Bioequivalence prediction with small-scale biphasic dissolution and simultaneous dissolution-permeation apparatus-An aripiprazole case study.

Both biphasic dissolution and simultaneous dissolution-permeation (D-P) systems have great potential to improve the in vitro-in vivo correlation compared to simple dissolution assays, but the assay conditions, and the evaluation methods still need to be refined in order to effectively use these apparatuses in drug development. Therefore, this comprehensive study aimed to compare the predictive accuracy of small-volume (16-20 mL) D-P system and small-volume (40-80 mL) biphasic dissolution apparatus in bioequivalence prediction of five aripiprazole (ARP) containing marketed drug products. Assay conditions, specifically dose dependence were studied to overcome the limitations of both small-scale systems. In case of biphasic dissolution the in vivo maximum plasma concentration (Cmax) prediction greatly improved with the dose reduction of ARP, while in case of the D-P setup the use of whole tablet gave just as accurate prediction as the scaled dose. With the dose reduction strategy both equipment was able to reach 100 % accuracy in bioequivalence prediction for Cmax ratio. In case of the in vivo area under the curve (AUC) prediction the predictive accuracy for the AUC ratio was not dependent on the dose, and both apparatus had a 100 % accuracy predicting bioequivalence based on AUC results. This paper presents for the first time that not only selected parameters of flux assays (like permeability, initial flux, AUC value) were used as an input parameter of a mechanistic model (gastrointestinal unified theory) to predict absorption rate but the whole in vitro flux profile was used. All fraction absorbed values estimated by Predictor Software fell within the ±15 % acceptance range during the comparison with the in vivo data.

UV imaging for the rapid at-line content determination of different colourless APIs in their tablets with artificial neural networks.

This paper presents a novel high-resolution and rapid (50 ms) UV imaging system, which was used for at-line, non-destructive API content determination of tablets. For the experiments, amlodipine and valsartan were selected as two colourless APIs with different UV induced fluorescent properties according to the measured solid fluorescent spectra. Images were captured with a LED-based UV illumination (385-395 nm) of tablets containing amlodipine or valsartan and common tableting excipients. Blue or green colour components from the RGB colour space were extracted from the images and used as an input dataset to execute API content prediction with artificial neural networks. The traditional destructive, solution-based transmission UV measurement was applied as reference method. After the optimization of the number of hidden layer neurons it was found that the relative error of the content prediction was 4.41 % and 3.98 % in the case of amlodipine and valsartan containing tablets respectively. The results open the possibility to use the proposed UV imaging-based system as a rapid, in-line tool for 100 % API content screening in order to greatly improve pharmaceutical quality control and process understanding.

UV-VIS imaging-based investigation of API concentration fluctuation caused by the sticking behaviour of pharmaceutical powder blends.

Surface powder sticking in pharmaceutical mixing vessels poses a risk to the uniformity and quality of drug formulations. This study explores methods for evaluating the amount of pharmaceutical powder mixtures adhering to the metallic surfaces. Binary powder blends consisting of amlodipine and microcrystalline cellulose (MCC) were used to investigate the effect of the mixing order on the adherence to the vessel wall. Elevated API concentrations were measured on the wall and within the dislodged material from the surface, regardless of the mixing order of the components. UV imaging was used to determine the particle size and the distribution of the API on the metallic surface. The results were compared to chemical maps obtained by Raman chemical imaging. The combination of UV and VIS imaging enabled the rapid acquisition of chemical maps, covering a substantially large area representative of the analysed sample. UV imaging was also applied in tablet inspection to detect tablets that fail to meet the content uniformity criteria. The results present powder adherence as a possible source of poor content uniformity, highlighting the need for 100% inspection of pharmaceutical products to ensure product quality and safety.

Machine vision-based non-destructive dissolution prediction of meloxicam-containing tablets.

Machine vision systems have emerged for quality assessment of solid dosage forms in the pharmaceutical industry. These can offer a versatile tool for continuous manufacturing while supporting the framework of process analytical technology, quality-by-design, and real-time release testing. The aim of this work is to develop a digital UV/VIS imaging-based system for predicting the in vitro dissolution of meloxicam-containing tablets. The alteration of the dissolution profiles of the samples required different levels of the critical process parameters, including compression force, particle size and content of the API. These process parameters were predicted non-destructively by multivariate analysis of UV/VIS images taken from the tablets. The dissolution profile prediction was also executed using solely the image data and applying artificial neural networks. The prediction error (RMSE) of the dissolution profile points was less than 5%. The alteration of the API content directly affected the maximum concentrations observed at the end of the dissolution tests. This parameter was predicted with a relative error of less than 10% by PLS models that are based on the color components of UV and VIS images. In conclusion, this paper presents a modern, non-destructive PAT solution for real-time testing of the dissolution of tablets.

