Automatic system dynamics characterization of a pharmaceutical continuous production line.

Continuous Manufacturing (CM) of drug products is a new approach in the pharmaceutical industry. In the presented paper, a GMP continuous wet granulation line for production of solid oral dosage forms was investigated in order to assess the system dynamics of the line and to define the best control and diversion strategy. The following steps were involved in the continuous process: dosing/feeding, blending, twin-screw wet granulation, fluid-bed drying, sieving and tableting. Two drug products with two different drug substances were compared during this study: one drug substance as model drug compound and one formulation of a currently evaluated commercial drug product. Several step tests in API concentration were performed in order to characterize the process flow and assess the process dynamics. API content was monitored in real time by Process Analytical Technologies (PAT) thanks to three Near Infrared (NIR) probes located along the process and measuring the API content after blender, after dryer and in the tablet press feed frame. The process parameter values were changed during production in order to detect the impact on the quality of the final product. An automatic residence time distribution (RTD) computation method has been developed in order automate the RTD calculation on the basis of process data to further define and monitor the system dynamics with the final aim of out of specification material diversion during the continuous production. The RTD has been seen as a process fingerprint: a change in the RTD values implies a change in the process.

Towards real-time release of pharmaceutical tablets: 100% in-line control via near-infrared spatially resolved spectroscopy and 3D microwave resonance technology.

In the scope of 100% in-line quality control and real-time release of pharmaceutical tablets, the authors present a flexible inspection module for in-line tablet analysis with integrated multipoint near-infrared (NIR) spectroscopy and 3D microwave resonance technology (3D MRT). Via an industrial case study on Diclofenac Sodium tablets, the abilities of this versatile process analytical technology (PAT) tool are presented. It is demonstrated that the combination of Diclofenac concentration prediction via NIR spectroscopy and mass prediction via 3D MRT allow to estimate the dosage of each individual tablet. Single sample repetition tests were performed on 5 tablets, measured 10 times on three different days. A high accuracy and precision of prediction was shown, with an average standard deviation below 0.5 mg. The inspection run demonstrated the added value of such inspection and sorting strategies based on the calculated dosage of individual tablets.

Model predictive control in pharmaceutical continuous manufacturing: A review from a user's perspective.

Pharmaceutical continuous manufacturing is considered as an emerging technology by the regulatory agencies, which have defined a framework guided by an effective quality risk management. With the understanding of process dynamics and the appropriate control strategy, pharmaceutical continuous manufacturing is able to tackle the Quality-by-Design paradigm that paves the way to the future smart manufacturing described by Quality-by-Control. The introduction of soft sensors seems to be a helpful tool to reach smart manufacturing. In fact, soft sensors have the ability to keep the quality attributes of the final drug product as close as possible to their references set by regulatory agencies and to mitigate the undesired events by potentially discard out of specification products. Within this review, challenges related to implementing these technologies are discussed. Then, automation control strategies for pharmaceutical continuous manufacturing are presented and discussed: current control tools such as the proportional integral derivative controllers are compared to advanced control techniques like model predictive control, which holds promise to be an advanced automation concept for pharmaceutical continuous manufacturing. Finally, industrial applications of model predictive control in pharmaceutical continuous manufacturing are outlined. Simulations studies as well as real implementation on pharmaceutical plant are gathered from the control of one single operation unit such as the tablet press to the control of a full direct compaction line. Model predictive control is a key to enable the industrial revolution or Industry 4.0.

Deep learning for continuous manufacturing of pharmaceutical solid dosage form.

