[{"language":[{"iso":"eng"}],"department":[{"_id":"DEP4000"},{"_id":"DEP4028"},{"_id":"DEP4014"}],"publication_status":"published","year":"2024","author":[{"full_name":"Ramm, Selina","last_name":"Ramm","id":"68713","first_name":"Selina","orcid":"https://orcid.org/0000-0002-0502-8032"},{"id":"74218","first_name":"Ulrich","last_name":"Odefey","full_name":"Odefey, Ulrich"},{"last_name":"Frahm","id":"45666","first_name":"Björn","full_name":"Frahm, Björn"},{"orcid":"0000-0002-7920-0595","full_name":"Pein-Hackelbusch, Miriam","id":"64952","first_name":"Miriam","last_name":"Pein-Hackelbusch"}],"main_file_link":[{"open_access":"1","url":"https://www.biorxiv.org/content/10.1101/2024.05.30.596619v1"}],"title":"Semi-automated vs. manual: Comparative study of cell culture counting methods using validation parameters","date_created":"2025-01-29T13:48:31Z","publisher":"bioRxiv","abstract":[{"lang":"eng","text":"Determining cell density and cell viability is fundamental for any cell cultivation process. In addition to the manual counting method using hemocytometers, (semi-)automated methods offer advantages such as lower variability and shortened analysis times. However, these methods should provide at least comparable results to the manual method, which is why a comparison of methods is essential. We conducted a dilution series experimental design according to ISO 20391-2:2019 and compared two cell counting methods based on validation parameters aligned with the ICH Q2(R1) guideline. Regarding specificity and linearity, the manual (hemocytometer) and semi-automated (Countstar BioTech®) method exhibited similar results in the two evaluated characteristics total cell density and cell viability of CHO-K1 cells. Regarding repeatability of determining total cell density, the semi-automated method achieved significant (α = 0.05) better results with average relative standard deviations of < 6 %, than the manual method with average relative standard deviations of > 9 %. Concerning repeatability of the cell viability measurement, no significant difference between the two methods were shown. These results show the suitabililty of the dilution series experimental design. For the applied example, they indicate that the investigated semi-automated method is an appropriate alternative to the manual method."}],"citation":{"ieee":"S. Ramm, U. Odefey, B. Frahm, and M. Pein-Hackelbusch, “Semi-automated vs. manual: Comparative study of cell culture counting methods using validation parameters.” bioRxiv, 2024. doi: <a href=\"https://doi.org/10.1101/2024.05.30.596619\">10.1101/2024.05.30.596619</a>.","bjps":"<b>Ramm S <i>et al.</i></b> (2024) Semi-Automated vs. Manual: Comparative Study of Cell Culture Counting Methods Using Validation Parameters.","apa":"Ramm, S., Odefey, U., Frahm, B., &#38; Pein-Hackelbusch, M. (2024). <i>Semi-automated vs. manual: Comparative study of cell culture counting methods using validation parameters</i>. bioRxiv. <a href=\"https://doi.org/10.1101/2024.05.30.596619\">https://doi.org/10.1101/2024.05.30.596619</a>","van":"Ramm S, Odefey U, Frahm B, Pein-Hackelbusch M. Semi-automated vs. manual: Comparative study of cell culture counting methods using validation parameters. bioRxiv; 2024.","mla":"Ramm, Selina, et al. <i>Semi-Automated vs. Manual: Comparative Study of Cell Culture Counting Methods Using Validation Parameters</i>. bioRxiv, 2024, <a href=\"https://doi.org/10.1101/2024.05.30.596619\">https://doi.org/10.1101/2024.05.30.596619</a>.","short":"S. Ramm, U. Odefey, B. Frahm, M. Pein-Hackelbusch, (2024).","havard":"S. Ramm, U. Odefey, B. Frahm, M. Pein-Hackelbusch, Semi-automated vs. manual: Comparative study of cell culture counting methods using validation parameters, (2024).","din1505-2-1":"<span style=\"font-variant:small-caps;\">Ramm, Selina</span> ; <span style=\"font-variant:small-caps;\">Odefey, Ulrich</span> ; <span style=\"font-variant:small-caps;\">Frahm, Björn</span> ; <span style=\"font-variant:small-caps;\">Pein-Hackelbusch, Miriam</span>: Semi-automated vs. manual: Comparative study of cell culture counting methods using validation parameters, bioRxiv (2024)","ufg":"<b>Ramm, Selina u. a.