Quantitative and qualitative analysis of cell culture media powders for mammalian cells by Raman microscopy.

Cell culture media are essential for large-scale recombinant protein production using mammalian cell cultures. The composition and quality of media significantly impact cell growth and product formation. Analyzing media poses challenges due to complex compositions and undisclosed exact compositions. Traditional methods like NMR and chromatography offer sensitivity but require time-consuming sample preparation and lack spatial information. Raman chemical mapping characterizes solids, but its use in cell culture media analysis is limited so far. We present a chemometric evaluation for Raman maps to qualify and quantify media components, evaluate powder homogeneity, and perform lot-to-lot comparisons. Three lots of a marketed cell culture media powder were measured with Raman mapping technique. Chemometrics techniques have outlined a strategy to extract information from complex data. First, a spectral library has been structured. In addition to the 23 spectra for presumed ingredients, we obtained another 9 pure components with Multivariate Curve Resolution-Alternating Least Squares (MCR-ALS). Then the Spectral Angle Mapper-Orthogonal Projection (SAM-OP) algorithm revealed whether references actually occur in the mapped media powders. Finally, a quantification was provided by Classical Least Squares (CLS) modelling. Quantities of 18 significant amino acids mostly correlated with the reference method. The proposed method can be generally applied even for such complicated samples. Leveraging Raman mapping and innovative chemometric methods enhance recombinant protein production by improving the understanding of the spatial distribution and composition of cell culture media in mammalian cell cultivations.

All-Organic Battery Based on Deep Eutectic Solvent and Redox-Active Polymers.

Sustainable battery concepts are of great importance for the energy storage demands of the future. Organic batteries based on redox-active polymers are one class of promising storage systems to meet these demands, in particular when combined with environmentally friendly and safe electrolytes. Deep Eutectic Solvents (DESs) represent a class of electrolytes that can be produced from sustainable sources and exhibit in most cases no or only a small environmental impact. Because of their non-flammability, DESs are safe, while providing an electrochemical stability window almost comparable to established battery electrolytes and much broader than typical aqueous electrolytes. Here, we report the first all-organic battery cell based on a DES electrolyte, which in this case is composed of sodium bis(trifluoromethanesulfonyl)imide (NaTFSI) and N-methylacetamide (NMA) alongside the electrode active materials poly(2,2,6,6-tetramethylpiperidin-1-yl-oxyl methacrylate) (PTMA) and crosslinked poly(vinylbenzylviologen) (X-PVBV2+ ). The resulting cell shows two voltage plateaus at 1.07 V and 1.58 V and achieves Coulombic efficiencies of 98 %. Surprisingly, the X-PVBV/X-PVBV+ redox couple turned out to be much more stable in NaTFSI : NMA 1 : 6 than the X-PVBV+ /X-PVBV2+ couple, leading to asymmetric capacity fading during cycling tests.

Exact p-value calculation for XCorr scoring of high-resolution MS/MS data.

Exact p-value (XPV)-based methods for dot product-like score functions-such as the XCorr score implemented in Tide, SEQUEST, Comet or shared peak count-based scoring in MSGF+ and ASPV-provide a fairly good calibration for peptide-spectrum-match (PSM) scoring in database searching-based MS/MS spectrum data identification. Unfortunately, standard XPV methods, in practice, cannot handle high-resolution fragmentation data produced by state-of-the-art mass spectrometers because having smaller bins increases the number of fragment matches that are assigned to incorrect bins and scored improperly. In this article, we present an extension of the XPV method, called the high-resolution exact p-value (HR-XPV) method, which can be used to calibrate PSM scores of high-resolution MS/MS spectra obtained with dot product-like scoring such as the XCorr. The HR-XPV carries remainder masses throughout the fragmentation, allowing them to greatly increase the number of fragments that are properly assigned to the correct bin and, thus, taking advantage of high-resolution data. Using four mass spectrometry data sets, our experimental results demonstrate that HR-XPV produces well-calibrated scores, which in turn results in more trusted spectrum annotations at any false discovery rate level.

Chronic postoperative pain after non-intubated uniportal VATS lobectomy.

