Eric Ziemons

Advances in validation, risk and uncertainty assessment of bioanalytical methods

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.

Moisture content determination of pharmaceutical pellets by near infrared spectroscopy: Method development and validation

The aim of the present study was to develop and validate a near infrared method able to accurately determine a moisture content of pharmaceutical pellets ranging from 1% to 8% in order to check their moisture content conformity. A calibration and validation set were designed for the conception and evaluation of the method adequacy. An experimental protocol was then followed, involving two operators, independent production campaign batches and different temperatures for data acquisition. On the basis of this protocol, prediction models based on partial least squares (PLS) regression were then carried out. Conventional criteria such as the R(2), the root mean square errors of calibration and prediction (RMSEC and RMSEP) as well as the number of PLS factors enabled the selection of three preliminary models. However, such criteria did not clearly demonstrate the models ability to give accurate predictions over the whole analyzed water content range. Consequently, a novel approach based on accuracy profiles which allow the selection of the most fitted model for purpose was used. According to this novel approach, the model using multiplicative scatter correction (MSC) pre-treatment was obviously the most suitable. Indeed, the resulting accuracy profile clearly showed that this model was able to determine moisture content over the range of 1-8% with a very acceptable accuracy. The present study confirmed that NIR spectroscopy could be used in the PAT concept as a non-invasive, non-destructive and fast technique for moisture content determination in pharmaceutical pellets. In addition, facing the limit of the classical and commonly used criteria, the use of accuracy profiles proved to be useful as a powerful decision tool to demonstrate the suitability of the proposed analytical method.

Critical review of near-infrared spectroscopic methods validations in pharmaceutical applications

Based on the large number of publications reported over the past five years, near-infrared spectroscopy (NIRS) is more and more considered an attractive and promising analytical tool regarding Process Analytical Technology and Green Chemistry. From the reviewed literature, few of these publications present a thoroughly validated NIRS method even if some guidelines have been published by different groups and regulatory authorities. However, as any analytical method, the validation of NIRS method is a mandatory step at the end of the development in order to give enough guarantees that each of the future results during routine use will be close enough to the true value. Besides the introduction of PAT concepts in the revised document of the European Pharmacopoeia (2.2.40) dealing with near-infrared spectroscopy recently published in Pharmeuropa, it agrees very well with this mandatory step. Indeed, the latter suggests to use similar analytical performance characteristics than those required for any analytical procedure based on acceptance criteria consistent with the intended use of the method. In this context, this review gives a comprehensive and critical overview of the methodologies applied to assess the validity of quantitative NIRS methods used in pharmaceutical applications.

Acetaminophen determination in low-dose pharmaceutical syrup by NIR spectroscopy

The aim of the present study was first to develop a robust near infrared (NIR) calibration model able to determine the acetaminophen content of a low-dose syrup formulation (2%, w/v). Therefore, variability sources such as production campaigns, batches, API concentration, syrup basis, operators and sample temperatures were introduced in the calibration set. A prediction model was then built using partial least square (PLS) regression. First derivative followed by standard normal variate (SNV) were chosen as signal pre-processing. Based on the random subsets cross-validation, 4 PLS factors were selected for the prediction model. The method was then validated for an API concentration ranging from 16 to 24 mg/mL (1.6-2.4%, w/v) using an external validation set. The 0.26 mg/mL RMSEP suggested the global accuracy of the model. The accuracy profile obtained from the validation results, based on tolerance intervals, confirmed the adequate accuracy of the results generated by the method all over the investigated API concentration range. Finally, the NIR model was used to monitor in real time the API concentration while mixing syrups containing various amounts of API, a good agreement was found between the NIR method and the theoretical concentrations.

Active content determination of non-coated pharmaceutical pellets by near infrared spectroscopy: method development, validation and reliability evaluation.

A robust near infrared (NIR) method able to quantify the active content of pilot non-coated pharmaceutical pellets was developed. A protocol of calibration was followed, involving 2 operators, independent pilot batches of non-coated pharmaceutical pellets and two different NIR acquisition temperatures. Prediction models based on Partial Least Squares (PLS) regression were then carried out. Afterwards, the NIR method was fully validated for an active content ranging from 80 to 120% of the usual active content using new independent pilot batches to evaluate the adequacy of the method to its final purpose. Conventional criteria such as the R(2), the Root Mean Square Error of Calibration (RMSEC), the Root Mean Square Error of Prediction (RMSEP) and the number of PLS factors enabled the selection of models with good predictive potential. However, such criteria sometimes fail to choose the most fitted for purpose model. Therefore, a novel approach based on accuracy profiles of the validation results was used, providing a visual representation of the actual and future performances of the models. Following this approach, the prediction model using signal pre-treatment Multiplicative Scatter Correction (MSC) was chosen as it showed the best ability to quantify accurately the active content over the 80-120% active content range. The reliability of the NIR method was tested with new pilot batches of non-coated pharmaceutical pellets containing 90 and 110% of the usual active content, with blends of validation batches and industrial batches. All those batches were also analyzed by the HPLC reference method and relative errors were calculated: the results showed low relative errors in full accordance with the results obtained during the validation of the method, indicating the reliability of the NIR method and its interchangeability with the HPLC reference method.

Critical analysis of several analytical method validation strategies in the framework of the fit for purpose concept.

