Tesi etd-06252024-120156 |
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Tipo di tesi
Tesi di laurea magistrale
Autore
JAMIL, SHEHNEELA
URN
etd-06252024-120156
Titolo
Optimization of the Novel Production Protocols for the Drug Delivery System
Dipartimento
INGEGNERIA CIVILE E INDUSTRIALE
Corso di studi
MATERIALS AND NANOTECHNOLOGY
Relatori
relatore Prof.ssa Danti, Serena
supervisore Günday-Türeli, Nazende
supervisore Günday-Türeli, Nazende
Parole chiave
- Critical quality attributes
- Design-of-experiments
- Drug delivery systems
- Key enabling technologies
- Nanoparticles
- Process optimization
Data inizio appello
16/07/2024
Consultabilità
Non consultabile
Data di rilascio
16/07/2094
Riassunto
This study employed a continuous manufacturing platform named spinning disc system (SDS) to produce poly (lactic-co-glycolic acid) nanoparticles (PLGA NPs) employed as potential drug delivery system (DDS) for curcumin while ensuring process continuity and scalability. Therefore, PLGA NPs with and without drug were produced by nanoprecipitation method with a modification of adding nonsolvent in solvent phase under fast stirring at room temperature. Critical process parameters (CPPs) of SDS such as disc speed, flow rate, and cannula size were screened. Characterization of their effects on critical quality attributes (CQAs) of NPs such as particle size, polydispersity index (PDI), and zeta potential (ζ), was done using dynamic light scattering (DLS) studies. Encapsulation efficiency (EE%) was evaluated using an indirect method by measuring the free drug using fluorometric assay. The design of experiment (DOE) strategy for optimization of obtained curcumin-loaded PLGA NPs was done using full-factorial-two-level Box-Behnken design. The selected 4 factors and 3 responses were evaluated using regression analysis of variance (ANOVA) and response surface modelling (RSM) for their interactions. Overall, the obtained results showed efficiency, potential, and scalability of SDS to produce NPs with desired properties as well as the applicability of DOE Box-Behnken design for optimization of CPPs and predictability of CQAs using desirability approach.
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