TY - JOUR AU - Mészáros, Lilla Alexandra AU - Madarász, Lajos AU - Kádár, Szabina AU - Ficzere, Máté AU - Farkas, Attila AU - Nagy, Zsombor Kristóf TI - Machine vision-based non-destructive dissolution prediction of meloxicam-containing tablets JF - INTERNATIONAL JOURNAL OF PHARMACEUTICS J2 - INT J PHARM VL - 655 PY - 2024 PG - 13 SN - 0378-5173 DO - 10.1016/j.ijpharm.2024.124013 UR - https://m2.mtmt.hu/api/publication/34771157 ID - 34771157 N1 - Export Date: 5 April 2024 CODEN: IJPHD Correspondence Address: Kristóf Nagy, Z.; Department of Organic Chemistry and Technology, Műegyetem rakpart 3, Hungary; email: zsknagy@oct.bme.hu AB - 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. © 2024 The Author(s) LA - English DB - MTMT ER - TY - JOUR AU - Galata, Dorián László AU - Sinka Lázárné, Melinda AU - Kiss-Kovács, Dorottya AU - Fülöp, Gergő AU - Dávid, Barnabás AU - Bogáti, Botond AU - Ficzere, Máté AU - Péterfi, Orsolya AU - Nagy, Brigitta AU - Marosi, György AU - Nagy, Zsombor Kristóf TI - Effects of omitting titanium dioxide from the film coating of a pharmaceutical tablet – An industrial case study of attempting to comply with EU regulation 2022/63 JF - EUROPEAN JOURNAL OF PHARMACEUTICAL SCIENCES J2 - EUR J PHARM SCI VL - 196 PY - 2024 PG - 8 SN - 0928-0987 DO - 10.1016/j.ejps.2024.106750 UR - https://m2.mtmt.hu/api/publication/34759143 ID - 34759143 N1 - Department of Organic Chemistry and Technology, Faculty of Chemical Technology and Biotechnology, Budapest University of Technology and Economics, Műegyetem rkp. 3, Budapest, H-1111, Hungary Gedeon Richter Plc., Formulation R&D, Gyömrői u. 19-21, Budapest, H-1103, Hungary Export Date: 2 April 2024 CODEN: EPSCE Correspondence Address: Nagy, Z.K.; Department of Organic Chemistry and Technology, Műegyetem rkp. 3, Hungary; email: zsknagy@oct.bme.hu LA - English DB - MTMT ER - TY - JOUR AU - Péterfi, Orsolya AU - Mészáros, Lilla Alexandra AU - Szabó-Szőcs, Bence AU - Ficzere, Máté AU - Sipos, Emese AU - Farkas, Attila AU - Galata, Dorián László AU - Nagy, Zsombor Kristóf TI - UV–VIS imaging-based investigation of API concentration fluctuation caused by the sticking behaviour of pharmaceutical powder blends JF - INTERNATIONAL JOURNAL OF PHARMACEUTICS J2 - INT J PHARM VL - 655 PY - 2024 PG - 11 SN - 0378-5173 DO - 10.1016/j.ijpharm.2024.124010 UR - https://m2.mtmt.hu/api/publication/34759117 ID - 34759117 N1 - Department of Organic Chemistry and Technology, Faculty of Chemical Technology and Biotechnology, Budapest University of Technology and Economics, Műegyetem rkp. 3., Budapest, H-1111, Hungary Department of Pharmaceutical Industry and Management, Faculty of Pharmacy, George Emil Palade University of Medicine, Pharmacy, Sciences and Technology of Targu Mures, Gheorghe Marinescu Street 38, Targu Mures, 540142, Romania Export Date: 5 April 2024 CODEN: IJPHD Correspondence Address: Galata, D.L.; Department of Organic Chemistry and Technology, Műegyetem rkp. 3., Hungary; email: galata.dorian.laszlo@vbk.bme.hu AB - 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. LA - English DB - MTMT ER - TY - JOUR AU - Hirsch, Edit AU - Bornemissza, Zsuzsanna AU - Nagy, Zsombor Kristóf AU - Marosi, György AU - Farkas, Attila TI - Quantitative and qualitative analysis of cell culture media powders for mammalian cells by Raman microscopy JF - SPECTROCHIMICA ACTA PART A-MOLECULAR AND BIOMOLECULAR SPECTROSCOPY J2 - SPECTROCHIM ACTA A VL - 310 PY - 2024 PG - 11 SN - 1386-1425 DO - 10.1016/j.saa.2024.123906 UR - https://m2.mtmt.hu/api/publication/34544805 ID - 34544805 N1 - Export Date: 23 February 2024 CODEN: SAMCA Correspondence Address: Farkas, A.; Department of Organic Chemistry and Technology, Müegyetem rkp. 3., Hungary; email: farkas.attila@vbk.bme.hu Chemicals/CAS: Culture Media; Powders; Recombinant Proteins Funding details: 19-21, RRF-2.3.1-21-2022-00015 Funding details: European Commission, EC Funding details: Nemzeti Kutatási, Fejlesztési és Innovaciós Alap, NKFIA, K143039, ÚNKP-22-4-II-BME-128 Funding text 1: The research has been implemented with the support provided by the Ministry of Culture and Innovation of Hungary from the National Research, Development and Innovation Fund, financed under the K143039 funding scheme, and ÚNKP-22-4-II-BME-128 New National Excellence Program; Gedeon Richter Plc. Centennial Foundation (1103 Budapest, Gyömrői str. 19-21); and RRF-2.3.1-21-2022-00015 project provided