In situ Diazonium Salt Formation and Photochemical Aryl-Aryl Coupling in Continuous Flow Monitored by Inline NMR Spectroscopy.

A novel class of diazonium salts is introduced for the photochemical aryl-aryl coupling to produce (substituted) biphenyls. As common diazonium tetrafluoroborate salts fail, soluble and safe aryl diazonium trifluoroacetates are applied. In this mild synthesis route no catalysts are required to generate an aryl-radical by irradiation with UV-A light (365 nm). This reactive species undergoes direct C-H arylation at an arene, forming the product in reasonable reaction times. With the implementation of a continuous flow setup in a capillary photoreactor 13 different biphenyl derivatives are successfully synthesized. By integrating an inline 19F-NMR benchtop spectrometer, samples are reliably quantified as the fluorine-substituents act as a probe. Here, real-time NMR spectroscopy is a perfect tool to monitor the continuously operated system, which produces fine chemicals of industrial relevance even in a multigram scale.

Robust platform for inline Raman monitoring and control of perfusion cell culture.

Perfusion cell culture has been gaining increasing popularity for biologics manufacturing due to benefits such as smaller footprint, increased productivity, consistent product quality and manufacturing flexibility, cost savings, and so forth. Process Analytics Technologies tools are highly desirable for effective monitoring and control of long-running perfusion processes. Raman has been widely investigated for monitoring and control of traditional fed batch cell culture process. However, implementation of Raman for perfusion cell culture has been very limited mainly due to challenges with high-cell density and long running times during perfusion which cause extremely high fluorescence interference to Raman spectra and consequently it is exceedingly difficult to develop robust chemometrics models. In this work, a platform based on Raman measurement of permeate has been proposed for effective analysis of perfusion process. It has been demonstrated that this platform can effectively circumvent the fluorescence interference issue while providing rich and timely information about perfusion dynamics to enable efficient process monitoring and robust bioreactor feed control. With the highly consistent spectral data from cell-free sample matrix, development of chemometrics models can be greatly facilitated. Based on this platform, Raman models have been developed for good measurement of several analytes including glucose, lactate, glutamine, glutamate, and permeate titer. Performance of Raman models developed this way has been systematically evaluated and the models have shown good robustness against changes in perfusion scale and variations in permeate flowrate; thus models developed from small lab scale can be directly transferred for implementation in much larger scale of perfusion. With demonstrated robustness, this platform provides a reliable approach for automated glucose feed control in perfusion bioreactors. Glucose model developed from small lab scale has been successfully implemented for automated continuous glucose feed control of perfusion cell culture at much larger scale.

Bioprocess in-line monitoring and control using Raman spectroscopy and Indirect Hard Modeling (IHM).

Process in-line monitoring and control are crucial to optimize the productivity of bioprocesses. A frequently applied Process Analytical Technology (PAT) tool for bioprocess in-line monitoring is Raman spectroscopy. However, evaluating bioprocess Raman spectra is complex and calibrating state-of-the-art statistical evaluation models is effortful. To overcome this challenge, we developed an Indirect Hard Modeling (IHM) prediction model in a previous study. The combination of Raman spectroscopy and the IHM prediction model enables non-invasive in-line monitoring of glucose and ethanol mass fractions during yeast fermentations with significantly less calibration effort than comparable approaches based on statistical models. In this study, we advance this IHM-based approach and successfully demonstrate that the combination of Raman spectroscopy and IHM is capable of not only bioprocess monitoring but also bioprocess control. For this purpose, we used this combination's in-line information as input of a simple on-off glucose controller to control the glucose mass fraction in Saccharomyces cerevisiae fermentations. When we performed two of these fermentations with different predefined glucose set points, we achieved similar process control quality as approaches using statistical models, despite considerably smaller calibration effort. Therefore, this study reaffirms that the combination of Raman spectroscopy and IHM is a powerful PAT tool for bioprocesses.

Accelerating attribute-focused process and product development through the development and deployment of autonomous process analytical technology platform system.

