ArticlePharmaceutics2023
Box-Behnken Design of Experiments of Polycaprolactone Nanoparticles Loaded with Irinotecan Hydrochloride.
Article in Pharmaceutics, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.
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Who cites it
11 citing papers in PubMed.
- Article
- Optimization of supercritical fluid processes for aripiprazole nanoparticle production using GAS-antisolvent technique and Box-Behnken design.Scientific reports · 2025Article
- Formulation and Systematic Optimisation of Polymeric Blend Nanoparticles via Box-Behnken Design.Pharmaceutics · 2025Article
- Research on Enhancing the Solubility and Bioavailability of Canagliflozin Using Spray Drying Techniques with a Quality-by-Design Approach.Pharmaceutics · 2025Article
- Development and optimization of hydrogel-forming microneedles fabricated with 3d-printed molds for enhanced dermal diclofenac sodium delivery: a comprehensive in vitro, ex vivo, and in vivo study.Drug delivery and translational research · 2025Article
- Amphiphilic mPEG-PLGA copolymer nanoparticles co-delivering colistin and niclosamide to treat colistin-resistant Gram-negative bacteria infections.Communications biology · 2025Article
- Article
- Preparation, characterisation andHeliyon · 2024Article
- Preparation and Evaluation of Folate Modified PEG-PLLA Nanoparticles Loaded with Lycorine for Glioma Treatment.Molecules (Basel, Switzerland) · 2024Article
- Ciprofloxacin- and levofloxacin-loaded nanoparticles efficiently suppressed fluoroquinolone resistance and biofilm formation in Acinetobacter baumannii.Scientific reports · 2024Article
- Box-Behnken Design for Assessing the Efficiency of Aflatoxin M1 Detoxification in Milk UsingLife (Basel, Switzerland) · 2023Article
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Authors and funding
2 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundThe Box-Behnken design of experiments (BBD) is a statistical modelling technique that allows the determination of the significant factors in developing nanoparticles (NPs) using a limited number of runs. It also allows the prediction of the best levels of variables to obtain the desired characteristics (size, charge, and encapsulation efficiency) of the NPs. The aim of this study was to examine the effect of the independent variables (amount of polymer and drug, and surfactant concentration) and their interaction on the characteristics of the irinotecan hydrochloride (IRH)-loaded polycaprolactone (PCL) NPs and to determine the most optimum conditions for producing the desired NPs.
methodsThe development of the NPs was carried out by a double emulsion solvent evaporation technique with yield enhancement. The NPs data were fitted in Minitab software to obtain the best fit model.
resultsBy using BBD, the most optimum conditions for producing the smallest size, highest magnitude of charge, and highest EE% of PCL NPs were predicted to be achieved by using 61.02 mg PCL, 9 mg IRH, and 4.82% PVA, which would yield 203.01 nm, -15.81 mV, and 82.35% EE.
conclusionThe analysis by BBD highlighted that the model was a good fit to the data, confirming the suitability of the design of the experiments.
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