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Factors Influencing Drug Absorption: Pharmaceutical Parameters01:28

Factors Influencing Drug Absorption: Pharmaceutical Parameters

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Solid dosage forms such as tablets and capsules undergo rigorous manufacturing processes to ensure stability and effectiveness. Their dissolution and absorption properties are influenced significantly by the choice of excipients (inactive ingredients that serve various roles in the formulation), and the methodology applied during production. The manufacturing parameters, such as compression force and granulation techniques, significantly affect dissolution rates. Elevated compression forces...
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Drug Dissolution: Requirements and Profile Comparison01:14

Drug Dissolution: Requirements and Profile Comparison

340
The acceptance criteria for dissolution profile data are anchored in Q values, representing the percentage of drug dissolved within a specified period. This assessment unfolds in three stages:First Stage: The test passes if all six drug dosage units are equal to or greater than Q plus 5%; otherwise, the sample proceeds to the second stage.Second Stage: The average of twelve units must be equal to or greater than Q, with no unit falling below Q - 15% to pass; if not, it progresses to the final...
340
Factors Affecting Dissolution: Particle Size and Effective Surface Area01:23

Factors Affecting Dissolution: Particle Size and Effective Surface Area

1.8K
Dissolution kinetics, an essential aspect of oral drug delivery, is significantly influenced by the drug's particle size. According to the Noyes-Whitney dissolution model, the dissolution rate correlates directly with the drug's surface area. The larger the surface area, the higher the drug's solubility in water, leading to a faster drug dissolution rate. Reducing particle size increases the effective surface area, enhancing the dissolution process. Micronization and nanosizing are...
1.8K
In Vitro Drug Dissolution: Alternative Methods01:17

In Vitro Drug Dissolution: Alternative Methods

291
Alternative drug dissolution methods include the rotating bottle, intrinsic dissolution test, peristalsis, and the Franz diffusion cell method. The rotating bottle method involves meticulously rotating tightly capped controlled-release beads in a temperature-controlled bath. Periodic decanting of samples allows for residue assay, followed by refilling with fresh medium and testing at various pH levels to emulate the gastrointestinal tract conditions.In contrast, the intrinsic dissolution test...
291
Determination of Multiple Dosing Parameters: Loading and Maintenance Doses01:25

Determination of Multiple Dosing Parameters: Loading and Maintenance Doses

299
A loading dose is an essential pharmacological strategy to rapidly achieve the target plasma drug concentration necessary for an immediate therapeutic effect. This approach is especially critical for drugs characterized by slow absorption or extended half-lives, where delaying therapeutic plasma levels could compromise treatment outcomes. By administering a loading dose, clinicians ensure a prompt onset of drug action, even for agents with complex pharmacokinetic profiles.Achieving steady-state...
299
Determination of Multiple Dosing Parameters: Steady-State, Minimum and Maximum Concentrations01:15

Determination of Multiple Dosing Parameters: Steady-State, Minimum and Maximum Concentrations

301
Gentamicin, an aminoglycoside antibiotic, is commonly administered via intermittent intravenous infusion to treat severe infections. An intermittent one-hour infusion of gentamicin, administered at eight-hour intervals, allows for precise control of plasma drug concentrations, minimizing toxicity while ensuring therapeutic efficacy. Pharmacokinetic principles govern the dynamics of plasma concentrations and can be mathematically described using specific equations.The plasma drug concentration...
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Related Experiment Video

Updated: Feb 28, 2026

Author Spotlight: Process Development for the Spray-Drying of Probiotic Bacteria and Evaluation of the Product Quality
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Author Spotlight: Process Development for the Spray-Drying of Probiotic Bacteria and Evaluation of the Product Quality

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Multi-Objective Spray Drying Process Optimization via BBD-ANN-AGWO Framework: Case of Andrographolide Amorphous Solid

Guangpu Fang1,2, Changhao Jia1,2, Zhiqi Guan1

  • 1College of Pharmaceutical Engineering of Traditional Chinese Medicine, Tianjin University of Traditional Chinese Medicine, Tianjin, 301617, China.

AAPS Pharmscitech
|February 25, 2026
PubMed
Summary
This summary is machine-generated.

This study introduces an intelligent framework for optimizing spray drying processes using artificial neural networks and an adaptive grey wolf optimizer. The method enhances drug formulation development by improving energy efficiency, yield, and drug release.

Keywords:
adaptive grey wolf optimizeramorphous solid dispersionandrographolideartificial neural networkmulti-objective

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Area of Science:

  • Pharmaceutical Sciences
  • Chemical Engineering
  • Computational Chemistry

Background:

  • Spray drying is a critical process in pharmaceutical formulation for creating amorphous solid dispersions.
  • Optimizing multi-objective spray drying parameters (e.g., energy consumption, yield, drug release) is complex.
  • Andrographolide (ADG) amorphous solid dispersion serves as a model system for process optimization.

Purpose of the Study:

  • To establish a multi-objective spray drying process optimization framework.
  • To integrate Box-Behnken design (BBD), artificial neural networks (ANN), and an adaptive grey wolf optimizer (AGWO).
  • To optimize the formulation of andrographolide (ADG) amorphous solid dispersion.

Main Methods:

  • Molecular docking screened potential polymeric carriers for optimal solubilizing performance.
  • In vitro dissolution experiments identified the best-performing carrier.
  • Single-factor and BBD trials evaluated process parameters' effects on key outcomes.
  • A multi-response ANN model was developed and augmented with virtual samples.
  • AGWO performed inverse optimization to determine optimal process parameters.

Main Results:

  • Experimental validation confirmed the model's predictive accuracy.
  • X-ray diffraction (XRD) and Fourier-transform infrared (FT-IR) analyses verified ADG's amorphous transformation and stability.
  • The optimized process demonstrated satisfactory short-term physical stability.
  • The framework successfully balanced multiple optimization objectives.

Conclusions:

  • The proposed framework offers a feasible and intelligent strategy for pharmaceutical formulation development.
  • The integration of BBD, ANN, and AGWO enables efficient multi-objective optimization.
  • This approach can be applied to optimize various pharmaceutical processes for enhanced drug delivery.