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[Display omitted] • NIR and granule size distribution data were fused to predict tableting properties. • ANN-based modeling offered an improved performance compared to PLS. • Tabletability and stress values during tablet detachment/ejection were predicted. In this work, the feasibility of implementing a process analytical technology (PAT) platform consisting of Near Infrared Spectroscopy (NIR) and particle size distribution (PSD) analysis was evaluated for the prediction of granule downstream processability. A Design of Experiments-based calibration set was prepared using a fluid bed melt granulation process by varying the binder content, granulation time, and granulation temperature. The granule samples were characterized using PAT tools and a compaction simulator in the 100–500 kg load range. Comparing the systematic variability in NIR and PSD data, their complementarity was demonstrated by identifying joint and unique sources of variation. These particularities of the data explained some differences in the performance of individual models. Regarding the fusion of data sources, the input data structure for partial least squares (PLS) based models did not significantly impact the predictive performance, as the root mean squared error of prediction (RMSEP) values were similar. Comparing PLS and artificial neural network (ANN) models, it was observed that the ANNs systematically provided superior model performance. For example, the best tensile strength, ejection stress, and detachment stress prediction with ANN resulted in an RMSEP of 0.119, 0.256, and 0.293 as opposed to the 0.180, 0.395, and 0.430 RMSEPs of the PLS models, respectively. Finally, the robustness of the developed models was assessed. [ABSTRACT FROM AUTHOR]

This work presents a system, where deep learning was used on images captured with a digital camera to simultaneously determine the API concentration and the particle size distribution (PSD) of two components of a powder blend. The blend consisted of acetylsalicylic acid (ASA) and calcium hydrogen phosphate (CHP), and the predicted API concentration was found corresponding with the HPLC measurements. The PSDs determined with the method corresponded with those measured with laser diffraction particle size analysis. This novel method provides fast and simple measurements and could be suitable for detecting segregation in the powder. By examining the powders discharged from a batch blender, the API concentrations at the top and bottom of the container could be measured, yielding information about the adequacy of the blending and improving the quality control of the manufacturing process. [Display omitted] [ABSTRACT FROM AUTHOR]

Polyhydroxybutyrate (PHB) is a very promising alternative to most petroleum-based plastics with the huge advantage of biodegradability. Biotechnological production processes utilizing cyanobacteria as sustainable source of PHB require fast in situ process analytical technology (PAT) tools for sophisticated process monitoring. Spectroscopic probes supported by ultrasound particle traps provide a powerful technology for in-line, nondestructive, and real-time process analytics in photobioreactors. This work shows the great potential of using ultrasound particle manipulation to improve spectroscopic attenuated total reflection Fourier-transformed mid-infrared (ATR-FTIR) spectra as a monitoring tool for PHB production processes in photobioreactors.

Patulin (PAT) belongs to the family of food-borne mycotoxins. Our previous studies revealed that PAT caused cytotoxicity in human embryonic kidney cells (HEK293). In the present research, we systematically explored the detailed mechanism of ROS production and ROS clearance in PAT-induced HEK293 cell apoptosis. Results showed that PAT treatment (2.5, 5, 7.5, 10 μM) for 10 h could regulate the expression of genes and proteins involved in the mitochondrial respiratory chain complex, resulting in dysfunction of mitochondrial oxidative phosphorylation and induction of ROS overproduction. We further investigated the role of N-acetylcysteine (NAC), an ROS scavenger, in promoting the survival of PAT-treated HEK293 cells. NAC improves PAT-induced apoptosis of HEK293 cells by clearing excess ROS, modulating the expression of mitochondrial respiratory chain complex genes and proteins, and maintaining normal mitochondrial function. In addition, NAC protects the activity of antioxidant enzymes, maintains normal GSH content, and relieves oxidative damage. Additionally, 4 mM NAC alleviated 7.5 μM PAT-mediated apoptosis through the caspase pathway in HEK293 cells. In summary, our study demonstrated that ROS is significant in PAT-mediated cytotoxicity, which provides valuable insight into the management of PAT-associated health issues.

The process analytical technology (PAT) initiative proposed by the US Food and Drug Administration (FDA) suggests innovative methods to better understand pharmaceutical processes. The development of analytical methods that quantify active pharmaceutical ingredients (APIs) in powders and tablets is fundamental to monitoring and controlling a drug product’s quality. Analytical methods based on vibrational spectroscopy do not require sample preparation and can be implemented during in-line manufacturing to maintain quality at each stage of operations. In this study, a mid-infrared (MIR) quantum cascade laser (QCL) spectroscopy-based protocol was performed to quantify ibuprofen in formulations of powder blends and tablets. Fourteen blends were prepared with varying concentrations from 0.0% to 21.0% (w/w) API. MIR laser spectra were collected in the spectral range of 990 to 1600 cm−1. Partial least squares (PLS) models were developed to correlate the intensities of vibrational signals with API concentrations in powder blends and tablets. PLS models were evaluated based on the following figures of merit: correlation coefficient (R2), root mean square error of calibration, root mean square error of prediction, root mean square error of cross-validation, and relative standard error of prediction. QCL assisted by multivariate analysis was demonstrated to be accurate and robust for analysis of the content and blend uniformity of pharmaceutical compounds.

AADL along with its Behavior Annex is an architecture and behavior description language for safety-critical domains, e.g. avionics, aerospace, and defence. In order to formally analyze behavior properties of AADL models, it is necessary to transform the AADL language into formal languages supported by formal verification tools. Moreover, comprehensive formal verification of AADL models highly requires that the transformation supports larger subset of the AADL language, as well as verification tools are able to capture various behavior of AADL, such as concurrency and timing. As an extended communicating sequential process (CSP), stateful timed CSP with its model checker-PAT provide an strongly expressive language and verification tool for real-time systems, distributed systems, and concurrent systems. This paper introduces a model transformation approach from a comparatively complete subset of AADL to stateful timed CSP, in particular supporting major components of AADL Behavior Annex. We propose a comprehensive set of transformation rules for AADL to stateful timed CSP. Then, we perform formal verification in PAT to analyze concurrent behavior properties of AADL models, such as safety, liveness, and trace refinement with various fairness assumptions, in which we consider time capacities, deadlines, periods of AADL threads and durations of AADL processes. As a study case, we develop an AADL model of F-16 “Auto Pilot Controller”and transform the model into Stateful Timed CSP. We specify a set of critical properties of the model and perform formal verification in PAT.

