WHEN?
Jun/05/2024Accelerating High Throughput Experimentation Workflows using Automated Data Processing
Join us for an engaging webinar on high throughput analytical data management featuring Holly Douglas, Senior Research Scientist from AstraZeneca. Discover how integrating the Reaction Optimization software solution is revolutionizing drug discovery by streamlining workflows and enhancing data quality. Register now for valuable insights into the future of high throughput experimentation.
Speaker
Holly Douglas
Senior Research Scientist
Holly has a broad range of experience applying analytical chemistry techniques to a variety of research projects. The majority of Holly’s experience has been in the pharmaceutical industry having worked as an analytical chemist at GSK, Novartis and the MHRA, with roles based in drug discovery, process chemistry and final product testing. More recently Holly has worked at Owlstone Medical where she developed separation and detection methods for identifying volatile biomarkers in breath samples and the Francis Crick Institute where she was involved in the LC-MS investigation of the metabolomics and drug resistance of Mycobacterium tuberculosis.
Abstract
The demand for accelerated development timelines coupled with the need for high sample throughput in the drug discovery process has amplified the adoption of high throughput experimentation (HTE) in discovery chemistry. However, the analysis of the vast number of samples produced daily has emerged as a major challenge, creating data processing bottlenecks that impede efficiency.
To address this issue, we have integrated the Reaction Optimisation (RO) brick within the Mgears software into our synthetic workflow. This facilitates the rapid and consistent processing of large data sets. The system provides visual and numerical summaries of chromatographic data, which are essential for further calculations and graphical representations. Furthermore, collaboration with the Mgears team has enabled customization of the RO brick to accommodate automated analysis of sample libraries which contain different compounds in each sample.
The implementation of the RO brick has significantly expedited our HTE workflows by reducing the data processing bottleneck and removing the need for manual transcription. Importantly, data quality has been enhanced through a reduction in transcription errors and incorrect peak assignments.
The adoption of the RO brick within Mgears software has proven to be a pivotal advancement in HTE for discovery chemistry. It has not only accelerated the data processing pipeline but has also contributed to improved accuracy and reliability of experimental results. This approach sets a new standard for efficiency in the synthesis and analysis stages of drug discovery, paving the way for faster and more effective development cycles.