by the European Union. Funding text 2: The research has been implemented with the support provided by the Ministry of Culture and Innovation of Hungary from the National Research, Development and Innovation Fund, financed under the K143039 funding scheme, and ÚNKP-22-4-II-BME-128 New National Excellence Program; Gedeon Richter Plc. Centennial Foundation (1103 Budapest, Gyömrői str. 19-21); and RRF-2.3.1-21-2022-00015 project provided by the European Union. LA - English DB - MTMT ER - TY - CHAP AU - Mrad, Mohamed Azouz AU - Csorba, Kristóf AU - Galata, Dorián László AU - Nagy, Zsombor Kristóf AU - Nagy, Brigitta ED - Vajk, István ED - Dunaev, Dmitriy TI - Droplet Based Prediction of Viscosity of Water-PVP Solutions Using Convolutional Neural Networks T2 - Proceedings of the Automation and Applied Computer Science Workshop 2023 (AACS'23) PB - Budapesti Műszaki Egyetem, Automatizálási és Alkalmazott Informatikai Tanszék CY - Budapest SN - 9789634219262 PY - 2023 SP - 1 EP - 15 PG - 15 UR - https://m2.mtmt.hu/api/publication/34476285 ID - 34476285 AB - The viscosity of a liquid is the property that measures the liquid internal resistance to flow. Monitoring viscosity is a vital component of quality control in several industrial fields including chemical, pharmaceutical, food, and energy-related industries. The most commonly used instrument for measuring viscosity is capillary viscometers, but their cost and complexity pose challenges for industries where accurate and real-time viscosity information is vital. In this work, we prepared thirteen solutions with different water and PVP (Polyvinylpyrrolidone) ratios, measured their different viscosity values, and produced videos of their droplets. We extracted the images of the fully developed droplets from the videos and we used the images to train a Convolutional neural network model to estimate the viscosity values of the WaterPVP solutions. The proposed model was able to predict the viscosity values of the samples using images of their droplets with a high accuracy on the test dataset. LA - English DB - MTMT ER - TY - JOUR AU - Casian, T. AU - Nagy, Brigitta AU - Lazurca, C. AU - Marcu, V. AU - Tőkés, E.O. AU - Kelemen, É.K. AU - Zöldi, K. AU - Oprean, R. AU - Nagy, Zsombor Kristóf AU - Tomuta, I. AU - Kovács, B. TI - Development of a PAT platform for the prediction of granule tableting properties JF - INTERNATIONAL JOURNAL OF PHARMACEUTICS J2 - INT J PHARM VL - 648 PY - 2023 SN - 0378-5173 DO - 10.1016/j.ijpharm.2023.123610 UR - https://m2.mtmt.hu/api/publication/34420142 ID - 34420142 N1 - Department of Pharmaceutical Technology and Biopharmacy, “Iuliu Hatieganu” University of Medicine and Pharmacy, Cluj-Napoca, 400012, Romania Department of Organic Chemistry and Technology, Faculty of Chemical Technology and Biotechnology, Budapest University of Technology and Economics, Műegyetem rkp. 3., Budapest, H-1111, Hungary Gedeon Richter Romania 540306, Tîrgu Mureș, Romania Analytical Chemistry Department, “Iuliu Haţieganu” University of Medicine and Pharmacy, Cluj-Napoca, 400349, Romania Department of Biochemistry and Environmental Chemistry, Faculty of Pharmacy, George Emil Palade University of Medicine, Pharmacy, Science, and Technology of Târgu Mureș, Târgu Mureș, 540139, Romania Export Date: 7 December 2023 CODEN: IJPHD Correspondence Address: Nagy, B.; Department of Organic Chemistry and Technology, Műegyetem rkp. 3., Hungary; email: nagy.brigitta@vbk.bme.hu LA - English DB - MTMT ER - TY - JOUR AU - Hegedűs, László AU - Hornyánszky, Gábor AU - Nagy, Zsombor Kristóf TI - Szerves Kémia és Technológia Tanszék JF - MAGYAR KÉMIKUSOK LAPJA J2 - MAGY KEM LAP VL - 78 PY - 2023 IS - 12 SP - 356 EP - 359 PG - 4 SN - 0025-0163 UR - https://m2.mtmt.hu/api/publication/34401080 ID - 34401080 LA - Hungarian DB - MTMT ER - TY - JOUR AU - Vaskó, Dorottya AU - Domján, Júlia AU - Szűcs, Bence AU - Bakk, László AU - Hajdinák, Péter AU - Marosi, György AU - Nagy, Zsombor Kristóf AU - Hirsch, Edit AU - Fehér, Csaba TI - Development and Comparison of Alternative Methods for the Purification of Adalimumab Directly from Harvested Cell Culture Fluid JF - FOOD TECHNOLOGY AND BIOTECHNOLOGY J2 - FOOD TECHNOL BIOTECH VL - 61 PY - 2023 IS - 3 SP - 339 EP - 349 PG - 11 SN - 1330-9862 DO - 10.17113/ftb.61.03.23.8094 UR - https://m2.mtmt.hu/api/publication/34352488 ID - 34352488 N1 - Department of Organic Chemistry and Technology, Faculty