ADMETlab: a platform for systematic ADMET evaluation based on a comprehensively collected ADMET database

By Jie Dong, Ning-Ning Wang, Zhi-Jiang Yao, Lin Zhang, Yan Cheng, Defang Ouyang, Aiping Lu, Dongsheng Cao. Journal of Cheminformatics, 2018

751 citations recorded by the source corpus.

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/.

Subfields: Computational Theory and Mathematics, Pharmacology, Spectroscopy

View Paper: https://www.semanticscholar.org/paper/2484e113884674bc05d836341b1dbb371dd6b2ec

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In Computational Theory and Mathematics

1. Xianhuan Shen
2. Langhui Li
3. M. Tan
4. Zunnan Huang
5. Xiaoqing Wang
6. Ganying Chen
7. Yuquan Zhou
8. Xianyang Liang

Citations in the corpus

• Computational Approaches in Preclinical Studies on Drug Discovery and Development (2020, methodology): “…intestinal absorption rate, oral bioavailability, blood-brain barrier permeation rate, Caco-2 permeability, human intestinal absorption, drug interactions, P-glycoprotein, plasma protein binding rate, CYP metabolic enzymes, and kidney clearance (Pires et al., 2015; Dong et al., 2018) ( Figure 5 ).”