| 摘要: | 活性藥物成分（Active Pharmaceutical Ingredient, API）是藥物中能提供治療作用的核心化學物質，根據生物製劑分類系統（Biopharmaceutics Classification System, BCS），API 可分為四大類。其中，第二類藥物因其水溶性差和溶解速率低，可能導致於人體內溶解緩慢，延長治療時效，對口服藥物的輸送效果產生顯著影響。然而，其高滲透性的特性使其成為增溶研究的主要目標。為改善其溶解性，常透過添加高分子形成無定形固體分散體（Amorphous Solid Dispersion, ASD）。常見的製備方式包括熔化淬火法、熱熔擠出法、噴霧乾燥法、球磨法和冷凍乾燥法等。然而，目前市場上成功開發的相關產品相對稀少，顯示此配方策略面臨極高挑戰性。其主要原因在於 ASD 通常處於熱力學亞穩態，容易發生再結晶風險，導致緩慢溶解甚至相分離的問題。為避免再結晶或相分離的發生，構建熱力學相圖顯得至關重要。
熱力學相圖的兩項關鍵數據為藥物在高分子中的溶解度及玻璃轉化溫度。溶解度能揭示高分子負載藥物的最大值，以避免過飽和或再結晶情況；而玻璃轉化溫度的數據則有助於在低於該溫度的情況下降低分子遷移率，穩定藥物的亞穩態無定形結構。然而，室溫下量測溶解度實驗具有相當高的挑戰性，由於利用 DSC 難以完全達到溶解平衡，無法直接測量溶解度數據，加上高分子的高黏度及大多數藥物在環境條件下呈現固態特性，進一步增添實驗數據的不確定性。因此，需依賴熱力學模型來估算相平衡數據。目前已有研究採用 PC-SAFT 和 Flory-Huggins 模型計算藥物溶解度，並使用 Gordon-Taylor 模型估算玻璃轉化溫度來建構所需要的熱力學相圖。本研究團隊之先期研究中發現可以利用COSMO-SAC模型方法搭配上高分子三聚體的分子表面電荷分布（σ-profile）可合理預測藥物在均聚物及簡單共聚物中的溶解度。在本研究中，進一步拓展COSMO-SAC模型方法於描述複雜共聚物之系統，開發出一套利用複雜共聚物中各單體三聚體之σ-profile來生成複雜共聚物之σ-profile，並以此模擬藥物在這些共聚物中的溶解度。此外，亦搭配使用 Gordon-Taylor 模型估算玻璃化轉變溫度，來生成藥物-聚合物雙元系統的熱力學相圖。
;In the development of modern drugs, the inclusion of active pharmaceutical ingredients （API） in polymers to form amorphous solid dispersions is commonly used to overcome challenges arising from their low solubility and crystalline properties. However, these solid dispersions are often in a thermodynamically metastable state, which may trigger the recrystallization of APIs, leading to a reduced dissolution rate. To prevent recrystallization or phase separation, reliable drug/polymer system phase diagrams can be established based on the solubility of the drug in the polymer and the glass transition temperature at various drug concentrations of drug/polymer binary mixtures. Nevertheless, measuring drug solubility in polymers poses a challenge due to the high viscosity of polymers. Currently, commonly used models for calculating drug solubility in polymers include the PC-SAFT EOS and Flory-Huggins models, while the Gordon-Taylor equation is used to estimate the glass transition temperature. In our previous study, we applied COSMO-SAC to predict the drug solubility in polymers with reasonable accuracy by using a trimer to generate the required information, i.e., σ-profile, for a polymer. However, this methodology works well for homopolymers and simple copolymers but is not easy to apply to systems containing complex copolymers, such as polymers composed of more than three monomers. Therefore, in this study, we attempt to model copolymers with multiple monomers by generating their σ-profiles from trimers of all their monomers. Then, using COSMO-SAC to simulate the drug solubility in these copolymers. Finally, the Gordon-Taylor model is also used to predict the glass transition temperature for generating phase diagrams of the studied drug-polymer binary systems. |
