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Merck
  • Toward the establishment of standardized in vitro tests for lipid-based formulations, part 4: proposing a new lipid formulation performance classification system.

Toward the establishment of standardized in vitro tests for lipid-based formulations, part 4: proposing a new lipid formulation performance classification system.

Journal of pharmaceutical sciences (2014-07-06)
Hywel D Williams, Philip Sassene, Karen Kleberg, Marilyn Calderone, Annabel Igonin, Eduardo Jule, Jan Vertommen, Ross Blundell, Hassan Benameur, Anette Müllertz, Christopher J H Porter, Colin W Pouton
摘要

The Lipid Formulation Classification System Consortium looks to develop standardized in vitro tests and to generate much-needed performance criteria for lipid-based formulations (LBFs). This article highlights the value of performing a second, more stressful digestion test to identify LBFs near a performance threshold and to facilitate lead formulation selection in instances where several LBF prototypes perform adequately under standard digestion conditions (but where further discrimination is necessary). Stressed digestion tests can be designed based on an understanding of the factors that affect LBF performance, including the degree of supersaturation generated on dispersion/digestion. Stresses evaluated included decreasing LBF concentration (↓LBF), increasing bile salt, and decreasing pH. Their capacity to stress LBFs was dependent on LBF composition and drug type: ↓LBF was a stressor to medium-chain glyceride-rich LBFs, but not more hydrophilic surfactant-rich LBFs, whereas decreasing pH stressed tolfenamic acid LBFs, but not fenofibrate LBFs. Lastly, a new Performance Classification System, that is, LBF composition independent, is proposed to promote standardized LBF comparisons, encourage robust LBF development, and facilitate dialogue with the regulatory authorities. This classification system is based on the concept that performance evaluations across three in vitro tests, designed to subject a LBF to progressively more challenging conditions, will enable effective LBF discrimination and performance grading.

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