PhD, Chemistry (Trinity College Dublin)
2015-2017 Process Development Chemist (Almac Sciences, Northern Ireland)
2017-2019 Postdoctoral Research Fellow (La Trobe University, Melbourne)
2019-present Senior Process Development Scientist (APC Ltd, Dublin)
Data-Rich Experimentation for the Late-Stage Process Development of MK-1026
Morgan Crawford - Senior Scientist, Merck
Morgan is a Senior Scientist at Merck & Co., Inc. in Chemical Engineering Research and Development. In her current role, Morgan supports process development, pilot plant demonstrations, and technology transfer for pharmaceutical processes. Prior to her current role, Morgan spent 6 years in the Merck Manufacturing Division where she completed three rotational assignments in the Manufacturing Leadership Development Program and subsequently worked in vaccine process development and commercialization.
Kinetic Modeling to De-risk Process Changes as a Part of Life-Cycle Management
Geoff Purdum - Principal Scientist, Chemical Process Development, Bristol Myers Squibb
Geoff Purdum is a Principal Scientist in the Chemical Process Development (CPD) department at Bristol Myers Squibb (New Brunswick, NJ). Geoff is a member of the Reaction Science and Engineering group within CPD, focusing on building process knowledge using real-time analytical tools. Geoff joined BMS in 2018 after completing his Ph.D. in Chemical Engineering at Princeton University, where he studied polymorphism in molecular semiconductor thin films (w. Prof. Lynn Loo). Geoff also holds a B.S. in Chemical Engineering from the University of Massachusetts-Amherst.
