@article{MTMT:35171691,
	title = {UV/VIS-imaging of white caffeine tablets for prediction of CQAs: API content, crushing strength, friability, disintegration time and dissolution profile},
	url = {https://m2.mtmt.hu/api/publication/35171691},
	author = {Mészáros, Lilla Alexandra and Madarász, Lajos and Ficzere, Máté and Bicsár, Rozália and Farkas, Attila and Nagy, Zsombor Kristóf},
	doi = {10.1016/j.ijpharm.2024.124565},
	journal-iso = {INT J PHARM},
	journal = {INTERNATIONAL JOURNAL OF PHARMACEUTICS},
	volume = {663},
	unique-id = {35171691},
	issn = {0378-5173},
	year = {2024},
	eissn = {1873-3476},
	orcid-numbers = {Farkas, Attila/0000-0002-8877-2587}
}

@article{MTMT:35162296,
	title = {Explainable deep recurrent neural networks for the batch analysis of a pharmaceutical tableting process in the spirit of Pharma 4.0},
	url = {https://m2.mtmt.hu/api/publication/35162296},
	author = {Honti,  Barbara and Farkas, Attila and Nagy, Zsombor Kristóf and Pataki, Hajnalka and Nagy, Brigitta},
	doi = {10.1016/j.ijpharm.2024.124509},
	journal-iso = {INT J PHARM},
	journal = {INTERNATIONAL JOURNAL OF PHARMACEUTICS},
	volume = {662},
	unique-id = {35162296},
	issn = {0378-5173},
	abstract = {Due to the continuously increasing Cost of Goods Sold, the pharmaceutical industry has faced several challenges, and the Right First-Time principle with data-driven decision-making has become more pressing to sustain competitiveness. Thus, in this work, three different types of artificial neural network (ANN) models were developed, compared, and interpreted by analyzing an open-access dataset from a real pharmaceutical tableting production process. First, the multilayer perceptron (MLP) model was used to describe the total waste based on 20 raw material properties and 25 statistical descriptors of the time series data collected throughout the tableting (e.g., tableting speed and compression force). Then using 10 process time series data in addition to the raw material properties, the cumulative waste, during manufacturing was also predicted by long short-term memory (LSTM) and bidirectional LSTM (biLSTM) recurrent neural networks (RNN). The LSTM network was used to forecast the waste production profile to allow preventive actions. The results showed that RNNs were able to predict the waste trajectory, the best model resulting in 1096 and 2174 tablets training and testing root mean squared errors, respectively. For a better understanding of the process, and the models and to help the decision-support systems and control strategies, interpretation methods were implemented for all ANNs, which increased the process understanding by identifying the most influential material attributes and process parameters. The presented methodology is applicable to various critical quality attributes in several fields of pharmaceutics and therefore is a useful tool for realizing the Pharma 4.0 concept. © 2024 The Author(s)},
	keywords = {ARTICLE; controlled study; velocity; Forecasting; PREVENTION; time series analysis; decision support system; drug industry; compression; artificial neural network; control strategy; short term memory; Open Access; Multilayer perceptron; Time series forecasting; Recurrent neural network; Long Short-Term Memory; long short term memory network; Explainable artificial intelligence; Explainable artificial intelligence; Pharma 4.0; root mean squared error; Interpretable artificial neural network; Pharmaceutical tableting waste},
	year = {2024},
	eissn = {1873-3476},
	orcid-numbers = {Farkas, Attila/0000-0002-8877-2587}
}