Introduction: Patients undergoing thoracic surgery are at increased risk of developing, long-lasting pain. Beyond the non-surgical factors, the type of operation, including the number of incisions, and the anesthetic assessment seemed to be important factors, although some studies are controversial. The aim of our study was to examine the presence of chronic postoperative pain after non-intubated uniportal VATS lobectomy. We examined the difference between the intubated, relaxed and non-intubated spontaneous ventilation surgical approaches in patients who underwent video-assisted thoracoscopic (VATS) uniportal lobectomy. Methods: Demographic and postoperative data were retrospectively collected and analyzed, focusing on the use of pain medications, in 67 patients of the 140 patients selected by propensity score matching who underwent intubated (iVATS) or non-intubated (NITS) uniportal VATS lobectomy. This study focused on the use of analgesic medications 3, 6, and 12 months after surgery. Results: Thirty-five intubated and 32 non-intubated patients were compared. Although the analgesic consumption was nearly 2% higher among the iVATS patients during the follow-up period, there were no statistically significant differences at 3 months (15.6 vs. 17.1%) (p = 0.868), at 6 months (9.4 vs. 12.4%) (p = 0.785), and at 12 months (3.3 vs. 5.9%) (p = 0.633) between the NITS and iVATS groups, respectively. More female than male patients reported chronic pain, but the difference was not statistically significant (p = 0.616). Diabetes mellitus was a statistically significant cofactor associated with chronic pain (p = 0.03), while cardiac disease (p = 0.6), perioperative morbidity (p = 0.228), prolonged air leak (p = 0.057), and repeat drainage (p = 0.626) were not. Conclusion: Our study suggests that after non-intubation VATS lobectomies, the postoperative pain was less at 3, 6, and 12 months in NITS patients compared to iVATS patients. The 2% difference was not significant, so it may not be appropriate to claim the advantages of NITS in terms of postoperative pain.

Image-based simultaneous particle size distribution and concentration measurement of powder blend components with deep learning and machine vision.

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.

Spontaneous Ventilation Combined with Double-Lumen Tube Intubation during Thoracic Surgery: A New Anesthesiologic Method Based on 141 Cases over Three Years.

BACKGROUND: Non-intubated thoracic surgery has not achieved widespread acceptance despite its potential to improve postoperative outcomes. To ensure airway safety, our institute has developed a technique combining spontaneous ventilation with double-lumen tube intubation (SVI). This study aimed to verify the feasibility and limitations of this SVI technique. METHODS: For the SVI method, anesthesia induction involves fentanyl and propofol target-controlled infusion, with mivacurium administration. Bispectral index monitoring was used to ensure the optimal depth of anesthesia. Short-term muscle relaxation facilitated double-lumen tube intubation and early surgical steps. Chest opening preceded local infiltration, followed by a vagal nerve blockade to prevent the cough reflex and a paravertebral blockade for pain relief. Subsequently, the muscle relaxant was ceased. The patient underwent spontaneous breathing without coughing during surgical manipulation. RESULTS: Between 10 March 2020 and 28 October 2022, 141 SVI surgeries were performed. Spontaneous respiration with positive end-expiratory pressure was sufficient in 65.96% (93/141) of cases, whereas 31.21% (44/141) required pressure support ventilation. Only 2.84% (4/141) of cases reversed to conventional anesthetic management, owing to technical or surgical difficulties. Results of the 141 cases: The mean maximal carbon dioxide pressure was 59.01 (34.4-92.9) mmHg, and the mean lowest oxygen saturation was 93.96% (81-100%). The mean one-lung, mechanical and spontaneous one-lung ventilation time was 74.88 (20-140), 17.55 (0-115) and 57.73 (0-130) min, respectively. CONCLUSIONS: Spontaneous ventilation with double-lumen tube intubation is safe and feasible for thoracic surgery. The mechanical one-lung ventilation time was reduced by 76.5%, and the rate of anesthetic conversion to relaxation was low (2.8%).

Inflammasome activation in peritumoral astrocytes is a key player in breast cancer brain metastasis development.

Inflammasomes, primarily responsible for the activation of IL-1ß, have emerged as critical regulators of the tumor microenvironment. By using in vivo and in vitro brain metastasis models, as well as human samples to study the role of the NLRP3 inflammasome in triple-negative breast cancer (TNBC) brain metastases, we found NLRP3 inflammasome components and IL-1ß to be highly and specifically expressed in peritumoral astrocytes. Soluble factors from TNBC cells induced upregulation and activation of NLRP3 and IL-1ß in astrocytes, while astrocyte-derived mediators augmented the proliferation of metastatic cells. In addition, inhibition of NLRP3 inflammasome activity using MCC950 or dampening the downstream effect of IL-1ß prevented the proliferation increase in cancer cells. In vivo, MCC950 reduced IL-1ß expression in peritumoral astrocytes, as well as the levels of inflammasome components and active IL-1ß. Most importantly, significantly retarded growth of brain metastatic tumors was observed in mice treated with MCC950. Overall, astrocytes contribute to TNBC progression in the brain through activation of the NLRP3 inflammasome and consequent IL-1ß release. We conclude that pharmacological targeting of inflammasomes may become a novel strategy in controlling brain metastatic diseases.

