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Quality by Design Approach Using Multiple Linear and Logistic Regression Modeling Enables Microemulsion Scale Up.


ABSTRACT: The development of pharmaceutical nanoformulations has accelerated over the past decade. However, the nano-sized drug carriers continue to meet substantial regulatory and clinical translation challenges. In order to address some of these key challenges in early development, we adopted a quality by design approach to develop robust predictive mathematical models for microemulsion formulation, manufacturing, and scale-up. The presented approach combined risk management, design of experiments, multiple linear regression (MLR), and logistic regression to identify a design space in which microemulsion colloidal properties were dependent solely upon microemulsion composition, thus facilitating scale-up operations. Developed MLR models predicted microemulsion diameter, polydispersity index (PDI), and diameter change over 30 days storage, while logistic regression models predicted the probability of a microemulsion passing quality control testing. A stable microemulsion formulation was identified and successfully scaled up tenfold to 1L without impacting droplet diameter, PDI, or stability.

SUBMITTER: Herneisey M 

PROVIDER: S-EPMC6600169 | biostudies-literature | 2019 May

REPOSITORIES: biostudies-literature

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Quality by Design Approach Using Multiple Linear and Logistic Regression Modeling Enables Microemulsion Scale Up.

Herneisey Michele M   Lambert Eric E   Kachel Allison A   Shychuck Emma E   Drennen James K JK   Janjic Jelena M JM  

Molecules (Basel, Switzerland) 20190530 11


The development of pharmaceutical nanoformulations has accelerated over the past decade. However, the nano-sized drug carriers continue to meet substantial regulatory and clinical translation challenges. In order to address some of these key challenges in early development, we adopted a quality by design approach to develop robust predictive mathematical models for microemulsion formulation, manufacturing, and scale-up. The presented approach combined risk management, design of experiments, mult  ...[more]

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