Objective . Proton therapy reduces the integral dose to the patient compared to conventional photon treatments. However, in vivo proton range uncertainties remain a considerable hurdle. Range uncertainty reduction benefits depend on clinical practices. During intensity-modulated proton therapy (IMPT), the target is irradiated from only a few directions, but proton arc therapy (PAT), for which the target is irradiated from dozens of angles, may see clinical implementation by the time considerable range uncertainty reductions are achieved. It is therefore crucial to determine the impact of PAT on range uncertainty reduction benefits. Approach . For twenty head-and-neck cancer patients, four different treatment plans were created: an IMPT and a PAT treatment plan assuming current clinical range uncertainties of 3.5% (IMPT 3.5% and PAT 3.5% ), and an IMPT and a PAT treatment plan assuming that range uncertainties can be reduced to 1% (IMPT 1% and PAT 1% ). Plans were evaluated with respect to target coverage and organ-at-risk doses as well as normal tissue complication probabilities (NTCPs) for parotid glands (endpoint: parotid gland flow <25%) and larynx (endpoint: larynx edema). Main results . Implementation of PAT (IMPT 3.5% -PAT 3.5% ) reduced mean NTCPs in the nominal and worst-case scenario by 3.2 percentage points (pp) and 4.2 pp, respectively. Reducing range uncertainties from 3.5% to 1% during use of IMPT (IMPT 3.5% -IMPT 1% ) reduced evaluated NTCPs by 0.9 pp and 2.0 pp. Benefits of range uncertainty reductions subsequently to PAT implementation (PAT 3.5% -PAT 1% ) were 0.2 pp and 1.0 pp, with considerably higher benefits in bilateral compared to unilateral cases. Significance . The mean clinical benefit of implementing PAT was more than twice as high as the benefit of a 3.5%-1% range uncertainty reduction. Range uncertainty reductions are expected to remain beneficial even after PAT implementation, especially in cases with target positions allowing for full leveraging of the higher number of gantry angles during PAT., (© 2024 Institute of Physics and Engineering in Medicine.)

Process Analytical Technologies (PATs) are taking a key role in the run for automatization in the biopharmaceutical industry. Spectroscopic methods such as Raman spectroscopy or mid-infrared (MIR) spectroscopy are getting more recognition in the recent years for inline monitoring of bioprocesses due to their ability to measure various molecules simultaneously. However, their dependency on laborious model calibration making them a challenge to implement. In this study, a novel one-point calibration that requires a single reference point prior to the inline monitoring of glucose and lactate in bioprocesses with MIR spectroscopy is assessed with 22 mammalian cell perfusion (PER) processes in two different scales and four different products. Concentrations are predicted over all PERs runs with a root mean square error (RMSE) of 0.29 g/L for glucose and 0.24 g/L for lactate, respectively. For comparison conventional partial least square regression (PLSR) models were used and trained with spectroscopic data from six bioreactor runs in two different scales and three products. The general accuracy of those models (RMSE of 0.41 g/L for glucose and 0.16 g/L for lactate) are in the range of the accuracy of the one-point calibration. This shows the potential of the one-point calibration as an approach making spectroscopy more accessible for bioprocess development., Competing Interests: Authors Anja Müller and Lorenz Sykora‐Mirle are shareholder of the IRUBIS GmbH., (© 2023 IRUBIS GmbH and Amgen Research (Munich) GmbH. Engineering in Life Sciences published by Wiley‐VCH GmbH.)

Recently, the pharmaceutical industry has undergone changes in the production of solid oral dosages from traditional inefficient and expensive batch production to continuous manufacturing. The latest advancements include increased use of continuous twin-screw wet granulation and application of advanced modeling tools such as Population Balance Models (PBMs). However, improved understanding of the physical process within the granulator and improvement of current population balance models are necessary for the continuous production process to be successful in practice. In this study, an existing compartmental one-dimensional PBM of a twin-screw granulation process was improved by altering the original aggregation kernel in the wetting zone as a result of an identifiability analysis. In addition, a strategy was successfully applied to reduce the number of model parameters to be calibrated in both the wetting zone and kneading zones. It was found that the new aggregation kernel in the wetting zone is capable of reproducing the particle size distribution that is experimentally observed at different process conditions as well as different types of formulations, varying in hydrophilicity and API concentration. Finally, it was observed that model parameters could be linked not only to the material properties but also to the liquid to solid ratio, paving the way to create a generic PBM to predict the particle size distribution of a new formulation.

Monitoring of scale progression in a pneumatic conveying system operating in a metal production plant was conducted during a five-month long monitoring period. A combination of an acoustic monitoring method and a laser imaging method provided detailed information of gradual scale growth in a test pipe. The results show that the scale grew steadily throughout the test campaign. Periods of increasing and decreasing scale growth rate as well as episodes where the scale was detached from the pipe surface could be identified. Additionally, visual inspection of images obtained by the laser device offered information about the spatial distribution of the scale in a cross section of the test pipe. Unlabelled Image • Monitoring of scaling by a combination of an acoustic method and an imaging method • Images describing spatial distribution of scale progression was obtained. • Periods with increasing and declining scaling rate was identified. [ABSTRACT FROM AUTHOR]

Low specific speed centrifugal pumps can operate as turbine in micro hydropower plants with relatively high head and low flowrate. Improving the hydraulic and mechanical characteristics of reverse pumps in such applications is highly appreciated. In the present study, the effect of tongue geometry on the performance and radial force of a low specific speed centrifugal reverse pump (10.3 [rpm, m3/s, m]) was studied experimentally. By measuring the flowrate, torque, inlet and outlet pressure as well as pressure distribution around the impeller periphery, hydraulic and mechanical characteristics of reverse pump for tongues of different stretchings and angles were obtained. Results showed that medium stretching can be used for reducing the radial force while further stretching of tongue is not beneficial. However, the longest tongue can boost efficiency the most. At nominal and high flowrates, tongue with medium stretching of angle −5° can rise the efficiency and output power at the highest level comparing with other angles, while that of −10° angle gives better condition at low capacities. The longest tongue of −10° could rise efficiency and output power up to 8% and 32% respectively in off-design conditions which makes it the best geometry for the reverse pump. • Measurements of hydraulics and mechanics of a centrifugal pump and PAT. • A novel method for investigating the effect of volute tongue on PAT performance. • Substantial effects of tongue geometry on both hydraulics and radial forces. • Obtaining the optimum design of volute tongue for reverse mode. [ABSTRACT FROM AUTHOR]