@article{MTMT:35075488,
	title = {Thermal investigation of relaxations of interacting and non-interacting amorphous solid dispersions},
	url = {https://m2.mtmt.hu/api/publication/35075488},
	author = {Péter-Haraszti, Anna and Záhonyi, Petra and Farkas, Attila and Csontos, István and Nagy, Zsombor Kristóf and Szabó, Edina and Van den Mooter, Guy and Marosi, György},
	doi = {10.1007/s10973-024-13281-7},
	journal-iso = {J THERM ANAL CALORIM},
	journal = {JOURNAL OF THERMAL ANALYSIS AND CALORIMETRY},
	volume = {149},
	unique-id = {35075488},
	issn = {1388-6150},
	abstract = {In the present research, thermal investigation of amorphous solid dispersions (ASDs) was performed in order to compare their relaxation transitions. Two different active pharmaceutical ingredients (APIs), namely naproxen (NAP) and spironolactone (SPIR), were used as model drugs and combined with polyvinylpyrrolidone vinyl acetate (PVPVA64) copolymer to form stable ASDs. The reason for the API selection was their different interacting potentials based on the presence (in the case of NAP) and the lack of H-bond donor group (in the case of SPIR). Determination of both Tg and sub-Tg transitions suggested that ASDs containing NAP and PVPVA64 are ‘interacting’ systems with respect to the H-bonding. Besides, temperature-dependent Raman spectroscopic experiments confirmed that the naphthalene ring of the NAP has a significant role in the sub-Tg relaxations. In contrast, SPIR-PVPVA64 systems proved to be ‘non-interacting’ ASDs according to the MDSC, TSDC, and Raman measurements. This study highlights that the combination of the results of different thermoanalytical investigations with spectroscopic methods helps to understand the molecular background of the relaxations in ASDs and thus contributes to the conscious design of stable amorphous pharmaceuticals in the early stage of development. © The Author(s) 2024.},
	keywords = {STABILITY; Molecular mobility; Amorphous solid dispersion; Intermolecular hydrogen bond; Relaxation transitions},
	year = {2024},
	eissn = {1572-8943},
	pages = {8067-8083},
	orcid-numbers = {Farkas, Attila/0000-0002-8877-2587; Csontos, István/0000-0002-6858-1388; Szabó, Edina/0000-0001-9616-5122; Marosi, György/0000-0002-4774-2023}
}

@article{MTMT:35075482,
	title = {Real-time release testing of in vitro dissolution and blend uniformity in a continuous powder blending process by NIR spectroscopy and machine vision},
	url = {https://m2.mtmt.hu/api/publication/35075482},
	author = {Mészáros, Lilla Alexandra and Gyürkés, Martin and Varga, Emese and Tacsi, Kornélia and Honti,  Barbara and Borbás, Enikő and Farkas, Attila and Nagy, Zsombor Kristóf and Nagy, Brigitta},
	doi = {10.1016/j.ejpb.2024.114368},
	journal-iso = {EUR J PHARM BIOPHARM},
	journal = {EUROPEAN JOURNAL OF PHARMACEUTICS AND BIOPHARMACEUTICS},
	volume = {201},
	unique-id = {35075482},
	issn = {0939-6411},
	abstract = {Continuous manufacturing is gaining increasing interest in the pharmaceutical industry, also requiring real-time and non-destructive quality monitoring. Multiple studies have already addressed the possibility of surrogate in vitro dissolution testing, but the utilization has rarely been demonstrated in real-time. Therefore, in this work, the in-line applicability of an artificial intelligence-based dissolution surrogate model is developed the first time. NIR spectroscopy-based partial least squares regression and artificial neural networks were developed and tested in-line and at-line to assess the blend uniformity and dissolution of encapsulated acetylsalicylic acid (ASA) – microcrystalline cellulose (MCC) powder blends in a continuous blending process. The studied blend is related to a previously published end-to-end manufacturing line, where the varying size of the ASA crystals obtained from a continuous crystallization significantly affected the dissolution of the final product. The in-line monitoring was suitable for detecting the variations in the ASA content and dissolution caused by the feeding of ASA with different particle sizes, and the at-line predictions agreed well with the measured validation dissolution curves (f2 = 80.5). The results were further validated using machine vision-based particle size analysis. Consequently, this work could contribute to the advancement of RTRT in continuous end-to-end processes. © 2024 The Author(s)},
	keywords = {Machine vision; Process analytical technology; End-to-end manufacturing; Real-time release testing; Continuous blending; Dissolution prediction},
	year = {2024},
	eissn = {1873-3441},
	orcid-numbers = {Farkas, Attila/0000-0002-8877-2587}
}

@article{MTMT:34845147,
	title = {UV imaging for the rapid at-line content determination of different colourless APIs in their tablets with artificial neural networks},
	url = {https://m2.mtmt.hu/api/publication/34845147},
	author = {Ficzere, Máté and Mészáros, Lilla Alexandra and Diószegi, Anna and Bánrévi, Zoltán and Farkas, Attila and Lenk, Sándor and Galata, Dorián László and Nagy, Zsombor Kristóf},
	doi = {10.1016/j.ijpharm.2024.124174},
	journal-iso = {INT J PHARM},
	journal = {INTERNATIONAL JOURNAL OF PHARMACEUTICS},
	volume = {657},
	unique-id = {34845147},
	issn = {0378-5173},
	year = {2024},
	eissn = {1873-3476},
	orcid-numbers = {Ficzere, Máté/0000-0002-0024-7375; Farkas, Attila/0000-0002-8877-2587; Lenk, Sándor/0000-0002-7207-0329; Galata, Dorián László/0000-0003-4760-2124}
}