Enabling real-time monitoring and control of the biomanufacturing processes through product quality insights continues to be an area of focus in the biopharmaceutical industry. The goal is to manufacture products with the desired quality attributes. To realize this rigorous attribute-focused Quality by Design approach, it is critical to support the development of processes that consistently deliver high-quality products and facilitate product commercialization. Time delays associated with offline analytical testing can limit the speed of process development. Thus, developing and deploying analytical technology is necessary to accelerate process development. In this study, we have developed the micro sequential injection process analyzer and the automatic assay preparation platform system. These innovations address the unmet need for an automatic, online, real-time sample acquisition and preparation platform system for in-process monitoring, control, and release of biopharmaceuticals. These systems can also be deployed in laboratory areas as an offline analytical system and on the manufacturing floor to enable rapid testing and release of products manufactured in a good manufacturing practice environment.

Application of PAT Probes in Aluminum Phosphate Adjuvant Manufacturing.

PURPOSE: This study is focused on monitoring process parameters and quality attributes of aluminum phosphate (AlPO4) using multiple in-line probes incorporated into an industrial-scale adjuvant suspension manufacturing unit. METHODS: The manufacturing of aluminum adjuvant suspension was monitored at manufacturing scale using conductivity, turbidity, infrared, and particle sizing and count probes to follow the continuous evolution of particle formation and size distribution, and the reaction kinetics during the synthesis of AlPO4. RESULTS: The data showed that AlPO4 forms large particles at the early stages of mixing, followed by a decrease in size and then stabilization towards the later stages of mixing and pH adjustment. The results provided a complementary view of process events and assisted in optimizing several parameters, e.g., flow rate of reactants AlCl3 and Na3PO4 solutions, mixing rate, pH, and conductivity of AlPO4, as well as adjuvant quality attribute such as particle size, thus streamlining and shortening the process development stage. CONCLUSION: The results of this study showed the usefulness of the in-line probes to automate continuous assessment of AlPO4 batch-to-batch consistency during in-house adjuvant production at the industrial scale.

Online monitoring of protein refolding in inclusion body processing using intrinsic fluorescence.

Inclusion bodies (IBs) are protein aggregates formed as a result of overexpression of recombinant protein in E. coli. The formation of IBs is a valuable strategy of recombinant protein production despite the need for additional processing steps, i.e., isolation, solubilization and refolding. Industrial process development of protein refolding is a labor-intensive task based largely on empirical approaches rather than knowledge-driven strategies. A prerequisite for knowledge-driven process development is a reliable monitoring strategy. This work explores the potential of intrinsic tryptophan and tyrosine fluorescence for real-time and in situ monitoring of protein refolding. In contrast to commonly established process analytical technology (PAT), this technique showed high sensitivity with reproducible measurements for protein concentrations down to 0.01 g L - 1 . The change of protein conformation during refolding is reflected as a shift in the position of the maxima of the tryptophan and tyrosine fluorescence spectra as well as change in the signal intensity. The shift in the peak position, expressed as average emission wavelength of a spectrum, was correlated to the amount of folding intermediates whereas the intensity integral correlates to the extent of aggregation. These correlations were implemented as an observation function into a mechanistic model. The versatility and transferability of the technique were demonstrated on the refolding of three different proteins with varying structural complexity. The technique was also successfully applied to detect the effect of additives and process mode on the refolding process efficiency. Thus, the methodology presented poses a generic and reliable PAT tool enabling real-time process monitoring of protein refolding.

Micro simulated moving bed chromatography-mass spectrometry as a continuous on-line process analytical tool.

Continuous manufacturing is becoming increasingly important in the (bio-)pharmaceutical industry, as more product can be produced in less time and at lower costs. In this context, there is a need for powerful continuous analytical tools. Many established off-line analytical methods, such as mass spectrometry (MS), are hardly considered for process analytical technology (PAT) applications in biopharmaceutical processes, as they are limited to at-line analysis due to the required sample preparation and the associated complexity, although they would provide a suitable technique for the assessment of a wide range of quality attributes. In this study, we investigated the applicability of a recently developed micro simulated moving bed chromatography system (µSMB) for continuous on-line sample preparation for MS. As a test case, we demonstrate the continuous on-line MS measurement of a protein solution (myoglobin) containing Tris buffer, which interferes with ESI-MS measurements, by continuously exchanging this buffer with a volatile ammonium acetate buffer suitable for MS measurements. The integration of the µSMB significantly increases MS sensitivity by removing over 98% of the buffer substances. Thus, this study demonstrates the feasibility of on-line µSMB-MS, providing a versatile PAT tool by combining the detection power of MS for various product attributes with all the advantages of continuous on-line analytics.