Background and purpose: The United States Preventative Services Task Force (USPSTF) recommends breast cancer risk-screening tools to help primary care providers determine which unaffected patients to refer to genetic specialists. The USPSTF does not recommend one tool above others. The purpose of this study was to compare tool performance in identifying women at risk for breast cancer. Methods: Pedigrees of 85 women aged 40-74 years with first-degree female relative with breast cancer were evaluated using five tools: Family History Screen-7 (FHS-7), Pedigree Assessment Tool, Manchester Scoring System, Referral Screening Tool, and Ontario Family History Assessment Tool (Ontario-FHAT). Sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) were calculated to describe each tool's ability to identify women with elevated risk as defined by Claus Model calculations (lifetime risk >=15%). Receiver operating curves were plotted. Differences between areas under the curve were estimated and compared through logistic regression to assess for differences in tool performance. Conclusions: Claus calculations identified 14 of 85 women with elevated risk. Two tools, Ontario-FHAT and FHS-7, identified all women with elevated risk (sensitivity 100%). The FHS-7 tool flagged all participants (specificity 0%). The Ontario-FHAT flagged 59 participants as needing referral (specificity 36.2%) and had a NPV of 100%. Area under the curve values were not significantly different between tools (all p values >.05), and thus were not helpful in discriminating between the tools. Implications for practice: The Ontario-FHAT outperformed other tools in sensitivity and NPV; however, low specificity and PPV must be balanced against these findings. Thus, the Ontario-FHAT can help determine which women would benefit from referral to genetics specialists. [ABSTRACT FROM AUTHOR]

Biopharmaceutical manufacturing processes can be affected by variability in cell culture media, e.g. caused by raw material impurities. Although efforts have been made in industry and academia to characterize cell culture media and raw materials with advanced analytics, the process of industrial cell culture media preparation itself has not been reported so far. Within this publication, we first compare mid‐infrared and two‐dimensional fluorescence spectroscopy with respect to their suitability as online monitoring tools during cell culture media preparation, followed by a thorough assessment of the impact of preparation parameters on media quality. Through the application of spectroscopic methods, we can show that media variability and its corresponding root cause can be detected online during the preparation process. This methodology is a powerful tool to avoid batch failure and is a valuable technology for media troubleshooting activities. Moreover, in a design of experiments approach, including additional liquid chromatography–mass spectrometry analytics, it is shown that variable preparation parameters such as temperature, power input and preparation time can have a strong impact on the physico‐chemical composition of the media. The effect on cell culture process performance and product quality in subsequent fed‐batch processes was also investigated. The presented results reveal the need for online spectroscopic methods during the preparation process and show that media variability can already be introduced by variation in media preparation parameters, with a potential impact on scale‐up to a commercial manufacturing process. [ABSTRACT FROM AUTHOR]

The ever-growing competition among global biotech industries has led to high demands on production consistency. A statistical strategy of performance mapping for production optimization is therefore of great economic significance. Process analytical technology (PAT)-based sensors such as mid-infrared (MIR) spectroscopy enable process monitoring through substrate and by-product concentrations that directly represent the physiology of cells. Combined with multivariate statistics, MIR can be employed as a strategy for production performance mapping. This study describes the use of at-line spectroscopy, chemometric modeling, and post-process fitting to characterize Lactobacillus acidophilus fermentations. The emphasis is on alternative arrangements of the data and chemometric methods principle component analysis (PCA), multivariate curve resolution (MCR), and parallel factor analysis (PARAFAC). Two key parameters, rate constant and time of inflection, are extracted by post-process fitting on the outcomes of these different models. Their use as process performance descriptors to characterize the dynamics of substrate consumption, product formation and batch-to-batch variations is suggested. The unconstrained PCA primarily described biomass change, while the constrained models PARAFAC and MCR (both the augmented and individual-run configurations) could model the decrease in sugars and increase in lactic acid over time. It was concluded that MCR on individual batch data, followed by post-process fitting, is the preferred strategy for MIR spectroscopic monitoring. [ABSTRACT FROM AUTHOR]

Polyhydroxyalkanoates (PHAs) are biodegradable plastic-like materials with versatile properties. Plant oils are excellent carbon sources for a cost-effective PHA production, due to their high carbon content, large availability, and comparatively low prices. Additionally, efficient process development and control is required for competitive PHA production, which can be facilitated by on-line or in-line monitoring devices. To this end, we have evaluated photon density wave (PDW) spectroscopy as a new process analytical technology for Ralstonia eutropha (Cupriavidus necator) H16 plant oil cultivations producing polyhydroxybutyrate (PHB) as an intracellular polymer. PDW spectroscopy was used for in-line recording of the reduced scattering coefficient µs' and the absorption coefficient µa at 638 nm. A correlation of µs' with the cell dry weight (CDW) and µa with the residual cell dry weight (RCDW) was observed during growth, PHB accumulation, and PHB degradation phases in batch and pulse feed cultivations. The correlation was used to predict CDW, RCDW, and PHB formation in a high-cell-density fed-batch cultivation with a productivity of 1.65 gPHB•L-1•h-1 and a final biomass of 106 g•L-1 containing 73 wt% PHB. The new method applied in this study allows in-line monitoring of CDW, RCDW, and PHA formation. [ABSTRACT FROM AUTHOR]

