The objectives of current investigation are (1) to find out wavelength of maximum absorbance (lambda(max)) for combined cyclosporin A and etodolac solution followed by selection of mobile phase suitable for the RP-HPLC method, (2) to define analytical target profile and critical analytical attributes (CAAs) for the analytical quality by design, (3) to screen critical method parameters with the help of full factorial design followed by optimization with face-centered central composite design (CCD) approach-driven artificial neural network (ANN)-linked with the Levenberg-Marquardt (LM) algorithm for finding the RP-HPLC conditions, (4) to perform validation of analytical procedures (trueness, linearity, precision, robustness, specificity and sensitivity) using combined drug solution, and (5) to determine drug entrapment efficiency value in dual drug-loaded nanocapsules/emulsions, percentage recovery value in human plasma spiked with two drugs and solution state stability analysis at different stress conditions for substantiating the double-stage systematically optimized RP-HPLC method conditions. Through isobestic point and scouting step, 205 nm and ACN:H2O mixture (74:26) were selected respectively as the lambda(max) and mobile phase. The ANN topology (3:10:4) indicating the input, hidden and output layers were generated by taking the 20 trials produced from the face-centered CCD model. The ANN-linked LM model produced minimal differences between predicted and observed values of output parameters (or CAAs), low mean squared error and higher correlation coefficient values in comparison to the respective values produced by face-centered CCD model. The optimized RP-HPLC method could be applied to analyze two drugs concurrently in different formulations, human plasma and solution state stability checking.
