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  • JupitR
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PROJECT JupitR

An advanced intelligence engine designed to model how a drug will perform in HUMAN TRIALS so that biopharmaceutical companies can make early rapid informed decisions.

FAQs

JupitR is

In Silico

Simulations can be done EARLY and are agnostic to drug and receptor type. 

AI-enhanced

Artificial Intelligence interprets the mathematical output into a biological context that clients can use instantly.

Rapid

 An average simulation takes 8 minutes. Full analysis and reports are available to clients in less than 1 hour.

How does JupitR produce rapid, usable intelligence?

Molecule Intake

JupitR is able to work with any ligand .sdf file (2D or 3D) or even parse from SMILES / InCHIKey

Curated Receptor Field

JupitR uses curated receptor batches to simulate a continuous quantum field system

Data Enrichment

JupitR enriches all uploaded data via OmnigeniQ’s

proprietary quantum biophysics protocol

Frequently Asked Questions

Please reach us at info@omnigeniq.com if you cannot find an answer to your question.

 JupitR predicts whether drug candidates will succeed or fail in human trials by simulating how molecules interact with human biology—capturing quantum charge redistribution, receptor harmonics, solvent behavior, and aggregation risk that traditional docking and AI methods miss


 Yes. JupitR is operational and has already been used to analyze many drug. It runs via custom code modules and validated ligand–receptor datasets 


 Biopharma, biotech, and translational researchers looking to prioritize clinical candidates, reduce late-stage attrition, and flag off-target risks early. 


 Future versions will expand into companion diagnostics, synthetic pathway prediction, and biomarker stratification to support full pipeline decision-making 


 It calculates receptor–ligand field harmonics using the Hadron UVE engine: a physics-based model that runs a fixed sequence of quantum and biophysical corrections to simulate biologically relevant outcomes 


Because JupitR is built from a proprietary field-theoretic approach—focused on waveform collapse- not traditional docking or black-box machine learning. It integrates physics, biology, and chemistry in a unique locked-sequence engine 


AI often learns statistical correlations. JupitR simulates mechanistic causation. Where AI may guess, JupitR models how and why biological effects occur, using deterministic or adaptive UVE scoring modes 


 Yes. The UVE framework, harmonic scoring logic, and the receptor prioritization algorithm are protected via trade secrets and controlled dissemination. Future filings may include patents on derivative modules. 


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T: 1800 329 157 | E: info@omnigeniq.com

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