A novel sensitive electrochemistry aptasensor was constructed for the detection of patulin (PAT) using AuNPs-CS-ZnO NFs as signal amplification and hierarchically porous metal organic framework@methylene blue connection aptamer as signal tags. • A novel electrochemical aptasensor strategy for the ultrasensitive detection of PAT is constructed. • ZnO NFs for electrode sensing platform preparation are used for signal amplification. • Aminated hierarchically porous Zr-MOFs labelled methylene blue are used as signal tags. • The protocol possesses accepted specificity and can be applied in apple juice sample. In this work, the feasibility of a novel sensitive electrochemistry aptasensor for the detection of patulin (PAT) using hierarchically porous metal organic framework@methylene blue connection aptamer as signal tags was demonstrated. The substrate electrode of the aptasensor was prepared by electrodeposited gold nanoparticles (AuNPs) on chitosan-zinc oxide nano flower-modified electrode. Subsequently, the complementary single-stranded DNA was attached to the surface of the modified electrode by Au-S bond. Signal tags self-assemble on the surface of modified electrodes by aptamer-cDNA binding, while methylene blue as mediator for electrochemical detection. Thanks to the large specific surface area provided by zinc oxide nano flower, the electrode can load more signal tags and AuNPs to achieve signal amplification. In presence of PAT, Apt preferentially binds to PAT, causing dissociation of some Apt-cDNA and releasing some signal tags leading, resulting in decreased electrical signals. Under optimal conditions, the change in electrochemical signal was proportional to the logarithm of PAT concentration, from 5 × 10−8-5 × 10-1 μg mL−1, and the detection limit was estimated to be 1.46 × 10-8 μg mL-1. The aptasensor exhibited aceptable reproducibility, renewability, long-term stability and specificity. Moreover, aptasensor was reliable in determination of PAT in spiked apple juice samples. [ABSTRACT FROM AUTHOR]

• Online PSD monitoring of continuous twin-screw wet granulation and drying. • Near IR spectroscopy (NIRS) used to monitor granule particle size distribution (PSD). • Method was able to predict dried granule PSD-fractions X10, X50 and X90. • Robustness of NIRS method based on three independent, in-line datasets in real-time. • NIRS method is fit for purpose to monitor trends and sudden changes in secondary PSD. 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. [ABSTRACT FROM AUTHOR]

• The feasibility of an acoustic method to monitor scale growth in a pipe is tested. • Measurements were performed during dilute phase pneumatic conveying. • The acoustic method provided reliable predictions of scale thickness. • Calibration models can be improved by transformation of the acoustic measurements. Scale formation in pneumatic conveying systems is a major industrial challenge. The underlying scale formation mechanisms can be intricate as they often involve a combination of several mutually enhancing binding forces and can be affected by a number of different factors. A non-intrusive monitoring technique capable of measuring scale growth would be a valuable tool to investigate different scaling mechanisms. In this study, the feasibility of an active acoustic sensor technique for monitoring of scale growth in a pneumatic conveying system is evaluated. Tests are performed in a pilot scale pneumatic conveying system transporting sand in dilute phase. The acoustic sensors conducts measurements on test pipes which are coated with a primer/powder mixture, one layer after the other, to simulate scale progression. Reference measurements of the coating layer thickness in the test pipes are obtained by a laser imaging technique for each added coating layer. A multivariate method is used to calibrate prediction models of the scale thickness using acoustic measurements as independent variables and the reference measurements as the dependent variable. Results show that the active monitoring method is capable of monitoring scale growth in pneumatic conveying systems and that dilute phase conveying of sand does not affect the precision of predictions made by the method. [ABSTRACT FROM AUTHOR]

The ideal PAT tool is an inline instrument that can monitor and measure process parameters simultaneously in real time while operating in a highly automated environment. Instruments must be of sanitary design, operate robustly within the full process cycle (production and cleaning). Inline determination of the rheological properties of moving fluids (i.e. dairy concentrates) is one of the process parameters where PAT tools can be add real value in terms of optimising process control. Measurement of process viscosity is crucial in the monitoring and control of a variety of concentration processes in the dairy industry. Continuous monitoring of the rheological behaviour of the fluid can allow for optimisation of the process e.g. pumping (avoid pump blockage and failure), evaporation (limit fouling and maximise water removal) and spray drying (avoidance of nozzle fouling). This review concentrates on the state of the art developments being made in the area of process viscometry. • Process viscosity is crucial for monitoring of dairy concentration processes. • The application of current sanitary process viscometers is assessed. • This review evaluates the potential of viscometers employed in other industries. • Recommendations on viscometers from other industries are presented. [ABSTRACT FROM AUTHOR]

In line with the ongoing shift from batch to continuous pharmaceutical production of solid oral dosage forms, a novel continuous fluid-bed dryer was developed. The forced feed nature of the Glatt GPCG2 CM fluid-bed dryer allows continuous, first-in-first-out drying of wet granulate materials based on its compartmentalized, rotating fluidizing chamber. The presented work aims to introduce the dryer's functionalities in detail, and to demonstrate that the rotating fluid-bed chambers facilitates a stable drying behavior, which ensures robust and repeatable residual moisture contents (loss-on-drying [LOD]) of the discharged granules. Furthermore, a mass and energy balance (MEB) is derived, based on the logged process values of the granulating and drying units. Two independent test experiments demonstrate that precise LOD prediction in real time is achievable by MEB to serve as an orthogonal process analytical technology method to common near-infrared spectroscopy. On average, MEB results differed by 0.36% LOD (absolute) from offline reference analyses, and by 0.61% LOD from predictions made with an in-house available near-infrared spectroscopy method. Furthermore, good correlation between the observed and expected thermal energy loss was found. The derived MEB is solely based on physical principles; hence it is product independent and transferable to other materials that are processed on the described equipment. [ABSTRACT FROM AUTHOR]

A series of case histories from IQ consortium member companies will be presented to exemplify how the application of the ICH Q11 vision for enhanced or quality by design (QbD) development for the active pharmaceutical ingredient (API) can lead to differentiated outcomes for elements such as the API supply chain and control strategy, and how changes to such outcomes are managed over the lifecycle. A series of articles will address "flexibility" and look to provide recommendations for the further development of the ICH Q11 vision. The focus of this work will address flexibility associated with the "Enhanced Approaches to the Identification, Evaluation and Control of Impurities." [ABSTRACT FROM AUTHOR]

