futianfan/clinical-trial-outcome-prediction

benchmark dataset and Deep learning method (Hierarchical Interaction Network, HINT) for clinical trial approval probability prediction, published in Cell Patterns 2022.

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Emerging

This project helps predict the success or failure of a drug in clinical trials. It takes in detailed information about a drug candidate, the disease it targets, and the trial's design (eligibility criteria) to output a probability of approval. This tool is valuable for pharmaceutical researchers, R&D strategists, and investment analysts in the healthcare sector.

150 stars. No commits in the last 6 months.

Use this if you need to assess the likelihood of success for a new drug candidate in clinical trials, especially across different phases.

Not ideal if you are looking for a tool for commercial application, as the benchmark dataset and code are restricted to non-commercial use only.

drug-discovery clinical-trials pharmaceutical-R&D biotechnology-investment disease-research
No License Stale 6m No Package No Dependents
Maintenance 2 / 25
Adoption 10 / 25
Maturity 8 / 25
Community 21 / 25

How are scores calculated?

Stars

150

Forks

43

Language

Python

License

Last pushed

Jun 24, 2025

Commits (30d)

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