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Related Concept Videos

Oral Drug Delivery Systems: Introduction01:23

Oral Drug Delivery Systems: Introduction

Oral drug delivery is the most common route of administration due to its convenience, cost-effectiveness, and high patient compliance. It enables precise formulation to ensure proper drug dosage and bioavailability. The development of oral dosage forms considers drug properties such as solubility, stability, and absorption to optimize therapeutic efficacy.Tablets, capsules, liquids, and chewable formulations enhance drug stability, mask undesirable tastes, and improve patient experience.
Biopharmaceutical Factors Influencing Drug Product Design: Overview01:22

Biopharmaceutical Factors Influencing Drug Product Design: Overview

Rational drug product design integrates knowledge of the drug’s physicochemical properties, formulation components, manufacturing techniques, and intended route of administration. Each factor influences the drug’s performance, including how it is released, absorbed, and eliminated in the body.The physicochemical properties of a drug—such as solubility, stability, and particle size—affect its compatibility with excipients and the choice of dosage form. Excipients, though pharmacologically...
Drug Delivery: Overview01:16

Drug Delivery: Overview

The selection of a drug's delivery route depends upon its physicochemical properties, including lipid or water solubility and ionization, as well as the therapeutic requirement, such as immediate or sustained effect. These routes can be divided into three primary categories: enteral, parenteral, and topical.
Enteral delivery involves administering drugs directly through swallowing, sublingual placement, or buccal application. Orally administered drugs predominantly navigate the gastrointestinal...
Drug Delivery Systems: Different Types01:27

Drug Delivery Systems: Different Types

Conventional oral drug products, termed immediate-release (IR) formulations, are engineered to promptly release their active pharmaceutical ingredient (API) upon ingestion, typically in tablets or capsules. This rapid release often results in swift drug absorption and consequent pharmacodynamic effects, although the timing and intensity can vary depending on the drug's properties. Prodrugs within these formulations require metabolic conversion to activate their pharmacodynamic effects,...
Modified-Release Drug Delivery Systems: Stimuli-Activated01:30

Modified-Release Drug Delivery Systems: Stimuli-Activated

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 called...
Modified-Release Drug Delivery Systems: Overview01:19

Modified-Release Drug Delivery Systems: Overview

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...

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Related Experiment Videos

Integrating artificial intelligence into drug delivery systems: Formulation development and current challenges.

Ines Lucas1, João Sousa1, Carla Vitorino1

  • 1Faculty of Pharmacy, University of Coimbra, Pólo das Ciências da Saúde, Azinhaga de Santa Comba, 3000-548 Coimbra, Portugal; Coimbra Chemistry Centre, Institute of Molecular Sciences - IMS, Department of Chemistry, University of Coimbra 3000-535 Coimbra, Portugal.

European Journal of Pharmaceutics and Biopharmaceutics : Official Journal of Arbeitsgemeinschaft Fur Pharmazeutische Verfahrenstechnik E.V
|June 4, 2026
PubMed
Summary
This summary is machine-generated.

Artificial intelligence (AI) enhances drug delivery by improving formulation design and optimization. AI acts as a decision-support tool, overcoming limitations of traditional methods for more systematic development.

Keywords:
Artificial intelligenceDrug delivery systemsFormulation optimizationMachine learningNanocarriersQuality by design

Related Experiment Videos

Area of Science:

  • Pharmaceutical Sciences
  • Computational Chemistry
  • Biotechnology

Background:

  • Drug delivery research faces challenges in formulation complexity, optimization efficiency, and controlled release.
  • Conventional trial-and-error methods are resource-intensive and struggle with multidimensional variable relationships.
  • Artificial intelligence (AI) offers a systematic and predictive approach to enhance data interpretation and guide formulation development.

Purpose of the Study:

  • To review the application of AI in drug delivery development stages.
  • To discuss machine learning (ML) and deep learning (DL) in formulation design, nanocarrier optimization, and controlled release systems.
  • To assess AI integration within Quality by Design (QbD) frameworks.

Main Methods:

  • Review of AI applications in formulation design, nanocarrier optimization, and smart/controlled release systems.
  • Discussion of ML/DL for pre-formulation, excipient selection, particle engineering, and release-profile optimization.
  • Critical assessment of AI integration within Quality by Design (QbD) frameworks.

Main Results:

  • AI serves as a decision-support tool, not an autonomous system, in drug delivery.
  • AI aids in identifying critical formulation variables and exploring design spaces within QbD.
  • AI-driven methods enhance data interpretation and guide formulation development systematically.

Conclusions:

  • AI is a valuable complementary tool for drug delivery development, offering systematic and predictive capabilities.
  • Challenges in data quality, validation, interpretability, and biological complexity hinder routine pharmaceutical implementation.
  • Addressing these barriers is crucial for reliable, scalable, and regulatory-aligned AI implementation in drug delivery.