Comprehensive Validation of Analytical Methods Using A Risk- Based Approach: Application to RP-HPLC and UV technique for Anti-Cancer Drugs

The research describes a complete validation protocol for anti-cancer drug quantification of Gemcitabine and Acalabrutinib through a combined method which unites RP-HPLC and UV spectrophotometry. The main goal of this work was to create and validate precise, robust and regulatory-suitable assays that incorporate risk-based strategies to boost analytical methodology reliability. The methods followed parameters for chromatographic and spectroscopic optimization before undergoing validation by implementing the requirements of ICH Q2(R2), IP 2022, and USP <1225> regulations. The research team used Python and SPSS statistical software to run regression analysis and ANOVA and Monte Carlo simulations and produced 3D plots to display multi-parameter relationships. The method showed excellent linear relationships (R² > 0.999) with accuracy between 98–102% and precision measured by %RSD below 1.5% while the detection limits reached 0.34 µg/mL and 0.42 µg/mL for Gemcitabine and Acalabrutinib respectively. The method passed robustness testing when subjected to changes in detection wavelength together with flow rate and pH variations. The FMEA risk analysis revealed pH as the most dangerous parameter which prompted the development of preventive control strategies. Analytical validation has achieved a significant advancement through the use of early computational modeling with multivariate risk assessment during method development. The dual-method risk-informed framework shows perfect alignment with modern quality-by-design principles and regulatory requirements and can be applied to multiple pharmaceutical applications including biological and bioanalytical matrices.