A new two‐dimensional fluorescence sensor system was developed for in‐line monitoring of mammalian cell cultures. Fluorescence spectroscopy allows for the detection and quantification of naturally occurring intra‐ and extracellular fluorophores in the cell broth. The fluorescence signals correlate to the cells' current redox state and other relevant process parameters. Cell culture pretests with twelve different excitation wavelengths showed that only three wavelengths account for a vast majority of spectral variation. Accordingly, the newly developed device utilizes three high‐power LEDs as excitation sources in combination with a back‐thinned CCD‐spectrometer for fluorescence detection. This setup was first tested in a lab design of experiments study with process relevant fluorophores proving its suitability for cell culture monitoring with LOD in the μg/L range. The sensor was then integrated into a CHO‐K1 cell culture process. The acquired fluorescence spectra of several batches were evaluated using multivariate methods. The resulting batch evolution models were challenged in deviating and "golden batch" validation runs. These first tests showed that the new sensor can trace the cells' metabolic state in a fast and reliable manner. Cellular distress is quickly detected as a deviation from the "golden batch". [ABSTRACT FROM AUTHOR]

This study was performed in order to evaluate a new LED‐based 2D‐fluorescence spectrometer for in‐line bioprocess monitoring of Chinese hamster ovary (CHO) cell culture processes. The new spectrometer used selected excitation wavelengths of 280, 365, and 455 nm to collect spectral data from six 10‐L fed‐batch processes. The technique provides data on various fluorescent compounds from the cultivation medium as well as from cell metabolism. In addition, scattered light offers information about the cultivation status. Multivariate data analysis tools were applied to analyze the large data sets of the collected fluorescence spectra. First, principal component analysis was used to accomplish an overview of all spectral data from all six CHO cultivations. Partial least square regression models were developed to correlate 2D‐fluorescence spectral data with selected critical process variables as offline reference values. A separate independent fed‐batch process was used for model validation and prediction. An almost continuous in‐line bioprocess monitoring was realized because 2D‐fluorescence spectra were collected every 10 min during the whole cultivation. The new 2D‐fluorescence device demonstrates the significant potential for accurate prediction of the total cell count, viable cell count, and the cell viability. The results strongly indicated that the technique is particularly capable to distinguish between different cell statuses inside the bioreactor. In addition, spectral data provided information about the lactate metabolism shift and cellular respiration during the cultivation process. Overall, the 2D‐fluorescence device is a highly sensitive tool for process analytical technology applications in mammalian cell cultures. [ABSTRACT FROM AUTHOR]

Biotherapeutics, such as those derived from monoclonal antibodies (mAbs), are industrially produced in controlled multiunit operation bioprocesses. Each unit operation contributes to the final characteristics of the bioproduct. The complexity of the bioprocesses, the cellular machinery, and the bioproduct molecules, typically leads to inherent heterogeneity and variability of the final critical quality attributes (CQAs). In order to improve process control and increase product quality assurance, online and real-time monitoring of product CQAs is most relevant. In this review, the recent advances in CQAs monitoring of biotherapeutic drugs, with emphasis on mAbs, and throughout, the different bioprocess unit operations are reviewed. Recent analytical techniques used for assessment of product-related CQAs of mAbs are considered in light of the analytical speed and ability to measure different CQAs. Furthermore, the state of art modeling approaches for CQA estimation in real-time are presented as a viable alternative for real-time bioproduct CQA monitoring under the process analytical technology and quality-by-design frameworks in the biopharmaceutical industry, which have recently been demonstrated. [ABSTRACT FROM AUTHOR]

Graphical abstract Abstract Real-time process analytical technology (PAT) is proposed as an effective approach for monitoring the performance of a Wurster coater. The coater was used for coating of 0.78 mm pharmaceutical pellets. The coating solution consisted of Hydroxypropyl methylcellulose/Poly ethylene glycol. During the coating process, small amounts of pellets (∼2 g) were sampled at 10 min. intervals and the pressure fluctuations were recorded at the same time. The signals were analyzed using the wavelet transform (WT) and decomposed into different sub-signals. Principal component analysis (PCA) was employed to the energies of these sub-signals, whose outliers were eliminated using the Mahalanobis distance method. The reference coating thickness data were obtained via spectrophotometry during the coating process. The partial least squares (PLS) regression was incorporated with the PCA for the development of a model for prediction of the coating thickness. The PLS regression revealed that the pressure fluctuations can be used to evaluate the thickness with a good precision. This study demonstrated the applicability of pressure fluctuations for the prediction of the coating thickness. This method can be regarded as a new robust, fast and non-intrusive PAT approach for monitoring the coating process which can be easily used by engineers and practitioners. [ABSTRACT FROM AUTHOR]

Abstract Near infrared spectroscopy (NIRS) used as process analytical technology tool to monitor Active Pharmaceutical Ingredient concentrations during tablet manufacturing has been reported to enhance overall product quality assurance. NIRS applications in different manufacturing stages are facilitated by their ability to handle different sample presentations – be it solids, liquids, gels or powders. The present study evaluates NIRS suitability for monitoring Ibuprofen concentrations (coated pellets form) inside the feed frame of a tableting press as well as in output tablets. Process monitoring was undertaken with quantitative chemometric analysis. NIRS-based predictions of concentrations both inside the feed frame and in tablets were compared to ultraviolet (UV) spectroscopy assays of temporally stratified tablet samples. Process dynamics were also compared in terms of concurrent concentrations change kinetics in the feed frame and in output tablets. NIRS showed good sensitivity to Ibuprofen concentrations despite the use of coated pellets. Ibuprofen contents as low as 1.7% w/w were detected effectively. NIRS-based quantitative predictions in the feed frame and in tablets closely matched the UV assay values of sampled tablets. As anticipated from the 2-wheel feed frame geometry, upon the addition of each consecutive blend, results show that the predicted concentration inside the feed frame were delayed compared with that of the tablets exiting the tablet press. For these tests, the delay was estimated to be 1.25 min. This finding highlights the importance of NIRS probe position inside the feed frame as a function of its geometry. Successive feed frame and tablet monitoring by NIRS could prove beneficial for real time release testing of tablet formulations. Graphical abstract fx1 Highlights • In-line monitoring of a tablet press both in the feed frame and in the tablets. • NIRS-PLS predicted Ibuprofen concentrations closely match with reference UV assays. • Concentration changes are not simultaneous in the feed frame and in the tablets. [ABSTRACT FROM AUTHOR]

