Automatic Optimization of Separation Conditions by AI Algorithm -Optimization under Isocratic Elution-

Beneficios para el usuario

- The AI algorithm of LabSolutions MD can automatically optimize separation conditions, greatly reducing the workload involved in LC method development. - By optimizing the separation under isocratic elution, method transfer between different systems becomes easier. - Automatic optimization under isocratic elution can efficiently convert existing gradient methods to isocratic ones.

Introducción

In the typical LC method development, the process begins with “preparation” which includes mobile phase preparation, column installation, and creation of analysis schedules, then analysis is started. Después, se analizan los datos adquiridos y se lleva a cabo la “preparación” para el análisis posterior, tras lo cual se inicia el siguiente análisis nuevamente. El desarrollo del método avanza repitiendo estos procesos, pero además de la considerable cantidad de tiempo que se requiere para crear repetidamente programas de análisis, se necesita experiencia en cromatografía para explorar condiciones óptimas basadas en el análisis de datos. En otras palabras, el desarrollo de métodos típico requiere “intervención humana”. Por consiguiente, eliminar la participación humana y automatizar dichos procesos de desarrollo de métodos sería deseable para mejorar la eficiencia laboral. In this article, a case study is presented in which a mixture of low-molecular-weight compounds was used as a model sample, and conditions meeting the resolution criteria were automatically explored using the dedicated software for supporting method development “LabSolutions MD”. For gradient elution, method transfer between different systems while maintaining the separation pattern requires appropriate adjustment of various LC parameters, and achieving an exact match of the separation pattern before and after transfer can be challenging. In this article, optimization of separation conditions under isocratic elution was carried out to facilitate smoother method transfer.

18 de noviembre de 2025 GMT