Comparing the Performance of Raman and Near-Infrared Imaging in the Prediction of the In Vitro Dissolution Profile of Extended-Release Tablets Based on Artificial Neural Networks.

In this work, the performance of two fast chemical imaging techniques, Raman and near-infrared (NIR) imaging is compared by utilizing these methods to predict the rate of drug release from sustained-release tablets. Sustained release is provided by adding hydroxypropyl methylcellulose (HPMC), as its concentration and particle size determine the dissolution rate of the drug. The chemical images were processed using classical least squares; afterwards, a convolutional neural network was applied to extract information regarding the particle size of HPMC. The chemical images were reduced to an average HPMC concentration and a predicted particle size value; these were used as inputs in an artificial neural network with a single hidden layer to predict the dissolution profile of the tablets. Both NIR and Raman imaging yielded accurate predictions. As the instrumentation of NIR imaging allows faster measurements than Raman imaging, this technique is a better candidate for implementing a real-time technique. The introduction of chemical imaging in the routine quality control of pharmaceutical products would profoundly change quality assurance in the pharmaceutical industry.

[Left pneumonectomy for intrapulmonary unicentric Castleman disease]. / Bal oldali teljes tüdoeltávolítás intrapulmonalisan elhelyezkedo Castleman betegség miatt.

Castleman disease is an uncommon lymphoproliferative disorder, located most commonly in the mediastinal lymph nodes. The intrapulmonary presentation is extremely rare, with 14 published cases in the English literature. The clinical presentation of the disorder is not specific and the diagnosis is often challenging. The main goal is to achieve an R0 surgical resection which gives the potential chance for a recurrence-free survival. We present the case of a symptomless, 15-year-old female patient with left-sided tumor mass. Transthoracal invasive tissue biopsy confirmed Castleman disease. The central mass involved the main structures in the left hilus and therefore left pulmonectomy was necessary to reach the complete, tumor-free resection margins. The patient had no local or distant relapse during the 7-year follow-up. Although Castleman disease treated by complete surgical resection provides excellent results, radical and extended lung resection is sometimes inevitable to reach tumor-free margins. Orv Hetil. 2023; 164(37): 1476-1483.

Influence of Residual Water Traces on the Electrochemical Performance of Hydrophobic Ionic Liquids for Magnesium-Containing Electrolytes.

A trace amount of water is typically unavoidable as an impurity in ionic liquids, which is a huge challenge for their application in Mg-ion batteries. Here, we employed molecular sieves of different pore diameters (3, 4, and 5 Å), to effectively remove the trace amounts of water from 1-methyl-1-propylpiperidinium bis(trifluoromethylsulfonyl)imide (MPPip-TFSI) and 1-butyl-1-methylpyrrolidinium bis(trifluoromethylsulfonyl)imide (BMP-TFSI). Notably, after sieving (water content <1 mg ⋅ L-1 ), new anodic peaks arise that are attributed to the formation of different anion-cation structures induced by minimizing the influence of hydrogen bonds. Furthermore, electrochemical impedance spectroscopy (EIS) reveals that the electrolyte resistance decreases by ∼10 % for MPPip-TFSI and by ∼28 % for BMP-TFSI after sieving. The electrochemical Mg deposition/dissolution is investigated in MPPip-TFSI/tetraglyme (1 : 1)+100 mM Mg(TFSI)2 +10 mM Mg(BH4 )2 using Ag/AgCl and Mg reference electrodes. The presence of a trace amount of water leads to a considerable shift of 0.9 V vs. Mg2+/ Mg in the overpotential of Mg deposition. In contrast, drying of MPPip-TFSI enhances the reversibility of Mg deposition/dissolution and suppresses the passivation of the Mg electrode.

Human pancreatic ductal organoids with controlled polarity provide a novel ex vivo tool to study epithelial cell physiology.