Abstract Solution preparation is the first unit operation of the manufacturing process for spray-dried solid dispersions. Visual inspection and offline high-performance liquid chromatography analysis are routinely used to assess the solution preparation end point as well as the final solution composition. However, the accuracy and appropriateness of these approaches are challenged by the scale of production and solvent evaporation during sample handling. Thus an appropriate online process analytical tool is needed to improve process and quality control for the solution preparation process. The objective of this report is to develop near infrared (NIR) models for real-time monitoring of the spray solution preparation process. These models were built and refined via 2 different experiments designs with different production scale. The potency of spray-dried intermediate was analyzed by high-performance liquid chromatography and used to verify the quantitative model. The results indicated that the quantitative NIR models can be used to predict the active pharmaceutical ingredient concentration of the final spray solution accurately with a standard error of prediction of 2.4 wt%. Based on this investigation, online NIR was deemed to be a suitable analytical tool on process and quality control for spray solution preparation. [ABSTRACT FROM AUTHOR]

Graphical abstract Highlights • We developed a mobile, wireless and spherical sensor with a diameter of 7.9 mm. • The micro-probes send their data wirelessly and online to a base station. • The sensor spheres are reusable and can be charged by induction. • The density of the spheres result in near neutral buoyancy in a well-mixed reactor. • They are applicable to many reactor types without the need of modifications on them. Abstract The application of standard sensor electrodes is often limited to stirred tank reactors due to their wired nature and their large space requirement. For other cultivation systems, sensors require a great technical effort to be implemented. Here we propose a new concept of sensors: miniaturized, mobile, wireless, and self-contained spherical sensors with diameters of only 7.9 mm. The micro-probes send their data wirelessly at a frequency band of about 433 MHz to a base station during the process run and are easily deployable for many biotechnological applications and reactor types, without any need to modify the cultivation system, as the probes are nearly non-invasive due to their small size. The system consists of a platform that can accommodate various sensor types, e.g., temperature as shown in this work. The sensor spheres are reusable and can be charged by induction before being deployed in a biotechnological application. Furthermore, redundancy can easily be realized by adding several sensors into a single reactor, since each base station can coordinate up to 24 spheres. From computational fluid dynamics (CFD) simulations we could infer the maximum allowable density of spheres that would still enable them to be homogeneously distributed within a reactor as 1.1 g/cm3. We could demonstrate the practical applicability of our concept by deploying the spheres in shaking flasks, lab-scale stirred tank reactors, and tube reactors in typical lab environments. In all cases, the spheres showed reliable data transmission despite the potentially shielding technical environment. [ABSTRACT FROM AUTHOR]

Graphical abstract Highlights • Develop a NIR calibration model to predict low drug concentration in a feed frame. • Monitoring low drug concentration and powder density using NIR spectroscopy. • Physical properties of the blends affect the predictions of the drug concentration. • PCA and physical properties of the blends provides insights on model performance. Abstract This study describes the development of a near infrared (NIR) calibration model for real time determination of drug concentration, powder density, and porosity or relative specific void volume (RSVV) of 3.00%w/w acetaminophen blends within a feed frame. The NIR calibration model was developed from 1.50 to 4.50%w/w of acetaminophen, using a high variability of major excipients (from 12.92 to 81.95%w/w) which facilitates the prediction of powder density and RSVV based on near infrared calibration spectra. The model using second derivative as spectral preprocessing explained the changes related to acetaminophen concentration in the first latent variable. The second latent variable was related to changes in concentration of microcrystalline cellulose and lactose in the powder blends. NIR calibrations were also developed based on the bulk density and RSVV of the powder blends using the same design as the API model, due to the physical properties of the particles and their effects on the NIR spectra. The RSVV was predicted for the independent set blends with an RSEP(%) below 4% with a significantly low bias (0.04 cm3/g) from reference values of 1.33 to 1.58 cm3/g. The bulk density model also exhibited excellent predictions with RSEP(%) below 2.6% and significantly low bias (0.01 g/cm3) from reference values of 0.45 to 0.51 g/cm3. The excellent results obtained show the potential of near infrared spectroscopic measurements within the feed frame for a Process Analytical Technology method to control the critical properties such as tablet mass, hardness and dissolution in batch and continuous manufacturing processes. [ABSTRACT FROM AUTHOR]

Abstract A two-step purification process for human basic fibroblast growth factor (FGF-2) from clarified E. coli homogenate has been developed in which the impurity level after the second step is below the limit of quantification. Endotoxin content is cleared to 0.02 EU/μg FGF-2 and the overall yield is 67%. The performance of the cation exchanger Carboxymethyl-Sepharose Fast Flow (CM-SFF) was compared to the affinity resin Heparin-SFF regarding the impurity profile and product quality in the elution peak. The CM-SFF eluate was further purified using hydrophobic interaction resin Toyopearl-Hexyl-650C. The relative amounts of target product, host cell proteins (HCPs), dsDNA, endotoxin, monomer content, and high molecular weight impurities differed along the elution peak depending on the applied method. The bioactive monomer (>99%) was obtained with a yield of 48% for CM-SFF and 68% for Heparin-SFF. A half-load reduction in CM-SFF increased the yield up to 67% without deterioration of the impurity content. Assuming a dose of 400 μg FGF-2, endotoxin was reduced to 188 EU/dose, dsDNA <10 ng/dose, and HCP <2 ppm/dose using the cation exchanger. In the pooled eluate fractions, dsDNA was removed 4-fold (291 ng/mL) and endotoxin 14-fold (0.47 EU/μg FGF-2) more efficiently by CM-SFF than by affinity chromatography. In contrast, HCP clearance was 3-fold (13 ppm) more efficient with Heparin-SFF than CM-SFF. In contrast to process monitoring by UV 280nm or SDS-PAGE, this characterization is the basis for a Process Analytical Technology attempt when correlated with online monitored signals, as it enables knowledge-based pooling according to defined quality criteria. Highlights • Impurity ratios in the eluate fractions differ depending on the capture method. • Clearance of host cell proteins and dsDNA under limit of quantification. • Ion exchange chromatographic step fulfills criteria for clinical application. • Two step purification allows direct processing of clarified E. coli homogenate. • Hydrophobic interaction method enables endotoxin clearance without product loss. [ABSTRACT FROM AUTHOR]

