Spice to Synapse — Neuroinformatics Drug Discovery Platform

MODULE 01 — COMPOUND SCREENING ENGINE

Plant → Drug Candidate in Minutes

Enter any medicinal plant or isolated compound. The AI engine returns predicted binding affinities, ADMET drug-likeness, network pharmacology targets, and a translational neuroprotection assessment — the same pipeline built on 84 real animals and Saigon cinnamon data.

15AD/Stroke targets screened

22Pathways mapped

5ADMET parameters

⚡ Cinnamon Reference Set — click to load

Cinnamaldehyde Eugenol Coumarin Caryophyllene Huperzine A ✓ref Garcinia kola Scent leaf

Plant or Compound Name

e.g. "Ashwagandha", "Withaferin A", "Moringa oleifera", "Resveratrol"

Plant Source (optional)

Known Activity / Notes

Any traditional use, known mechanisms, or structural features

Disease Focus

Detail Level

How it works: The AI engine simulates a full neuroinformatics pipeline — compound profiling, molecular docking prediction, ADMET scoring, network target mapping, and translational assessment — the same methodology applied to the Saigon cinnamon dataset (84 animals, 31 biomarkers, 7 groups).

Should this be trusted? This tool generates computational predictions to help prioritize which plants are worth lab investigation — it does not replace wet-lab assays, animal studies, or clinical trials. Compounds in the reference panel are calibrated against the validated Saigon cinnamon dataset; other inputs are estimated from compound-class pharmacology and should be treated as a hypothesis-generation starting point, not a confirmed result. Runs entirely in your browser — no data is transmitted, stored, or shared.

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Enter a plant or compound to begin screening. Use the reference set above to load cinnamon compounds and see how the pipeline works.

MODULE 02 — VIRTUAL PRECLINICAL COHORT GENERATOR

Replace 84 Animals with a Virtual Trial

Generate a complete synthetic preclinical cohort preserving the correlation structure of real biomarker data. Built on the Gaussian copula methodology validated on 84 real animals and 31 biomarkers. The AI generates predicted biomarker profiles for any compound — with no animals needed.

r=0.37Corr-of-corrs fidelity

100%KS marginal test pass

31Biomarkers modelled

📊 Load Cinnamon Study Design

Load real study parameters

Compound / Treatment

Disease Model

Virtual Cohort Size 120

Treatment Groups 7

Effect Size Estimate 0.6

Key Biomarkers to Model

Comma-separated

Reference Drug (positive control)

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Configure your virtual cohort parameters and click Generate. The AI will produce predicted biomarker profiles, correlation matrices, and statistical power estimates — without a single animal.

MODULE 03 — HUMAN TRIAL BRIDGE SIMULATOR

Predict Human Response Before the First Patient

The critical bridge between preclinical animal data and human clinical trials. Input your compound and preclinical profile. The AI simulates allometric scaling, PK/PD translation, population variability, safety signals, and predicted clinical trial outcomes — a robot tester for your drug candidate.

Phase ISafety simulation

Phase IIEfficacy prediction

INDReadiness score

🌿 Load Cinnamaldehyde Profile

Load from cinnamon study

Drug Candidate

Preclinical Effective Dose

Primary Mechanism

Preclinical Efficacy Summary

Target Patient Population

BBB Permeability

Disclaimer: This is a computational simulation to guide research planning. It does not replace formal IND-enabling studies, GLP toxicology, or regulatory review. Outputs are predictions, not clinical data.

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Load the Cinnamaldehyde profile or enter your compound details. The simulator will predict allometric dose scaling, Phase I safety windows, Phase II efficacy probability, and an IND readiness assessment.