ArticleAAPS PharmSciTech2023
Development of an Image-based Method for Tablet Microstructure Description and Its Correlation with API Release Rate.
Article in AAPS PharmSciTech, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
4 citing papers in PubMed, 5 citations in OpenAlex.
- Generative Model Enhanced X-ray Computed Tomography Imaging for Pharmaceutical Powder Microstructure Reconstruction and Evaluation.AAPS PharmSciTech · 2025Article
- Commentary and Review on Prospective Prediction of Bioequivalence of Oral Dosage Forms using Compendial Dissolution Testing and PBPK Modeling.The AAPS journal · 2025Review
- The Increase in the Plasticity of Microcrystalline Cellulose Spheres' When Loaded with a Plasticizer.Pharmaceutics · 2024Article
- Antibacterial and Antioxidant Study of New Pharmaceutical Formulation of Didecyldimethylammonium Bromide Via Pharmaceutical Deep Eutectic Solvents (PDESs) Principle.AAPS PharmSciTech · 2024Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors at 1 institution in 1 country.
Funding
Abstract
The performance of a pharmaceutical formulation, such as the drug (API) release rate, is significantly influenced by the properties of the materials used, the composition of the final product and the tablet compression process parameters. However, in some cases, the knowledge of these input parameters does not necessarily provide a reliable description or prediction of tablet performance. Therefore, the knowledge of tablet microstructure is desirable to understand such formulations. Commonly used analytical techniques, such as X-ray tomography and intrusion mercury porosimetry, are not widely used in pharmaceutical companies due to their price and/or toxicity, and therefore, efforts are made to develop a tool for fast and easy microstructure description. In this work, we have developed an image-based method for microstructure description and applied it to a model system consisting of ibuprofen and CaHPO
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.