Epithelial ion and fluid secretion determine the physiological functions of a broad range of organs, such as the lung, liver, or pancreas. The molecular mechanism of pancreatic ion secretion is challenging to investigate due to the limited access to functional human ductal epithelia. Patient-derived organoids may overcome these limitations, however direct accessibility of the apical membrane is not solved. In addition, due to the vectorial transport of ions and fluid the intraluminal pressure in the organoids is elevated, which may hinder the study of physiological processes. To overcome these, we developed an advanced culturing method for human pancreatic organoids based on the removal of the extracellular matrix that induced an apical-to-basal polarity switch also leading to reversed localization of proteins with polarized expression. The cells in the apical-out organoids had a cuboidal shape, whereas their resting intracellular Ca2+ concentration was more consistent compared to the cells in the apical-in organoids. Using this advanced model, we demonstrated the expression and function of two novel ion channels, the Ca2+ activated Cl- channel Anoctamin 1 (ANO1) and the epithelial Na+ channel (ENaC), which were not considered in ductal cells yet. Finally, we showed that the available functional assays, such as forskolin-induced swelling, or intracellular Cl- measurement have improved dynamic range when performed with apical-out organoids. Taken together our data suggest that polarity-switched human pancreatic ductal organoids are suitable models to expand our toolset in basic and translational research.

Convolutional neural network-based evaluation of chemical maps obtained by fast Raman imaging for prediction of tablet dissolution profiles.

In this work, the capabilities of a state-of-the-art fast Raman imaging apparatus are exploited to gain information about the concentration and particle size of hydroxypropyl methylcellulose (HPMC) in sustained release tablets. The extracted information is utilized to predict the in vitro dissolution profile of the tablets. For the first time, convolutional neural networks (CNNs) are used for the processing of the chemical images of HPMC distribution and to directly predict the dissolution profile based on the image. This new method is compared to wavelet analysis, which gives a quantification of the texture of HPMC distribution, carrying information regarding both concentration and particle size. A total of 112 training and 32 validation tablets were used, when a CNN was used to characterize the particle size of HPMC, the dissolution profile of the validation tablets was predicted with an average f2 similarity value of 62.95. Direct prediction based on the image had an f2 value of 54.2, this demonstrates that the CNN is capable of recognizing the patterns in the data on its own. The presented methods can facilitate a better understanding of the manufacturing processes, as detailed information becomes available with fast measurements.

AI-based analysis of in-line process endoscope images for real-time particle size measurement in a continuous pharmaceutical milling process.

This paper presents a case study on the first in-line application of AI-based image analysis for real-time pharmaceutical particle size measurement in a continuous milling process. An AI-based imaging system, which utilises a rigid endoscope, was tested for the real-time particle size measurement of solid NaCl powder used as a model API in the range of 200-1000 µm. After creating a dataset containing annotated images of NaCl particles, it was used to train an AI model for detecting particles and measuring their size. The developed system could analyse overlapping particles without dispersing air, thus broadening its applicability. The performance of the system was evaluated by measuring pre-sifted NaCl samples with the imaging tool, after which it was installed into a continuous mill for in-line particle size measurement of a milling process. By analysing ∼100 particles/s, the system was able to accurately measure the particle size of sifted NaCl samples and detect particle size reduction when applied in the milling process. The Dv50 values and PSDs measured real-time with the AI-based system correlated well with the reference laser diffraction measurements (<6% mean absolute difference over the measured samples). The AI-based imaging system shows great potential for in-line particle size analysis, which, in line with the latest pharmaceutical QC trends, can provide valuable information for process development and control.

Oligonucleotide Formulations Prepared by High-Speed Electrospinning: Maximizing Loading and Exploring Downstream Processability.

The aim of this study was to develop antisense oligonucleotide tablet formulations using high-speed electrospinning. Hydroxypropyl-beta-cyclodextrin (HPßCD) was used as a stabilizer and as an electrospinning matrix. In order to optimize the morphology of the fibers, electrospinning of various formulations was carried out using water, methanol/water (1:1), and methanol as solvents. The results showed that using methanol could be advantageous due to the lower viscosity threshold for fiber formation enabling higher potential drug loadings by using less excipient. To increase the productivity of electrospinning, high-speed electrospinning technology was utilized and HPßCD fibers containing 9.1% antisense oligonucleotide were prepared at a rate of ~330 g/h. Furthermore, to increase the drug content of the fibers, a formulation with a 50% drug loading was developed. The fibers had excellent grindability but poor flowability. The ground fibrous powder was mixed with excipients to improve its flowability, which enabled the automatic tableting of the mixture by direct compression. The fibrous HPßCD-antisense oligonucleotide formulations showed no sign of physical or chemical degradation over the 1-year stability study, which also shows the suitability of the HPßCD matrix for the formulation of biopharmaceuticals. The obtained results demonstrate possible solutions for the challenges of electrospinning such as scale-up and downstream processing of the fibers.