Continuous Manufacturing (CM) of pharmaceutical drug products is a new approach within the pharmaceutical industry. In the presented paper, a GMP continuous wet granulation line for production of solid dosage forms was investigated. The line was composed of the subsequent continuous unit: operations feeding - twin-screw wet-granulation - fluid-bed drying - sieving and tableting. The formulation of a commercial entity was selected for this study. Several critical process parameters were evaluated in order to probe the process and to characterize the impact on quality attributes. Seven critical process parameters have been selected after a risk analysis: API and excipient mass flows of the two feeders, liquid feed rate and rotation speed of the extruder and rotation speed, temperature and airflow of the dryer. Eight quality attributes were controlled in real time by Process Analytical Technologies (PAT): API content after blender, after dryer, in tablet press feed frame and of tablet, LOD after dryer and PSD after dryer (three PSD parameters: x10 x50 x90). The process parameter values were changed during production in order to detect the impact on the quality of the final product. The deep learning techniques have been used in order to predict the quality attribute (output) with the process parameters (input). The use of deep learning reduces the noise and simplify the data interpretation for a better process understanding. After optimization, three hidden layers neural network were selected with 6 hidden neurons. The activation function ReLU (Rectified Linear Unit) and the ADAM optimizer were used with 2500 epochs (number of learning cycle). API contents, PSD values and LOD values were estimated with an error of calibration lower than 10%. The level of error allow an adequate process monitoring by DNN and we have proven that the main critical process parameters can be identified at a higher levelof process understanding. The synergy between PAT and process data science creates a superior monitoring framework of the continuous manufacturing line and increase the knowledge of this innovative production line and the products that it makes.

Continuous manufacturing process monitoring of pharmaceutical solid dosage form: A case study.

Continuous Manufacturing (CM) of pharmaceutical drug products is a rather new approach within the pharmaceutical industry. In the presented paper, a GMP continuous wet granulation line used for clinical production of solid dosage forms was investigated with a thorough monitoring strategy regarding process performance and robustness. The line was composed of the subsequent continuous unit operations feeding - twin-screw wet-granulation - fluid-bed drying - sieving and tableting; the formulation of a new pharmaceutical entity in development was selected for this study. In detail, a Design of Experiments (DoE) was used to evaluate the impact of the three main factors (amount of water, filling rate, and shear force in twin-screw granulator) on the tablet quality. The process was monitored via in-process control (IPC) tests (e.g. weight, hardness, disintegration, and loss-on-drying), Process Analytical Technologies (PAT), and through the analysis of the process parameters (multivariate process control). The tested formulation was very robust to the large process variation of the DoE: all IPC results were in specification, the PAT probes provided stable results for the content uniformity and no critical variations can be detected in the process parameters. An adequate monitoring strategy was presented and the robustness of the process with one formulation has been demonstrated. In summary, this continuous process in combination with smart formulation development allows the robust production of constant quality tablets. The synergy between PAT, process data science and IPC creates an adequate monitoring framework of the continuous manufacturing line.

Near-Infrared Spectroscopy to Determine Residual Moisture in Freeze-Dried Products: Model Generation by Statistical Design of Experiments.

Moisture content (MC) is a critical quality attribute of lyophilized biopharmaceuticals and can be determined by near-infrared (NIR) spectroscopy as nondestructive alternative to Karl-Fischer titration. In this study, we create NIR models to determine MC in mAb lyophilisates by use of statistical design of experiments (DoE) and multivariate data analysis. We varied the composition of the formulation as well as lyophilization parameters covering a large range of representative conditions, which is commonly referred to as "robustness testing" according to quality-by-design concepts. We applied principles of chemometrics with partial least squares and principal component analysis. The NIR model excluded samples with complete collapse and MC > 6%. The 2 main components in the principal component analysis were MC (91%) and protein:sugar ratio (6%). The third component amounted to only 3% and remained unspecified but may include variations in process parameters and cake structure. In contrast to traditional approaches for NIR model creation, the DoE-based model can be used to monitor MC during drug product development work including scale-up, and transfer without the need to update the NIR model if protein:sugar ratio and MC stays within the tested limits and cake structure remains macroscopically intact. The use of the DoE approach and multivariate data analysis ensures product consistency and improves understanding of the manufacturing process.