of Chemical Technology and Biotechnology, Budapest University of Technology and Economics, Műegyetem rkp. 3, Budapest, 1111, Hungary Department of Applied Biotechnology and Food Science, Faculty of Chemical Technology and Biotechnology, Budapest University of Technology and Economics, Műegyetem rkp. 3, Budapest, 1111, Hungary Export Date: 2 January 2024 Correspondence Address: Hirsch, E.; Department of Organic Chemistry and Technology, Műegyetem rkp. 3, Hungary; email: hirsch.edit@vbk.bme.hu Funding details: Nemzeti Kutatási Fejlesztési és Innovációs Hivatal, NKFI, K143039, ÚNKP-21-4-II-BME-331 Funding text 1: This research was funded by the National Research, Development and Innovation Fund of Hungary under grant K143039 and ÚNKP-21-4-II-BME-331 New National Excellence Program of the Ministry of Culture and Innovation. The research was carried out in the frame of RRF-2.3.1-21-2022-00015 project provided by the European Union. AB - Research background. Protein A affinity chromatography is a well-established methodcurrently used in the pharmaceutical industry. However, the high costs usually associated with chromatographic separation of protein A and the difficulties in continuous operation make the investigation of alternative purification methods very important.Experimental approach. In this study, extraction/back-extraction and precipitation/dissolution methods were developed and optimised. They were compared with protein A and cation exchange chromatography separations in terms of yield of monoclonal antibody (mAb) and amount of residual impurities, such as DNA and host cell proteins, and amount of mAb aggregates. For a comprehensive comparison of the different methods, experiments were carried out with the same cell-free fermentation broth containing adalimumab.Results and conclusions. Protein A and cation exchange chromatographic separationsresulted in high yield and purity of adalimumab. The precipitation-based process resulted in high yield but with lower purity. The extraction-based purification resulted in low yield and purity. Thus, the precipitation-based method proved to be more promising than the extraction-based method for direct purification of adalimumab from harvested cell culture fluid.Novelty and scientific contribution. Although alternative purification methods may offerthe advantages of simplicity and low-cost operation, further significant improvementsare required to compete with the performance of chromatographic separations of adalimumab from true fermentation broth. LA - English DB - MTMT ER - TY - JOUR AU - Ficzere, Máté AU - Péterfi, Orsolya AU - Farkas, Attila AU - Nagy, Zsombor Kristóf AU - Galata, Dorián László TI - Image-based simultaneous particle size distribution and concentration measurement of powder blend components with deep learning and machine vision JF - EUROPEAN JOURNAL OF PHARMACEUTICAL SCIENCES J2 - EUR J PHARM SCI VL - 191 PY - 2023 SN - 0928-0987 DO - 10.1016/j.ejps.2023.106611 UR - https://m2.mtmt.hu/api/publication/34342443 ID - 34342443 N1 - Export Date: 16 November 2023 CODEN: EPSCE Correspondence Address: Nagy, Z.K.; Department of Organic Chemistry and Technology, Műegyetem rkp 3., Hungary; email: zsknagy@oct.bme.hu LA - English DB - MTMT ER - TY - JOUR AU - Galata, Dorián László AU - Gergely, Szilveszter AU - Nagy, Rebeka AU - Slezsák, János AU - Ronkay, Ferenc György AU - Nagy, Zsombor Kristóf AU - Farkas, Attila TI - 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 JF - PHARMACEUTICALS J2 - PHARMACEUTICALS-BASE VL - 16 PY - 2023 IS - 9 PG - 12 SN - 1424-8247 DO - 10.3390/ph16091243 UR - https://m2.mtmt.hu/api/publication/34131207 ID - 34131207 N1 - Department of Organic Chemistry and Technology, Faculty of Chemical Technology and Biotechnology, Budapest University of Technology and Economics, Budapest, H-1111, Hungary Department of Applied Biotechnology and Food Science, Faculty of Chemical Technology and Biotechnology, Budapest University of Technology and Economics, Budapest, H-1111, Hungary Department of Innovative Vehicles and Materials, GAMF Faculty of Engineering and Computer Science, John von Neumann University, Kecskemét, H-6000, Hungary Export Date: 6 October 2023 Correspondence Address: Galata, D.L.; Department of Organic Chemistry and Technology, Hungary; email: galata.dorian.laszlo@vbk.bme.hu AB - 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. LA - English DB - MTMT ER -