@article{MTMT:34845067,
	title = {Bioequivalence prediction with small-scale biphasic dissolution and simultaneous dissolution-permeation apparatus—An aripiprazole case study},
	url = {https://m2.mtmt.hu/api/publication/34845067},
	author = {Kádár, Szabina and Kennedy, Andrew and Lee, Samuel and Ruiz, Rebeca and Farkas, Attila and Tőzsér, Petra and Csicsák, Dóra and Tóth, Gergő and Sinkó, Bálint and Borbás, Enikő},
	doi = {10.1016/j.ejps.2024.106782},
	journal-iso = {EUR J PHARM SCI},
	journal = {EUROPEAN JOURNAL OF PHARMACEUTICAL SCIENCES},
	volume = {198},
	unique-id = {34845067},
	issn = {0928-0987},
	year = {2024},
	eissn = {1879-0720},
	orcid-numbers = {Farkas, Attila/0000-0002-8877-2587; Csicsák, Dóra/0000-0003-3663-3566; Tóth, Gergő/0000-0001-5341-319X}
}

@article{MTMT:34772009,
	title = {Thermal diffusity in copper benzene-1,3,5-tricarboxylate–reduced graphite oxide mechanical composites},
	url = {https://m2.mtmt.hu/api/publication/34772009},
	author = {Gál, Márton and Samaniego Andrade, Samantha Kathiuska and Fehér, Anna Éva and Farkas, Attila and Madarász, János and Horváth, Lili and Gordon, Péter and Kovács, Róbert Sándor and Nagyné László, Krisztina},
	doi = {10.1007/s10973-024-13021-x},
	journal-iso = {J THERM ANAL CALORIM},
	journal = {JOURNAL OF THERMAL ANALYSIS AND CALORIMETRY},
	volume = {149},
	unique-id = {34772009},
	issn = {1388-6150},
	abstract = {Metal organic frameworks (MOFs) and particularly copper benzene-1,3,5-tricarboxylate (HKUST-1) are excellent materials for gas storage (e.g., CH 4 , N 2 , H 2 adsorption) and gas separation. In this work, reduced graphene oxide (RGO)–HKUST-1 mechanical mixtures were studied in order to reveal the effect of RGO content on the pressure tolerance of the texture and heat conductivity. HKUST-1 was obtained by two different synthesis routes. Air-dried MOF and RGO were thoroughly mixed prior to the compression. Powder XRD and Raman spectroscopy were used to characterize the response of the crystal structure, while low-temperature nitrogen adsorption was used the follow the adsorption properties of the pellets. Finally, the "flash" heat pulse method was used to assess the thermal properties. The gas adsorption isotherms revealed that the adsorption capacity decreases when RGO is added. Based on Raman and XRD results, we found that the synthesis route has an effect on multiple scales. We experimentally confirmed that evaluation of the thermal diffusivity requires a model more complex than the simple Fourier equation, due to the inherent heterogeneous structure of the material. A good approximation of the Fourier coefficient of thermal diffusivity was obtained using the parameters of the Guyer–Krumhansl equation. The heat pulse experiments also revealed possible size-dependent behavior.},
	year = {2024},
	eissn = {1572-8943},
	pages = {5971-5983},
	orcid-numbers = {Fehér, Anna Éva/0000-0002-2366-6388; Farkas, Attila/0000-0002-8877-2587; Kovács, Róbert Sándor/0000-0001-5822-6035; Nagyné László, Krisztina/0000-0003-4499-3983}
}

@article{MTMT:34771157,
	title = {Machine vision-based non-destructive dissolution prediction of meloxicam-containing tablets},
	url = {https://m2.mtmt.hu/api/publication/34771157},
	author = {Mészáros, Lilla Alexandra and Madarász, Lajos and Kádár, Szabina and Ficzere, Máté and Farkas, Attila and Nagy, Zsombor Kristóf},
	doi = {10.1016/j.ijpharm.2024.124013},
	journal-iso = {INT J PHARM},
	journal = {INTERNATIONAL JOURNAL OF PHARMACEUTICS},
	volume = {655},
	unique-id = {34771157},
	issn = {0378-5173},
	abstract = {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)},
	keywords = {meloxicam; Quality assessment; artificial neural network; Machine vision; Dissolution testing; Dissolution prediction},
	year = {2024},
	eissn = {1873-3476},
	orcid-numbers = {Farkas, Attila/0000-0002-8877-2587}
}

