Kuentz, Martin
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Kuentz, Martin
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Publikation Hydrophobic deep eutectic solvent (HDES) as oil phase in lipid-based drug formulations(Elsevier, 15.08.2024) Panbachi, Shaida; Beranek, Josef; Kuentz, MartinThere is increasing pharmaceutical interest in deep eutectic solvents not only as a green alternative to organic solvents in drug manufacturing, but also as liquid formulation for drug delivery. The present work introduces a hydrophobic deep eutectic solvent (HDES) to the field of lipid-based formulations (LBF). Phase behavior of a mixture with 2:1 M ratio of decanoic- to dodecanoic acid was studied experimentally and described by thermodynamic modelling. Venetoclax was selected as a hydrophobic model drug and studied by atomistic molecular dynamics simulations of the mixtures. As a result, valuable molecular insights were gained into the interaction networks between the different components. Moreover, experimentally the HDES showed greatly enhanced drug solubilization compared to conventional glyceride-based vehicles, but aqueous dispersion behavior was limited. Hence surfactants were studied for their ability to improve aqueous dispersion and addition of Tween 80 resulted in lowest droplet sizes and high in vitro drug release. In conclusion, the combination of HDES with surfactant(s) provides a novel LBF with high pharmaceutical potential. However, the components must be finely balanced to keep the integrity of the solubilizing HDES, while enabling sufficient dispersion and drug release.01A - Beitrag in wissenschaftlicher ZeitschriftPublikation A study of hydrophobic domain formation of polymeric drug precipitation inhibitors in aqueous solution(Elsevier, 01.07.2024) Zeneli, Egis; Lange, Justus Johann; Holm, René; Kuentz, MartinDespite the widespread use of polymers as precipitation inhibitors in supersaturating drug formulations, the current understanding of their mechanisms of action is still incomplete. Specifically, the role of hydrophobic drug interactions with polymers by considering possible supramolecular conformations in aqueous dispersion is an interesting topic. Accordingly, this study investigated the tendency of polymers to create hydrophobic domains, where lipophilic compounds may nest to support drug solubilisation and supersaturation. Fluorescence spectroscopy with the environment-sensitive probe pyrene was compared with atomistic molecular dynamics simulations of the model drug fenofibrate (FENO). Subsequently, kinetic drug supersaturation and thermodynamic solubility experiments were conducted. As a result, the different polymers showed hydrophobic domain formation to a varying degree and the molecular simulations supported interpretation of fluorescence spectroscopy data. Molecular insights were gained into the conformational structure of how the polymers interacted with FENO in solution phase, which apart from nucleation and crystal growth effects, determined drug concentrations in solution. Notable was that even at the lowest polymer concentration of 0.01 %, w/v, there were polymer-specific solubilisation effects of FENO observed and the resulting reduction in apparent drug supersaturation provided relevant knowledge both from a mechanistic and practical perspective.01A - Beitrag in wissenschaftlicher ZeitschriftPublikation Lipid based formulations as supersaturating oral delivery systems. From current to future industrial applications(Elsevier, 01.10.2023) Holm, René; Kuentz, Martin; Ilie-Spiridon, Alexandra-Roxana; Griffin, Brendan T.01A - Beitrag in wissenschaftlicher ZeitschriftPublikation Leveraging the use of in vitro and computational methods to support the development of enabling oral drug products. An InPharma commentary(Elsevier, 01.09.2023) Reppas, Christos; Kuentz, Martin; Bauer-Brandl, Annette; Carlert, Sara; Dallmann, André; Dietrich, Shirin; Dressman, Jennifer; Ejskjaer, Lotte; Frechen, Sebastian; Guidetti, Matteo; Holm, René; Holzem, Florentin Lukas; Karlsson, Εva; Kostewicz, Edmund; Panbachi, Shaida; Paulus, Felix; Senniksen, Malte Bøgh; Stillhart, Cordula; Turner, David B.; Vertzoni, Maria; Vrenken, Paul; Zöller, Laurin; Griffin, Brendan T.; O'Dwyer, Patrick J.01A - Beitrag in wissenschaftlicher ZeitschriftPublikation Polymer-embedded deep eutectic solvents (PEDES) as a novel bio-enabling formulation approach(Elsevier, 07/2023) Panbachi, Shaida; Beranek, Josef; Kuentz, MartinThere is a growing interest in using deep eutectic solvents (DES) as a pharmaceutical delivery system for poorly water-soluble compounds. To reduce the risk of drug precipitation following oral administration, this study addresses the hypothesis that directly including a polymeric precipitation inhibitor (PI) in a DES mixture could obtain a polymer-embedded deep eutectic system (PEDES) as a novel bio-enabling formulation principle. Following broad formulation screening, a PEDES embedding 15% w/w of polyvinyl pyrrolidone K30 (PVP) in L-carnitine:ethylene glycol (1:4, molar ratio) DES was successfully formulated as a supersaturating formulation using indomethacin as model compound. The drug solubility of 175.6 mg/mL obtained in DES was remarkably high, and upon release (phosphate buffer, pH 6.5) a maximum supersaturation factor of 9.8 was recorded, whereby the release kinetics displayed a suitable “parachute effect”. The formulation was further characterized to include a molecular dynamics simulation. It can be concluded that PEDES appears to be a viable novel formulation approach, setting solid grounds for further research to assess the full potential of this novel type of supersaturating drug delivery system.01A - Beitrag in wissenschaftlicher ZeitschriftPublikation 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 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 Corrigendum to “Powder cohesion and energy to break an avalanche. Can we address surface heterogeneity?” [Int. J. Pharm. 626 (2022) 122198](Elsevier, 2023) Brokešová, Jana; Niederquell, Andreas; Kuentz, Martin; Zámostný, Petr; Vraníková, Barbora; Šklubalová, Zdenka01A - 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 Zeitschrift