On-demand webinar: Practical considerations for improving high throughput synthesis
Eliminate manual transcription, automate analytical data processing, and make decisions based on data directly linked with high throughput experiments.
Traditional drivers for high throughput experimentation (HTE) are the desire for increased productivity and shorter discovery-to-commercialization timelines. Unfortunately, the lack of integration of the tools to get from experimental design to the final decision mean scientists spend too much time on tedious, error-prone tasks. Learn about software that supports the entire HTE workflow. Hear how scientists at BMS are benefitting from their deployment and see the software in action.