應用COSMO-SAC模型預測藥物於高分子 之溶解度;Prediction of Drug Solubility in Polymer with COSMO-SAC model

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Title:	應用COSMO-SAC模型預測藥物於高分子之溶解度;Prediction of Drug Solubility in Polymer with COSMO-SAC model
Authors:	林筱慈;Lin, Xiao-Ci
Contributors:	化學工程與材料工程學系
Keywords:	COSMO-SAC;藥物溶解度;無定型固體分散體;高分子;預測;COSMO-SAC;Drug Solubility;Amorphous Solid Dispersions;Polymer;Prediction
Date:	2024-07-25
Issue Date:	2024-10-09 15:24:49 (UTC+8)
Publisher:	國立中央大學
Abstract:	由於生物製劑分類系統的第二類藥物，其低溶解度性質限制製藥發展，透過添加高分子使其改善變成無定形分散體，但分散體大多為亞穩態，可能使活性藥物傾向再結晶，產生緩慢溶解情形，為了避免再結晶或相分離，藥物/高分子相圖很重要，主要是由溶解度與玻璃轉化溫度線構成，前者可知高分子負載藥物的最大值避免發生過飽和或再結晶，後者在低於其溫度下，使分子遷移率降低，讓藥物的亞穩態無定形狀態可長時間維持穩定。然而，受到高分子的性質影響，使室溫下量測溶解度之實驗相當困難，因此透過熱力學模型估算相平衡數據，常見用於計算藥物溶解度模型為PC-SAFT以及Flory-Huggins，而玻璃轉化溫度估算可用Gordon−Taylor模型。本研究利用量子化學計算軟體(amsterdam modeling suite, AMS)計算19種藥物與22種不同分子量與種類之高分子性質，搭配成59個固液二元相系統，使用COSMO-SAC模型探討藥物於高分子之溶解度，並比較三種COSMO-SAC模型的計算誤差值以找出最佳版本，同時與其他模型進行比較，也針對不同高分子分子量觀察溶解度之變化，此外，探討共聚物PVPVA結構排列組合差異所產生之影響，接著選擇最常使用之Gordon−Taylor模型來計算玻璃轉化溫度，最後繪製負載藥物含量與溫度關係之熱力學相圖，有益於應用藥物設計開發與優化，以及大幅降低實驗時間與成本。 ;As a Class II drug in the Biologics Classification System, its inherently low solubility significantly hampers pharmaceutical development. These challenges can be mitigated by incorporating polymers to create amorphous dispersions. However, these solid dispersions are frequently in a thermodynamically metastable state, which can trigger the reformation of active pharmaceutical ingredients (API) crystals, resulting in a slower dissolution rate. The reliable phase diagram for the studied drug/polymer system provides essential information to prevent recrystallization or phase separation. This diagram contains the drug solubility in polymer and glass transition temperature at different amounts of a drug in a polymer. Nonetheless, conducting solubility measurements at room temperature is challenging due to the high viscosity of the polymer. Currently, commonly used models for calculating drug solubility in polymer include PC-SAFT EOS and Flory-Huggins, while the Gordon-Taylor equation is used to estimate the glass transition temperature. In this study, the accuracy of the COSMO-SAC model in predicting drug solubility in a polymer is investigated. A total of 59 drug-polymer binary systems composed of 19 drugs and 22 polymers with varying molecular weights and types are collected from open literature. Compare the AARD calculations of the three COSMO-SAC models to identify the optimal version and contrast them with other prominent models. Additionally, observe the changes in solubility for different polymer molecular weights and explore the influence of the copolymer PVPVA on variations in structural arrangements. Subsequently, a phase diagram of a studied drug-polymer binary system is generated by the solubility predicted from COSMO-SAC and the glass transition temperature estimated from the commonly used Gordon-Taylor model. It is beneficial to apply drug design, development, and optimization as it significantly reduces the duration and costs associated with experimental procedures.
Appears in Collections:	[National Central University Department of Chemical & Materials Engineering] Electronic Thesis & Dissertation

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