Detalle de: Multivariate curve resolution of incomplete and partly trilinear multiblock datasets

We extend the application of MCR-ALS to incomplete multiblock datasets, allowing for missing data in some blocks and the application of flexible trilinearity constraints. We test this extension on three experimental datasets: one involving ultraviolet (UV) spectroscopic monitoring of a drug's degradation and its further liquid chromatography coupled to diode array detection and mass spectrometric detection (LC-DAD-MS) analysis, another with UV and Excitation Emission Matrix (EEM) fluorescence monitoring of drug degradation and its LC-DAD-FLD analysis, and a third with two sets of LC data (with DAD-FLD and DAD-MS detection) for the same drug's degradation. We concatenate and arrange these data into a unified incomplete multiblock data structure. Our results demonstrate the benefits of using this approach, showcasing the versatility of MCR-ALS for various data scenarios, including these coming from chlorination, photodegradation and the combination of both degradation treatments into drug stability studies.