Real-time monitoring of particle size distribution in a continuous granulation and drying process by near infrared spectroscopy.

In continuous granulation, it can be important to control granules particle size distribution (PSD), as it may affect final product quality. Near infrared spectroscopy (NIRS) is already a routine analytical procedure within pharmaceutical continuous manufacturing for the in-line analysis of chemical material-characteristics. Consequently, the extraction of additional information related to granules' physical properties like particle size distribution is tempting, as it would enhance process knowledge without the need for new capital investments. Three in-line NIRS methods were developed via partial least squares regression, to predict dried granules PSD-fractions X10, X50, and X90 within a GMP-qualified continuous twin-screw wet granulation and fluid-bed drying process. Methods were developed for the size range of 20-234 µm (X10), 98-1017 µm (X50), and 748-2297 µm (X90) and assessed with one internal and three external validation datasets in agreement with current guidelines on NIRS. Internal validation indicated root mean square error of predictions (RMSEPs) of 17 µm, 97 µm, and 174 µm, for PSD X10, X50, and X90 respectively, with acceptable linearity, slope, and bias. Furthermore, the ratio of prediction to deviation (RPD), the ratio of prediction error to laboratory error (PRL), and the range error ratio (RER) were evaluated, with all values within the acceptance range for adequate to good NIR methods (1.75 > RPD < 3, PRL ≤ 2, RER ≥ 10). Methods applicability to in-line processes and their robustness towards water content and active pharmaceutical ingredient content was further demonstrated with three independent in-line datasets in real-time, showing good agreement between predicted and reference values. In summary, methods demonstrated to be sufficient for their intended purpose to monitor trends and sudden changes in dried granules PSD during continuous granulation and drying. Because of their fast response time, they are unique tools to characterize the dynamic behavior and navigate the agglomeration state of the material in static and transient process conditions during continuous granulation and drying.

Process analytical technology for continuous manufacturing tableting processing: A case study.

The use of Near Infrared Spectroscopy (NIRS) as a fast and non-destructive technique was employed for the control and monitoring of the tableting step during a continuous manufacturing process. Two NIRS methods were optimized in order to in-line control the blend uniformity in the tablet feed frame and the API concentration of freshly pressed tablets prior the ejection. The novelty of this work first lies in the acquisition speed of NIR spectra reaching up to 70,000 tablets/h. Partial Least Square (PLS) regression was used as chemometric tool for the computation that resulted in excellent predictive calibration results. A coefficient of correlation (r) value of 0.99 was obtained for both probes. The root mean square error of calibration (RMSEC) and the root mean square error of prediction (RMSEP) were respectively 1.8% and 1.8% for active content in the tablet feeder and 2.2% and 2.3% for the tablet content. In addition, calibration performance and robustness of the methods were evaluated. Moreover several qualitative methods were proposed to monitor the tableting process in different stages of development (single wavelength, Principal Component Analysis, and Independent Component Analysis). In early phase development, the requirement/quality of the input material is not established yet; hence the use of a qualitative approach allows to confirm the suitability of the PAT methodology for in-process material monitoring & control. Later, the qualitative approach constitutes the foundation for the quantitative approach when input materials are fixed and larger production size occurs. The proposed strategy is a performant PAT tool for continuous manufacturing and a step forward to real time release.

Packaging analysis of counterfeit medicines.