Abstract The modern rotary pharmaceutical tablet press is capable of accepting or rejecting individual tablets based on the measured compression force of the tablet. Because during steady operation, each tablet is compressed to the same thickness, a larger compression force implies a heavier tablet. Tablets that are too heavy likely contain more than the desired content of drug substance. The measured compression force thus becomes an important input to the overall control strategy, and variability in the compression force from one tablet to the next corresponds directly with the uniformity of dosage units. This provides an extraordinary opportunity to use the instantaneous compression force signal as a process analytical technology to make product collection decisions on every individual tablet. Only 1 question requires investigation: how to set the main compression force limits to achieve the desired tablet weights? In this work, a small-scale characterization method and associated mathematical model are developed to answer this question. [ABSTRACT FROM AUTHOR]

Highlights • Method for monitoring ADC conjugation reactions in (near) real-time. • Shift in UV/Vis spectrum of the reactants correlated to the reaction progress. • Method applied in situ (microplate) and on-line (lab scale). • Predictive PLS models established for two surrogate drugs and two detectors. Abstract The conjugation reaction of monoclonal antibodies (mAbs) with small-molecule drugs is a central step during production of antibody-drug conjugates (ADCs). The ability to monitor this step in real time can be advantageous for process understanding and control. Here, we propose a method based on UV/Vis spectroscopy in conjunction with partial least squares (PLS) regression for non-invasive monitoring of conjugation reactions. In experiments, the method was applied to conjugation reactions with two surrogate drugs in microplate format as well as at 20 ml scale. All calibrated PLS models performed well in cross-validation (Q 2 > 0.975 for all models). In microplate format, the PLS models were furthermore successfully validated with an independent prediction set (R p r e d 2 = 0.9770 resp. 0.8940). In summary, the proposed method provides a quick and easily implementable tool for reaction monitoring of ADC conjugation reactions and may in the future support the implementation of Process Analytical Technologies (PAT). [ABSTRACT FROM AUTHOR]

This statement provides guidance for health care providers to ensure the safe discharge of healthy term infants who are born in hospital and who are ≥37 weeks' gestational age. Hospital care for mothers and infants should be family-centred, with healthy mothers and infants remaining together and going home at the same time. The specific length of stay for newborn infants depends on the health of their mother, infant health and stability, the mother's ability to care for her infant, support at home, and access to follow-up care. Many mother–infant dyads are ready to go home 24 h after birth. Parent or guardian education and assessment of discharge readiness are important components of discharge planning. Each infant must have an appropriate discharge plan, including identification of the infant's primary health care provider and assessment by a health care provider 24 h to 72 h after discharge. [ABSTRACT FROM AUTHOR]

Background: OSA-patients with persistent excessive daytime sleepiness (EDS) despite CPAP treatment are challenging in daily clinical life. To rule out residual sleep-disordered breathing (SDB), CPAP device-derived data are used in outpatient setting. In case of no pathological finding, a more intensive work-up with is necessary. 6-channel portable monitoring (6Ch-PM) is frequently used to exclude residual SDB. Peripheral arterial tonometry (PAT), as embodied in the WatchPAT device, represents an alternative technique for detecting SDB based on changes in autonomic tone. We wanted to investigate whether PAT might be a useful tool to improve diagnostic work-up in this specific patient group by better identifying residual SDB due to insufficient CPAP-adjustment.Methods: Forty-nine OSA patients (39 male, 10 female) with sufficient CPAP treatment according to device-derived data were consecutively recruited. EDS was assessed by Epworth Sleepiness Scale (ESS). All patients underwent home-based CPAP therapy control by 6Ch-PM and portable monitoring using PAT technology on two consecutive nights. A sequence of both types of monitoring was randomized to prevent possible first night effect bias.Results: Twelve out of 49 patients showed persistent EDS according to ESS (ESS > 10 points). 6Ch-PM showed a residually increased AHI under CPAP-treatment in 2 of those 12 subjects (positive predictive value, PPV = 16.7%). PAT-PM revealed 5 patients of those 12 with residual SDB (PPV = 41.7%).Conclusion: PAT could detect significantly more residual SDB under CPAP treatment than 6Ch-PM. Diagnostic work-up of CPAP-treated OSA patients with persistent EDS might be optimized, as insufficient pressure level adjustments could be recognized more precisely in time, possibly preventing more resource-consuming procedures, and potentially increased morbidity.Clinical trial registration: DRKS00007705 [ABSTRACT FROM AUTHOR]

In the era of changing business dynamics and evolving socio economic systems the concept of Corporate Social Responsibility (CSR) has become widespread. In the recent decades this ideology is gaining momentum in both academic and business life, i.e., the company exists for and has responsibilities towards a wider group of stakeholders and it must have some objectives other than profitability. The Friedman's formulation that "The Business of Business is Business" has outlived its utility, and corporate social responsibility and being a good corporate citizen are the buzzwords today. It is believed that organizations which do not consider any social responsibility towards society will ultimately tend to lose in the long run. It is questioned whether any relationship exists between financial performance and social performance. The present study aims to examine the impact of financial performance on CSR investments of selected banks in India. The research based on 20 banks (listed in BSE) investigates the impact of financial indicators viz a viz Profit After Taxes (PAT) and Earning Per Share (EPS) on CSR investments in some selected banks in India. Correlation and multiple regressions have been used to analyze the relationship among these financial profitability indicators and CSR investments. Results indicated a high significant positive correlation between PAT and CSR investments indicating that with an increase in profits, banks are increasingly spending on their CSR initiatives and vice versa. On the contrary though a significant positive correlation exits between PAT and EPS, the association between EPS and CSR investments though positive was found to be insignificant. [ABSTRACT FROM AUTHOR]