</b>: Semi-automated vs. manual: Comparative study of cell culture counting methods using validation parameters, o. O. 2024.","ama":"Ramm S, Odefey U, Frahm B, Pein-Hackelbusch M. Semi-automated vs. manual: Comparative study of cell culture counting methods using validation parameters. Published online 2024. doi:<a href=\"https://doi.org/10.1101/2024.05.30.596619\">10.1101/2024.05.30.596619</a>","chicago":"Ramm, Selina, Ulrich Odefey, Björn Frahm, and Miriam Pein-Hackelbusch. “Semi-Automated vs. Manual: Comparative Study of Cell Culture Counting Methods Using Validation Parameters.” bioRxiv, 2024. <a href=\"https://doi.org/10.1101/2024.05.30.596619\">https://doi.org/10.1101/2024.05.30.596619</a>.","chicago-de":"Ramm, Selina, Ulrich Odefey, Björn Frahm und Miriam Pein-Hackelbusch. 2024. Semi-automated vs. manual: Comparative study of cell culture counting methods using validation parameters. bioRxiv. doi:<a href=\"https://doi.org/10.1101/2024.05.30.596619\">10.1101/2024.05.30.596619</a>, ."},"oa":"1","status":"public","date_updated":"2025-07-29T13:23:30Z","type":"preprint","doi":"10.1101/2024.05.30.596619","user_id":"83781","_id":"12400"},{"issue":"8","date_created":"2023-08-15T10:48:15Z","publisher":"MDPI","abstract":[{"text":"Wet granulation is a frequent process in the pharmaceutical industry. As a starting point for numerous dosage forms, the quality of the granulation not only affects subsequent production steps but also impacts the quality of the final product. It is thus crucial and economical to monitor this operation thoroughly. Here, we report on identifying different phases of a granulation process using a machine learning approach. The phases reflect the water content which, in turn, influences the processability and quality of the granule mass. We used two kinds of microphones and an acceleration sensor to capture acoustic emissions and vibrations. We trained convolutional neural networks (CNNs) to classify the different phases using transformed sound recordings as the input. We achieved a classification accuracy of up to 90% using vibrational data and an accuracy of up to 97% using the audible microphone data. Our results indicate the suitability of using audible sound and machine learning to monitor pharmaceutical processes. Moreover, since recording acoustic emissions is contactless, it readily complies with legal regulations and presents Good Manufacturing Practices.","lang":"eng"}],"author":[{"full_name":"Fulek, Ruwen","first_name":"Ruwen","id":"79527","last_name":"Fulek"},{"orcid":"https://orcid.org/0000-0002-0502-8032","full_name":"Ramm, Selina","last_name":"Ramm","id":"68713","first_name":"Selina"},{"full_name":"Kiera, Christian","last_name":"Kiera","first_name":"Christian"},{"full_name":"Pein-Hackelbusch, Miriam","id":"64952","first_name":"Miriam","last_name":"Pein-Hackelbusch","orcid":"0000-0002-7920-0595"},{"full_name":"Odefey, Ulrich","last_name":"Odefey","first_name":"Ulrich","id":"74218"}],"title":"A machine learning approach to qualitatively evaluate different granulation phases by acoustic emissions","language":[{"iso":"eng"}],"department":[{"_id":"DEP4022"},{"_id":"DEP4028"},{"_id":"DEP4014"}],"year":"2023","publication":"Pharmaceutics","volume":15,"doi":"https://doi.org/10.3390/pharmaceutics15082153","user_id":"83781","type":"scientific_journal_article","quality_controlled":"1","date_updated":"2025-07-29T13:21:40Z","pmid":"1","article_number":"2153","intvolume":"        15","citation":{"van":"Fulek R, Ramm S, Kiera C, Pein-Hackelbusch M, Odefey U. A machine learning approach to qualitatively evaluate different granulation phases by acoustic emissions. Pharmaceutics. 