Analytical Quality by Design: Achieving Robustness of an LC-CAD Method for the Analysis of Non-Volatile Fatty Acids.

An alternative to the time-consuming and error-prone pharmacopoeial gas chromatography method for the analysis of fatty acids (FAs) is urgently needed. The objective was therefore to propose a robust liquid chromatography method with charged aerosol detection for the analysis of polysorbate 80 (PS80) and magnesium stearate. FAs with different numbers of carbon atoms in the chain necessitated the use of a gradient method with a Hypersil Gold C18 column and acetonitrile as organic modifier. The risk-based Analytical Quality by Design approach was applied to define the Method Operable Design Region (MODR). Formic acid concentration, initial and final percentages of acetonitrile, gradient elution time, column temperature, and mobile phase flow rate were identified as critical method parameters (CMPs). The initial and final percentages of acetonitrile were fixed while the remaining CMPs were fine-tuned using response surface methodology. Critical method attributes included the baseline separation of adjacent peaks (α-linolenic and myristic acid, and oleic and petroselinic acid) and the retention factor of the last compound eluted, stearic acid. The MODR was calculated by Monte Carlo simulations with a probability equal or greater than 90%. Finally, the column temperature was set at 33 °C, the flow rate was 0.575 mL/min, and acetonitrile linearly increased from 70 to 80% (v/v) within 14.2 min.

Alternative methods to assess the impurity profile of a monographed API using acarbose as an example.

Even though the impurity analysis of the Ph. Eur. is considered well-studied, its methodology should be reviewed periodically to ensure that it is working properly, and all impurities are captured by the section "Related substances" of the monograph. Within this study, the biotechnological produced antidiabetic drug acarbose was chosen to demonstrate some of the advantages as well as the shortcomings arising from the current related substances test of acarbose. Due to its weak chromophore, acarbose is studied by UV detection at 210 nm after being separated on aminopropyl-silyl stationary phases. Thus, the use of alternative detection techniques, such as charge aerosol detection (CAD) and a volatile mobile phase can be beneficial here. Since a simple method transfer to a mobile phase usable with the CAD was not possible, more stable stationary phases were tested. For the rapid determination of the sum of impurities, a method was developed using a pentafluorophenyl column and a mobile phase of 0.1% TFA in water. Maltose and maltotriose were further identified as additional impurities of the API. Furthermore, a method was developed and validated by means of an Amide-HILIC phase, that adequately separated acarbose and all of its impurities. However, the sensitivity of this method needs to be further improved. Additionally, a method was also developed and validated, taking into account the temperature stability of graphite columns. Thus, the separation was carried out at temperatures of about 90 °C to solve the problem of anomerization of acarbose and some of its impurities. In comparison with the other developed methods, the elution order was changed and has to be confirmed, but all components were separated and detected at a sufficient LOQ of 0.10%.

Charged aerosol detector response modeling for fatty acids based on experimental settings and molecular features: a machine learning approach.

The charged aerosol detector (CAD) is the latest representative of aerosol-based detectors that generate a response independent of the analytes' chemical structure. This study was aimed at accurately predicting the CAD response of homologous fatty acids under varying experimental conditions. Fatty acids from C12 to C18 were used as model substances due to semivolatile characterics that caused non-uniform CAD behaviour. Considering both experimental conditions and molecular descriptors, a mixed quantitative structure-property relationship (QSPR) modeling was performed using Gradient Boosted Trees (GBT). The ensemble of 10 decisions trees (learning rate set at 0.55, the maximal depth set at 5, and the sample rate set at 1.0) was able to explain approximately 99% (Q2: 0.987, RMSE: 0.051) of the observed variance in CAD responses. Validation using an external test compound confirmed the high predictive ability of the model established (R2: 0.990, RMSEP: 0.050). With respect to the intrinsic attribute selection strategy, GBT used almost all independent variables during model building. Finally, it attributed the highest importance to the power function value, the flow rate of the mobile phase, evaporation temperature, the content of the organic solvent in the mobile phase and the molecular descriptors such as molecular weight (MW), Radial Distribution Function-080/weighted by mass (RDF080m) and average coefficient of the last eigenvector from distance/detour matrix (Ve2_D/Dt). The identification of the factors most relevant to the CAD responsiveness has contributed to a better understanding of the underlying mechanisms of signal generation. An increased CAD response that was obtained for acetone as organic modifier demonstrated its potential to replace the more expensive and environmentally harmful acetonitrile.

Impurity profiling of dapsone using gradient HPLC method.

The quality control of active pharmaceutical ingredients (APIs) is a very important aspect for drug products entering the market. However, also for the well-established drugs, there ought to be a state-of-the-art impurity control. Some of the pharmacopoeial tests for related substances still make use of thin layer chromatography, even though selectivity and sensitivity are suboptimal. Here, we report on the development of a new gradient high performance liquid chromatography (HPLC) method for dapsone in order to replace the currently described pharmacopoeial TLC method. The separation of all relevant components was achieved on a C18 stationary phase (Waters XTerra® RP18 5 µm 4.6 × 250 mm) using a water-acetonitrile gradient. A limit of detection (LOD) of 0.02% was registered for all specified impurities. Additionally, within this study an "impurity of an impurity" was identified by means of LC-MS/MS.

Risk assessment report of potential impurities in cetirizine dihydrochloride.

Recently, the European Medicines Agency (EMA) and the U.S. Food and Drug Administration (FDA) had reported on "unexpected" impurities in a couple of sartans, ranitidine, and metformin. These events led to a lot of discussion with regard to the risk assessment for the production process itself. Most of these discussions covered the field of nitrosamine impurities only, but that would be too short-sighted. One should expand that scope. It is impossible to synthesize a 100 % pure compound which holds true for all active pharmaceutical ingredients (APIs). Different synthetic routes result in different impurity profiles. Therefore, pharmacopoeias try to consider all possible impurities that can arise from different drug synthesis routes in one a single monograph for impurity assessment. However, API manufacturers cannot simply rely on the impurity profile reported in pharmacopoeias for the production of a high-quality product. They have to implement a whole risk assessment to rate the presence of impurities in the API. Here, a strategy to evaluate and minimize the load of potential risks of impurities during the manufacturing process of the drug substance cetirizine dihydrochloride within the frame of a detailed risk assessment report is demonstrated.