How to use Admetica Online

Use Admetica online for open-source ADMET property prediction across small-molecule libraries.

Admetica is an open-source ADMET prediction toolkit from Datagrok for estimating absorption, distribution, metabolism, excretion, and toxicity properties from small-molecule structure. The project packages Chemprop-based predictive models, curated public datasets, comparison notebooks, and a command-line prediction workflow under an MIT license.

On Neurosnap, researchers submit Input Molecules as SMILES, SDF, or CCD entries and choose either all available endpoints or a focused subset grouped by ADMET category. The service is useful for early medicinal-chemistry triage, analog comparison, and library filtering before docking, synthesis, or experimental DMPK testing.

How Admetica Works

Admetica uses molecular graph models from the Chemprop ecosystem to learn structure-property relationships for pharmacokinetic and toxicity endpoints. The available endpoint set covers practical medicinal-chemistry questions such as Caco-2 permeability, lipophilicity, solubility, P-glycoprotein behavior, plasma protein binding, volume of distribution, CYP inhibition and substrate liability, clearance, half-life, hERG risk, and acute toxicity.

The Neurosnap workflow converts each submitted molecule to a validated SMILES representation, runs the selected Admetica models, and returns a single CSV table with readable endpoint names. Selecting only the endpoints relevant to a project can reduce runtime and make result review cleaner, while the all-properties mode is better for broad first-pass screening.

Researchers should treat Admetica predictions as prioritization signals rather than definitive experimental replacements. The most useful interpretation is comparative: identify molecules with potential liabilities, compare analog trends, and decide which candidates deserve deeper modeling or assay follow-up.

What is Neurosnap?

Neurosnap is the leading platform for bioinformatics and computational science focused on expanding access to powerful modeling and simulation tools. Because many state-of-the-art machine learning systems remain complex to install, configure, and scale, Neurosnap offers a clean, browser-based workspace that removes the burden of infrastructure management, dependency conflicts, and command-line tooling.

Built for biologists, chemists, and cross-disciplinary scientists, the platform enables advanced computational workflows without requiring expertise in software engineering or cloud architecture. Researchers can launch analyses through an intuitive interface, connect programmatically through a comprehensive API, and rely on automated resource management to scale workloads efficiently. By taking care of the underlying compute and operational complexity, Neurosnap allows teams to devote their energy to scientific progress and faster iteration. Security and data protection remain foundational principles, with clear safeguards outlined in our Terms of Use and Privacy Policy to ensure your work stays protected.

Advancing Discovery with Admetica on Neurosnap

Using Admetica on Neurosnap could drastically accelerate open-source ADMET screening for small-molecule design and medicinal-chemistry triage.

Broad ADMET coverage: Admetica spans absorption, distribution, metabolism, excretion, and toxicity endpoints in one workflow.
Focused endpoint control: Neurosnap groups model selection by ADMET category so researchers can run broad or targeted screens.
Flexible molecule input: SMILES, SDF, and CCD entries can be screened without local cheminformatics conversion scripts.
Clean tabular output: Predictions are returned as a CSV table with readable endpoint names for ranking, filtering, and downstream analysis.
Open-source basis: The underlying Admetica project provides transparent datasets, models, and notebooks that support reproducible method review.

How to Use Admetica on Neurosnap

To harness the capabilities of Admetica, researchers can follow this streamlined workflow within Neurosnap:

Access Neurosnap: Start by logging in to the Neurosnap website.
Select Tool: From the list of available tools, choose Admetica.
Provide Inputs: Provide all the inputs specified within the submission panel and optionally configure the tool as desired.
Run Tool: Submit the Admetica job and Neurosnap will execute it in the cloud, automatically notifying you as soon as your results are ready.
Review Output: Explore your results through rich visualizations, including figures, plots, and interactive views designed to help you analyze findings with clarity and confidence.

Citations

Please cite the original work when using Admetica in publications or research outputs.

Datagrok. Admetica: Datagrok repository for ADMET property evaluation. GitHub, https://github.com/datagrok-ai/admetica.

Yang K, Swanson K, Jin W, et al. Analyzing Learned Molecular Representations for Property Prediction. Journal of Chemical Information and Modeling. 2019;59(8):3370-3388. https://doi.org/10.1021/acs.jcim.9b00237

Neurosnap Inc. (2022). Neurosnap: An online platform for computational biology and chemistry. Available at: https://neurosnap.ai/

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