2023;15(8).","apa":"Fulek, R., Ramm, S., Kiera, C., Pein-Hackelbusch, M., &#38; Odefey, U. (2023). A machine learning approach to qualitatively evaluate different granulation phases by acoustic emissions. <i>Pharmaceutics</i>, <i>15</i>(8), Article 2153. <a href=\"https://doi.org/10.3390/pharmaceutics15082153\">https://doi.org/10.3390/pharmaceutics15082153</a>","mla":"Fulek, Ruwen, et al. “A Machine Learning Approach to Qualitatively Evaluate Different Granulation Phases by Acoustic Emissions.” <i>Pharmaceutics</i>, vol. 15, no. 8, 2153, 2023, <a href=\"https://doi.org/10.3390/pharmaceutics15082153\">https://doi.org/10.3390/pharmaceutics15082153</a>.","short":"R. Fulek, S. Ramm, C. Kiera, M. Pein-Hackelbusch, U. Odefey, Pharmaceutics 15 (2023).","havard":"R. Fulek, S. Ramm, C. Kiera, M. Pein-Hackelbusch, U. Odefey, A machine learning approach to qualitatively evaluate different granulation phases by acoustic emissions, Pharmaceutics. 15 (2023).","din1505-2-1":"<span style=\"font-variant:small-caps;\">Fulek, Ruwen</span> ; <span style=\"font-variant:small-caps;\">Ramm, Selina</span> ; <span style=\"font-variant:small-caps;\">Kiera, Christian</span> ; <span style=\"font-variant:small-caps;\">Pein-Hackelbusch, Miriam</span> ; <span style=\"font-variant:small-caps;\">Odefey, Ulrich</span>: A machine learning approach to qualitatively evaluate different granulation phases by acoustic emissions. In: <i>Pharmaceutics</i> Bd. 15. Basel, MDPI (2023), Nr. 8","ieee":"R. Fulek, S. Ramm, C. Kiera, M. Pein-Hackelbusch, and U. Odefey, “A machine learning approach to qualitatively evaluate different granulation phases by acoustic emissions,” <i>Pharmaceutics</i>, vol. 15, no. 8, Art. no. 2153, 2023, doi: <a href=\"https://doi.org/10.3390/pharmaceutics15082153\">https://doi.org/10.3390/pharmaceutics15082153</a>.","bjps":"<b>Fulek R <i>et al.</i></b> (2023) A Machine Learning Approach to Qualitatively Evaluate Different Granulation Phases by Acoustic Emissions. <i>Pharmaceutics</i> <b>15</b>.","chicago":"Fulek, Ruwen, Selina Ramm, Christian Kiera, Miriam Pein-Hackelbusch, and Ulrich Odefey. “A Machine Learning Approach to Qualitatively Evaluate Different Granulation Phases by Acoustic Emissions.” <i>Pharmaceutics</i> 15, no. 8 (2023). <a href=\"https://doi.org/10.3390/pharmaceutics15082153\">https://doi.org/10.3390/pharmaceutics15082153</a>.","chicago-de":"Fulek, Ruwen, Selina Ramm, Christian Kiera, Miriam Pein-Hackelbusch und Ulrich Odefey. 2023. A machine learning approach to qualitatively evaluate different granulation phases by acoustic emissions. <i>Pharmaceutics</i> 15, Nr. 8. doi:<a href=\"https://doi.org/10.3390/pharmaceutics15082153\">https://doi.org/10.3390/pharmaceutics15082153</a>, .","ufg":"<b>Fulek, Ruwen u. a.</b>: A machine learning approach to qualitatively evaluate different granulation phases by acoustic emissions, in: <i>Pharmaceutics</i> 15 (2023), H. 8.","ama":"Fulek R, Ramm S, Kiera C, Pein-Hackelbusch M, Odefey U. A machine learning approach to qualitatively evaluate different granulation phases by acoustic emissions. <i>Pharmaceutics</i>. 