Automatic Optimization of Gradient Conditions by AI Algorithm Using Integrated LC System

User Benefits

- The AI algorithm of LabSolutions MD can automatically optimize gradient conditions to greatly reduce labor of LC method development. - Automatic optimization of gradient conditions can be applied not only to new method development, but also to existing method to efficiently improve resolution.

Introduction

In the typical LC method development, the process begins with “preparation” which includes mobile phase preparation, column installation, and creation of analysis schedules, then the analysis is started. After that, the acquired data is analyzed and “preparation” for the subsequent analysis is carried out, followed by starting the next analysis again. The method development progresses by repeating these processes, but in addition to the significant time required to repeatedly create analysis schedules, expertise in chromatography is necessary to explore optimal conditions based on data analysis. In other words, typical method development requires “human intervention”. Therefore, eliminating human involvement and automating such method development processes would be desirable to improve labor efficiency. This article introduces an example of automatic optimization of gradient conditions that meet resolution criteria using LabSolutions MD (Technical Report C190-E309), a dedicated software for supporting method development. A mixture of seven small-molecule compounds was used as a model sample, and the optimization was performed by combining the AI algorithm in LabSolutions MD with the integrated LC system “i-Series”.

August 31, 2025 GMT