ArticleDrug design, development and therapy2020
Artificial Neural Network (ANN) Approach to Predict an Optimized pH-Dependent Mesalamine Matrix Tablet.
Article in Drug design, development and therapy, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
What it found
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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
5 citing papers in PubMed, 21 citations in OpenAlex.
- Advancing Pharmaceutical Science with Artificial Neural Networks: A Review on Optimizing Drug Delivery Systems Formulation.Current pharmaceutical design · 2025Review
- Optimization and evaluation of modified release solid dosage forms using artificial neural network.Scientific reports · 2024Article
- State-of-the-Art Review of Artificial Neural Networks to Predict, Characterize and Optimize Pharmaceutical Formulation.Pharmaceutics · 2022Review
- Costunolide Loaded in pH-Responsive Mesoporous Silica Nanoparticles for Increased Stability and an Enhanced Anti-Fibrotic Effect.Pharmaceuticals (Basel, Switzerland) · 2021Article
- Fixed Dose Single Tablet Formulation with Differential Release of Amlodipine Besylate and Simvastatin and Its Pharmacokinetic Profile: QbD and Risk Assessment Approach.Drug design, development and therapy · 2021Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
7 authors at 3 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundSevere bleeding and perforation of the colon and rectum are complications of ulcerative colitis which can be treated by a targeted drug delivery system. PURPOSE: Development of colon-targeted delivery usually involves a complex formulation process and coating steps of pH-sensitive methacrylic acid based Eudragit MATERIALS AND
methodsMesalamine formulations were compressed using wet granulation technique with varying compositions of dicalcium phosphate (DCP) and Eudragit-S100. The developed formulations were characterized for physicochemical and drug release profiles. Infrared studies were carried out to ensure that there was no interaction between active ingredients and excipients. Artificial neural network (ANN) was used for the optimization of final DCP-Eudragit-S100 complex and the experimental data were employed to train a multi-layer perception (MLP) using quick propagation (QP) training algorithm until a satisfactory root mean square error (RMSE) was reached. The ANN-aided optimized formulation was compared with commercially available Masacol
resultsCompressed tablets met the desirability criteria in terms of thickness, hardness, weight variation, friability, and content uniformity, ie, 5.34 mm, 7.7 kg/cm
conclusionDCP-Eudragit-S100 blend was found explicative for mesalamine release without coating in gastric and colonic regions. This combination may provide a better control of ulcerative colitis.
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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.