The authentication of the packaging represents an important step in the investigation of suspected counterfeits of pharmaceutical products. The visual comparison with a retained sample is the first step to detect a counterfeited packaging. Due to the improvement of technologies like printing, the emergence of counterfeits with a better appearance can be observed. Moreover counterfeits are nowadays often a combination of fake and genuine parts that have been manipulated. Authenticating each part of the product is important in the frame of the investigation to understand how the counterfeiters proceed, and which prevention measures should be taken. Lab instruments like spectrometers can help confirm counterfeits of packaging for packaging components on which visually, no difference with a reference would be observed. In this study several analytical tools were evaluated to help support the authentication of the primary and secondary packaging of one medicinal product as an example using seven reference materials and five counterfeits. In some cases, visual examination of the packaging already enabled to detect counterfeits of the studied features. Also the boxes, leaflets and vials have been analysed with Infrared (IR) spectroscopy, Raman microspectroscopy, X-ray fluorescence (XRF) spectroscopy, Scanning Electron Microscopy (SEM) and microcomputed tomography (microCT). According to the obtained results, IR and XRF could support the visual examination of the different packaging components. Despite the small amount of counterfeits, relevant links could also be detected between the studied cases based on the packaging characteristics.

Forensic investigation in the pharmaceutical industry: Identification procedure of visible particles in (drug) solutions and different containers by combining vibrational and X-ray spectroscopic techniques.

Vibrational and X-ray spectroscopic techniques are based on the interaction between radiation and matter. This interaction produces various signals that can be detected and that contain information about the morphology, structure or composition of molecules analyzed. When combined together, these complementary techniques are very powerful and facilitate the identification of the samples investigated. Nevertheless, prior sample preparation plays an important role in this identification, since it should allow combining analytical methods without damaging the samples. Through 5 case studies involving visible particles found in various containers, this article shows how an accurate sample preparation procedure associated to a combination of Infrared, Raman and energy dispersive X-ray (EDX) spectroscopies applies for the troubleshooting of foreign matters in pharmaceutical drug products. The forensic investigation procedure proved to be successful for the precise identification of samples.

Protein-based medicines analysis by Raman spectroscopy for the detection of counterfeits.

Protein-based medicines, or large molecule medicines, are innovative products used to treat various diseases like hepatitis or cancer. This new generation of molecules are usually expensive, and thus represents an attractive target for the counterfeiters. Due to the complexity of their chemical structure, their analysis for counterfeit detection is more difficult than small molecule medicines. The aim of the article is to demonstrate that Raman spectroscopy and microscopy can be used for the fast analysis of counterfeits of protein-based medicines. Twelve types of medicines, under liquid or lyophilized form, have been analyzed by a Raman spectrometer through their glass packaging and ten of them also by a Raman microscope with drop deposition on a gold plate. The optimization of the acquisition parameters has first been described. Then the identification of the studied products has been presented with the attribution of the protein bands observed on the spectra. Finally the methods were successfully applied to seven counterfeits of these products and their chemical composition identified by spectral analysis. Counterfeits can indeed be detected if the excipient profile differs, if no protein is present, or if the genuine sample has been strongly diluted by the counterfeiters. Raman spectroscopy and microscopy have thus proved efficient for the fast analysis of counterfeits of protein-based medicines.

Global regression model for moisture content determination using near-infrared spectroscopy.

Near-infrared (NIR) global quantitative models were evaluated for the moisture content (MC) determination of three different freeze-dried drug products. The quantitative models were based on 3822 spectra measured on two identical spectrometers to include variability. The MC, measured with the reference Karl Fischer (KF) method, were ranged from 0.05% to 4.96%. Linear and non-linear regression models using Partial Least Square (PLS), Decision Tree (DT), Bayesian Ridge Regression (Bayes-RR), K-Nearest Neighbors (KNN), and Support Vector Regression (SVR) algorithms were created and evaluated. Among them, the SVR model was retained for a global application. The Standard Error of Calibration (SEC) and the Standard Error of Prediction (SEP) were respectively 0.12% and 0.15%. This model was then evaluated in terms of total error and risk-based assessment, linearity, and accuracy. It was observed that MC can be fastly and simultaneously determined in freeze-dried pharmaceutical products thanks to a global NIR model created with different medicines. This innovative approach allows to speed up the validation time and the in-lab release analyses.

Performance of NIR handheld spectrometers for the detection of counterfeit tablets.

