Synergistic Computational Modeling Approaches as Team Players in the Game of Solubility Predictions
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Autor:innen
Autor:in (Körperschaft)
Publikationsdatum
17.11.2020
Typ der Arbeit
Studiengang
Sammlung
Typ
01A - Beitrag in wissenschaftlicher Zeitschrift
Herausgeber:innen
Herausgeber:in (Körperschaft)
Betreuer:in
Übergeordnetes Werk
Journal of Pharmaceutical Sciences
Themenheft
DOI der Originalpublikation
Reihe / Serie
Reihennummer
Jahrgang / Band
110
Ausgabe / Nummer
1
Seiten / Dauer
22-34
Patentnummer
Verlag / Herausgebende Institution
Elsevier
Verlagsort / Veranstaltungsort
Auflage
Version
Programmiersprache
Abtretungsempfänger:in
Praxispartner:in/Auftraggeber:in
Zusammenfassung
Several approaches to predict and model drug solubility have been used in the drug discovery and development processes during the last decades. Each of these approaches have their own benefits and place, and are typically used as standalone approaches rather than in concert. The synergistic effects of these are often overlooked, partly due to the need of computational experts to perform the modeling and simulations as well as analyzing the data obtained. Here we provide our views on how these different approaches can be used to retrieve more information on drug solubility, ranging from multivariate data analysis over thermodynamic cycle modeling to molecular dynamics simulations. We are discussing aqueous solubility as well as solubility in more complex mixed solvents and media with colloidal structures present. We conclude that the field of computational pharmaceutics is in its early days but with a bright future ahead. However, education of computational formulators with broad knowledge of modeling and simulation approaches is imperative if computational pharmaceutics is to reach its full potential.
Schlagwörter
Colloid(s), Computational ADME, Dissolution, Drug-excipient interaction(s), Lipid-based formulation(s), Solubility, Solubilization
Fachgebiet (DDC)
Veranstaltung
Startdatum der Ausstellung
Enddatum der Ausstellung
Startdatum der Konferenz
Enddatum der Konferenz
Datum der letzten Prüfung
ISBN
ISSN
0022-3549
1520-6017
1520-6017
Sprache
Englisch
Während FHNW Zugehörigkeit erstellt
Ja
Publikationsstatus
Veröffentlicht
Begutachtung
Peer-Review der ganzen Publikation
Open Access-Status
Lizenz
Zitation
KUENTZ, Martin, 2020. Synergistic Computational Modeling Approaches as Team Players in the Game of Solubility Predictions. Journal of Pharmaceutical Sciences. 17 November 2020. Bd. 110, Nr. 1, S. 22–34. DOI 10.1016/j.xphs.2020.10.068. Verfügbar unter: https://irf.fhnw.ch/handle/11654/32423