ArticleJournal of cheminformatics2018
ADMETlab: a platform for systematic ADMET evaluation based on a comprehensively collected ADMET database.
Article in Journal of cheminformatics, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 267 papers, 1 of them a synthesis that pooled it.
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.
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Who cites it
267 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Pooled it
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- Molecular docking, Group Interaction Contribution (GIC), and ADMET studies on the role of surfactants in improving the permeability and solubility of mitoxantrone.Journal of molecular modeling · 2026Article
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- Design and synthesis of novel quinazoline derivatives as KDM6B selective inhibitors.Molecular diversity · 2026Article
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- A putative SGLT-relevant mechanistic perspective on quercetin-3-O-glucoside and rutin in diabetic kidney disease.Diabetology & metabolic syndrome · 2026Review
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- Accurate and task-agnostic modeling of enzymatic reactions through multimodal relational learning.Acta pharmaceutica Sinica. B · 2026Article
- In Silico Discovery of mTOR Inhibitors as Potential Therapeutics for Feline Hypertrophic Cardiomyopathy.Journal of molecular modeling · 2026Article
- DCPM-ADMET: fusion of dual-component pre-trained model and molecular fingerprints to enhance drug ADMET properties prediction.Journal of cheminformatics · 2026Article
- Algicidal Monoterpenes Against Toxin-ProducingToxins · 2026Article
207 more citing papers are in PubMed but not listed here.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
8 authors.
Funding
Abstract
Current pharmaceutical research and development (R&D) is a high-risk investment which is usually faced with some unexpected even disastrous failures in different stages of drug discovery. One main reason for R&D failures is the efficacy and safety deficiencies which are related largely to absorption, distribution, metabolism and excretion (ADME) properties and various toxicities (T). Therefore, rapid ADMET evaluation is urgently needed to minimize failures in the drug discovery process. Here, we developed a web-based platform called ADMETlab for systematic ADMET evaluation of chemicals based on a comprehensively collected ADMET database consisting of 288,967 entries. Four function modules in the platform enable users to conveniently perform six types of drug-likeness analysis (five rules and one prediction model), 31 ADMET endpoints prediction (basic property: 3, absorption: 6, distribution: 3, metabolism: 10, elimination: 2, toxicity: 7), systematic evaluation and database/similarity searching. We believe that this web platform will hopefully facilitate the drug discovery process by enabling early drug-likeness evaluation, rapid ADMET virtual screening or filtering and prioritization of chemical structures. The ADMETlab web platform is designed based on the Django framework in Python, and is freely accessible at http://admet.scbdd.com/ .
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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.