Application of Doehlert design combined with chemometrics tools: Example of the optimization of the elution of neurotransmitters and metabolites by HPLC

Experimental designs are essential mathematical tools in fields like agronomy, chemistry, and analytical chemistry for optimizing processes and minimizing variations. Doehlert designs, in particular, are valued for their efficiency in exploring experimental space with minimal experiments, providing detailed insights into complex processes. In analytical chemistry, these designs are extensively used for tasks such as extraction, purification, and method optimization, allowing systematic variation of factors to enhance accuracy and efficiency. To further optimize the method, a combination of experimental design and chemometric tools is necessary to understand the chromatographic behavior of the compounds of interest. This study uses Doehlert experimental design combined with chemometric tools to optimize the elution and separation of neurotransmitters and their metabolites using HPLC-ECD. Pearson correlation and Partial Least Squares Discriminant Analysis (PLS-DA) reveal significant relationships between chromatographic parameters and experimental conditions. Notably, the pH of the mobile phase significantly impacts column efficiency and elution time, while the polarity index and pressure influence peak asymmetry. Optimized conditions include a mobile phase of ACN/MeOH/H₂O (11.25/3.25/85.5; v/v/v) with a pH near 1.65, achieving optimal elution times around 20 min, column efficiency with a mean number of theoretical plates close to 8000, and peak asymmetry of approximately 1.23. The limits of detection and quantification of interest compounds are close to 10^-11 and 10^-10 mol L^-1 respectively. This new combined approach allows for effective, rapid, and resolved elution of compounds, reducing resource consumption and time. Moreover, the combination of parameters has been taken into account with chemometrics, allowing a highly effective enhancement of compound elution. The optimized method achieves low detection and quantification limits in the nanomolar range, making it suitable for precise neurotransmitter analysis in complex biological samples.