WeChat Mini Program
Old Version Features

The Development of an Innovative Method to Improve the Dissolution Performance of Rivaroxaban

HELIYON(2024)

Department of Pharmaceutical Technology and Biopharmacy

Cited 0|Views2
Abstract
Recent advancements in the formulation of solid dosage forms involving active ingredientcyclodextrin complexes have garnered considerable attention in pharmaceutical research. While previous studies predominantly focused on incorporating these complexes into solid states, issues regarding incomplete inclusion prompted the exploration of novel methods. In this study, we aimed to develop an innovative approach to integrate liquid-state drug-cyclodextrin inclusion complexes into solid dosage forms. Our investigation centered on rivaroxaban, a hydrophobic compound practically insoluble in water, included in hydroxypropyl-beta-cyclodextrin at a 1:1 M ratio, and maintained in a liquid state. To enhance viscosity, hydroxypropyl-cellulose (2 % w/w) was introduced, and the resulting dispersion was sprayed onto the surface of cellulose pellets (CELLETS (R) 780) (R) 780) using a Caleva Mini Coater. The process parameters were meticulously controlled, with atomization air pressure set at 1.1 atm and a fluidizing airflow maintained at 35-45 m3/h. 3 /h. Characterization of the coated cellets, alongside raw materials, was conducted using Fourier Transform Infrared Spectroscopy (FTIR), X-ray diffraction (XRD), scanning electron microscopy (SEM), and differential scanning calorimetry (DSC) analyses. Physicochemical evaluations affirmed the successful incorporation of rivaroxaban into hydroxypropyl-beta-cyclodextrin, with the final cellets demonstrating excellent flowability, compressibility, and adequate hardness. Quantitative analysis via the HPLC-DAD method confirmed a drug loading of 10 mg rivaroxaban/ 750 mg coated cellets. In vitro dissolution studies were performed in two distinct media: 0.022 M sodium acetate buffer pH 4.5 with 0.2 % sodium dodecyl sulfate (mirroring compendial conditions for 10 mg rivaroxaban tablets), and 0.05 M phosphate buffer pH 6.8 without surfactants, compared to reference capsules and conventional tablet formulations. The experimental capsules exhibited similar release profiles to the commercial product, Xarelto (R) (R) 10 mg, with enhanced dissolution rates observed within the initial 10 min. This research presents a significant advancement in the development of solid dosage forms incorporating liquid-state drug-cyclodextrin inclusion complexes, offering a promising avenue for improving drug delivery and bioavailability.
More
Translated text
Key words
Inclusion complexes,Rivaroxaban,Hydroxypropyl-beta-cyclodextrin,Drug release,Dissolution rate,Solid dosage forms
求助PDF
上传PDF
Bibtex
AI Read Science
AI Summary
AI Summary is the key point extracted automatically understanding the full text of the paper, including the background, methods, results, conclusions, icons and other key content, so that you can get the outline of the paper at a glance.
Example
Background
Key content
Introduction
Methods
Results
Related work
Fund
Key content
  • Pretraining has recently greatly promoted the development of natural language processing (NLP)
  • We show that M6 outperforms the baselines in multimodal downstream tasks, and the large M6 with 10 parameters can reach a better performance
  • We propose a method called M6 that is able to process information of multiple modalities and perform both single-modal and cross-modal understanding and generation
  • The model is scaled to large model with 10 billion parameters with sophisticated deployment, and the 10 -parameter M6-large is the largest pretrained model in Chinese
  • Experimental results show that our proposed M6 outperforms the baseline in a number of downstream tasks concerning both single modality and multiple modalities We will continue the pretraining of extremely large models by increasing data to explore the limit of its performance
Upload PDF to Generate Summary
Must-Reading Tree
Example
Generate MRT to find the research sequence of this paper
Data Disclaimer
The page data are from open Internet sources, cooperative publishers and automatic analysis results through AI technology. We do not make any commitments and guarantees for the validity, accuracy, correctness, reliability, completeness and timeliness of the page data. If you have any questions, please contact us by email: report@aminer.cn
Chat Paper
Summary is being generated by the instructions you defined