2023;15(8). doi:<a href=\"https://doi.org/10.3390/pharmaceutics15082153\">https://doi.org/10.3390/pharmaceutics15082153</a>"},"oa":"1","status":"public","place":"Basel","external_id":{"isi":["001119084200001"],"pmid":["37631367"]},"main_file_link":[{"open_access":"1","url":"https://www.mdpi.com/1999-4923/15/8/2153"}],"isi":"1","publication_status":"published","keyword":["wet granulation","acoustic classification","machine learning","convolutional neural networks"],"_id":"10216","publication_identifier":{"eissn":["1999-4923 "]}},{"date_updated":"2025-07-29T13:23:12Z","conference":{"location":"Rosenberg","end_date":"2023-03-15","name":"Ph.D. Student's Symposium on Tabletting Technology 2023","start_date":"2023-03-13"},"type":"conference_speech","user_id":"83781","_id":"9627","language":[{"iso":"eng"}],"department":[{"_id":"DEP4022"},{"_id":"DEP4028"},{"_id":"DEP4014"}],"publication_status":"published","year":"2023","author":[{"orcid":"https://orcid.org/0000-0002-0502-8032","first_name":"Selina","id":"68713","last_name":"Ramm","full_name":"Ramm, Selina"},{"full_name":"Fulek, Ruwen","first_name":"Ruwen","id":"79527","last_name":"Fulek"},{"full_name":"Eberle, Veronika Anna","first_name":"Veronika Anna","last_name":"Eberle"},{"last_name":"Kiera","first_name":"Christian","full_name":"Kiera, Christian"},{"last_name":"Odefey","id":"74218","first_name":"Ulrich","full_name":"Odefey, Ulrich"},{"id":"64952","first_name":"Miriam","last_name":"Pein-Hackelbusch","full_name":"Pein-Hackelbusch, Miriam","orcid":"0000-0002-7920-0595"}],"title":"Compression Density as an Alternative to Identify an Optimal Moisture Content for High Shear Wet Granulation as an Initial Step for Spheronisation","date_created":"2023-03-16T09:46:10Z","citation":{"ama":"Ramm S, Fulek R, Eberle VA, Kiera C, Odefey U, Pein-Hackelbusch M. <i>Compression Density as an Alternative to Identify an Optimal Moisture Content for High Shear Wet Granulation as an Initial Step for Spheronisation</i>.; 2023.","ufg":"<b>Ramm, Selina u. a.</b>: Compression Density as an Alternative to Identify an Optimal Moisture Content for High Shear Wet Granulation as an Initial Step for Spheronisation, o. O. 2023.","chicago":"Ramm, Selina, Ruwen Fulek, Veronika Anna Eberle, Christian Kiera, Ulrich Odefey, and Miriam Pein-Hackelbusch. <i>Compression Density as an Alternative to Identify an Optimal Moisture Content for High Shear Wet Granulation as an Initial Step for Spheronisation</i>, 2023.","chicago-de":"Ramm, Selina, Ruwen Fulek, Veronika Anna Eberle, Christian Kiera, Ulrich Odefey und Miriam Pein-Hackelbusch. 2023. <i>Compression Density as an Alternative to Identify an Optimal Moisture Content for High Shear Wet Granulation as an Initial Step for Spheronisation</i>.","ieee":"S. Ramm, R. Fulek, V. A. Eberle, C. Kiera, U. Odefey, and M. Pein-Hackelbusch, <i>Compression Density as an Alternative to Identify an Optimal Moisture Content for High Shear Wet Granulation as an Initial Step for Spheronisation</i>. 2023.","bjps":"<b>Ramm S <i>et al.</i></b> (2023) <i>Compression Density as an Alternative to Identify an Optimal Moisture Content for High Shear Wet Granulation as an Initial Step for Spheronisation</i>. .","van":"Ramm S, Fulek R, Eberle VA, Kiera C, Odefey U, Pein-Hackelbusch M. Compression Density as an Alternative to Identify an Optimal Moisture Content for High Shear Wet Granulation as an Initial Step for Spheronisation. 2023.","mla":"Ramm, Selina, et al. <i>Compression Density as an Alternative to Identify an Optimal Moisture Content for High Shear Wet Granulation as an Initial Step for Spheronisation</i>. 2023.","apa":"Ramm, S., Fulek, R., Eberle, V. A., Kiera, C., Odefey, U., &#38; Pein-Hackelbusch, M. (2023). <i>Compression Density as an Alternative to Identify an Optimal Moisture Content for High Shear Wet Granulation as an Initial Step for Spheronisation</i>. Ph.D. Student’s Symposium on Tabletting Technology 2023, Rosenberg.","short":"S. Ramm, R. Fulek, V.A. Eberle, C. Kiera, U. Odefey, M. Pein-Hackelbusch, Compression Density as an Alternative to Identify an Optimal Moisture Content for High Shear Wet Granulation as an Initial Step for Spheronisation, 2023.","havard":"S. Ramm, R. Fulek, V.A. Eberle, C. Kiera, U. Odefey, M. Pein-Hackelbusch, Compression Density as an Alternative to Identify an Optimal Moisture Content for High Shear Wet