Near Infrared (NIR) spectroscopy is an attractive tool for pharmaceutical analyses. While lab spectrometers are very performant, they are expensive and due to their size, not adapted for field analyses. In this study, two handheld NIR spectrometers have been evaluated for the fast detection of counterfeits of pharmaceutical tablets: one low cost sensor providing a short wavelength NIR range (swNIR) and one handheld spectrometer providing a classical NIR range (cNIR). A large database containing almost all the tablets produced by the firm was created on each spectrometer. A screening for supervised classifications was performed in order to determine the most accurate model for product authentication. A Support Vector Machine (SVM) model was finally chosen for the swNIR, providing 100% of correct identification in calibration and 96.0% in validation, and a Linear Discriminant Analysis (LDA) model was chosen for the cNIR delivering 99.9% of correct identification in calibration and 91.1% in validation. Challenging samples (counterfeits and generics) could be 100% identified by the chosen classifiers combined with a class name check and a correlation distance. Statistical tests were used to compare the performance of selected swNIR and cNIR models. These results demonstrate that both devices can be used for tablet identification and the detection of counterfeits.

Moisture content determination in an antibody-drug conjugate freeze-dried medicine by near-infrared spectroscopy: A case study for release testing.

The use of Near-infrared spectroscopy (NIRS) as a fast and non-destructive technique was employed for moisture content (MC) determination in Antibody-drug conjugates (ADCs) in replacement to Karl Fischer (KF) method. The lab analysis of ADCs, high potent medicines, should be performed in conditions ensuring the operator's safety and using secured analytical tools like NIRS. A NIRS method was first developed and validated in compliance with current guidelines. The novelty of this work first lies in the large number of samples prepared for a wide moisture calibration range of 0.51%-4.01%. Then, the classical Partial Least Square (PLS) regression was used as chemometric tool for the computation of the model. Excellent predictive calibration results were shown. A coefficient of correlation (r) value of 0.99 was obtained. An intercept value of 0.02 and a slope of 0.99 were observed, while the root mean square error of calibration (RMSEC) and the root mean square error of prediction (RMSEP) were respectively 0.10% and 0.12%. In addition, instrumentation, model performances and robustness of the method were evaluated, demonstrating the validation results. Calibration transfer issue and impact of the number of samples were also evaluated. Consequently, a validation strategy was introduced as a basis for submission to the health authorities' for release and stability activities in a cGMP environment in replacement of the KF method.

Near infrared spectroscopy for counterfeit detection using a large database of pharmaceutical tablets.

Medicine counterfeiting is one of the current burdens of the pharmaceutical world. Reliable technologies have become available for the chemical analysis of suspect medicines. Near infrared spectroscopy (NIRS) allows for instance fast, specific and non-destructive authentication of pharmaceutical products. In this paper, a NIRS method is presented for the identification of 29 different pharmaceutical product families of tablets, one family containing one or more formulation (s), e.g. different dosages. This selection represents the whole tablet portfolio of our firm. The high number of product families constituted a challenge, given that the measurement of the samples, made on two similar instruments, generated a dataset of 7120 spectra. Several chemometric tools proved efficient for the identification of these medicines. The dataset was first investigated with a Principal Component Analysis (PCA) in order to provide an overview of the distribution of the samples. The K-Nearest Neighbors (KNN), the Support Vector Machines (SVM) and the Discriminant Analysis (DA) supervised classification tools were successfully applied and generated an outstanding classification rate of 100% of correct answer. The methods were then fully validated with an independent set of spectra. The DA was selected as the method for the routine analysis of suspect tablets with the Mahalanobis distance as acceptance criterion for identification. Counterfeits, generics and placebos samples, constituting a second validation set, were tested and rejected by the method. NIRS has thus been demonstrated as an efficient tool for the quick identification of a large dataset of pharmaceutical tablets and the detection of counterfeit medicines.

Impact of Vial Capping on Residual Seal Force and Container Closure Integrity.

