Principal component analysis of HPLC retention data and molecular modeling structural parameters of cardiovascular system drugs in view of their pharmacological activity

Pharmacological classification of anticancer drugs applying chromatographic retention data and chemometric analysis

The combination of chromatography and chemometrics has been introduced in order to provide information about drug analytes, biological macromolecules, the stationary phase, whose properties are related to molecular pharmacology and rational drug design. In this work a pharmacological classification was made in order to find strategy for predicting an activity of anticancer drugs. Principal Component Analysis (PCA) method has been employed to build some relationship models between the following: lipophilicity parameters of selected antitumor drugs obtained by chromatographic analysis, some molecular modeling descriptors from HyperChem software, lipophilicity parameters calculated by proper program, biological activity, as well as mechanism of actions and therapeutic properties of selected anticancer drugs. The most significant influence on factors value had parameters, which described compounds’ lipophilicity. Important debt on antitumor properties had some other molecular descriptors, which were considered in this paper (e.g. topological, physico-chemical, and energy ones). In addition, distribution of individual drugs on plots determined by two principal components had shown points in good accordance with their chemical structures and cytostatic activity as well as their mechanism of actions and therapeutic properties.

QbD-steered development and validation of an RP-HPLC method for quantification of ferulic acid: Rational application of chemometric tools

The present work describes the systematic development of a simple, rapid, sensitive, robust, effective and cost-effective reversed-phase high performance liquid chromatographic method for quantitative analysis of ferulic acid using analytical quality by design paradigms. Initially, apt wavelength for the analysis of ferulic acid was selected employing principal component analysis as the chemometric tool. An Ishikawa fishbone diagram was constructed to delineate various plausible variables influencing analytical target profile, viz. peak area, theoretical plate count, retention time and peak tailing as the critical analytical attributes. Risk assessment using risk estimation matrix and factor screening studies employing Taguchi design aided in demarcating two critical method parameters, viz. mobile phase ratio and flow rate affecting critical analytical attributes. Subsequently, the optimum operational conditions of the liquid chromatographic method were delineated using face-centred composite design. Multicollinearity among the chosen factors for optimization was analyzed by the magnitude of variance inflation factor optimized analytical design space, providing optimum method performance, was earmarked using numerical and graphical optimization and corroborated using Monte Carlo simulations. Validation, as per the ICH Q2(R1) guidelines, ratified the efficiency and sensitivity of the developed novel analytical method of ferulic acid in the mobile phase and the human plasma matrix. The optimal method used a mobile phase, comprising of acetonitrile: water (47:53% v/v, pH adjusted to 3.0 with glacial acetic acid), at a flow rate of 0.8 mL·min^-1, at a λ_max of 322 nm using a C₁₈ column. Use of principal component analysis unearthed the suitable wavelength for analysis, while analytical quality by design approach, along with Monte Carlo simulations, facilitated the identification of influential variables in obtaining the "best plausible" validated chromatographic solution for efficient quantification of ferulic acid.