EFFECT OF THE UNCERTAINTY OF THE STABILITY DATA ON THE SHELF LIFE ESTIMATION OF PHARMACEUTICAL PRODUCTS

The estimated shelf life of a drug product is highly influenced by the variability of the measured data. The fluctuation of the stability data is composed of the manufacturing process variation (batch-to-batch and within batch variability) and of the uncertainty of the analytical method (reproducibility and repeatability). The aim of the paper is to show a calculation method by which all of the variance components can be estimated before commencing the stability study. The effect of the uncertainty on the estimated shelf life is also considered: the expected variance of a single stability time point and the width of the 95\% one-sided confidence limit after 2 storage years are calculated. For the computation the results of the content uniformity test and the validation (specifically the precision study) of the analytical method are used. The applied mathematical method is the analysis of variance. The advantage of the concept is that if the magnitude of the uncertainty is known in advance, one may consider whether the present manufacturing process and analytical method is suitable for the stability study

Testing the Fit of Regression Models Estimated with Extremely Small Samples: Application in Pharmaceutical Stability Studies

Pharmaceutical stability studies are conducted to estimate the shelf life, i.e. the period during which the drug product maintains its identity and stability. In the evaluation of process, regression curve is fitted on the data obtained during the study and the shelf life is determined using the fitted curve. The evaluation process suggested by ICH considers only the case of the true relationship between the measured attribute and time being linear. However, no method is suggested for the practitioner to decide if the linear model is appropriate for their dataset. This is a major problem, as a falsely selected model may distort the estimated shelf life to a great extent, resulting in unreliable quality control. The difficulty of model misspecification detection in stability studies is that very few observations are available. The conventional methods applied for model verification might not be appropriate or efficient due to the small sample size. In this paper, this problem is addressed and some developed methods are proposed to detect model misspecification. The methods can be applied for any process where the regression estimation is performed on independent small samples. Besides stability studies, frequently performed construction of single calibration curves for an analytical measurement is another case where the methods may be applied. It is shown that our methods are statistically appropriate and some of them have high efficiency in the detection of model misspecification when applied in simulated situations which resemble pre-approval and post-approval stability studies

Tolerance Limit-based Estimation of the Proportion of Non-conforming Parts in a Multiple Stream Process

The conventional way to characterize the proportion of non-conforming parts in a process is to calculate process capability indices and transform them into a ratio. These widely used indices are able to give digestible information about the ratio of non-conforming parts if some assumptions are fulfilled. A correct estimation method should be based on the output distribution of the process, and the uncertainty of the parameter estimates should be considered, as well. In this article, a special case of the output distribution is examined: a mixture of normal distributions is considered. In practice, this output distribution appears if a multiple stream process is investigated. The novelty of this study is to apply the tolerance interval-based estimation method for the proportion of non-conforming parts in a case study of a multiple stream process and to qualify the limitations of the proposed estimation method. A simulation study is performed to investigate the bias, mean square error, and root mean square error of the estimates from the two estimation methods (process performance index-based and tolerance interval-based) for different sample sizes for each stream (N ). It was found that, if it may be assumed that the speed of the streams is equal in the case of the sample sizes investigated (N = 25, 50, 100 per head), the proposed (tolerance interval-based) method overestimates the proportion of non-conforming parts while the conventional (process performance index-based) method underestimates it. The tolerance-limit based estimation method has asymptotically better properties than the process performance index-based estimation method

Acute Ecotoxicological Effects of Bauxite Residue Addition on Mortality and Motion-frequency of Dendrobaena veneta and Enchytraeus albidus (Annelida) in Three Types of Soils

The bauxite residue is produced in high amounts all over the world. This industrial waste is a possible soil-amendment material. Although the material has been produced in high amounts, it is not frequently reused. We investigated its ecotoxicological effects on two annelid species: Dendrobaena veneta and Enchytraeus albidus. Two forms of bauxite residue (BR: S – untreated; G – dried, filter pressed, and gypsum neutralized) and three natural soils (NH: Nagyhörcsök, NY: Nyírlugos, OB: Őrbottyán) were examined. To determine the safe concentration of bauxite residue in soil on the short, acute mortality and sublethal behavioral tests (peristaltic motion-frequency) were performed. The bauxite residue addition (<5/10%) raised the pH and water holding capacity level of soils. Both types of the bauxite residue increased the motion-frequency of the worms. The untreated type had an acute mortality effect (>25%). Both species refused the soils containing both bauxite residue types at higher concentrations (>10%). Slight bauxite residue addition may improve the life circumstances of annelids in acidic sandy soils because of the potential rise of the pH level and water holding capacity

Model Building on Selectivity of Gas Antisolvent Fractionation Method Using the Solubility Parameter

Solubility parameters are widely used in the polymer industry and are often applied in the high pressure field as well as they give the possibility of combining the effects of all operational parameters on solubility in a single term. We demonstrate a statistical methodology to apply solubility parameters in constructing a model to describe antisolvent fractionation based chiral resolution, which is a complex process including a chemical equilibrium, precipitation and extraction as well. The solubility parameter used in this article, is the Hansen parameter. The evaluation of experimental results of resolution and crystallization of ibuprofen with (R)-phenylethylamine based on diastereomeric salt formation by gas antisolvent fractionation method was carried out. Two sets of experiments were performed, one with methanol as organic solvent in an undesigned experiment and one with ethanol in a designed experiment. The utilization of D-optimal design in order to decrease the necessary number of experiments and to overcome the problem of constrained design space was demonstrated. Linear models including dependence of pressure, temperature and the solubility parameter were appropriate to describe the selectivity of the GASF optical resolution method in both sets of experiments