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Related Concept Videos

Modified-Release Drug Delivery Systems: Classification01:23

Modified-Release Drug Delivery Systems: Classification

315
Modified-release drug delivery systems improve drug efficacy and minimize side effects by controlling the rate and location of drug release. These systems fall into three categories: rate-programmed, stimuli-activated, and site-targeted.Rate-programmed systems release drugs at a predetermined rate, maintaining consistent therapeutic levels and reducing fluctuations that could lead to toxicity or subtherapeutic effects. These systems use polymeric matrices, reservoir-based designs, or osmotic...
315
Modified-Release Drug Delivery Systems: Stimuli-Activated01:30

Modified-Release Drug Delivery Systems: Stimuli-Activated

177
Stimuli-activated drug delivery systems are designed to release drugs in response to specific physical, chemical, or biological stimuli. These systems often utilize hydrogels—three-dimensional, hydrophilic polymer networks capable of swelling in aqueous environments and retaining significant fluid volumes. Upon exposure to particular stimuli, these hydrogels undergo structural transitions that allow the embedded drug to be released. Due to this adaptive behavior, such systems are also...
177
Modified-Release Drug Delivery Systems: Rate-Programmed II01:19

Modified-Release Drug Delivery Systems: Rate-Programmed II

137
Rate-programmed drug delivery systems release drugs in a controlled manner to maintain therapeutic levels. Three main designs include reservoir, matrix, and hybrid systems.Reservoir systems consist of a drug core enclosed within a membrane that controls drug release. In non-swelling reservoir systems, polymers like ethyl cellulose or polymethacrylates are used. These do not hydrate in aqueous media and control release through membrane thickness, porosity, or insolubility. This type includes...
137
Modified-Release Drug Delivery Systems: Rate-Programmed I01:22

Modified-Release Drug Delivery Systems: Rate-Programmed I

172
Rate-programmed drug delivery systems (DDS) are designed to release drugs at specific, controlled rates to maintain consistent therapeutic levels. These systems are categorized based on their release mechanisms, including dissolution-controlled DDS, diffusion-controlled DDS, and combined dissolution-diffusion-controlled DDS.In dissolution-controlled DDS, the release rate depends on the slow dissolution of the drug itself or the surrounding matrix. Drugs with inherently slow dissolution rates,...
172
Modified-Release Drug Delivery Systems: Overview01:19

Modified-Release Drug Delivery Systems: Overview

236
Modified-release dosage forms are designed to address the limitations of drugs with short biological half-lives. These forms maintain stable therapeutic drug concentrations over extended periods, reducing the need for frequent dosing. A consistent drug level helps minimize peak-trough fluctuations, which can reduce adverse effects, lower the risk of drug resistance, and improve overall treatment effectiveness.One common type of modified-release form is the extended-release (ER) formulation. ER...
236
Modified-Release Drug Delivery Systems: Drug Release Characteristics01:22

Modified-Release Drug Delivery Systems: Drug Release Characteristics

257
Drug release from modified-release dosage forms is designed to achieve specific therapeutic effects by controlling the rate and extent of drug release. The classification of these drug release systems is based on key pharmacokinetic assumptions: drug disposition follows first-order kinetics, drug release is the rate-limiting step in absorption, and the released drug is rapidly and completely absorbed.There are four major models of drug release patterns. The first model is the slow zero-order...
257

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Artificial neural networks in evaluation and optimization of modified release solid dosage forms.

Svetlana Ibrić, Jelena Djuriš, Jelena Parojčić

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    |December 5, 2013
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    Artificial Neural Networks (ANN) are increasingly used in pharmaceutical development for optimizing modified-release drug products. This review covers ANN applications in modeling production, drug release, and stability, enhancing drug formulation.

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    Area of Science:

    • Pharmaceutical Sciences
    • Computational Chemistry
    • Drug Delivery Systems

    Background:

    • Quality by Design (QbD) necessitates statistical tools like Design of Experiments (DoE) in pharmaceutical development.
    • Response Surface Methodology (RSM) is a common DoE technique, but machine learning, particularly Artificial Neural Networks (ANN), is gaining prominence.
    • ANNs have been applied to modified-release products for approximately 20 years.

    Purpose of the Study:

    • To review the application of Artificial Neural Networks (ANN) in the evaluation and optimization of modified-release solid dosage forms.
    • To highlight the role of ANNs in modeling key aspects of modified-release product development.

    Main Methods:

    • Literature review of studies employing Artificial Neural Networks (ANN) in pharmaceutical formulation.
    • Analysis of ANN applications in modeling production, drug release profiles, and drug stability.
    • Focus on modified-release solid dosage forms.

    Main Results:

    • ANNs are effective tools for modeling complex relationships in pharmaceutical development.
    • Applications include optimization of drug release kinetics and prediction of product stability.
    • ANNs complement traditional DoE methods like RSM.

    Conclusions:

    • Artificial Neural Networks (ANN) are valuable for optimizing modified-release solid dosage forms.
    • ANNs facilitate enhanced modeling of drug product performance and stability.
    • The integration of ANNs represents a significant advancement in pharmaceutical development strategies.