Abstract Background By resolving complicated spectra from drug combinations, chemometric techniques are valuable for multi-component investigation. The capacity to properly estimate combinations of components without separating drugs from their mixture is one of the benefits of chemometric analysis approaches over traditional analytical methods. These approaches are easy to use and sensitive even to the lowest concentrations. They are also practical, affordable, and cost-effective. In the current study, the chemometric aided spectrophotometric approach was used to evaluate the two drugs naringin and verapamil. The approach is multidimensional and based on chemometrics, which includes an orthogonal partial least square method that is a new refinement of the partial least squares regression analysis method. With this technique, no conversions are made to the spectrum that overlaps the two drugs. The tools UV-PROBE, SIMCA version 17, and excel were used to process the chemometric data. Results According to results from an orthogonal partial least square model, the mean percent recovery and relative standard deviation for the combination of verapamil with naringin were 100.80/1.19 and 100.836/1.35, respectively.The calibration model was used to predict known synthetic mixtures.This method shows good consistency in recovery ranging between 98.92 and 103.59% for VER and from 96.21 to 101.84% NAR. As saying the synthetic mixture revealed that it had a high percentage of purity. Conclusions The proposed chemometric method can estimate the quantitative amount of pharmaceuticals based on their dosage forms. This approach meets the requirements for the international conference on harmonization's (ICH) analytical criteria, such as precision and accuracy. Graphical Abstract
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