Patric Schyman, Ruifeng Liu, Valmik Desai, Anders Wallqvist
Abstract
In drug development, early assessments of pharmacokinetic and toxic properties are important stepping stones to avoid costly and unnecessary failures. Considerable progress has recently been made in the development of computer-based (in silico) models to estimate such properties. Nonetheless, such models can be further improved in terms of their ability to make predictions more rapidly, easily, and with greater reliability. To address this issue, we have used our vNN method to develop 15 absorption, distribution, metabolism, excretion, and toxicity (ADMET) prediction models. These models quickly assess some of the most important properties of potential drug candidates, including their cytotoxicity, mutagenicity, cardiotoxicity, drug-drug interactions, microsomal stability, and likelihood of causing drug-induced liver injury. Here we summarize the ability of each of these models to predict such properties and discuss their overall performance. All of these ADMET models are publically available on our website (https://vnnadmet.bhsai.org/), which also offers the capability of using the vNN method to customize and build new models.
Pharmacology, Toxicology and Pharmaceutical Science
22
13%
Chemistry
20
12%
Biochemistry, Genetics and Molecular Biology
19
11%
Agricultural and Biological Sciences
8
5%
Medicine and Dentistry
6
3%
Other
28
16%
Unknown
69
40%
Attention Score in Context
Attention Score in Context
This research output has an Altmetric Attention Score of 1. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 04 December 2017.
All research outputs
#17,921,555
of 23,009,818 outputs
Outputs from Frontiers in Pharmacology
#7,193
of 16,315 outputs
Outputs of similar age
#306,832
of 439,388 outputs
Outputs of similar age from Frontiers in Pharmacology
#110
of 260 outputs
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So far Altmetric has tracked 16,315 research outputs from this source. They receive a mean Attention Score of 5.0. This one is in the 48th percentile – i.e., 48% of its peers scored the same or lower than it.
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