Dynamic Parameter Screening for Accelerated Mechanistic Analysis
9 affiliations
- 1Department of Chemistry
- 2University of British Columbia
- 3Acceleration Consortium
- 4University of Toronto
- 5Chemical Process Research and Development
- 6Johnson & Johnson Innovative Medicine
- 7University of Bergen
- 8Department of Chemistry, Scripps Research Institute, 10550 North Torrey Pines Road, La Jolla, California, 92037
- 9Department of Chemical and Biological Engineering, Seoul National University, 1 Gwanak-ro, Seoul, South Korea
Abstract
Mechanistic studies are essential for the continued advancement of the chemical sciences however; classical approaches remain laborious and material intensive. Graphical reaction analysis techniques such as RPKA and VTNA have substantially reduced this burden, yet the time and resources required to comprehensively study increasingly complex reactions remain high. Medium- and high-throughput batch and flow kinetic methods have been developed to further streamline data acquisition, but their widespread adoption is limited by the need for specialized equipment or expertise. Here we introduce dynamic parameter screening (DPS), in which a single batch reaction is monitored continuously while sequential reagent and catalyst additions are used to probe kinetic impacts of multiple species within one experimental setup. Using the palladium-catalyzed Kumada–Tamao–Corriu cross-coupling as a model system, we compared DPS with traditional one-factor-at-a-time approach across three catalytic systems (PdCl2(dppf)·CH2Cl2, PEPPSI-iPr, and XPhos Pd G2). DPS afforded essentially identical qualitative and quantitative (kinetic modeling) conclusions except for the case of XPhos Pd G2. This latter system exhibited multiple kinetic regimes where the traditional approach revealed the global impact of reagent concentrations, whereas DPS provided complementary, higher-resolution insight into reagent effects within a specific kinetic regime. The insights obtained from DPS guided a simple slow-dosing strategy that markedly improved reaction rates even at reduced catalyst loadings. DPS therefore provides a practical, low-barrier route to high-resolution kinetic information that is fully compatible with conventional modeling, broadening access to mechanistic understanding in resource-limited settings.
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BibTeX
@misc{pyle2026dynamic,
title = {{Dynamic Parameter Screening for Accelerated Mechanistic Analysis}},
author = {Dylan J. Pyle and Finn Bork and Wesley McNutt and Ekaterina Trushina and Joshua S. Derasp and Sara M. Guzman and Jan Dijkmans and Robert Van Putten and Bertrand Schweitzer-Chaput and Matthew Mower and Jason E. Hein},
howpublished = {ChemRxiv},
year = {2026},
month = sep,
doi = {10.26434/chemrxiv.15008823/v1},
url = {https://chemrxiv.org/doi/full/10.26434/chemrxiv.15008823/v1},
note = {CC BY},
}
RIS
TY - UNPB
TI - Dynamic Parameter Screening for Accelerated Mechanistic Analysis
AU - Dylan J. Pyle
AU - Finn Bork
AU - Wesley McNutt
AU - Ekaterina Trushina
AU - Joshua S. Derasp
AU - Sara M. Guzman
AU - Jan Dijkmans
AU - Robert Van Putten
AU - Bertrand Schweitzer-Chaput
AU - Matthew Mower
AU - Jason E. Hein
PY - 2026
DA - 2026/09/14
PB - ChemRxiv
DO - 10.26434/chemrxiv.15008823/v1
UR - https://chemrxiv.org/doi/full/10.26434/chemrxiv.15008823/v1
AB - Mechanistic studies are essential for the continued advancement of the chemical sciences however; classical approaches remain laborious and material intensive. Graphical reaction analysis techniques such as RPKA and VTNA have substantially reduced this burden, yet the time and resources required to comprehensively study increasingly complex reactions remain high. Medium- and high-throughput batch and flow kinetic methods have been developed to further streamline data acquisition, but their widespread adoption is limited by the need for specialized equipment or expertise. Here we introduce dynamic parameter screening (DPS), in which a single batch reaction is monitored continuously while sequential reagent and catalyst additions are used to probe kinetic impacts of multiple species within one experimental setup. Using the palladium-catalyzed Kumada–Tamao–Corriu cross-coupling as a model system, we compared DPS with traditional one-factor-at-a-time approach across three catalytic systems (PdCl2(dppf)·CH2Cl2, PEPPSI-iPr, and XPhos Pd G2). DPS afforded essentially identical qualitative and quantitative (kinetic modeling) conclusions except for the case of XPhos Pd G2. This latter system exhibited multiple kinetic regimes where the traditional approach revealed the global impact of reagent concentrations, whereas DPS provided complementary, higher-resolution insight into reagent effects within a specific kinetic regime. The insights obtained from DPS guided a simple slow-dosing strategy that markedly improved reaction rates even at reduced catalyst loadings. DPS therefore provides a practical, low-barrier route to high-resolution kinetic information that is fully compatible with conventional modeling, broadening access to mechanistic understanding in resource-limited settings.
ER -