Real-time detection of mAb aggregates in an integrated downstream process.

The implementation of continuous processing in the biopharmaceutical industry is hindered by the scarcity of process analytical technologies (PAT). To monitor and control a continuous process, PAT tools will be crucial to measure real-time product quality attributes such as protein aggregation. Miniaturizing these analytical techniques can increase measurement speed and enable faster decision-making. A fluorescent dye (FD)-based miniaturized sensor has previously been developed: a zigzag microchannel which mixes two streams under 30 s. Bis-ANS and CCVJ, two established FDs, were employed in this micromixer to detect aggregation of the biopharmaceutical monoclonal antibody (mAb). Both FDs were able to robustly detect aggregation levels starting at 2.5%. However, the real-time measurement provided by the microfluidic sensor still needs to be implemented and assessed in an integrated continuous downstream process. In this work, the micromixer is implemented in a lab-scale integrated system for the purification of mAbs, established in an ÄKTA™ unit. A viral inactivation and two polishing steps were reproduced, sending a sample of the product pool after each phase directly to the microfluidic sensor for aggregate detection. An additional UV sensor was connected after the micromixer and an increase in its signal would indicate that aggregates were present in the sample. The at-line miniaturized PAT tool provides a fast aggregation measurement, under 10 min, enabling better process understanding and control.

Advances in bioreactor control for production of biotherapeutic products.

Advanced control strategies are well established in chemical, pharmaceutical, and food processing industries. Over the past decade, the application of these strategies is being explored for control of bioreactors for manufacturing of biotherapeutics. Most of the industrial bioreactor control strategies apply classical control techniques, with the control system designed for the facility at hand. However, with the recent progress in sensors, machinery, and industrial internet of things, and advancements in deeper understanding of the biological processes, coupled with the requirement of flexible production, the need to develop a robust and advanced process control system that can ease process intensification has emerged. This has further fuelled the development of advanced monitoring approaches, modeling techniques, process analytical technologies, and soft sensors. It is seen that proper application of these concepts can significantly improve bioreactor process performance, productivity, and reproducibility. This review is on the recent advancements in bioreactor control and its related aspects along with the associated challenges. This study also offers an insight into the future prospects for development of control strategies that can be designed for industrial-scale production of biotherapeutic products.

Bioprocess in-line monitoring using Raman spectroscopy and Indirect Hard Modeling (IHM): A simple calibration yields a robust model.

To increase the process productivity and product quality of bioprocesses, the in-line monitoring of critical process parameters is highly important. For monitoring substrate, metabolite, and product concentrations, Raman spectroscopy is a commonly used Process Analytical Technology (PAT) tool that can be applied in-situ and non-invasively. However, evaluating bioprocess Raman spectra with a robust state-of-the-art statistical model requires effortful model calibration. In the present study, we in-line monitored a glucose to ethanol fermentation by Saccharomyces cerevisiae (S. cerevisiae) using Raman spectroscopy in combination with the physics-based Indirect Hard Modeling (IHM) and showed successfully that IHM is an alternative to statistical models with significantly lower calibration effort. The IHM prediction model was developed and calibrated with only 16 Raman spectra in total, which did not include any process spectra. Nevertheless, IHM's root mean square errors of prediction (RMSEPs) for glucose (3.68 g/L) and ethanol (1.69 g/L) were comparable to the prediction quality of similar studies that used statistical models calibrated with several calibration batches. Despite our simple calibration, we succeeded in developing a robust model for evaluating bioprocess Raman spectra.

Identification of Four Similar Cell Culture Media According to their Glucose, Glutamine, and Pyruvate Content by Handheld Raman Spectroscopy.

PURPOSE: This study describes the first efforts to build a spectral library to identify four cell culture media in powder form with spectra obtained with a handheld Raman spectrometer. These complex mixtures contain over 30 components and are among the most widely used cell culture media. METHODS: A total of 32 spectra were collected for the four Dulbecco's Modified Eagle Medium cell culture media and pure materials (glucose and L-glutamine) in powder form. The spectra were preprocessed using standard normal variate with second derivative, and the barcode method before performing principal component analysis (PCA). RESULTS: The PCA model differentiated the pure glucose and the cell culture media according to the glucose concentration along the first principal component. The second principal component differentiated the three cell culture media with high glucose content according to the pyruvate concentration. The correlation coefficient showed that powdered cell culture media with high glucose concentration have a higher correlation with pure glucose, when compared with the cell culture media with low glucose. CONCLUSION: The Raman spectra made it possible to differentiate the four DMEM in the cell culture media from the majority of the external samples used in the method evaluation. However, sample heterogeneity affected the predictions. Additional studies are needed to improve the method's ability to differentiate the DMEM with high glucose.

