A new, simple, specific, sensitive, rapid, accurate and precise RP-HPLC method was developed for the proportioning of the methylparaben and the propylparaben in pharmaceutical formulations as well as the phenol, which is their main degradation product. These parabens are widely used as preservatives in pharmaceutical and cosmetic products. The separation was performed on a C18-column using a mobile phase elution gradient (Acetate buffer 50mM pH 5/Acetonitrile). The detection was performed at a fixed wavelength (lambda = 271nm), with a flow rate of 1.3 ml/min. The detector response was linear in concentrations ranging from 10 to 60 mu g/ml for the methylparaben, from 3 to 15 mu g/ml for the propylparaben and from 0.125 to 2.5 mu g/ml for the phenol. The intra and inter day variation was found to be less than 2%. The limits of quantification and of detection of the phenol are of 0.1 mu g/ml and 0.03 mu g/ml, respectively. The recovery ratio was equal to 101.8 % for the methylparaben, 101.2 % for the propylparaben and 98.4 % for the phenol. The proposed method was used to monitor the degradation of the parabens and the production of the phenol in studied solutions.

In this paper, we report the results of quality control based in physicochemical characterization and impurities determination of three samples of fluconazole drug substances marketed in Morocco. These samples were supplied by different pharmaceuticals companies. The sample A, as the discovered product, was supplied by Pfizer, while samples B and C (generics), were manufactured by two different Indian industries. Solid-state characterization of the three samples was realized with different physicochemical methods as: X-ray powder diffraction, Fourier-transformation infrared spectroscopy, differential scanning calorimetry. High performance liquid chromatography was used to quantify the impurities in the different samples. The results from the physicochemical methods cited above, showed difference in polymorph structure of the three drug substances. Sample A consisted in pure polymorph III, sample B consisted in pure polymorph II, sample C consisted in a mixture of fluconazole Form III, form II and the monohydrate. This result was confirmed by differential scanning calorimetry. Also it was demonstrated that solvents used during the re-crystallization step were among the origins of these differences in the structure form. On the other hand, the result of the stability study under humidity and temperature showed that fluconazole polymorphic transformation could be owed to the no compliance with the conditions of storage. The HPLC analysis of these compounds showed the presence of specific impurities for each polymorphic form, and a possible relationship could be exist between impurities and crystalline form of fluconazole.

Analytical methods capability evaluation can be a useful methodology to assess the fitness of purpose of these methods for their future routine application. However, care on how to compute the capability indices have to be made. Indeed, the commonly used formulas to compute capability indices such as Cpk, will highly overestimate the true capability of the methods. Especially during methods validation or transfer, there are only few experiments performed and, using in these situations the commonly applied capability indices to declare a method as valid or as transferable to a receiving laboratory will conduct to inadequate decisions. In this work, an improved capability index, namely Cpk-tol and the corresponding estimator of proportion of non-conforming results (π(Cpk-tol)) have been proposed. Through Monte-Carlo simulations, they have been shown to greatly increase the estimation of analytical methods capability in particular in low sample size situations as encountered during methods validation or transfer. Additionally, the usefulness of this capability index has been illustrated through several case studies covering applications commonly encountered in the pharmaceutical industry. Finally a methodology to determine the optimal sample size required to validate analytical methods is also given using the proposed capability metric.

An innovative versatile strategy using Total Error has been proposed to decide about the method's validity that controls the risk of accepting an unsuitable assay together with the ability to predict the reliability of future results. This strategy is based on the simultaneous combination of systematic (bias) and random (imprecision) error of analytical methods. Using validation standards, both types of error are combined through the use of a prediction interval or β-expectation tolerance interval. Finally, an accuracy profile is built by connecting, on one hand all the upper tolerance limits, and on the other hand all the lower tolerance limits. This profile combined with pre-specified acceptance limits allows the evaluation of the validity of any quantitative analytical method and thus their fitness for their intended purpose. In this work, the approach of accuracy profile was evaluated on several types of analytical methods encountered in the pharmaceutical industrial field and also covering different pharmaceutical matrices. The four studied examples depicted the flexibility and applicability of this approach for different matrices ranging from tablets to syrups, different techniques such as liquid chromatography, or UV spectrophotometry, and for different categories of assays commonly encountered in the pharmaceutical industry i.e. content assays, dissolution assays, and quantitative impurity assays. The accuracy profile approach assesses the fitness of purpose of these methods for their future routine application. It also allows the selection of the most suitable calibration curve, the adequate evaluation of a potential matrix effect and propose efficient solution and the correct definition of the limits of quantification of the studied analytical procedures.

The aim of the present study was to develop near infrared (NIR) and X-ray powder diffraction methods (XRPD) able to determine pure crystalline form II of fluconazole in a binary polymorphic mixtures containing forms II and III. In order to give a first performance estimation of both methods, these latters were pre-validated using accuracy profiles, a statistical approach based on β-expectation tolerance intervals. Both methods showed a good trueness, precision and accuracy and their β-expectation tolerance intervals were fully included within the acceptance limits. The comparative study was carried out using statistical analysis based on the work of Bland and Altman. A good agreement between the two methods was demonstrated indicating the interchangeability of NIR method with XRPD method.

Analytical methods validation is a mandatory step to evaluate the ability of developed methods to provide accurate results for their routine application. Validation usually involves validation standards or quality control samples that are prepared in placebo or reconstituted matrix made of a mixture of all the ingredients composing the drug product except the active substance or the analyte under investigation. However, one of the main concerns that can be made with this approach is that it may lack an important source of variability that come from the manufacturing process. The question that remains at the end of the validation step is about the transferability of the quantitative performance from validation standards to real authentic drug product samples. In this work, this topic is investigated through three case studies. Three analytical methods were validated using the commonly spiked placebo validation standards at several concentration levels as well as using samples coming from authentic batch samples (tablets and syrups). The results showed that, depending on the type of response function used as calibration curve, there were various degrees of differences in the results accuracy obtained with the two types of samples. Nonetheless the use of spiked placebo validation standards was showed to mimic relatively well the quantitative behaviour of the analytical methods with authentic batch samples. Adding these authentic batch samples into the validation design may help the analyst to select and confirm the most fit for purpose calibration curve and thus increase the accuracy and reliability of the results generated by the method in routine application.