yifan1207/Quantum-Based-Machine-Learning-Simulation

A Quantum Computing and Machine Learning Model that accelerates the Drug Research and Development process

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Emerging

This project helps pharmaceutical researchers and drug discovery scientists accelerate the early stages of drug development. It takes information about a target virus and an initial pool of potential molecules, then uses advanced computational methods to generate, filter, and optimize drug candidates. The output is a list of promising, safe, and effective drug candidates ready for pre-clinical trials, significantly shortening the drug discovery timeline.

No commits in the last 6 months.

Use this if you are a drug discovery scientist looking to drastically reduce the time and cost associated with identifying promising drug candidates for a specific viral target.

Not ideal if you are seeking a solution for later-stage clinical trials, manufacturing optimization, or a general-purpose molecular simulation tool not focused on drug candidate identification.

drug-discovery pharmaceutical-research pre-clinical-development molecule-screening drug-candidate-optimization
Stale 6m No Package No Dependents
Maintenance 0 / 25
Adoption 7 / 25
Maturity 16 / 25
Community 14 / 25

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Stars

39

Forks

6

Language

Python

License

CC0-1.0

Last pushed

Nov 07, 2024

Commits (30d)

0

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