Department of Pharmaceutical Engineering and Technology, Indian Institute of Technology (BHU), Varanasi, 221005, India.
School of Pharmacy, Complutense University, Madrid, Spain.
AAPS PharmSciTech. 2022 Sep 2;23(7):249. doi: 10.1208/s12249-022-02408-4.
Amorphous solid dispersions enhance solubility and oral bioavailability of poorly water-soluble drugs. The escalating number of drugs with poor aqueous solubility, poor dissolution, and poor oral bioavailability is an unresolved problem that requires adequate interventions. This review article highlights recent solubility and bioavailability enhancement advances using amorphous solid dispersions (ASDs). The review also highlights the mechanism of enhanced dissolution and the challenges faced by ASD-based products, such as stability and scale-up. The role of process analytical technology (PAT) supporting continuous manufacturing is highlighted. Accurately predicting interactions between the drug and polymeric carrier requires long experimental screening methods, and this is a space where computational tools hold significant potential. Recent advancements in data science, computational tools, and easy access to high-end computation power are set to accelerate ASD-based research. Hence, particular emphasis has been given to molecular modeling techniques that can address some of the unsolved questions related to ASDs. With the advancement in PAT tools and artificial intelligence, there is an increasing interest in the continuous manufacturing of pharmaceuticals. ASDs are a suitable option for continuous manufacturing, as production of a drug product from an ASD by direct compression is a reality, where the addition of multiple excipients is easy to avoid. Significant attention is necessary for ongoing clinical studies based on ASDs, which is paving the way for the approval of many new ASDs and their introduction into the market.
无定形固体分散体提高了水溶性差、溶解差和口服生物利用度差的药物的溶解度和口服生物利用度。越来越多的水溶性差、溶解差和口服生物利用度差的药物是一个未解决的问题，需要进行充分的干预。本文重点介绍了利用无定形固体分散体（ASD）提高溶解度和生物利用度的最新进展。本文还重点介绍了提高溶解度的机制以及基于 ASD 的产品所面临的挑战，如稳定性和放大问题。过程分析技术（PAT）支持连续制造的作用也得到了强调。准确预测药物与聚合物载体之间的相互作用需要长期的实验筛选方法，而计算工具在这方面具有很大的潜力。数据科学、计算工具的最新进展以及获得高端计算能力的便利性，都将加速基于 ASD 的研究。因此，特别强调了可以解决与 ASD 相关的一些未解决问题的分子建模技术。随着 PAT 工具和人工智能的进步，人们对制药的连续制造越来越感兴趣。ASD 是连续制造的一个合适选择，因为直接压缩 ASD 生产药物产品是一种现实，很容易避免添加多种赋形剂。正在进行的基于 ASD 的临床研究需要引起高度重视，这为许多新的 ASD 的批准及其进入市场铺平了道路。
