Hamdallah Sherif I, Zoqlam Randa, Yang Bin, Campbell Andrew, Booth Rebecca, Booth Jonathan, Belton Peter, Qi Sheng
School of Pharmacy, University of East Anglia Norwich NR4 7TJ UK
Department of Pharmaceutics, Faculty of Pharmacy, Alexandria University Alexandria Egypt.
Nanoscale Adv. 2024 May 8;6(12):3188-3198. doi: 10.1039/d4na00087k. eCollection 2024 Jun 11.
The synthesis of drug-loaded PLGA nanoparticles through nanoprecipitation in solvent/antisolvent mixtures is well reported but lacks clarity in explaining drug loading mechanisms and the prediction of efficiency of drug entrapment. Various methods using physical parameters such as log and solid-state drug-polymer solubility aim to predict the intensity of drug-polymer interactions but lack precision. In particular, the zero-enthalpy method for drug/polymer solubility may be intrinsically inaccurate, as we demonstrate. Conventional measurement of loading capacity (LC), expressed in weight ratios, can be misleading for comparing different drugs and we stress the importance of using molar units. This research aims to provide new insights and critically evaluate the established methodologies for drug loading of PLGA nanoparticles. The study employs four model drugs with varying solubilities in solvent/antisolvent mixtures, log values, and solid-state solubility in PLGA: ketoprofen (KPN), indomethacin (IND), sorafenib (SFN), and clofazimine (CFZ). This study highlights that drug loading efficiency is primarily influenced by the drug's solubilities within the solvent system. We emphasise that both kinetic and thermodynamic factors play a role in the behaviour of the system by considering the changes in drug solubility during mixing. The study introduces a pseudo-constant * to characterise drug-polymer interactions, with CFZ and SFN showing the highest * values. Interestingly, while IND and KPN have lower * values, they achieve higher loading capacities due to their greater solubilities, indicating the key role of solubility in determining LC.
通过在溶剂/反溶剂混合物中进行纳米沉淀来合成载药PLGA纳米颗粒已有大量报道,但在解释载药机制和预测药物包封效率方面仍缺乏清晰度。各种使用诸如log 和固态药物 - 聚合物溶解度等物理参数的方法旨在预测药物 - 聚合物相互作用的强度,但缺乏精确性。特别是,正如我们所证明的,药物/聚合物溶解度的零焓方法可能本质上不准确。以重量比表示的传统载药量(LC)测量方法在比较不同药物时可能会产生误导,我们强调使用摩尔单位的重要性。本研究旨在提供新的见解,并批判性地评估已确立的PLGA纳米颗粒载药方法。该研究采用了四种在溶剂/反溶剂混合物中具有不同溶解度、log 值以及在PLGA中的固态溶解度的模型药物:酮洛芬(KPN)、吲哚美辛(IND)、索拉非尼(SFN)和氯法齐明(CFZ)。本研究强调载药效率主要受药物在溶剂系统中的溶解度影响。我们强调,通过考虑混合过程中药物溶解度的变化,动力学和热力学因素都在系统行为中起作用。该研究引入了一个伪常数来表征药物 - 聚合物相互作用,CFZ和SFN显示出最高的值。有趣的是,虽然IND和KPN的*值较低,但由于它们较高的溶解度,它们实现了更高的载药量,这表明溶解度在决定LC方面的关键作用。