Longitudinal two-dimensional gas chromatography mass spectrometry as a non-destructive at-line monitoring tool during cell manufacturing identifies volatile features correlative to cell product quality.

BACKGROUND AIMS: Cell therapies have emerged as a potentially transformative therapeutic modality in many chronic and incurable diseases. However, inherent donor and patient variabilities, complex manufacturing processes, lack of well-defined critical quality attributes and unavailability of in-line or at-line process or product analytical technologies result in significant variance in cell product quality and clinical trial outcomes. New approaches for overcoming these challenges are needed to realize the potential of cell therapies. METHODS: Here the authors developed an untargeted two-dimensional gas chromatography mass spectrometry (GC×GC-MS)-based method for non-destructive longitudinal at-line monitoring of cells during manufacturing to discover correlative volatile biomarkers of cell proliferation and end product potency. RESULTS: Specifically, using mesenchymal stromal cell cultures as a model, the authors demonstrated that GC×GC-MS of the culture medium headspace can effectively discriminate between media types and tissue sources. Headspace GC×GC-MS identified specific volatile compounds that showed a strong correlation with cell expansion and product functionality quantified by indoleamine-2,3-dioxygenase and T-cell proliferation/suppression assays. Additionally, the authors discovered increases in specific volatile metabolites when cells were treated with inflammatory stimulation. CONCLUSIONS: This work establishes GC×GC-MS as an at-line process analytical technology for cell manufacturing that could improve culture robustness and may be used to non-destructively monitor culture state and correlate with end product function.

Gray-box Soft Sensor for Water Content Monitoring in Fluidized Bed Granulation.

Soft sensors are powerful tools for the implementation of process analytical technology (PAT). They are categorized into white-box (first-principle), black-box (statistical), and gray-box models. Gray-box models integrate white-box and black-box models to address each drawback, i.e., prediction accuracy and intuitiveness. Although they have been applied to various industrial processes, their applicability to water content monitoring in fluidized bed granulation has not been reported. In this study, we evaluated three types of gray-box models, i.e., parallel, serial, and combined gray-box models, in terms of prediction accuracy using real operating data on a commercial scale with two formulations. The gray-box models were constructed by integrating the heat and mass balance model (white-box model) and locally weighted partial least squares regression (LW-PLSR) model (black-box model). LW-PLSR was utilized to cope with collinearity and nonlinearity. In the serial gray-box models, LW-PLSR models adjusted the fitting parameters of the white-box model depending on the process parameters for each query. In the parallel gray-box or combined gray-box models, LW-PLSR models compensated for the output error of the white-box or serial gray-box models, respectively. The results demonstrated that all three types of gray-box models improved the prediction accuracy of the white-box models regardless of the formulation. Besides, we proposed the assessment method based on Hotelling's T2 and Q residual for gray-box models using LW-PLSR, which contributes decision support to select gray-box or white-box model. The accurate and descriptive gray-box models are expected to enhance process understanding and precise quality control in fluidized bed granulation.

Automated Data Generation for Raman Spectroscopy Calibrations in Multi-Parallel Mini Bioreactors.

Raman spectroscopy is an analytical technology for the simultaneous measurement of important process parameters, such as concentrations of nutrients, metabolites, and product titer in mammalian cell culture. The majority of published Raman studies have concentrated on using the technique for the monitoring and control of bioreactors at pilot and manufacturing scales. This research presents a novel approach to generating Raman models using a high-throughput 250 mL mini bioreactor system with the following two integrated analysis modules: a prototype flow cell enabling on-line Raman measurements and a bioanalyzer to generate reference measurements without a significant time-shift, compared to the corresponding Raman measurement. Therefore, spectral variations could directly be correlated with the actual analyte concentrations to build reliable models. Using a design of experiments (DoE) approach and additional spiked samples, the optimized workflow resulted in robust Raman models for glucose, lactate, glutamine, glutamate and titer in Chinese hamster ovary (CHO) cell cultures producing monoclonal antibodies (mAb). The setup presented in this paper enables the generation of reliable Raman models that can be deployed to predict analyte concentrations, thereby facilitating real-time monitoring and control of biologics manufacturing.