UNLABELLED: The vial capping process is a critical unit operation during drug product manufacturing, as it could possibly generate cosmetic defects or even affect container closure integrity. Yet there is significant variability in capping equipment and processes, and their relation to potential defects or container closure integrity has not been thoroughly studied. In this study we applied several methods-residual seal force tester, a self-developed system of a piezo force sensor measurement, and computed tomography-to characterize different container closure system combinations that had been sealed using different capping process parameter settings. Additionally, container closure integrity of these samples was measured using helium leakage (physical container closure integrity) and compared to characterization data. The different capping equipment settings lead to residual seal force values from 7 to 115 N. High residual seal force values were achieved with high capping pre-compression force and a short distance between the capping plate and plunge. The choice of container closure system influenced the obtained residual seal force values. The residual seal force tester and piezoelectric measurements showed similar trends. All vials passed physical container closure integrity testing, and no stopper rupture was seen with any of the settings applied, suggesting that container closure integrity was warranted for the studied container closure system with the chosen capping setting ranges. LAY ABSTRACT: The vial capping process is a critical unit operation during drug product manufacturing, as it could possibly generate cosmetic defects or even affect container closure integrity. Yet there is significant variability in capping equipment and processes, and their relation to potential defects or container closure integrity has not been thoroughly studied. In this study we applied several methods-residual seal force tester, a self-developed system of a piezo force sensor measurement, and computed tomography-to characterize different container closure system combinations that had been sealed using different capping process parameter settings. The residual seal force tester can analyze a variety of different container closure systems independent of the capping equipment. An adequate and safe residual seal force range for each container closure system configuration can be established with the residual seal force tester and additional methods like computed tomography scans and leak testing. In the residual seal force range studied, the physical container closure integrity of the container closure system was warranted.

Influence of Different Container Closure Systems and Capping Process Parameters on Product Quality and Container Closure Integrity (CCI) in GMP Drug Product Manufacturing.

Capping equipment used in good manufacturing practice manufacturing features different designs and a variety of adjustable process parameters. The overall capping result is a complex interplay of the different capping process parameters and is insufficiently described in literature. It remains poorly studied how the different capping equipment designs and capping equipment process parameters (e.g., pre-compression force, capping plate height, turntable rotating speed) contribute to the final residual seal force of a sealed container closure system and its relation to container closure integrity and other drug product quality parameters. Stopper compression measured by computer tomography correlated to residual seal force measurements.In our studies, we used different container closure system configurations from different good manufacturing practice drug product fill & finish facilities to investigate the influence of differences in primary packaging, that is, vial size and rubber stopper design on the capping process and the capped drug product. In addition, we compared two large-scale good manufacturing practice manufacturing capping equipment and different capping equipment settings and their impact on product quality and integrity, as determined by residual seal force.The capping plate to plunger distance had a major influence on the obtained residual seal force values of a sealed vial, whereas the capping pre-compression force and the turntable rotation speed showed only a minor influence on the residual seal force of a sealed vial. Capping process parameters could not easily be transferred from capping equipment of different manufacturers. However, the residual seal force tester did provide a valuable tool to compare capping performance of different capping equipment. No vial showed any leakage greater than 10(-8)mbar L/s as measured by a helium mass spectrometry system, suggesting that container closure integrity was warranted in the residual seal force range tested for the tested container closure systems. LAY ABSTRACT: Capping equipment used in good manufacturing practice manufacturing features different designs and a variety of adjustable process parameters. The overall capping result is a complex interplay of the different capping process parameters and is insufficiently described in the literature. It remains poorly studied how the different capping equipment designs and capping equipment process parameters contribute to the final capping result.In this study, we used different container closure system configurations from different good manufacturing process drug product fill & finish facilities to investigate the influence of the vial size and the rubber stopper design on the capping process. In addition, we compared two examples of large-scale good manufacturing process capping equipment and different capping equipment settings and their impact on product quality and integrity, as determined by residual seal force.

