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Tools for Early Prediction of Drug Loading in Lipid-Based Formulations
Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Pharmacy, Department of Pharmacy.
Monash Univ, Monash Inst Pharmaceut Sci, Drug Delivery Disposit & Dynam, Parkville, Vic 3052, Australia..
Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Pharmacy, Department of Pharmacy. UMonash Univ, Monash Inst Pharmaceut Sci, Drug Delivery Disposit & Dynam, Parkville, Vic 3052, Australia..
2016 (English)In: Molecular Pharmaceutics, ISSN 1543-8384, E-ISSN 1543-8392, Vol. 13, no 1, 251-261 p.Article in journal (Refereed) Published
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Text
Abstract [en]

Identification of the usefulness of lipid-based formulations (LBFs) for delivery of poorly water-soluble drugs is at date mainly experimentally based. In this work we used a diverse drug data set, and more than 2,000 solubility measurements to develop experimental and computational tools to predict the loading capacity of LBFs. Computational models were developed to enable in silico prediction of solubility, and hence drug loading capacity, in the LBFs. Drug solubility in mixed mono-, di-, triglycerides (Maisine 35-1 and Capmul MCM EP) correlated (R-2 0.89) as well as the drug solubility in Carbitol and other ethoxylated excipients (PEG400, R-2 0.85; Polysorbate 80, R-2 0.90; Cremophor EL, R-2 0.93). A melting point below 150 degrees C was observed to result in a reasonable solubility in the glycerides. The loading capacity in LBFs was accurately calculated from solubility data in single excipients (R-2 0.91). In silico models, without the demand of experimentally determined solubility, also gave good predictions of the loading capacity in these complex formulations (R-2 0.79). The framework established here gives a better understanding of drug solubility in single excipients and of LBF loading capacity. The large data set studied revealed that experimental screening efforts can be rationalized by solubility measurements in key excipients or from solid state information. For the first time it was shown that loading capacity in complex formulations can be accurately predicted using molecular information extracted from calculated descriptors and thermal properties of the crystalline drug.

Place, publisher, year, edition, pages
2016. Vol. 13, no 1, 251-261 p.
Keyword [en]
lipid-based formulations, solubility prediction, loading capacity, molecular properties, in silico prediction
National Category
Pharmaceutical Sciences
Identifiers
URN: urn:nbn:se:uu:diva-275856DOI: 10.1021/acs.molpharmaceut.5b00704ISI: 000367866200026PubMedID: 26568134OAI: oai:DiVA.org:uu-275856DiVA: diva2:903629
Funder
Swedish Research Council, 621-2011-2445 621-2014-3309EU, European Research Council, 638965
Available from: 2016-02-16 Created: 2016-02-08 Last updated: 2017-11-30Bibliographically approved

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Alskär, Linda C.Bergström, Christel A. S.

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