Optimization of methods of quality control of drugs using genetic algorithm and tabu search

Two new methodologies of analysis for the antihypertensive drugs quantification are provided in this work, using meta-heuristic algorithms optimization with infrared spectroscopy by diffuse reflectance Fourier transform (DRIFTS) and partial-least squares regression method (PLS). A diffuse reflectance joined to a spectrophotometry in the mid-infrared region was used. The calibration was through PLS in order to use it as a pre-processing. The data were used in multiplicative signal correction (MSC). After the best wavelength selection, which results in models with better coefficient regression (R²), these were improved using routines based on genetic algorithm heuristic and tabu search methods. For the evaluation of the optimization a standard error of validation (SEV) was used. The new technique using DRIFTS/PLS/AG or DRIFTS/PLS/TS shows excellent choices for the quality control of the productive process of factories and drugstore.