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Rozet E.,University of Liege | Ziemons E.,University of Liege | Marini R.D.,University of Liege | Boulanger B.,Arlenda SA | Hubert P.,University of Liege
Analytical Chemistry | Year: 2012

The concept of quality by design (QbD) has recently been adopted for the development of pharmaceutical processes to ensure a predefined product quality. Focus on applying the QbD concept to analytical methods has increased as it is fully integrated within pharmaceutical processes and especially in the process control strategy. In addition, there is the need to switch from the traditional checklist implementation of method validation requirements to a method validation approach that should provide a high level of assurance of method reliability in order to adequately measure the critical quality attributes (CQAs) of the drug product. The intended purpose of analytical methods is directly related to the final decision that will be made with the results generated by these methods under study. The final aim for quantitative impurity assays is to correctly declare a substance or a product as compliant with respect to the corresponding product specifications. For content assays, the aim is similar: making the correct decision about product compliance with respect to their specification limits. It is for these reasons that the fitness of these methods should be defined, as they are key elements of the analytical target profile (ATP). Therefore, validation criteria, corresponding acceptance limits, and method validation decision approaches should be settled in accordance with the final use of these analytical procedures. This work proposes a general methodology to achieve this in order to align method validation within the QbD framework and philosophy. β-Expectation tolerance intervals are implemented to decide about the validity of analytical methods. The proposed methodology is also applied to the validation of analytical procedures dedicated to the quantification of impurities or active product ingredients (API) in drug substances or drug products, and its applicability is illustrated with two case studies. © 2011 American Chemical Society.

Rozet E.,University of Liege | Marini R.D.,University of Liege | Ziemons E.,University of Liege | Boulanger B.,Arlenda SA | Hubert P.,University of Liege
Journal of Pharmaceutical and Biomedical Analysis | Year: 2011

Bioanalytical method validation is a mandatory step to evaluate the ability of developed methods to provide accurate results for their routine application in order to trust the critical decisions that will be made with them. Even if several guidelines exist to help perform bioanalytical method validations, there is still the need to clarify the meaning and interpretation of bioanalytical method validation criteria and methodology. Yet, different interpretations can be made of the validation guidelines as well as for the definitions of the validation criteria. This will lead to diverse experimental designs implemented to try fulfilling these criteria. Finally, different decision methodologies can also be interpreted from these guidelines. Therefore, the risk that a validated bioanalytical method may be unfit for its future purpose will depend on analysts personal interpretation of these guidelines. The objective of this review is thus to discuss and highlight several essential aspects of methods validation, not only restricted to chromatographic ones but also to ligand binding assays owing to their increasing role in biopharmaceutical industries. The points that will be reviewed are the common validation criteria, which are selectivity, standard curve, trueness, precision, accuracy, limits of quantification and range, dilutional integrity and analyte stability. Definitions, methodology, experimental design and decision criteria are reviewed. Two other points closely connected to method validation are also examined: incurred sample reproducibility testing and measurement uncertainty as they are highly linked to bioanalytical results reliability. Their additional implementation is foreseen to strongly reduce the risk of having validated a bioanalytical method unfit for its purpose. © 2010 Elsevier B.V.

Rozet E.,University of Liege | Marini R.D.,University of Liege | Ziemons E.,University of Liege | Hubert P.,University of Liege | And 3 more authors.
TrAC - Trends in Analytical Chemistry | Year: 2011

Guidelines ISO 17025 and ISO 15189 aim to improve the quality-assurance scheme of laboratories. Reliable analytical results are of central importance due to the critical decisions that are taken with them. ISO 17025 and ISO 15189 therefore require that analytical methods be validated and that laboratories can routinely provide the measurement uncertainty of the results of measurements. To evaluate the fitness of purpose of analytical methods, total error is increasingly applied to assess the reliability of results generated by analytical methods. However, the ISO requirement to estimate measurement uncertainty seems opposed to the concept of total error, leading to delays in laboratories implementing ISO 17025 and ISO 15189 and confusion for the analysts. This article therefore aims to clarify the divergences between total error and measurement uncertainty, but also to discuss their main similarities and emphasize their implementation. © 2011 Elsevier Ltd.

Rozet E.,University of Liege | Lebrun P.,University of Liege | Hubert P.,University of Liege | Debrus B.,University of Geneva | Boulanger B.,Arlenda SA
TrAC - Trends in Analytical Chemistry | Year: 2013

Since the adoption of the ICH Q8 document concerning the development of pharmaceutical processes following a Quality by Design (QbD) approach, there have been many discussions on the opportunity for analytical method developments to follow a similar approach. A key component of the QbD paradigm is the definition of the Design Space (DS) of analytical methods where assurance of quality is provided. Several DSs for analytical methods have been published, stressing the importance of this concept. This article aims to explain what an analytical method DS is, why it is useful for the robust development and optimization of analytical methods and how to build such a DS. We distinguish the usual mean response surface approach, overlapping mean response surfaces and the desirability function as only they correctly define a DS. We also review and discuss recent publications assessing the DS of analytical methods. © 2012 Elsevier Ltd.

Pestieau A.,University of Liege | Krier F.,University of Liege | Lebrun P.,Arlenda SA | Brouwers A.,Galephar Research Center M F | And 2 more authors.
International Journal of Pharmaceutics | Year: 2015

The aim of this study was to develop a formulation containing fenofibrate and Gelucire® 50/13 (Gattefossé, France) in order to improve the oral bioavailability of the drug. Particles from gas saturated solutions (PGSS) process was chosen for investigation as a manufacturing process for producing a solid dispersion. The PGSS process was optimized according to the in vitro drug dissolution profile obtained using a biphasic dissolution test. Using a design of experiments approach, the effects of nine experimental parameters were investigated using a PGSS apparatus provided by Separex® (Champigneulles, France). Within the chosen experimental conditions, the screening results showed that the drug loading level, the autoclave temperature and pressure, the connection temperature and the nozzle diameter had a significant influence on the dissolution profile of fenofibrate. During the optimization step, the three most relevant parameters were optimized using a central composite design, while other factors remained fixed. In this way, we were able to identify the optimal production conditions that would deliver the highest level of fenofibrate in the organic phase at the end of the dissolution test. The closeness between the measured and the predicted optimal dissolution profiles in the organic phase demonstrated the validity of the statistical analyses. © 2015 Elsevier B.V. All rights reserved.

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