ArticleBioengineering (Basel, Switzerland)2022
Prediction of the Ibuprofen Loading Capacity of MOFs by Machine Learning.
Article in Bioengineering (Basel, Switzerland), 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 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
9 citing papers in PubMed.
- Biomacromolecule-MOF Composites for Intracellular Delivery: From Empirical Construction to Rational Design and AI-Assisted Screening.Small (Weinheim an der Bergstrasse, Germany) · 2026Review
- Machine learning reshapes the paradigm of nanomedicine research.Acta pharmaceutica Sinica. B · 2026Review
- Engineered Metal-Organic Frameworks (MOFs)-electrospun nanofibers for wound healing: a review.Journal of biological engineering · 2026Review
- Article
- Removal of pharmaceutical pollutants by adsorption onto novel metal-organic frameworks.Environmental science and pollution research international · 2025Review
- Theoretical analysis of MOFs for pharmaceutical applications by using machine learning models to predict loading capacity and cell viability.Scientific reports · 2025Article
- Biomedical Applications of Metal-Organic Frameworks Revisited.Industrial & engineering chemistry research · 2025Review
- Biocompatibility and Effectiveness of Amphotericin B-Loaded Metal-Organic Structures (AmB-ZIF-8) as Dermal Drug Transporters in Experimental Cutaneous Leishmaniasis.Journal of experimental pharmacology · 2025Article
- Functionalization of a porous copper(ii) metal-organic framework and its capacity for loading and delivery of ibuprofen.RSC advances · 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
9 authors.
Funding
Abstract
Metal-organic frameworks (MOFs) have been widely researched as drug delivery systems due to their intrinsic porous structures. Herein, machine learning (ML) technologies were applied for the screening of MOFs with high drug loading capacity. To achieve this, first, a comprehensive dataset was gathered, including 40 data points from more than 100 different publications. The organic linkers, metal ions, and the functional groups, as well as the surface area and the pore volume of the investigated MOFs, were chosen as the model's inputs, and the output was the ibuprofen (IBU) loading capacity. Thereafter, various advanced and powerful machine learning algorithms, such as support vector regression (SVR), random forest (RF), adaptive boosting (AdaBoost), and categorical boosting (CatBoost), were employed to predict the ibuprofen loading capacity of MOFs. The coefficient of determination (R
Indexed as
Identifiers
What Socratic 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 Socratic graph.