Granulation as an Initial Step for Spheronisation, 2023.","din1505-2-1":"<span style=\"font-variant:small-caps;\">Ramm, Selina</span> ; <span style=\"font-variant:small-caps;\">Fulek, Ruwen</span> ; <span style=\"font-variant:small-caps;\">Eberle, Veronika Anna</span> ; <span style=\"font-variant:small-caps;\">Kiera, Christian</span> ; <span style=\"font-variant:small-caps;\">Odefey, Ulrich</span> ; <span style=\"font-variant:small-caps;\">Pein-Hackelbusch, Miriam</span>: <i>Compression Density as an Alternative to Identify an Optimal Moisture Content for High Shear Wet Granulation as an Initial Step for Spheronisation</i>, 2023"},"status":"public"},{"external_id":{"isi":["000883998100001"],"pmid":["36365122"]},"main_file_link":[{"open_access":"1","url":"https://www.mdpi.com/1999-4923/14/11/2303"}],"isi":"1","publication_status":"published","citation":{"chicago-de":"Ramm, Selina, Ruwen Fulek, Veronika Anna Eberle, Christian Kiera, Ulrich Odefey und Miriam Pein-Hackelbusch. 2022. Compression Density as an Alternative to Identify an Optimal Moisture Content for High Shear Wet Granulation as an Initial Step for Spheronisation. <i>Pharmaceutics</i> 14, Nr. 11. doi:<a href=\"https://doi.org/10.3390/pharmaceutics14112303\">https://doi.org/10.3390/pharmaceutics14112303</a>, .","chicago":"Ramm, Selina, Ruwen Fulek, Veronika Anna Eberle, Christian Kiera, Ulrich Odefey, and Miriam Pein-Hackelbusch. “Compression Density as an Alternative to Identify an Optimal Moisture Content for High Shear Wet Granulation as an Initial Step for Spheronisation.” <i>Pharmaceutics</i> 14, no. 11 (2022). <a href=\"https://doi.org/10.3390/pharmaceutics14112303\">https://doi.org/10.3390/pharmaceutics14112303</a>.","ama":"Ramm S, Fulek R, Eberle VA, Kiera C, Odefey U, Pein-Hackelbusch M. Compression Density as an Alternative to Identify an Optimal Moisture Content for High Shear Wet Granulation as an Initial Step for Spheronisation. <i>Pharmaceutics</i>. 2022;14(11). doi:<a href=\"https://doi.org/10.3390/pharmaceutics14112303\">https://doi.org/10.3390/pharmaceutics14112303</a>","ufg":"<b>Ramm, Selina u. a.</b>: Compression Density as an Alternative to Identify an Optimal Moisture Content for High Shear Wet Granulation as an Initial Step for Spheronisation., in: <i>Pharmaceutics</i> 14 (2022), H. 11.","din1505-2-1":"<span style=\"font-variant:small-caps;\">Ramm, Selina</span> ; <span style=\"font-variant:small-caps;\">Fulek, Ruwen</span> ; <span style=\"font-variant:small-caps;\">Eberle, Veronika Anna</span> ; <span style=\"font-variant:small-caps;\">Kiera, Christian</span> ; <span style=\"font-variant:small-caps;\">Odefey, Ulrich</span> ; <span style=\"font-variant:small-caps;\">Pein-Hackelbusch, Miriam</span>: Compression Density as an Alternative to Identify an Optimal Moisture Content for High Shear Wet Granulation as an Initial Step for Spheronisation. In: <i>Pharmaceutics</i> Bd. 14. Basel, MDPI (2022), Nr. 11","havard":"S. Ramm, R. Fulek, V.A. Eberle, C. Kiera, U. Odefey, M. Pein-Hackelbusch, Compression Density as an Alternative to Identify an Optimal Moisture Content for High Shear Wet Granulation as an Initial Step for Spheronisation., Pharmaceutics. 14 (2022).","short":"S. Ramm, R. Fulek, V.A. Eberle, C. Kiera, U. Odefey, M. Pein-Hackelbusch, Pharmaceutics 14 (2022).","van":"Ramm S, Fulek R, Eberle VA, Kiera C, Odefey U, Pein-Hackelbusch M. Compression Density as an Alternative to Identify an Optimal Moisture Content for High Shear Wet Granulation as an Initial Step for Spheronisation. Pharmaceutics. 