Commercial scale transfer of a twin-screw melt granulation process for high drug load fevipiprant tablets.

OBJECTIVE: This work summarizes select methodology of twin-screw melt granulation (TSMG) and process analytical technology that were used in the successful scaling-up and commercial transfer of high drug load (80.5% w/w) immediate release fevipiprant tablets. SIGNIFICANCE: The unique and compelling learnings from this industry work are (1) insights into Novartis AG's commercial scale transfer using TSMG and (2) rapid, nondestructive NIR methodology as a PAT tool for RTR testing. No prior literature combines these two aspects at the level of detail we present/disclose. METHODS: Scaling up of TSMG was guided by specific energy values obtained for the 27 mm (pilot scale) and 50 mm (commercial scale) twin-screw extruders (TSE). Proven acceptable ranges (PARs) were confirmed by varying the critical process parameters (CPPs) for granulation (screw speed) and tableting (dwell time and crushing strength) at three process levels (upper, target, and lower). An at-line NIR method was developed and validated for real-time release testing (RTRT). RESULTS: The combination of CPPs were selected to have the same effect on critical quality attributes (CQAs), that is, lower (-) and upper (+) process level challenged tablet aspect/appearance and dissolution, respectively. TSMG was performed using a 50 mm extruder at constant feed rate. Compression of the six final blends (∼300 kg) showed no impact of varied granulation and compression process conditions on both CQAs. A near-infrared spectroscopy method was validated to determine content uniformity, assay, identity, and to predict CQAs on uncoated tablets in preparation for a real RTRT of future batches.

Process analytical technology for on-line monitoring of quality attributes during single-use ultrafiltration/diafiltration.

Process analytical technology (PAT) is a fast-growing field within bioprocessing that enables innovation in biological drug manufacturing. This study demonstrates novel PAT methods for monitoring multiple quality attributes simultaneously during the ultrafiltration and diafiltration (UF/DF) process operation, the final step of monoclonal antibody (mAb) purification. Size exclusion chromatography (SEC) methods were developed to measure excipients arginine, histidine, and high molecular weight (HMW) species using a liquid chromatography (LC) system with autosampler for both on-line and at-line PAT modes. The methods were applied in UF/DF studies for the comparison of single-use tangential flow filtration (TFF) cassettes to standard reusable cassettes to achieve very high concentration mAb drug substance (DS) in the order of 100-200 g/L. These case studies demonstrated that single-use TFF cassettes are a functionally equivalent, low-cost alternative to standard reusable cassettes, and that the on-line PAT measurement of purity and excipient concentration was comparable to orthogonal offline methods. These PAT applications using an on-line LC system equipped with onboard sample dilution can become a platform system for monitoring of multiple attributes over a wide dynamic range, a potentially valuable tool for biological drug development and manufacturing.

Online monitoring and control of upstream cell culture process using 1D and 2D-LC with SegFlow interface.

The biopharmaceutical industry is transitioning from currently deployed batch-mode bioprocessing to a highly efficient and agile next-generation bioprocessing with the adaptation of continuous bioprocessing, which reduces capital investment and operational costs. Continuous bioprocessing, aligned with FDA's quality-by-design platform, is designed to develop robust processes to deliver safe and effective drugs. With the deployment of knowledge-based operations, product quality can be built into the process to achieve desired critical quality attributes (CQAs) with reduced variability. To facilitate next-generation continuous bioprocessing, it is essential to embrace a fundamental shift-in-paradigm from "quality-by-testing" to "quality-by-design," which requires the deployment of process analytical technologies (PAT). With the adaptation of PAT, a systematic approach of process and product understanding and timely process control are feasible. Deployment of PAT tools for real-time monitoring of CQAs and feedback control is critical for continuous bioprocessing. Given the current deficiency in PAT tools to support continuous bioprocessing, we have integrated Infinity 2D-LC with a post-flow-splitter in conjunction with the SegFlow autosampler to the bioreactors. With this integrated system, we have established a platform for online measurements of titer and CQAs of monoclonal antibodies as well as amino acid analysis of bioreactor cell culture.

Advances in monitoring and control of refolding kinetics combining PAT and modeling.

