de Castro Matheus, Cordeiro Ana Sara, Li Mingzhong, Lübbert Christian, McColl Catherine, Khurana Jatin, Evans Mark, Schlindwein Walkiria S
Leicester School of Pharmacy, De Montfort University, Leicester LE1 9BH, United Kingdom.
amofor GmbH, Otto-Hahn-Str. 15, 44227 Dortmund, Germany.
Int J Pharm X. 2025 Aug 9;10:100373. doi: 10.1016/j.ijpx.2025.100373. eCollection 2025 Dec.
This study investigates the solubility and miscibility of ibuprofen (IBU) with four pharmaceutical polymers, KOLVA64®, KOL17PF®, HPMCAS, and Eudragit® EPO, using a combination of empirical and hybrid modeling approaches, supported by differential scanning calorimetry (DSC) experiments. Traditional group contribution methods based on Hildebrand and Hansen solubility parameters (Fedors, Hoftyzer-van Krevelen, and Just-Breitkreutz) showed variability in solubility predictions but consistently classified all polymer-API blends as miscible (Δδ < 7 MPa). Bagley plots reinforced these findings, although borderline miscibility was indicated for HPMCAS and EPO depending on the method used. A novel attempt to derive the Flory-Huggins (FH) interaction parameter (χ) from solubility parameters at near-melting temperatures showed poor agreement with experimental data, underscoring the limitations of such extrapolations and the semi-empirical nature of the FH model. Phase diagrams were constructed from DSC-based melting point depression data using three modeling strategies: FH theory, the empirical approach by Kyeremateng (with two fitting methods), and the perturbed-chain statistical associating fluid theory (PC-SAFT) equation of state, both in pure predictions and with fitted binary interaction parameters (k). The glass transition temperature (T) of the mixtures was modeled using the Gordon-Taylor and Kwei equations. All models provided a consistent polymer ranking based on their solubilizing capacity, with KOL17PF as the most compatible and HPMCAS as the least. Demixing zones (liquid-liquid equilibrium - LLE) predicted by FH and PC-SAFT models suggest that for HPMCAS-based ASDs only very low drug loadings (< 5 % w/w) could potentially be stable at room temperature. In contrast, higher drug loadings (> 10 % w/w) fall under a meta-stable zone with the other polymers, making them better candidates for IBU formulation. HPMCAS also exhibited consistently prediction errors across all T models, (AARD ∼4.5 %), indicating poorer agreement with experimental data. By integrating empirical and hybrid modeling approaches, this study highlights the strengths and limitations of commonly used solubility prediction methods and advocates for a shift toward a harmonized framework.
本研究采用经验建模与混合建模相结合的方法，并辅以差示扫描量热法（DSC）实验，研究了布洛芬（IBU）与四种药用聚合物KOLVA64®、KOL17PF®、羟丙基甲基纤维素琥珀酸酯（HPMCAS）和尤特奇®EPO的溶解度和混溶性。基于希尔德布兰德和汉森溶解度参数的传统基团贡献法（费多尔斯法、霍夫蒂泽 - 范克雷维伦法和贾斯特 - 布赖特克鲁茨法）在溶解度预测中表现出差异，但始终将所有聚合物 - API共混物归类为可混溶（Δδ < 7 MPa）。巴格利图强化了这些发现，不过根据所使用的方法，HPMCAS和EPO显示出临界混溶性。在接近熔点温度下从溶解度参数推导弗洛里 - 哈金斯（FH）相互作用参数（χ）的新尝试与实验数据的一致性较差，凸显了此类外推法的局限性以及FH模型的半经验性质。利用三种建模策略，基于DSC熔点降低数据构建了相图：FH理论、凯雷马滕的经验方法（有两种拟合方法）以及状态方程的扰动链统计缔合流体理论（PC - SAFT），包括纯预测和拟合二元相互作用参数（k）的情况。使用戈登 - 泰勒方程和奎伊方程对混合物的玻璃化转变温度（T）进行了建模。所有模型根据其增溶能力提供了一致的聚合物排序，其中KOL17PF最具相容性，HPMCAS最不相容。FH和PC - SAFT模型预测的分层区（液 - 液平衡 - LLE）表明，对于基于HPMCAS的无定形固体分散体（ASD），只有非常低的药物载量（< 5 % w/w）在室温下可能是稳定的。相比之下，较高的药物载量（> 10 % w/w）在与其他聚合物的亚稳区内，这使它们成为布洛芬制剂的更好候选物。HPMCAS在所有T模型中也始终表现出预测误差（平均绝对相对偏差约为4.5 %），表明与实验数据的一致性较差。通过整合经验建模与混合建模方法，本研究突出了常用溶解度预测方法的优势和局限性，并倡导转向统一框架。