The Pharmaceutical Capping Process-Correlation between Residual Seal Force, Torque Moment, and Flip-off Removal Force.

The majority of parenteral drug products are manufactured in glass vials with an elastomeric rubber stopper and a crimp cap. The vial sealing process is a critical process step during fill-and-finish operations, as it defines the seal quality of the final product. Different critical capping process parameters can affect rubber stopper defects, rubber stopper compression, container closure integrity, and also crimp cap quality. A sufficiently high force to remove the flip-off button prior to usage is required to ensure quality of the drug product unit by the flip-off button during storage, transportation, and until opening and use. Therefore, the final product is 100% visually inspected for lose or defective crimp caps, which is subjective as well as time- and labor-intensive. In this study, we sealed several container closure system configurations with different capping equipment settings (with corresponding residual seal force values) to investigate the torque moment required to turn the crimp cap. A correlation between torque moment and residual seal force has been established. The torque moment was found to be influenced by several parameters, including diameter of the vial head, type of rubber stopper (serum or lyophilized) and type of crimp cap (West(®) or Datwyler(®)). In addition, we measured the force required to remove the flip-off button of a sealed container closure system. The capping process had no influence on measured forces; however, it was possible to detect partially crimped vials. In conclusion, a controlled capping process with a defined target residual seal force range leads to a tight crimp cap on a sealed container closure system and can ensure product quality. LAY ABSTRACT: The majority of parenteral drug products are manufactured in a glass vials with an elastomeric rubber stopper and a crimp cap. The vial sealing process is a critical process step during fill-and-finish operations, as it defines the seal quality of the final product. An adequate force to remove the flip-off button prior to usage is required to ensure product quality during storage and transportation until use. In addition, the complete crimp cap needs to be fixed in a tight position on the vial. In this study, we investigated the torque moment required to turn the crimp cap and the force required to remove the flip-off button of container closure system sealed with different capping equipment process parameters (having different residual seal force values).

Counterfeit analysis strategy illustrated by a case study.

Medicine counterfeiting is a current problem that the whole pharmaceutical field has to deal with. In 2014, counterfeits entered the legitimate supply chain in Europe. Quick and efficient action had to be taken. The aim of this paper is to explain which analytical strategy was chosen to deal with six of the cases concerned and which criteria have to be considered to provide quick and thorough information about the counterfeits. The evaluation of the packaging was performed in a first step, based on a comparison with genuine samples and evaluation of manipulation signs. Chemical methods were then used, consisting of near infrared and infrared spectroscopy, capillary zone electrophoresis and ultraviolet-visible spectrophotometry, in order to authenticate the samples and provide the chemical composition of the confirmed counterfeits. Among the 20 samples analyzed, 17 were confirmed as counterfeits. The counterfeits were the results of the manipulation of genuine samples, and one contained totally counterfeited parts. Several manipulation signs were asserted, like the addition of glue on the boxes and the vials. Genuine stolen goods had been diluted with water, while for an isolated case, a different active ingredient had been introduced in a vial. The analytical data generated were further investigated from a forensic intelligence perspective. Links could be revealed between the analyzed counterfeits, together with some interesting information about the modus operandi of the counterfeiters. The study was performed on a limited number of cases, and therefore encourages chemical and packaging profiling of counterfeits at a bigger scale. Copyright © 2015 John Wiley & Sons, Ltd.

Micro Computer Tomography for medical device and pharmaceutical packaging analysis.

Biomedical device and medicine product manufacturing are long processes facing global competition. As technology evolves with time, the level of quality, safety and reliability increases simultaneously. Micro Computer Tomography (Micro CT) is a tool allowing a deep investigation of products: it can contribute to quality improvement. This article presents the numerous applications of Micro CT for medical device and pharmaceutical packaging analysis. The samples investigated confirmed CT suitability for verification of integrity, measurements and defect detections in a non-destructive manner.