Analytical method validation is a mandatory step at the end of the development in all analytical laboratories. It is a highly regulated step of the life cycle of a quantitative analytical method. However, even if some documents have been published there is a lack of clear guidance for the methodology to follow to adequately decide when a method can be considered as valid. This situation has led to the availability of several methodological approaches and it is therefore the responsibility of the analyst to choose the best one. The classical decision processes encountered during method validation evaluation are compared, namely the descriptive, difference and equivalence approaches. Furthermore a validation approach using accuracy profile computed by means of beta-expectation tolerance interval and total measurement error is also available. In the present paper all of these different validation approaches were applied to the validation of two analytical methods. The evaluation of the producer and consumer risks by Monte Carlo simulations were also made in order to compare the appropriateness of these various approaches. The classical methodologies give rise to inadequate and contradictory conclusions which do not allow them to answer adequately the objective of method validation, i.e. to give enough guarantees that each of the future results that will be generated by the method during routine use will be close enough to the true value. It is found that the validation methodology which gives the most guarantees with regards to the reliability or adequacy of the decision to consider a method as valid is the one based on the use of the accuracy profile.

Data processing of vibrational chemical imaging for pharmaceutical applications.

Vibrational spectroscopy (MIR, NIR and Raman) based hyperspectral imaging is one of the most powerful tools to analyze pharmaceutical preparation. Indeed, it combines the advantages of vibrational spectroscopy to imaging techniques and allows therefore the visualization of distribution of compounds or crystallization processes. However, these techniques provide a huge amount of data that must be processed to extract the relevant information. This review presents fundamental concepts of hyperspectral imaging, the basic theory of the most used chemometric tools used to pre-process, process and post-process the generated data. The last part of the present paper focuses on pharmaceutical applications of hyperspectral imaging and highlights the data processing approaches to enable the reader making the best choice among the different tools available.

Building the quality into pellet manufacturing environment – Feasibility study and validation of an in-line quantitative near infrared (NIR) method

The present study focuses on the implementation of an in-line quantitative near infrared (NIR) spectroscopic method for determining the active content of pharmaceutical pellets. The first aim was to non-invasively interface a dispersive NIR spectrometer with four realistic particle streams existing in the pellets manufacturing environment. Regardless of the particle stream characteristics investigated, NIR together with Principal Component Analysis (PCA) was able to classify the samples according to their active content. Further, one of these particle stream interfaces was non-invasively investigated with a FT-NIR spectrometer. A predictive model based on Partial Least Squares (PLS) regression was able to determine the active content of pharmaceutical pellets. The NIR method was finally validated with an external validation set for an API concentration range from 80 to 120% of the targeted active content. The prediction error of 0.9% (root mean standard error of prediction, RMSEP) was low, indicating the accuracy of the NIR method. The accuracy profile on the validation results, an innovative approach based on tolerance intervals, demonstrated the actual and future performance of the in-line NIR method. Accordingly, the present approach paves the way for real-time release-based quality system.

Improvement of a stability-indicating method by Quality-by-Design versus Quality-by-Testing: A case of a learning process

The understanding of the method is a major concern when developing a stability-indicating method and even more so when dealing with impurity assays from complex matrices. In the presented case study, a Quality-by-Design approach was applied in order to optimize a routinely used method. An analytical issue occurring at the last stage of a long-term stability study involving unexpected impurities perturbing the monitoring of characterized impurities needed to be resolved. A compliant Quality-by-Design (QbD) methodology based on a Design of Experiments (DoE) approach was evaluated within the framework of a Liquid Chromatography (LC) method. This approach allows the investigation of Critical Process Parameters (CPPs), which have an impact on Critical Quality Attributes (CQAs) and, consequently, on LC selectivity. Using polynomial regression response modeling as well as Monte Carlo simulations for error propagation, Design Space (DS) was computed in order to determine robust working conditions for the developed stability-indicating method. This QbD compliant development was conducted in two phases allowing the use of the Design Space knowledge acquired during the first phase to define the experimental domain of the second phase, which constitutes a learning process. The selected working condition was then fully validated using accuracy profiles based on statistical tolerance intervals in order to evaluate the reliability of the results generated by this LC/ESI-MS stability-indicating method. A comparison was made between the traditional Quality-by-Testing (QbT) approach and the QbD strategy, highlighting the benefit of this QbD strategy in the case of an unexpected impurities issue. On this basis, the advantages of a systematic use of the QbD methodology were discussed.

Evaluation of the quantitative performances of supercritical fluid chromatography: from method development to validation.

Recently, the number of papers about SFC increased drastically but scientists did not truly focus their work on quantitative performances of this technique. In order to prove the potential of UHPSFC, the present work discussed about the different steps of the analytical life cycle of a method: from development to validation and application. Moreover, the UHPSFC quantitative performances were evaluated in comparison with UHPLC, which is the main technique used for quality control in the pharmaceutical industry and then could be considered as a reference. The methods were developed using Design Space strategy, leading to the optimization of robust method. In this context, when the Design Space optimization shows guarantee of quality, no more robustness study is required prior to the validation. Then, the methods were geometrically transferred in order to reduce the analysis time. The UHPSFC and UHPLC methods were validated based on the total error approach using accuracy profile. Even if UHPLC showed better precision and sensitivity, UHPSFC method is able to give accurate results in a dosing range larger than the 80-120% range required by the European Medicines Agency. Consequently, UHPSFC results are valid and could be used for the control of active substance in a finished pharmaceutical product. Finally, UHPSFC validated method was used to analyse real samples and gave similar results than the reference method (UHPLC).