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- PublikationStudy of disordered mesoporous silica regarding intrinsic compound affinity to the carrier and drug-accessible surface area(ACS, 2023) Niederquell, Andreas; Vraníková, Barbora; Kuentz, Martin [in: Molecular Pharmaceutics]There 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 Zeitschrift
- PublikationHow technical innovations may help to prevent drug shortages in switzerland(Schweizerische Chemische Gesellschaft, 2023) Gygax, Daniel; Eigenmann, Kaspar; Suter, Christian; Hürzeler Müller, Marianne; Mahmoud, Ahmed; Mosbacher, Johannes; Pöllinger, Norbert [in: Chimia]In this work, we investigated the technical feasibility of 'on-demand' production of selected drugs to cover their demand for a time window of 90 days. We focused on two sub-processes 'automated chemical synthesis' and 'formulation in micropellets' to enable personalized dosing. The production of drugs 'on-demand' is challenging, important, but also attractive. Switzerland could thus gain access to an additional instrument for increasing resilience for supply-critical drugs. The biggest challenge in the case study presented here is the scalability of automated chemical synthesis and the application range of micropellet formulations.01A - Beitrag in wissenschaftlicher Zeitschrift
- PublikationAnalysis of the physical characteristics of an anhydrous vehicle for compounded pediatric oral liquids(MDPI, 2023) Banov, Daniel; Liu, Yi; Ip, Kendice; Shan, Ashley; Vu, Christine; Zdoryk, Oleksandr; Bassani, August S.; Carvalho, Maria [in: Pharmaceutics]The paucity of suitable drug formulations for pediatric patients generates a need for customized, compounded medications. This research study was set out to comprehensively analyze the physical properties of the new, proprietary anhydrous oral vehicle SuspendIt® Anhydrous, which was designed for compounding pediatric oral liquids. A wide range of tests was used, including sedimentation volume, viscosity, droplet size after dispersion in simulated gastric fluid, microscopic examination and content uniformity measurements to evaluate the properties of the anhydrous vehicle. The results showed that the vehicle exhibited consistent physical properties under varying conditions and maintained stability over time. This can be attributed to the unique blend of excipients in its formulation, which not only maintain its viscosity but also confer thixotropic behavior. The unique combination of viscous, thixotropic and self-emulsifying properties allows for rapid redispersibility, sedimentation stability, accurate dosing, potential drug solubility, dispersion and promotion of enhanced gastrointestinal distribution and absorption. Furthermore, the vehicle demonstrated long-term sedimentation stability and content uniformity for a list of 13 anhydrous suspensions. These results suggest that the anhydrous oral vehicle could serve as a versatile base for pediatric formulation, potentially filling an important gap in pediatric drug delivery. Future studies can further investigate its compatibility, stability and performance with other drugs and in different clinical scenarios.01A - Beitrag in wissenschaftlicher Zeitschrift
- PublikationAdvancing 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. [in: European Journal of Pharmaceutical Sciences]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 Zeitschrift
- PublikationComparative 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, Abolghasem [in: AAPS PharmSciTech]Drug 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