ArticleRoyal Society open science2019
Application of statistical design to evaluate critical process parameters and optimize formulation technique of polymeric nanoparticles.
Article in Royal Society open science, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
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Who cites it
5 citing papers in PubMed.
- Differential Self-Assembly Behaviors and Proteolytic Stability of Bicyclic Peptides Compared to Monocyclic Peptides.Chemistry, an Asian journal · 2026Article
- Chitinase-functionalized UiO-66 framework nanoparticles active against multidrug-resistant Candida Auris.BMC microbiology · 2024Article
- Development of Statistically Optimized Piperine-Loaded Polymeric Nanoparticles for Breast Cancer: In Vitro Evaluation and Cell Culture Studies.ACS omega · 2023Article
- Development of Carvedilol-Loaded Albumin-Based Nanoparticles with Factorial Design to Optimize In Vitro and In Vivo Performance.Pharmaceutics · 2023Article
- Investigation of Alogliptin-Loaded In Situ Gel Implants by 2Pharmaceutics · 2022Article
Corrections and comments
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Authors and funding
3 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
In advanced medication, drug-loaded polymeric nanoparticles (NPs) appeared as a novel drug delivery system with lots of advantages over conventional medicines. Despite all the advantages, NPs do not gain popularity for manufacturing hurdles. The study focused on the formulation difficulties and implementation of statistical design to establish an effective model for manufacturing NPs. In this study, physico-chemical properties of the drug and polymer (PLGA) were incorporated to understand the mechanistic insights of nanoformulations. Primarily, the process controlling parameters were screened by Plackett-Burman design and the critical process parameters (Cpp) were further fabricated by Box-Behnken design (BBD). The TLM-PLGA-NPs (telmisartan loaded PLGA NPs) exhibited particle size, encapsulation efficiency and zeta potential of 232.4 nm, 79.21% and -9.92 mV respectively. The NPs represented drug loading of 76.31%. Korsmeyer-Peppas model (
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Registered trials
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