Development of a retention prediction model in ion-pair reversed-phase HPLC for nucleoside triphosphates used as mRNA vaccine raw materials

The International Conference on Harmonization guidelines for quality on pharmaceutical development recommends a systematic development approach including robustness studies which assure performance of manufacturing and analytical method development of drug product. It was demonstrated that the retention prediction model for nucleoside triphosphates (NTPs) on ion-pair reversed-phase HPLC was developed by a highly accurate Kawabe's model which supports the development of robust HPLC methods. As NTPs and its derivatives are typically used for Messenger ribonucleic acid (mRNA) vaccine production, adenosine-5'-triphosphate (ATP), guanosine-5'-triphosphate (GTP), cytidine-5'-triphosphate (CTP), 5-methylcytidine-5'-triphosphate (m5-CTP), uridine-5'-triphosphate (UTP), 5-methyluridine-5'-triphosphate (m5-UTP), pseudouridine-5'-triphosphate (Ψ-UTP) and N1-methylpseudouridine-5'-triphosphate (m1Ψ-UTP) were applied for prediction model development. By a comparison of the predicted retention factor in eight studied samples with the retention factor measured under six isocratic conditions, the absolute prediction error was 0.075 and also the prediction error (%) was 2.70%. In practical examples, analytical method for residual ATP, GTP, CTP, and m1Ψ-UTP in the commercial mRNA-based drugs and purity method for UTP derivatives were optimized by QbD approach. The design space for the minimum resolution between adjacent peaks was simulated with the models developed to evaluate the robustness of peak separation, and the optimal mobile phase condition was also simulated. As a conclusion, the desired peak was successfully separated under the optimized condition, and we thought that these retention models could optimize the mobile phase condition of the NTP analysis method for applying to various quality tests, such as quantity, purity and identity test for NTPs and its derivates in the mRNA-based drugs.