薬物-ポリマーの溶解性および混合性の経験的およびハイブリッドモデリングを通じて無形固体分散を進める:イブプロフェンを用いたケース研究
Matheus de Castro1, Ana Sara Cordeiro1, Mingzhong Li1
1Leicester School of Pharmacy, De Montfort University, Leicester LE1 9BH, United Kingdom.
International journal of pharmaceutics: X
|August 21, 2025
まとめ
この研究では,モデリングとDSCを用いて,4つのポリマーでイブプロフェンの溶解性を評価した. KOL17PFは最高の互換性を示し,HPMCASは薬物の負荷が高くても無形固体分散 (ASD) の安定性が限られていた.
科学分野:
- 材料科学
- 医薬品科学
- コンピュータ化学
背景:
- 薬-ポリマーの混合性を予測することは,無形固体分散 (ASD) 製法において極めて重要です.
- 伝統的な溶解性パラメータは,薬物-ポリマーシステムの変数予測を提供します.
- 混合性と安定性を正確に評価するには,高度なモデリング技術が必要です.
研究 の 目的:
- KOLVA64®,KOL17PF®,HPMCAS,およびEudragit® EPOの4つの製薬ポリマーとの溶解性と混合性を調査する.
- 実験データに対する経験的およびハイブリッドモデリングのアプローチのパフォーマンスを比較する.
- 予測された安定性に基づいてイブプロフェンASD製剤に最も適したポリマーを決定する.
主な方法:
- 実験的検証のために差分スキャニングカロメトリー (DSC) を利用した.
- 溶解性パラメータの分析のために伝統的なグループ貢献方法 (Fedors,Hoftyzer-van Krevelen,Just-Breitkreutz) とBagleyプロットを使用した.
- Flory-Huggins (FH) 理論,Kyerematengの経験的アプローチ,およびDSC由来の融点低圧データを組み込んだ混乱連鎖統計関連流体理論 (PC-SAFT) を使用して相図を構築した.
- ゴードン・テイラー方程式とクエイ方程式を用いて,グラス移行温度 (Tg) をモデル化した.
主要な成果:
- すべての試験されたポリマーは溶解性パラメータを使用して混合可能であると予測されたが,予測の精度は異なっていた.
- KOL17PFは最も高いポリマー-API互換性を示し,HPMCASは最低でした.
- PC-SAFTおよびFHモデルは,液体-液体均衡 (LLE) の脱混合の可能性を示唆し,HPMCASベースのASDの薬物の負荷が5%を超える場合に限られた安定性を予測しました.
- KOLVA64®,KOL17PF®,およびEudragit® EPOにより高い薬量 (> 10% w/ w) がより安定していることが判明しました.
結論:
- この研究は,様々な溶解性および混合性予測モデルの強みと限界を強調しています.
- KOL17PFとEudragit® EPOは,薬量が高いイブプロフェンASDの有望な候補として特定されています.
- ASDにおける薬物-ポリマー相互作用の正確な予測のために,調和したモデリングフレームワークが推奨されています.
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