Dried blood spots (DBSs) are formed by collecting a small sample of blood on specialized filter paper and allowing it to dry naturally. Various domains of life sciences and drug research extensively use DBSs as a sampling technique. The “Hematocrit (Ht) effect” affects assay bias, and several strategies have been put forth to deal with it, including the correction of quantified concentrations using an appropriate correction factor. The approach was previously applied, following the utilization of an image processing algorithm developed in Matlab^® to derive a reliable equation correlating DBS areas to Ht% values. The present work looks more closely at the application of image analysis to the evaluation of Ht in DBS samples. Utilizing image analysis software, DBS samples with known Ht values were processed. Preparation of cards has followed a previously developed protocol for the appropriate formation of uniform area DBSs, irrespective of Ht. The resulting areas showed close resemblance to the respective theoretical areas calculated by applying the correlation equation. Following that, the equation was utilized to determine the Ht values for each sample, and a comprehensive comparison of measured versus calculated Ht was carried out using various statistical approaches for method comparison. The results demonstrated a strong correlation, suggesting the method’s viability in estimating Ht for unknown DBS samples.

In this study, an AQbD-compliant chaotropic chromatography method for ziprasidone and the determination of its five impurities was developed. The influence of critical method parameters (initial and final methanol fraction in the mobile phase, gradient duration) on the set of selected critical method attributes (t_{_imp. V}, t_{_imp. V} − t_{_imp. I}, S and <W_USP>) was studied by Box–Behnken design. The errors resulting from the calculation of the model coefficients were propagated to the selected responses by Monte Carlo simulations, and their predictive distribution was obtained. The design space was computed (π ≥ 80%), and a working point was selected: initial methanol fraction 38.5%, final methanol fraction 77.5%, and gradient duration 16.25 min. Furthermore, the quantitative robustness of the developed method was tested using the Plackett–Burman design. P_{_imp II} and P_{_imp V} were found to be significantly affected, the first by mobile phase flow rate and the second by gradient duration. Finally, the method was validated, and its reliability for routine quality control in capsules was confirmed.

Impurity profiling is of significant analytical and regulatory importance, particularly in the context of lifecycle quality management. A robust chaotropic chromatography method was developed for the determination of olanzapine and its two oxidative degradation products in tablets, in accordance with the ICH Q14 guideline and the principles of Analytical Quality by Design (AQbD). Risk assessment was performed using a combination of the Ishikawa diagram, CNX (Control, Noise and eXperimental) classification, and Failure Mode and Effect Analysis (FMEA). This multistep evaluation identified the critical analytical procedure parameters (APPs) as the acetonitrile content in the mobile phase, the concentration of perchloric acid in the aqueous phase, and the pH of the aqueous phase. These APPs were studied using an experimental design approach to model their effects on key analytical procedure attributes and to compute a multidimensional design space. Robust optimization supported by Monte Carlo simulations ensured compliance with predefined acceptance criteria with a probability of at least 95%. Method validation demonstrated adequate selectivity, limits of quantification of 0.75 µg/mL and 0.5 µg/mL for impurities B and D, linearity with correlation coefficients ≥0.990, accuracy of 98–102% for olanzapine and 70–130% for impurities, and repeatability with RSD ≤2% for the assay and ≤10% for impurities. The method was successfully applied to commercial tablet analysis.