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Bereich: Suchergebnisse
Publikation Study of disordered mesoporous silica regarding intrinsic compound affinity to the carrier and drug-accessible surface area(ACS, 2023) Niederquell, Andreas; Vraníková, Barbora; Kuentz, MartinThere is increasing research interest in using mesoporous silica for the delivery of poorly water-soluble drugs that are stabilized in a noncrystalline form. Most research has been done on ordered silica, whereas far fewer studies have been published on using nonordered mesoporous silica, and little is known about intrinsic drug affinity to the silica surface. The present mechanistic study uses inverse gas chromatography (IGC) to analyze the surface energies of three different commercially available disordered mesoporous silica grades in the gas phase. Using the more drug-like probe molecule octane instead of nitrogen, the concept of a “drug-accessible surface area” is hereby introduced, and the effect on drug monolayer capacity is addressed. In addition, enthalpic interactions of molecules with the silica surface were calculated based on molecular mechanics, and entropic energy contributions of volatiles were estimated considering molecular flexibility. These free energy contributions were used in a regression model, giving a successful comparison with experimental desorption energies from IGC. It is proposed that a simplified model for drugs based only on the enthalpic interactions can provide an affinity ranking to the silica surface. Following this preformulation research on mesoporous silica, future studies may harness the presented concepts to guide formulation scientists. © 2023 American Chemical Society.01A - Beitrag in wissenschaftlicher ZeitschriftPublikation Advancing algorithmic drug product development. Recommendations for machine learning approaches in drug formulation(Elsevier, 2023) Murray, Jack D.; Lange, Justus J.; Bennett-Lenane, Harriet; Holm, René; Kuentz, Martin; O'Dwyer, Patrick J.; Griffin, Brendan T.Artificial intelligence is a rapidly expanding area of research, with the disruptive potential to transform traditional approaches in the pharmaceutical industry, from drug discovery and development to clinical practice. Machine learning, a subfield of artificial intelligence, has fundamentally transformed in silico modelling and has the capacity to streamline clinical translation. This paper reviews data-driven modelling methodologies with a focus on drug formulation development. Despite recent advances, there is limited modelling guidance specific to drug product development and a trend towards suboptimal modelling practices, resulting in models that may not give reliable predictions in practice. There is an overwhelming focus on benchtop experimental outcomes obtained for a specific modelling aim, leaving the capabilities of data scraping or the use of combined modelling approaches yet to be fully explored. Moreover, the preference for high accuracy can lead to a reliance on black box methods over interpretable models. This further limits the widespread adoption of machine learning as black boxes yield models that cannot be easily understood for the purposes of enhancing product performance. In this review, recommendations for conducting machine learning research for drug product development to ensure trustworthiness, transparency, and reliability of the models produced are presented. Finally, possible future directions on how research in this area might develop are discussed to aim for models that provide useful and robust guidance to formulators. © 202301A - Beitrag in wissenschaftlicher ZeitschriftPublikation Comparative drug solubility studies using shake-flask versus a laser-based robotic method(Springer, 2023) Rahimpour, Elaheh; Moradi, Milad; Sheikhi-Sovari, Atefeh; Rezaei, Homa; Rezaei, Hadis; Jouyban-Gharamaleki, Vahid; Kuentz, Martin; Jouyban, AbolghasemDrug solubility is of central importance to the pharmaceutical sciences, but reported values often show discrepancies. Various factors have been discussed in the literature to account for such differences, but the influence of manual testing in comparison to a robotic system has not been studied adequately before. In this study, four expert researchers were asked to measure the solubility of four drugs with various solubility behaviors (i.e., paracetamol, mesalazine, lamotrigine, and ketoconazole) in the same laboratory with the same instruments, method, and material sources and repeated their measurements after a time interval. In addition, the same solubility data were determined using an automated laser-based setup. The results suggest that manual testing leads to a handling influence on measured solubility values, and the results were discussed in more detail as compared to the automated laser-based system. Within the framework of unavoidable uncertainties of solubility testing, it is a possibility to combine minimal experimental testing that is preferably automated with mathematical modeling. That is a practical suggestion to support future