Purpose: The purpose of the present study was to investigate the feasibility of developing a fast non-destructive at-line transmission Raman spectroscopy (TRS) method for core tablet potency and content uniformity (CU) as part of a real-time release testing (RTRt) control strategy.Methods: The effects of tablet hardness and weight (thickness), API particle size, and concentration were studied by using a novel experimental design called generalized subset designs (GSDs). A subset of 28 experiments plus three replicate center points were selected for a total of 31 experiments. Matrix effects included tablets with active pharmaceutical ingredient (API) at seven concentration levels (14 to 26%w/w), and API particle size (17 to 71 μm), tablet weight (275 to 328 mg), and tablet hardness (8 to 16 SCU) at two levels.Results: Three calibration models were developed, by using partial least squares (PLS) and different preprocessing conditions (model nos. 1 to 3). In model no. 1, all matrix effects were excluded. This model showed high potency prediction errors (RMSEP of 10.0%). When all matrix variations were included in the multivariate calibration according to the GSD as shown in model nos. 2 and 3, the prediction accuracy was greatly improved (RMSEP 2.56 and 1.74% respectively). The statistical significance of the tablet weight, hardness, and API particle size in the %Recovery (TRS vs. the reference HPLC method) was investigated by using MODDE Pro (Sartorius Stedim Data Analytics). Statistically significant effects were identified if the calculated p value was ≤ 0.05. The main effect hardness, the cross-term hardness×particle size, and the quadratic term cal level×cal level showed to be statistically significant. However, these effects had a very small impact on tablet prediction accuracy (± 1.0%w/w) well within the intermediate precision of the method.Conclusion: A non-destructive TRS method for core tablet potency and CU was fully validated, following ICH Q2 and EMEA NIR guidelines. The applicability of the method to process development batches was demonstrated and compared to a previously developed and validated NIR method. [ABSTRACT FROM AUTHOR]

The last decade has witnessed extensive growth in the field of co-crystallization for mitigating the solubility and dissolution-related issues of poorly soluble drugs. This is largely because co-crystals can modify the physicochemical properties of drugs without any covalent modification in the drug molecules. The US Food and Drug Administration (FDA) now considers drug products that are designed to contain a new co-crystal, analogous to new polymorph of the active pharmaceutical ingredient (API). This positive change in regulatory perspective coupled with successful commercialization of valsartan-sacubitril co-crystal (Entresto, Novartis) has now brought co-crystals into focus, in both industries as well as academia. Co-crystal prediction, screening, and synthesis have been reported in literature; however, co-crystal production at a larger scale needs further investigations. With this aim, the article describes various continuous methods for co-crystal production, along with in-line monitoring during co-crystal production, emphasizing on process analytical technology (PAT). In addition, the scale-up issues of continuous and batch co-crystallization and other suitable techniques for pharmaceutical scale up are detailed. Quality control aspects and regulatory viewpoint crucial for commercial success are elaborated in the future perspective. [ABSTRACT FROM AUTHOR]

(1) Background: Portable NIR spectrometers gain more and more ground in the field of Process Analytical Technology due to the easy on-site flexibility and interfacing versatility. These advantages that originate from the instrument miniaturization, also come with a downside with respect to performance compared to benchtop devices. The objective of this work was to evaluate the performance of MicroNIR in a pharmaceutical powder blend application, having three active ingredients and 5 excipients. (2) Methods: Spectral data was recorded in reflectance mode using static and dynamic acquisition, on calibration set samples developed using an experimental design. (3) Results: The developed method accurately predicted the content uniformity of these complex mixtures, moreover it was validated in the entire calibration range using ±10% acceptance limits. With respect to at-line prediction, the method presented lower performance compared to a previously studied benchtop spectrometer. Regarding the in-line monitoring of the blending process, it was shown that the spectral variability-induced by dynamic acquisition could be efficiently managed using spectral pre-processing. (4) Conclusions: The in-line process monitoring resulted in accurate concentration profiles, highlighting differences in the mixing behaviour of the investigated ingredients. For the low dose component homogeneity was not reached due to an inefficient dispersive mixing.

The use of Pumps As Turbines (PATs) can be the best solution for exploiting small hydraulic resources. Pump manufacturers do not provide the performances of their machines running in reverse mode, thus several authors developed appropriate prediction models. Some of them can only correlate the pump Best Efficiency Point (BEP) to the PAT corresponding one; other ones are able to obtain the characteristic curves. In this paper, a review of these methodologies is presented with the aim to find the best strategy that allows a designer of a small hydropower plant to select the PAT to be used and to predict its characteristic curves. The study also highlights the possibility of disassembling some models in order to merge the best parts in a more reliable strategy.

In a historical context where renewable energy is increasingly being adopted, the installation of Pumps as Turbines (PaTs) in Water Distribution Networks (WDNs) is gaining relevance in the scientific community. The selection of a PaT to be installed in a WDN is complex, requiring a trade-off between technical and economic aspects. This paper presents a methodology for guiding the selection of a PaT based on the characteristics of the WDN, predicting its characteristic curves, and estimating the daily power generation. The proposed algorithm has been automated in a computer tool called PaT-ID. The innovative aspects of this tool concern its general applicability to any WDN and machine catalogue. It automatically selects the most useful machine considering the input water demand trend and the hydraulic head available for the PaT. In addition, the tool decides on series or parallel layouts if necessary. Finally, in the absence of hydraulic input data, PaT-ID provides a first-level analysis to define the potential of the site for energy production, simulating the flow rate data. The code has been validated with two case studies analysed in previous works. • PaT-ID is a decision-making tool for selecting PaT. • Characteristic curves and daily power generated are estimated. • Catalogue implemented in PaT-ID counts 200 pumps from Xylem company. • For a preliminary survey, PaT-ID can simulate the daily water demand pattern. [ABSTRACT FROM AUTHOR]

This study investigated whether Raman and Near Infrared (NIR) spectroscopy could predict tablet properties. Granules were produced on a continuous line by varying granulation parameters. Tableting process parameters were adjusted to obtain uniform tablet weight and thickness. Spectra were collected offline and tablet properties determined with traditional analyzing methods. Partial Least Squares (PLS) regression was used to correlate spectral information to tablet properties, but predictive models couldn't be established. Principal component analysis (PCA) was effectively used to distinguish theophylline concentrations and hydration levels and multiple linear regression (MLR) analysis allowed insight on how granulation parameters affect granule and tablet properties.