1. References
2. Stability

Shown here are examples of additional references for Stability: 

Abstract:

Captopril, an anti-hypertensive drug, is seriously susceptible to oxidative degradation by high temperatures, humidity, and by the presence of hygroscopic excipients. Captopril disulphide is the main degradation product. In this study, multivariate control charts have been designed in order to monitor the captopril stability by using Hotelling's T² statistics and the Squared Prediction Error (SPE). High-Performance Liquid Chromatography was the analytical technique used. The performance of T² and SPE charts depend on the pre-processing applied. The scaling methods, particularly the chromatograms weighting in the region of captopril disulphide, highlight the relevant chemical information and sensitize the charts for the detection of minor changes in the operating conditions.

Fifty-two chromatograms from different batches of captopril in normal operating conditions were used for the preparation of T² and SPE charts during the training stage. Eleven samples, seven within their shelf life and four after their expiration date were used in the validation stage. A stability study was performed by putting captopril samples in a 40 ± 2 °C and 75 ± 5% relative humidity climatic chamber. Captopril samples have been removed weekly from the climatic chamber over the course of six months. A Principal Components Analysis (PCA) was performed on the data set and the scores of the first 3 components were employed in the Hotelling's T² building, while the SPE chart was designed with the model residuals. The multivariate control charts are sensitized to monitor chromatographic profile changes and captopril stability standard changes.

 

Highlights:

• The International Conference on Harmonisation (ICH) Q3 guidance currently recommends a pharmaceutical products definition change.  The focus of the quality control changed from purity in active pharmaceutical ingredients (API) to impurity and degradation in finished pharmaceutical products.  The need to develop and apply analytical chemistry and chemometrics techniques to monitor impurities is currently quite evident in the pharmaceutical industry.
• The Multivariate Statistical Process Control (MSPC) basis is collecting a historical data set when the process is working under normal operating conditions (NOC), performing a principal component analysis with historical data for modelling and extracting the correlation structure of several correlated variables and using the modelled information in the multivariate control chart design.
• Pre-processing of the chromatograms was required such as alignment of the retention times using algorithms such as Correlation Optimised Warping, removal of regions on the chromatograms that are not of interest and mean square root scaling to increase the sensitivity of multivariate analysis charts to detect small impurity peaks.
• The sensitivity for change detection of chromatographic profiles depended on the representativeness of the historic data (NOC), the pre-processing methods and on the number of principal components included in the NOC model, which was determined by minimizing the amount of type 1 errors of T² during the training phase, when only NOC samples were used.
• The weighting of chromatograms in the region of captopril disulphide sensitized control charts for the detection of minor variations in impurity peaks.
• The validation stage with NOC samples allowed for the tuning of the sensitivity by weight adjusting until the minimization of type 1 and 2 errors.
• The SPE statistics were more sensitive to small variations in the impurity peaks.
• When applied to the stability set, the sample control output could be associated with changes in the chromatographic profile due to the increase of captopril disulphide content.
• Systematic variations of the T² chart monitored signal also indicated a control output.

Abstract:

Certified reference materials (CRMs) certified for the mass fraction of different metal species have been monitored for stability over the course of many years and the results are presented in the paper.

Components tested include organotin, organomercury, organolead and organoarsenic species in different matrices like sediments or fish tissue.

The stability monitoring points were set to yearly or every 3 years, based on the quality of the original stability data. Several labs were involved in the stability testing, presenting unique challenges to the comparability of the results. The use of ratios is presented to eliminate the possible between-run bias and lab bias.

 

Highlights:

• Reference samples (stored at lower temperature than the normal samples) were used for comparison with the normal samples.
• Typically, 4 bottles (2 normal stock, 2 reference stock) with 3 measurements each with independent sample preparation were tested per measurement run.
• To check for stability, comparison of the mean of results with the certified value was done, under consideration of lab uncertainty. If the lab uncertainty had been underestimated, the uncertainty from the certification process was used.
• A visual check for a possible trend over time was done.
• The ratio of means of normal stock and reference stock were compared (expected value = 1) and checked if significantly different.
• Furthermore, regression analysis was used over the test series to approximate a possible degradation. The slope was tested for significant difference from zero. If it is not significant, the uncertainty of the slope was then used as ustab for a shelf life of an additional 24 months on top of the “age” of the material.
• If in the comparison, ustab is negligible (max. 1/3) compared to other uncertainty contributions, this was seen as a positive demonstration of stability and the shelf life could be derived from this approach.
• This paper shows the usefulness of the evaluation via ratios - even if absolute values differ significantly from the certified values.