UV–VIS spectrophotometry is a simple, fast and relatively environmentally protective instrumental technique (depending on the solvents employed), which is commonly used in pharmaceutical quantitative analyses, if an absence of signal interference between the component of interest and other matrix constituents is assured. However, chemometric modelling broadens the applicability of UV–VIS spectrophotometry to multicomponent mixtures of active pharmaceutical ingredients, even when there is a significant overlap between their spectra, achieving simultaneous selective quantification without the need for prior separation, thus simplifying sample preparation and reducing waste generation, time and cost of analysis.

The aim of this work was to develop reliable and robust chemometric models coupled with UV–VIS spectrophotometry that will be applied in routine dissolution testing of combined tablet formulations of two analgesics: Ibuprofen and Paracetamol.

Two quantitative chemometric models: Principal component regression (PCR) and Partial least squares regression (PLS) were built in concentration range 40–140 % of the declared content for both components (corresponding to 2.22 — 7.78 µg/mL for Ibuprofen and 5.56 — 19.44 µg/mL for Paracetamol). After comprehensive assessment and validation, they proved to be precise (<2 % variability) and accurate (<2 % error) for prediction of new samples. Different sources of variability, not related with concentration differences between the samples, were incorporated into the calibration data in order to obtain stable models which wouldn’t be affected from expected variations during routine use.

The similarity between model-obtained results and the results from a reference HPLC procedure confirmed the capability of chemometrics to facilitate its replacement with a more sustainable alternative