Tan Lihua, Jing Zhongli, Li Na, Yu Xuan, Liu Yi, Wang Meng, Ren Xiaoliang
State Key Laboratory of Component-Based Chinese Medicine, Tianjin University of Traditional Chinese Medicine, Tianjin, 301617, China.
Haihe Laboratory of Modern Chinese Medicine, Tianjin, 301617, People's Republic of China.
AAPS PharmSciTech. 2025 Jul 29;26(7):201. doi: 10.1208/s12249-025-03176-7.
This study introduced a novel vectorized Biopharmaceutics Classification System (BCS) model designed to evaluate the biopharmaceutical properties of active pharmaceutical ingredients (APIs) and their variations under different influencing factors. The model was validated using water-soluble supramolecular p-Sulfonatocalix[n]arenes (SCnA, n = 6, 8), promising pharmaceutical adjuvants, to enhance the solubility and bioavailability of a series of APIs in vitro. The binding interactions of SCnA with 22 alkaloids were assessed for their impact on solubility and permeability using the classical shake-flask method and the parallel artificial membrane permeability assay (PAMPA). To quantify the effects, the change in directional cosine (θ) for each API was calculated by measuring the ratio of the differences in x- and y-coordinates before and after binding. The linear distance and modulus length (r) changes for each API were determined using the Pythagorean theorem, enabling a quantitative assessment of the modifications in solubility and permeability. The potential changes in oral bioavailability pre- and post-binding were visualized using heat maps based on θ and r, highlighting significant improvements in the solubility of compounds such as allicin, tetrandrine, lycorisine, and others. These changes corresponded with shifts in BCS classification, indicating a positive relationship between SCnA concentration, cavity size, and enhanced solubility. The study also evaluated the influence of pH, and concentrations of host and guest, to assess the tolerance of SCnA for further pharmaceutical applications. Based on prior safety assessments, SCnA (n = 6, 8) demonstrated significant potential as solubilizing excipients. The vectorized BCS model enabled precise, quantitative analysis of biopharmaceutical property variations without added experimental complexity, offering a tool for high-throughput screening of excipients in pharmaceutical formulation and processing.
本研究引入了一种新型的向量化生物药剂学分类系统(BCS)模型,旨在评估活性药物成分(API)的生物药剂学性质及其在不同影响因素下的变化。该模型使用水溶性超分子对磺酸钠杯[n]芳烃(SCnA,n = 6, 8)进行了验证,SCnA是一种有前景的药物辅料,用于在体外提高一系列API的溶解度和生物利用度。使用经典摇瓶法和平行人工膜通透性测定法(PAMPA)评估了SCnA与22种生物碱的结合相互作用对溶解度和通透性的影响。为了量化这些影响,通过测量结合前后x和y坐标差异的比率,计算了每种API的方向余弦(θ)变化。使用勾股定理确定了每种API的线性距离和模量长度(r)变化,从而能够对溶解度和通透性的变化进行定量评估。基于θ和r,使用热图直观显示了结合前后口服生物利用度的潜在变化,突出了大蒜素、粉防己碱、石蒜碱等化合物溶解度的显著提高。这些变化与BCS分类的转变相对应,表明SCnA浓度、空腔大小与溶解度提高之间存在正相关关系。该研究还评估了pH值、主体和客体浓度的影响,以评估SCnA在进一步药物应用中的耐受性。基于先前的安全性评估,SCnA(n = 6, 8)作为增溶辅料具有显著潜力。向量化BCS模型能够在不增加实验复杂性的情况下,对生物药剂学性质变化进行精确、定量分析,为药物制剂和加工中辅料的高通量筛选提供了一种工具。