ArticleJournal of molecular modeling2022
ADMETboost: a web server for accurate ADMET prediction.
Article in Journal of molecular modeling, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 57 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
57 citing papers in PubMed.
- Soft Computing Approaches toward Density-Based Analysis of Many-Electron Systems.ACS physical chemistry Au · 2026Review
- AI-driven computational drug design: tools, workflow and challenges.RSC advances · 2026Review
- Ensemble Docking, MD, and MM/PBSA Identify Flavonoids as Putative Modulators of EFNB2/B3-Nipah Virus G Interaction.International journal of molecular sciences · 2026Article
- DCPM-ADMET: fusion of dual-component pre-trained model and molecular fingerprints to enhance drug ADMET properties prediction.Journal of cheminformatics · 2026Article
- Integrated computational evaluation of flavonoids from Artemisia campestris L. as FLT3 inhibitors: molecular docking, dynamics, ADMET, DFT, and topological (ELF, LOL) insights.Journal of molecular modeling · 2026Article
- ADMET-vault: an interactive framework for real-time ADMET prediction and molecular optimization.Journal of computer-aided molecular design · 2026Article
- L-Type Voltage-Gated CaMedical sciences (Basel, Switzerland) · 2026Article
- BioMADE: Predicting Torsades de Pointes from molecular structures through biologically informed representations.bioRxiv : the preprint server for biology · 2026Article
- Pharmacokinetic Prediction of Repurposed Drugs for PDAC Using Artificial Intelligence.ACS omega · 2026Article
- Enhancing ADMET property predictions using cross-aligned multimodal attention mechanisms.Molecular diversity · 2026Article
- Article
- A review on integrated machine learning and deep learning driven artificial intelligence models for pharmacokinetics and toxicokinetics predictions, and their application.Drug metabolism and disposition: the biological fate of chemicals · 2026Review
- A machine learning-based pharmacokinetics predictor (EGFR-PROPK) for EGFR-targeting PROTACs.Communications chemistry · 2026Article
- Article
- Article
- Opportunities for machine learning and artificial intelligence in physiologically-based pharmacokinetic (PBPK) modeling.Advanced drug delivery reviews · 2025Review
- Beyond QSARs: Quantitative Knowledge-Activity Relationships (QKARs) for enhanced drug toxicity prediction.Toxicological sciences : an official journal of the Society of Toxicology · 2025Article
- Phenol and chromone compounds forPharmaceutical science advances · 2025Article
- Computational Evaluation of Potential c-Abl Kinase Inhibitors for Parkinson's Disease: QSAR, Docking, Bioisosteric Replacement, ADMET, and MD Simulations.Applied biochemistry and biotechnology · 2025Article
- Exploring Artificial Intelligence's Potential to Enhance Conventional Anticancer Drug Development.Drug development research · 2025Review
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.
Funding
Abstract
The absorption, distribution, metabolism, excretion, and toxicity (ADMET) properties are important in drug discovery as they define efficacy and safety. In this work, we applied an ensemble of features, including fingerprints and descriptors, and a tree-based machine learning model, extreme gradient boosting, for accurate ADMET prediction. Our model performs well in the Therapeutics Data Commons ADMET benchmark group. For 22 tasks, our model is ranked first in 18 tasks and top 3 in 21 tasks. The trained machine learning models are integrated in ADMETboost, a web server that is publicly available at https://ai-druglab.smu.edu/admet .
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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.