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药物物质固有溶出性能的测定。

Determination of Inherent Dissolution Performance of Drug Substances.

作者信息

Sleziona Dominik, Mattusch Amelie, Schaldach Gerhard, Ely David R, Sadowski Gabriele, Thommes Markus

机构信息

TU Dortmund, Laboratory of Solids Process Engineering, Faculty of Biochemical and Chemical Engineering, Emil-Figge-Str. 68, 44227 Dortmund, Germany.

Ivy Tech Community College Lafayette, School of Advanced Manufacturing, Engineering and Applied Science, 3101 S Creasy Ln, Lafayette, IN 47905, USA.

出版信息

Pharmaceutics. 2021 Jan 22;13(2):146. doi: 10.3390/pharmaceutics13020146.

Abstract

The dissolution behavior of novel active pharmaceutical ingredients (API) is a crucial parameter in drug formulation since it frequently affects the drug release. Generally, a distinction is made between surface-reaction- and diffusion-controlled drug release. Therefore, dissolution studies such as the intrinsic dissolution test defined in the pharmacopeia have been performed for many years. In order to overcome the disadvantages of the common intrinsic dissolution test, a new experimental setup was developed within this study. Specifically, a flow channel was designed and tested for measuring the mass transfer from a flat, solid surface dissolving into a fluid flowing over the surface with well-defined flow conditions. A mathematical model was developed that distinguishes between surface-reaction- and diffusion-limited drug release based on experimental data. Three different drugs-benzocaine, theophylline and griseofulvin-were used to investigate the mass flux during dissolution due to surface reaction, diffusion and convection kinetics. This new technique shows potential to be a valuable tool for the identification of formulation strategies.

摘要

新型活性药物成分(API)的溶出行为是药物制剂中的一个关键参数,因为它常常会影响药物释放。一般来说,药物释放可分为表面反应控制型和扩散控制型。因此,诸如药典中定义的固有溶出度试验等溶出度研究已经进行多年。为了克服常规固有溶出度试验的缺点,本研究开发了一种新的实验装置。具体而言,设计并测试了一个流动通道,用于测量在明确的流动条件下,从平坦固体表面溶解到流过该表面的流体中的传质情况。基于实验数据建立了一个数学模型,该模型能够区分表面反应限制型和扩散限制型药物释放。使用三种不同的药物——苯佐卡因、茶碱和灰黄霉素——来研究由于表面反应、扩散和对流动力学导致的溶出过程中的质量通量。这项新技术显示出有望成为确定制剂策略的有价值工具。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/032a/7911123/d508519634a3/pharmaceutics-13-00146-g0A1.jpg

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