Challenges of High Throughput Experimentation
HTE workflows are scattered across many systems
Scientists often use many software interfaces to get from experimental design to final decision. Valuable time is spent on data entry, and errors arise as data is transcribed from program to program.
Experiment time is lost to configuring equipment
Manual intervention is typical for most HTE groups at some point in the workflow. Even when labs are equipped with robotics for experiment execution, analysis usually means manually setting up samples.
Experiments are disconnected from analytical results
Connecting analytical data back to the experiment is a manual process. Comparing and reviewing results is slow and time-consuming.
Software is not chemically intelligent
Statistical design software does not accommodate chemical information. Separate software is needed to display and review chemical structures, so the scientist can ensure the experimental design covers the appropriate chemical space.
Reprocessing of analytical data is tedious
Most HT scientists find they need to reprocess analytical data. When methods are not optimized for high throughput experiments this can mean 50% of the data or more. Reprocessing analytical data means opening each dataset in the instrument software for manual reprocessing, one at a time.
From design to decide, carry out entire high throughput workflows in a single interface. With all your information in one place, you wonโt lose experiment time manually transcribing/connecting data or configuring equipment. You can even export instruction lists for manual steps like the preparation of stock solutions.
Like using a particular software?
Thatโs not a problem. We work with a variety of third-party systems to import and/or export data. These include the design of experiments (DoE) software, inventory systems, automated reactors, dispensing equipment, data analytics software, statistical software, and data science applications.
Katalyst software is designed by scientists, for scientists. We want you to be able to apply your expertise and not waste your time with monotonous tasks that require checking and re-checking.
- Conveniently set up experiments by drag and drop from inventory lists connected to your internal systems
- See the identity of every component in each well. Reaction schemes may be displayed as structures or text.
- Save an experimental design as a template for re-use in similar experiments
- Input pre-dispensed kits (plates) directly into the experiment to get started quickly
- The identity of each component in the experiment is stored for each reaction in the array, allowing for automatic targeted analysis of spectra
AI for Chemical Reaction Design
Katalyst is the only commercial HTE software with integrated tools for AI-enabled design of experiments (DoE). Reduce the number of experiments you need to run to achieve optimal conditions using the Bayesian Optimization module (EDBO).
Want to explore AI further?
We have partnered with AI experts so you can choose to add a no-code AI solution for the design and optimization of experiments.
Get Serious About Using Your Experiment Data for AI/ML
HT experiments generate the kinds of datasets that are ideal for data science. Katalyst structures your experimental reaction data so that it may be exported for use in AI/ML frameworks. Have your own experimental data accelerate future studies without the pain of engineering and normalizing data from heterogeneous systems in various formats.
Our software reads >150 instrument vendor data formats. Our expertise in analytical data helps you automate data analysis too.
We integrate with the analytical instruments on your network to sweep data (including LC/UV/MS and NMR), automatically process and interpret it, and display the results for visualization. See everything in one interface. Stack data for comparison and review. Create plots to extract trends.
With analytical results linked to each well in the HTE plate, you wonโt spend hours arranging and organizing data and double-checking that results are connected to the correct well. You can concentrate on making decisions.
Is there an important peak in your spectrum that wasnโt integrated or labelled? Is a value missing?
You donโt need to open another application to reprocess your data. Directly reanalyze the whole plate or a selection of wells.
