A non-linear modelling approach to predict the dissolution profile of extended-release tablets

IF 4.3 3区 医学 Q1 PHARMACOLOGY & PHARMACY European Journal of Pharmaceutical Sciences Pub Date : 2024-11-28 DOI:10.1016/j.ejps.2024.106976
Ana Sofia Lourenço , Tobias Schuster , João Almeida Lopes , Annette Kirsch
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Abstract

This study proposes a novel non-linear modelling approach to predict the dissolution profiles of extended-release tablets, by combining a full-factorial design, curve fitting to the dissolution profiles, and artificial neural networks (ANN), with linear regression methods, partial least squares (PLS) and multiple linear regression (MLR) as benchmarks.
Hydroxypropylmethylcellulose (HPMC) and carboxymethylcellulose (CMC) grades, active pharmaceutical ingredient (API) lubrication, and compression force were chosen as DoE factors. The resulting batches were tested to obtain their corresponding dissolution profile, and a first-order dissolution equation was fitted to each profile. ANN, PLS and MLR were used to model and predict the tablet-specific constant k which then served to simulate dissolution profiles.
This study demonstrates how non-linear methods, specifically ANN, outperform traditional linear models in predicting the complex interactions affecting drug release from extended-release formulations.

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用非线性模型方法预测缓释片的溶出度
本研究提出了一种新的非线性建模方法来预测缓释片的释放度分布,该方法结合全因子设计、曲线拟合和人工神经网络(ANN),以线性回归方法、偏最小二乘法(PLS)和多元线性回归(MLR)为基准。选择羟丙基甲基纤维素(HPMC)和羧甲基纤维素(CMC)等级、活性药物成分(API)、润滑和压缩力作为DoE因素。对所得批次进行测试,得到相应的溶出谱,并对每个谱拟合一阶溶出方程。利用人工神经网络、PLS和MLR模型预测片剂特异性常数k,然后用于模拟溶出曲线。本研究展示了非线性方法,特别是人工神经网络,如何在预测影响缓释制剂药物释放的复杂相互作用方面优于传统的线性模型。
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来源期刊
CiteScore
9.60
自引率
2.20%
发文量
248
审稿时长
50 days
期刊介绍: The journal publishes research articles, review articles and scientific commentaries on all aspects of the pharmaceutical sciences with emphasis on conceptual novelty and scientific quality. The Editors welcome articles in this multidisciplinary field, with a focus on topics relevant for drug discovery and development. More specifically, the Journal publishes reports on medicinal chemistry, pharmacology, drug absorption and metabolism, pharmacokinetics and pharmacodynamics, pharmaceutical and biomedical analysis, drug delivery (including gene delivery), drug targeting, pharmaceutical technology, pharmaceutical biotechnology and clinical drug evaluation. The journal will typically not give priority to manuscripts focusing primarily on organic synthesis, natural products, adaptation of analytical approaches, or discussions pertaining to drug policy making. Scientific commentaries and review articles are generally by invitation only or by consent of the Editors. Proceedings of scientific meetings may be published as special issues or supplements to the Journal.
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