@article{MTMT:34759117,
	title = {UV–VIS imaging-based investigation of API concentration fluctuation caused by the sticking behaviour of pharmaceutical powder blends},
	url = {https://m2.mtmt.hu/api/publication/34759117},
	author = {Péterfi, Orsolya and Mészáros, Lilla Alexandra and Szabó-Szőcs, Bence and Ficzere, Máté and Sipos, Emese and Farkas, Attila and Galata, Dorián László and Nagy, Zsombor Kristóf},
	doi = {10.1016/j.ijpharm.2024.124010},
	journal-iso = {INT J PHARM},
	journal = {INTERNATIONAL JOURNAL OF PHARMACEUTICS},
	volume = {655},
	unique-id = {34759117},
	issn = {0378-5173},
	abstract = {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.},
	year = {2024},
	eissn = {1873-3476},
	orcid-numbers = {Péterfi, Orsolya/0000-0002-1921-1452; Farkas, Attila/0000-0002-8877-2587}
}

@article{MTMT:34753165,
	title = {Insight into the Structure and Redox Chemistry of [Carbonatotetraamminecobalt(III)] Permanganate and Its Monohydrate as Co-Mn-Oxide Catalyst Precursors of the Fischer-Tropsch Synthesis},
	url = {https://m2.mtmt.hu/api/publication/34753165},
	author = {Béres, Kende Attila and Dürvanger, Zsolt and Homonnay, Zoltán and Nagyné Bereczki, Laura and Barta Holló, Berta and Farkas, Attila and Petruševski, Vladimir M. and Kótai, László},
	doi = {10.3390/inorganics12040094},
	journal-iso = {INORGANICS},
	journal = {INORGANICS},
	volume = {12},
	unique-id = {34753165},
	abstract = {[Carbonatotetraamminecobalt(III)] permanganate monohydrate was synthesized first in the metathesis reaction of [Co(NH3)4CO3]NO3 and NaMnO4 in aqueous solution. Its thermal dehydration at 100 °C resulted in phase-pure [Co(NH3)4CO3]MnO4 (compound 1). Compounds 1 and 2 (i.e., the hydrated form) were studied with IR, far-IR, and low-temperature Raman spectroscopies, and their vibrational modes were assigned. The lattice parameters were determined by powder X-ray diffraction (PXRD) and single crystal X-ray diffraction (SXRD) methods for the triclinic and orthorhombic compounds 1 and 2, respectively. The detailed structure of compound 2 was determined, and the role of hydrogen bonds in the structural motifs was clarified. UV studies on compounds 1 and 2 showed the distortion of the octahedral geometry of the complex cation during dehydration because of the partial loss of the hydrogen bonds between the crystal water and the ligands of the complex cation. The thermal decomposition consists of a solid phase quasi-intramolecular redox reaction between the ammonia ligands and permanganate anions with the formation of ammonia oxidation products (H2O, NO, N2O, and CO2). The solid phase reaction product is amorphous cobalt manganese oxide containing ammonium, carbonate (and nitrate) anions. The temperature-controlled thermal decomposition of compound 2 in toluene at 110 °C showed that one of the decomposition intermediates is ammonium nitrate. The decomposition intermediates are transformed into Co1.5Mn1.5O4 spinel with MnCo2O4 structure upon further heating. Solid compound 2 gave the spinel at 500 °C both in an inert and air atmosphere, whereas the sample pre-treated in toluene at 110 °C without and with the removal of ammonium nitrate by aqueous washing, gave the spinel already at 300 and 400 °C, respectively. The molten NH4NO3 is a medium to start spinel crystallization, but its decomposition stops further crystal growth of the spinel phase. By this procedure, the particle size of the spinel product as low as ~4.0 nm could be achieved for the treatments at 300 and 400 °C, and it increased only to 5.7 nm at 500 °C. The nano-sized mixed cobalt manganese oxides are potential candidates as Fischer-Tropsch catalysts.},
	year = {2024},
	eissn = {2304-6740},
	orcid-numbers = {Béres, Kende Attila/0000-0003-4257-0581; Dürvanger, Zsolt/0000-0002-2652-4916; Homonnay, Zoltán/0000-0001-5299-5394; Barta Holló, Berta/0000-0002-5786-442X; Farkas, Attila/0000-0002-8877-2587}
}