UCL School of Pharmacy, University College London, 29-39 Brunswick Square, London WC1N 1AX, UK; Federal University of Paraíba (UFPB), Department of Pharmaceutical Sciences, Pharmaceutical Biotechnology Laboratory (BioTecFarm), Campus I, Castelo Branco III, Cidade Universitária, 58051-900 João Pessoa, PB, Brazil; Postgraduate Program in Natural and Synthetic Bioactive Products (PPgPNSB/UFPB), R. Tab. Stanislau Eloy, 41 - Conj. Pres. Castelo Branco III, 58050-585 João Pessoa, PB, Brazil.
UCL School of Pharmacy, University College London, 29-39 Brunswick Square, London WC1N 1AX, UK; Nanomerics Ltd. Northwick Park and St Mark's Hospital, Y Block, Watford Road, Harrow, Middlesex HA1 3UJ, UK.
J Colloid Interface Sci. 2025 Jan 15;678(Pt B):1181-1193. doi: 10.1016/j.jcis.2024.08.250. Epub 2024 Sep 6.
Predicting the exact nature of the self-assembly of amphiphilic molecules into supramolecular structures is of utmost importance for a variety of applications, but this is a challenge for nanotechnology. The amphiphilic drug delivery polymer-N-palmitoyl-N-monomethyl-N,N-dimethyl-N,N,N-trimethyl-6-O-glycolchitosan (GCPQ) self-assembles in aqueous media to form nanoparticles.
This work aimed to develop a systematic predictive mathematical model on the eventual nature of oil-loaded GCPQ-nanoparticles and to determine the main independent variables that affect their nanoarchitecture following self-assembly. GCPQ polymers were produced with varying degree of palmitoylation (DP, 5.7-23.8 mol%), degree of quaternization (DQ, 7.2-22.7 mol%), and molecular weight (MW, 11.2-44.2 kDa) and their critical hydrophilic-lipophilic balance (cHLB) optimized to produce oil-loaded nanocapsules.
Non-linear mathematical models (Particle size (nm) = 466.05 - 5.64DP - 6.52DQ + 0.13DQ - 0.03 MW - 14.48cHLB + 0.48cHLB) were derived to predict the nanoparticle sizes (R = 0.998, R = 0.995). Smaller nanoparticle sizes (148-157 nm) were obtained at high DP, DQ, and cHLB values, in which DP was the main independent variable responsible for nanoparticle size. Single or multiple-oil cores with small particles stabilizing polymer shells could be observed depending on the oil volume. Nanoparticle architectures, especially the nature of the oil-core(s), were driven by the DP, DQ, cHLB, and oil concentration. Here, we have developed a predictive model that may be applied to understand the nanoarchitecture of oil-loaded GCPQ-nanoparticles.
预测两亲分子自组装成超分子结构的确切性质对于各种应用至关重要，但这对纳米技术来说是一个挑战。两亲性药物传递聚合物-N-棕榈酰-N-单甲基-N,N-二甲基-N,N,N-三甲基-6-O- 糖基壳聚糖（GCPQ）在水介质中自组装形成纳米颗粒。
本工作旨在开发一种关于油载 GCPQ-纳米颗粒最终性质的系统预测数学模型，并确定影响自组装后纳米结构的主要独立变量。生产了具有不同棕榈酰化程度 (DP，5.7-23.8 mol%)、季铵化程度 (DQ，7.2-22.7 mol%) 和分子量 (MW，11.2-44.2 kDa) 的 GCPQ 聚合物，并优化其临界亲水亲脂平衡 (cHLB) 以生产载油纳米胶囊。
得出了非线性数学模型（粒径（nm）=466.05-5.64DP-6.52DQ+0.13DQ-0.03MW-14.48cHLB+0.48cHLB），以预测纳米颗粒尺寸（R=0.998，R=0.995）。在 DP、DQ 和 cHLB 值较高的情况下，得到了较小的纳米颗粒尺寸（148-157nm），其中 DP 是影响纳米颗粒尺寸的主要独立变量。根据油的体积，可以观察到具有较小粒子稳定聚合物壳的单或多油核。纳米颗粒结构，尤其是油核的性质，受 DP、DQ、cHLB 和油浓度的驱动。在这里，我们开发了一种预测模型，可用于理解油载 GCPQ-纳米颗粒的纳米结构。