Overexpression of recombinant proteins in Escherichia coli results in misfolded and non-active protein aggregates in the cytoplasm, so-called inclusion bodies (IB). In recent years, a change in the mindset regarding IBs could be observed: IBs are no longer considered an unwanted waste product, but a valid alternative to produce a product with high yield, purity, and stability in short process times. However, solubilization of IBs and subsequent refolding is necessary to obtain a correctly folded and active product. This protein refolding process is a crucial downstream unit operation-commonly done as a dilution in batch or fed-batch mode. Drawbacks of the state-of-the-art include the following: the large volume of buffers and capacities of refolding tanks, issues with uniform mixing, challenging analytics at low protein concentrations, reaction kinetics in non-usable aggregates, and generally low re-folding yields. There is no generic platform procedure available and a lack of robust control strategies. The introduction of Quality by Design (QbD) is the method-of-choice to provide a controlled and reproducible refolding environment. However, reliable online monitoring techniques to describe the refolding kinetics in real-time are scarce. In our view, only monitoring and control of re-folding kinetics can ensure a productive, scalable, and versatile platform technology for re-folding processes. For this review, we screened the current literature for a combination of online process analytical technology (PAT) and modeling techniques to ensure a controlled refolding process. Based on our research, we propose an integrated approach based on the idea that all aspects that cannot be monitored directly are estimated via digital twins and used in real-time for process control. KEY POINTS: • Monitoring and a thorough understanding of refolding kinetics are essential for model-based control of refolding processes. • The introduction of Quality by Design combining Process Analytical Technology and modeling ensures a robust platform for inclusion body refolding.

Prediction Performance and Economic Efficiency of Soft Sensors for in-Line Water Content Monitoring in Fluidized Bed Granulation: PP-Based Model vs. NIRS-Based Model.

Soft sensors play a crucial role as process analytical technology (PAT) tools. They are classified into physical models, statistical models, and their hybrid models. In general, statistical models are better estimators than physical models. In this study, two types of standard statistical models using process parameters (PPs) and near-infrared spectroscopy (NIRS) were investigated in terms of prediction accuracy and development cost. Locally weighted partial least squares regression (LW-PLSR), a type of nonlinear regression method, was utilized. Development cost was defined as the cost of goods required to construct an accurate model of commercial-scale equipment. Eleven granulation lots consisting of three laboratory-scale, two pilot-scale, and six commercial-scale lots were prepared. Three commercial-scale granulation lots were selected as a validation dataset, and the remaining eight granulation lots were utilized as calibration datasets. The results demonstrated that the PP-based and NIRS-based LW-PLSR models achieved high prediction accuracy without using the commercial-scale data in the calibration dataset. This practical case study clarified that the construction of accurate LW-PLSR models requires the calibration samples with the following two features: 1) located near the validation samples on the subspace spanned by principal components (PCs), and 2) having a wide range of variations in PC scores. In addition, it was confirmed that the reduction in cost and mass fraction of active pharmaceutical ingredient (API) made the PP-based models more cost-effective than the NIRS-based models. The present work supports to build accurate models efficiently and save the development cost of PAT.

Characterization of Pharmaceutical Tablets Using UV Hyperspectral Imaging as a Rapid In-Line Analysis Tool.

A laboratory prototype for hyperspectral imaging in ultra-violet (UV) region from 225 to 400 nm was developed and used to rapidly characterize active pharmaceutical ingredients (API) in tablets. The APIs are ibuprofen (IBU), acetylsalicylic acid (ASA) and paracetamol (PAR). Two sample sets were used for a comparison purpose. Sample set one comprises tablets of 100% API and sample set two consists of commercially available painkiller tablets. Reference measurements were performed on the pure APIs in liquid solutions (transmission) and in solid phase (reflection) using a commercial UV spectrometer. The spectroscopic part of the prototype is based on a pushbroom imager that contains a spectrograph and charge-coupled device (CCD) camera. The tablets were scanned on a conveyor belt that is positioned inside a tunnel made of polytetrafluoroethylene (PTFE) in order to increase the homogeneity of illumination at the sample position. Principal component analysis (PCA) was used to differentiate the hyperspectral data of the drug samples. The first two PCs are sufficient to completely separate all samples. The rugged design of the prototype opens new possibilities for further development of this technique towards real large-scale application.