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利用 pH 调节剂改善具有 pH 依赖性溶解度的药物的溶出行为和口服吸收:一种生理现实的质量传递分析。

Improving Dissolution Behavior and Oral Absorption of Drugs with pH-Dependent Solubility Using pH Modifiers: A Physiologically Realistic Mass Transport Analysis.

机构信息

Department of Chemical Engineering, University of Michigan, Ann Arbor, Michigan 48109, United States.

Department of Pharmaceutical Sciences, University of Michigan, Ann Arbor, Michigan 48109, United States.

出版信息

Mol Pharm. 2021 Sep 6;18(9):3326-3341. doi: 10.1021/acs.molpharmaceut.1c00262. Epub 2021 Aug 24.

DOI:10.1021/acs.molpharmaceut.1c00262
PMID:34428047
Abstract

Orally dosed drugs must dissolve in the gastrointestinal (GI) tract before being absorbed through the epithelial cell membrane. drug dissolution depends on the GI tract's physiological conditions such as pH, residence time, luminal buffers, intestinal motility, and transit and drug properties under fed and fasting conditions (Paixão, P. and Bermejo, M. ). The dissolution of an ionizable drug may benefit from manipulating variables such as the environmental pH using pH-modifying agents incorporated into the dosage form. A successful example is the use of such agents for dissolution enhancement of BCS class IIb (high-permeability, low-solubility, and weak base) drugs under high gastric pH due to the disease conditions or by co-administration of acid-reducing agents (, proton pump inhibitors, H2-antagonists, and antacids). This study provides a rational approach for selecting pH modifiers to improve monobasic and dibasic drug compounds' dissolution rate and extent under high-gastric pH dissolution conditions, since the oral absorption of BCS class II drugs can be limited by either the solubility or the dissolution rate depending on the initial dose number. Betaine chloride, fumaric acid, and tartaric acid are examples of promising pH modifiers that can be included in oral dosage forms to enhance the rate and extent of monobasic and dibasic drug formulations. However, selection of a suitable pH modifier is dependent on the drug properties ( solubility and p) and its interplay with the pH modifier p or ps. As an example of this complex interaction, for basic drugs with high p and intrinsic solubility values and large doses, a polyprotic pH modifier can be expected to outperform a monoacid pH modifier. We have developed a hierarchical mass transport model to predict drug dissolution of formulations under varying pH conditions including high gastric pH. This model considers the effect of physical and chemical properties of the drug and pH modifiers such as p, solubility, and particle size distribution. This model also considers the impact of physiological conditions such as stomach emptying rate, stomach acid and buffer secretion, residence time in the GI tract, and aqueous luminal volume on drug dissolution. The predictions from this model are directly applicable to multi-compartment dissolution vessels and are validated by experiments in the gastrointestinal simulator. This model's predictions can serve as a potential data source to predict plasma concentrations for formulations containing pH modifiers administered under the high-gastric pH conditions. This analysis provides an improved formulation design procedure using pH modifiers by minimizing the experimental iterations under both and conditions.

摘要

口服药物必须在胃肠道 (GI) 中溶解,然后才能通过上皮细胞膜被吸收。药物的溶解取决于 GI 道的生理条件,如 pH 值、停留时间、腔内缓冲液、肠动力和进食和禁食条件下的转运(Paixão,P. 和 Bermejo,M.)。可通过在剂型中加入 pH 调节剂来操纵环境 pH 值等变量,从而有利于可电离药物的溶解。一个成功的例子是在高胃 pH 值下,由于疾病条件或同时给予减少胃酸的药物(质子泵抑制剂、H2 拮抗剂和抗酸剂),使用此类试剂来增强 BCS 类 IIb(高通透性、低溶解度和弱碱性)药物的溶解。这项研究为选择 pH 调节剂提供了一种合理的方法,以提高在高胃 pH 值溶解条件下一元和二元药物化合物的溶解速率和程度,因为 BCS 类 II 药物的口服吸收可能受到溶解度或溶解速率的限制,具体取决于初始剂量数。盐酸甜菜碱、富马酸和酒石酸是有前途的 pH 调节剂的示例,可将其包含在口服剂型中以提高一元和二元药物制剂的速率和程度。然而,合适的 pH 调节剂的选择取决于药物的性质(溶解度和 p)及其与 pH 调节剂 p 或 ps 的相互作用。作为这种复杂相互作用的一个例子,对于具有高 p 和内在溶解度值和大剂量的碱性药物,可以预期多质子 pH 调节剂的性能优于单酸 pH 调节剂。我们已经开发了一个分层质量传输模型,以预测在不同 pH 条件下(包括高胃 pH 值)制剂的药物溶解。该模型考虑了药物和 pH 调节剂的物理和化学性质的影响,例如 p、溶解度和粒径分布。该模型还考虑了胃排空速度、胃酸和缓冲液分泌、在胃肠道中的停留时间以及水腔体积等生理条件对药物溶解的影响。该模型的预测可直接应用于多隔室溶解容器,并通过在胃肠道模拟器中的实验进行验证。对于在高胃 pH 值条件下给予 pH 调节剂的制剂,该模型的预测可以作为预测血浆浓度的潜在数据源。该分析通过在和条件下最小化实验迭代次数,为使用 pH 调节剂进行的改进制剂设计过程提供了帮助。

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