2022;14(11).","apa":"Ramm, S., Fulek, R., Eberle, V. A., Kiera, C., Odefey, U., &#38; Pein-Hackelbusch, M. (2022). Compression Density as an Alternative to Identify an Optimal Moisture Content for High Shear Wet Granulation as an Initial Step for Spheronisation. <i>Pharmaceutics</i>, <i>14</i>(11), Article 2303. <a href=\"https://doi.org/10.3390/pharmaceutics14112303\">https://doi.org/10.3390/pharmaceutics14112303</a>","mla":"Ramm, Selina, et al. “Compression Density as an Alternative to Identify an Optimal Moisture Content for High Shear Wet Granulation as an Initial Step for Spheronisation.” <i>Pharmaceutics</i>, vol. 14, no. 11, 2303, 2022, <a href=\"https://doi.org/10.3390/pharmaceutics14112303\">https://doi.org/10.3390/pharmaceutics14112303</a>.","bjps":"<b>Ramm S <i>et al.</i></b> (2022) Compression Density as an Alternative to Identify an Optimal Moisture Content for High Shear Wet Granulation as an Initial Step for Spheronisation. <i>Pharmaceutics</i> <b>14</b>.","ieee":"S. Ramm, R. Fulek, V. A. Eberle, C. Kiera, U. Odefey, and M. Pein-Hackelbusch, “Compression Density as an Alternative to Identify an Optimal Moisture Content for High Shear Wet Granulation as an Initial Step for Spheronisation.,” <i>Pharmaceutics</i>, vol. 14, no. 11, Art. no. 2303, 2022, doi: <a href=\"https://doi.org/10.3390/pharmaceutics14112303\">https://doi.org/10.3390/pharmaceutics14112303</a>."},"oa":"1","status":"public","place":"Basel","publication_identifier":{"eissn":["1999-4923"]},"keyword":["wet granulation","liquid requirement","granulation endpoint","compression density"],"_id":"9568","author":[{"orcid":"https://orcid.org/0000-0002-0502-8032","full_name":"Ramm, Selina","first_name":"Selina","id":"68713","last_name":"Ramm"},{"last_name":"Fulek","id":"79527","first_name":"Ruwen","full_name":"Fulek, Ruwen"},{"full_name":"Eberle, Veronika Anna","last_name":"Eberle","first_name":"Veronika Anna"},{"full_name":"Kiera, Christian","first_name":"Christian","last_name":"Kiera"},{"id":"74218","first_name":"Ulrich","last_name":"Odefey","full_name":"Odefey, Ulrich"},{"full_name":"Pein-Hackelbusch, Miriam","first_name":"Miriam","id":"64952","last_name":"Pein-Hackelbusch","orcid":"0000-0002-7920-0595"}],"title":"Compression Density as an Alternative to Identify an Optimal Moisture Content for High Shear Wet Granulation as an Initial Step for Spheronisation.","language":[{"iso":"eng"}],"department":[{"_id":"DEP4022"},{"_id":"DEP4028"},{"_id":"DEP4014"}],"publication":"Pharmaceutics","year":"2022","issue":"11","date_created":"2023-03-03T11:23:01Z","abstract":[{"text":"Pellet production is a multi-step manufacturing process comprising granulation, extrusion and spheronisation. The first step represents a critical control point, since the quality of the granule mass highly influences subsequent process steps and, consequently, the quality of final pellets. The most important parameter of wet granulation is the liquid requirement, which can often only be quantitatively evaluated after further process steps. To identify an alternative for optimal liquid requirements, experiments were conducted with a formulation based on lactose and microcrystalline cellulose. Granules were analyzed with a Powder Vertical Shear Rig. We identified the compression density (ρpress) as the said alternative, linking information from the powder material and the moisture content (R2 = 0.995). We used ρpress to successfully predict liquid requirements for unknown formulation compositions. By means of this prediction, pellets with high quality, regarding shape and size distribution, were produced by carrying out a multi-step manufacturing process. Furthermore, the applicability of ρpress as an alternative quality parameter to other placebo formulations and to formulations containing active pharmaceutical ingredients (APIs) was demonstrated.","lang":"eng"}],"publisher":"MDPI","date_updated":"2025-07-29T13:22:53Z","article_number":"2303","pmid":"1","intvolume":"        14","volume":14,"doi":"https://doi.org/10.3390/pharmaceutics14112303","user_id":"83781","type":"scientific_journal_article"}]