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Factors Influencing Drug Absorption: Pharmaceutical Parameters01:28

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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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Various dissolution theories provide insight into the factors that influence the dissolution rate. Danckwerts' Model suggests that turbulence, rather than a stagnant layer, characterizes the dissolution medium at the solid-liquid interface. In this model, the agitated solvent contains macroscopic packets that move to the interface via eddy currents, facilitating the absorption and delivery of the drug to the bulk solution. The regular replenishment of solvent packets maintains the...
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Dissolution, the process by which drug particles dissolve in a solvent, is explained by the diffusion layer model, a theoretical framework that simulates the absorption of oral drugs and allows us to analyze experimental data.
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Various dissolution methods are utilized to assess a drug’s dissolution rate, including the flow-through cell, paddle-over-disk, cylinder, and reciprocating disk methods.The flow-through cell apparatus (USP (United States Pharmacopeia) method 4) comprises a reservoir for the dissolution medium and a pump that propels the medium through the cell containing the test sample. This method is crucial for assessing modified-release dosage forms with minimally soluble active ingredients,...
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Compendial dissolution methods are standardized procedures defined by pharmacopeias to evaluate the rate at which a drug dissolves in a specific medium. These methods ensure batch-to-batch consistency, enable quality control, and support the prediction of drug bioavailability. They are critical for both immediate and modified-release drug products.The apparatuses used for dissolution testing differ in their design and mechanical function, but all aim to simulate the physiological environment of...
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Development of a Multivariate Predictive Dissolution Model for Tablets Coated with Cellulose Ester Blends.

Eman M Mohamed1,2, Tahir Khuroo1, Hamideh Afrooz1

  • 1Irma Lerma Rangel College of Pharmacy, Texas A&M Health Science Center, Texas A&M University, College Station, TX 77843, USA.

Pharmaceuticals (Basel, Switzerland)
|October 20, 2020
PubMed
Summary
This summary is machine-generated.

This study developed predictive models for tablet dissolution using cellulose ester coatings. Both design of experiment and chemometric approaches accurately predicted drug release profiles for coated tablets.

Keywords:
cellaburatecellulose acetate butyratediclofenacdissolutionhyperspectroscopymultivariate

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Area of Science:

  • Pharmaceutical Sciences
  • Materials Science

Background:

  • Predictive dissolution modeling is crucial for optimizing drug delivery systems.
  • Cellulose acetate butyrate (CAB) and cellulose acetate phthalate (C-A-P) are widely used coating materials.

Purpose of the Study:

  • To develop predictive dissolution models for diclofenac sodium tablets coated with CAB 171-15 and C-A-P blends.
  • To evaluate the efficacy of design of experiment (DoE) and chemometric approaches in predicting drug release.

Main Methods:

  • Utilized a full factorial design with coating weight gain and CAB 171-15 percentage as independent variables.
  • Monitored dissolution at 1, 8, and 24 hours as responses.
  • Employed near-infrared (NIR) spectroscopy and partial least square regression (PLSR) for chemometric modeling.

Main Results:

  • Both DoE and PLSR models demonstrated significant correlations between actual and predicted dissolution values (R² > 0.91).
  • Coating weight gain and CAB 171-15 percentage significantly impacted drug release profiles.
  • Predicted dissolution values closely matched actual values for independent samples.

Conclusions:

  • Predictive dissolution models for cellulose ester-coated tablets can be successfully developed using DoE and chemometric methods.
  • These approaches offer a reliable means to forecast drug release, aiding in formulation development and quality control.