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.

The development of retention time prediction model using multilinear gradient profiles of seven pharmaceuticals.

The ICH guidance on pharmaceutical development recommends a systematic development approach including robustness studies which assure performance of manufacturing and analytical method development of drug product. The retention model by T. Kawabe et al have an excellent correlation between observed and predicted retention time in various kinds of pharmaceutical compounds during isocratic elution by the multiple regression modeling of solvent strength parameters. However, it cannot be successfully applied to the predictability of the retention time during multilinear gradient elution and also it does not consider the instrument dependent parameters such as dwell volume. The current study demonstrated that the solution of the fundamental gradient elution equation was applied to T. Kawabe's retention time prediction model to predict the retention time using a multilinear gradient profile with taking the delay volume of HPLC system into account. Seven pharmaceutical compounds were used for evaluation of prediction models for retention time. The predicted retention time was compared with the measured retention time obtained by several multilinear gradient using two HPLC systems with different dwell volume. The evaluated prediction error (%) was 1.10 % and 1.54 % with H-Class and Nexera XR HPLC systems, respectively. In order to evaluate the robustness of the analytical method and to set the system suitability test (SST) for proper method performance, the design space for the ACN/MeOH mixture ratio in the total organic solvent and the full width at half maximum (FWHM) relationship to the minimum resolution was simulated by the developed retention time prediction. The optimized condition of the ACN/MeOH mixture ratio, the acceptance criterion of the SST for achieving the robust separation was estimated based on the simulated design space. As a conclusion, the developed retention time prediction will be useful during analytical method transfer among different manufacturing/analytical sites of the pharmaceuticals with different HPLC systems.

Impact of Magnesium Stearate Content: Modeling of Drug Degradation Using a Modified Arrhenius Equation.

To accelerate drug development, the pharmaceutical industry is working to shorten and improve studies on stability. The Accelerated Stability Assessment Program (ASAP) incorporating the humidity-corrected Arrhenius equation as an accelerated methodology has been proposed for both drug substances and drug products. In this study, the effect of magnesium stearate (MgSt) content on the chemical stability of acetylsalicylic acid was evaluated as a model system of drug-excipient compatibility studies using ASAP. In the acetylsalicylic acid powder blends, temperature and humidity showed a first-order linear response to the natural logarithm of the reaction rate constant, and MgSt content also showed a first-order linear response. A polynomial model was built in which temperature, humidity, and MgSt content were independent each other. The fitting index of the model, the coefficient of determination, was 0.9567, which was a good fit. In the long-term stability study (25 °C/60% relative humidity, 6 months), there was good agreement in total between measured values and model-predicted values. Using this model, we inferred that the degradation rates were depended on MgSt content at the fixed temperature and humidity because the micro-environmental pH of the excipient was catalytically affected. Applying this model equation can significantly reduce the duration of formulation design and stability studies and save time and costs in drug development.

Degradation Pathway of a Taxane Derivative DS80100717 Drug Substance and Drug Product.

The degradation pathway of a taxane derivative and anticancer agent, DS80100717, was investigated. Several degradants were generated under acidic, basic, and oxidative stress conditions in solution. The chemical structures of eight degradants of DS80100717 were elucidated using MS and NMR. The major degradant of the DS80100717 drug substance derived by heating in solid-state was the N-oxide form via oxidation and C2'-epimer of the side chain via acid hydrolysis. We proposed previously unreported degradation pathways of DS80100717 with taxane derivatives such as paclitaxel, docetaxel, and cabazitaxel.

Ternary isocratic mobile phase optimization utilizing resolution Design Space based on retention time and peak width modeling.

An optimization procedure of ternary isocratic mobile phase composition in the HPLC method using a statistical prediction model and visualization technique is described. In this report, two prediction models were first evaluated to obtain reliable prediction results. The retention time prediction model was constructed by modification from past respectable knowledge of retention modeling against ternary solvent strength changes. An excellent correlation between observed and predicted retention time was given in various kinds of pharmaceutical compounds by the multiple regression modeling of solvent strength parameters. The peak width of half height prediction model employed polynomial fitting of the retention time, because a linear relationship between the peak width of half height and the retention time was not obtained even after taking into account the contribution of the extra-column effect based on a moment method. Accurate prediction results were able to be obtained by such model, showing mostly over 0.99 value of correlation coefficient between observed and predicted peak width of half height. Then, a procedure to visualize a resolution Design Space was tried as the secondary challenge. An artificial neural network method was performed to link directly between ternary solvent strength parameters and predicted resolution, which were determined by accurate prediction results of retention time and a peak width of half height, and to visualize appropriate ternary mobile phase compositions as a range of resolution over 1.5 on the contour profile. By using mixtures of similar pharmaceutical compounds in case studies, we verified a possibility of prediction to find the optimal range of condition. Observed chromatographic results on the optimal condition mostly matched with the prediction and the average of difference between observed and predicted resolution were approximately 0.3. This means that enough accuracy for prediction could be achieved by the proposed procedure. Consequently, the procedure to search the optimal range of ternary solvent strength achieving an appropriate separation is provided by using the resolution Design Space based on accurate prediction.

High-efficiency liquid chromatographic separation utilizing long monolithic silica capillary columns.

Long monolithic silica-C18 capillary columns of 100 microm i.d. were prepared, and the efficiency was examined using reversed-phase HPLC under a pressure of up to 47 MPa. At linear velocities of 1-2 mm/s, 100,000-500,000 theoretical plates could be generated with a single column (90-440 cm in length) using an acetonitrile-water (80/20) mobile phase with a column dead time (t0) of 5-40 min. It was possible to prepare columns with a minimum plate height of 8.5 +/- 0.5 microm and permeability of (1.45 +/- 0.09) x 10(-13) m(2). The chromatographic performance of a long octadecylsilylated monolithic silica capillary column was demonstrated by the high-efficiency separations of aromatic hydrocarbons, benzene derivatives, and a protein digest. The efficiency for a peptide was maintained for an injection of up to 0.5-2 ng. When three 100 microm i.d. columns were connected to form a 1130-1240 cm column system, 1,000,000 theoretical plates were generated for aromatic hydrocarbons with retention factors of up to 2.4 with a t0 of 150 min. The fact that very high efficiencies were obtained for the retained solutes suggests the practical utility of these long monolithic silica capillary columns.