Foundational chemistry underlies every chromatographic method. Starting your method development tools from these principles helps you choose better starting conditions.
What does that mean? Use software tools to predict physicochemical properties, such as pKa, logD, and solubility, and find the best solvents and pH range to screen. Use databases of Tanaka parameters to understand column properties, and find the best columns to test. By starting from a better place, you’ll reduce the work needed to reach the optimal point.
Every experiment gives you some information, but trial-and-error gives you less than other approaches. Instead, plan every experiment to paint a better picture of your separation space. The software helps here by suggesting experimental conditions, and building models with your data, so you can understand your separation space in multiple dimensions. Use simulated chromatograms for an intuitive understanding of your model.
Product Recommendations
Models are helpful, but they’re only as useful as they’re accurate. Ensure the model matches your data by choosing software that lets you customize equations. Adjust to suit the parameters you’re optimizing, your experimental conditions, and your samples. For example, protein and small-molecule separations are known to behave differently with temperature—build models that reflect those differences.
Product Recommendations
Every project adds to your chromatographic knowledge. By now, your organization might have years or decades of accumulated experience. But if the information isn’t readily findable, it languishes unused.
Searchable databases help you share project data, so you or your colleagues can use past attempts as starting points for future projects. With search that runs by structure, substructure, method parameters, retention time, and more, it’ll be hard to lose knowledge again. And with support for every major instrument vendor data format, all your information will be collected seamlessly together.