pharmaceutical development in a more efficient way. © 2023, The Author(s), under exclusive licence to American Association of Pharmaceutical Scientists.01A - Beitrag in wissenschaftlicher ZeitschriftPublikation Co‐current filtrate flow in TFF perfusion processes. Decoupling transmembrane pressure from crossflow to improve product sieving(Wiley, 2023) Romann, Patrick; Giller, Philip; Sibilia, Antony; Herwig, Christoph; Zydney, Andrew L.; Perilleux, Arnaud; Souquet, Jonathan; Bielser, Jean‐Marc; Villiger, ThomasHollow fiber‐based membrane filtration has emerged as the dominant technology for cell retention in perfusion processes yet significant challenges in alleviating filter fouling remain unsolved. In this work, the benefits of co‐current filtrate flow applied to a tangential flow filtration (TFF) module to reduce or even completely remove Starling recirculation caused by the axial pressure drop within the module was studied by pressure characterization experiments and perfusion cell culture runs. Additionally, a novel concept to achieve alternating Starling flow within unidirectional TFF was investigated. Pressure profiles demonstrated that precise flow control can be achieved with both lab‐scale and manufacturing‐scale filters. TFF systems with co‐current flow showed up to 40% higher product sieving compared to standard TFF. The decoupling of transmembrane pressure from crossflow velocity and filter characteristics in co‐current TFF alleviates common challenges for hollow fiber‐based systems such as limited crossflow rates and relatively short filter module lengths, both of which are currently used to avoid extensive pressure drop along the filtration module. Therefore, co‐current filtrate flow in unidirectional TFF systems represents an interesting and scalable alternative to standard TFF or alternating TFF operation with additional possibilities to control Starling recirculation flow.01A - Beitrag in wissenschaftlicher ZeitschriftPublikation Not the usual suspects. Alternative surfactants for biopharmaceuticals(American Chemical Society, 2023) Brosig, Sebastian; Cucuzza, Stefano; Serno, Tim; Bechtold-Peters, Karoline; Buecheler, Jakob; Zivec, Matej; Germershaus, Oliver; Gallou, Fabrice01A - Beitrag in wissenschaftlicher ZeitschriftPublikation Tablet formulation with dual control concept for efficient colonic drug delivery(Elsevier, 25.01.2023) Doggwiler, Viviane; Lanz, Michael; Paredes, Valeria; Lipps, Georg; Imanidis, Georgios01A - Beitrag in wissenschaftlicher ZeitschriftPublikation Efficient colonic drug delivery in domestic pigs employing a tablet formulation with dual control concept(Elsevier, 06/2023) Doggwiler, Viviane; Puorger, Chasper; Paredes, Valeria; Lanz, Michael; Nuss, Katja M.; Lipps, Georg; Imanidis, Georgios01A - Beitrag in wissenschaftlicher ZeitschriftPublikation Using a laser monitoring technique for dissolution and thermodynamic study of celecoxib in 2-propanol and propylene glycol mixtures(Dissolution Technologies, 2023) Jouyban-Gharamaleki, Vahid; Martinez, Fleming; Kuentz, Martin; Rahimpour, Elaheh; Jouyban, Abolghasem01A - Beitrag in wissenschaftlicher ZeitschriftPublikation Indigenous yeasts from rose oil distillation wastewater and their capacity for biotransformation of phenolics(MDPI, 12.01.2023) Rusanova, Mila; Rusanov, Krasimir; Butterweck, Veronika; Atanassov, IvanThe indigenous yeasts associated with the spontaneous fermentation of phenolic-rich rose oil distillation wastewater (RODW) generated after the industrial distillation of rose oil were studied. The ITS-rDNA sequence analysis of the samples collected from RODW fermented at semi-sterile conditions, a waste deposition lagoon and endophytic yeasts isolated from industrially cultivated Rosa damascena suggests that the spontaneous RODW fermentation is caused by yeasts from the genus Cyberlindnera found also as endophytes in the rose flowers. Phylogenetic analysis based on the nucleotide sequences of the translation elongation factor (TEF1α) and 18S- and 26S- rRNA genes further confirmed the taxonomic affiliation of the RODW yeast isolates with the genus Cyberlindnera. The RODW fermentation capacity of a selected set of indigenous yeast isolates was studied and compared with those of common yeast strains. The indigenous yeast isolates demonstrated a superior growth rate, resulting in a nearly double reduction in the phenolic content in the fermented RODW. The indigenous yeasts’ fermentation changed the RODW phenolics’ composition. The levels of some particular phenolic glycosides decreased through the depletion and fermentation of their sugar moiety. Hence, the relative abundance of the corresponding aglycons and other phenolic compounds increased. The capacity for the biotransformation of RODW phenolics by indigenous yeasts is discussed.01A - Beitrag in wissenschaftlicher ZeitschriftPublikation Physiological buffer effects in drug supersaturation - a mechanistic study of hydroxypropyl cellulose as precipitation inhibitor(2023) Niederquell, Andreas; Stoyanov, Edmont; Kuentz, Martin01A - Beitrag in wissenschaftlicher Zeitschrift