Validated liquid chromatography tandem mass spectrometry for simultaneous quantification of foretinib and lapatinib, and application to metabolic stability investigation

Response surface methodology for optimization of micellar-enhanced spectrofluorimetric method for assay of foretinib in bulk powder and human urine

This work investigates a sensitive and precise enhanced spectrofluorimetric assay for assay of foretinib (FTB); a tyrosine kinase inhibitor drug used for treatment of breast cancer, in tablets and urine through response surface optimization by micelle mediated protocol. The basis of the described method is the enhancement of the fluorescence behavior of FTB in Cremophor RH 40 (Cr RH 40) micellar medium and measuring the fluorescence of FTB at 344 nm after excitation at 245 nm. Optimization was performed through evaluation of diluting solvent, types of organized media, buffer type and its relevant pH. Response surface methodology was applied to obtain the optimized values of variables that mostly affect interaction of Cr RH 40 with FTB using Box-Behnken design. ICH guidelines were adhered for the validation of merit figures. Acceptable linear relationship was obtained between relative fluorescence intensity (RFI) and FTB concentrations in the range of 50 - 1000 µg L^-1, with correlation coefficient of 0.998. Accuracy was ≥ 99.82% and calculated limit of detection (LOD) was 10.60 µg L^-1. Method applications included FTB assaying in pure bulk powder. Furthermore, applications on urine samples were performed with accuracy of 100.59 ± 3.40%. The method represents echo-friendly approach and effective alternating methodology to the relevant analytical ones for FTB assaying.

Development of innovative artificial neural networks for simultaneous determination of lapatinib and foretinib in human urine by micellar enhanced synchronous spectrofluorimetry

A highly selective and simple micellar synchronous spectrofluorimetric method was described for simultaneous analysis of two tyrosine kinase inhibitors (TKIs); namely lapatinib (LPB) and foretinib (FTB) in human urine. The method depended on measuring synchronous fluorescence of the two drugs in micellar media composed of cremophor RH 40 (Cr RH 40) surfactant using feed-forward and cascade-forward neural networks preceded by genetic algorithm for data manipulation. Different experimental conditions that affect fluorescence of the cited drugs are optimized including pH, diluting solvent, surfactant's type and concentration. A training set of nine mixtures containing different concentrations of both drugs was prepared for models' construction. Extra validation set composed of other nine mixtures was prepared to validate prediction performance for the constructed models. Root mean square error of prediction (RMSEP) was used as a tool to compare prediction power of each model. The method was extended for quantification of LPB and FTB in spiked human urine.