Welcome to PyTrial documentation!

PyTrial is an easy-to-use Python package for a series of AI for drug development tasks. Clinical trial is the major step of the drug development process, where phase I, II, III, & IV trials are performed to comprehensively evaluate the efficacy and safety of a new drug.

PyTrial is featured for the following tasks and we are adding more!

Patient outcome prediction: predict the patient outcomes using tabular or sequential patient data.
Trial site selection: pick the best trial sites considering multiple objectives.
Trial outcome prediction: predict the trial outcomes using tabular or sequential trial data.
Patient-trial matching: match trials’ elibility criteria to patients’ EHRs for participant recruitment of clinical trials.
Trial similarity search: encode and retrieve similar clinical trials based on trial design documents.
Trial data simulation: generate synthetic EHRs or trial patient records in table or sequence.

_images/pytrial_tasks.png — The demonstration of clinical trial tasks supported by PyTrial.

If you find this package useful, please consider citing it in your scientific publications:

@article{wang2023pytrial,
  title={PyTrial: A Comprehensive Platform for Artificial Intelligence for Drug Development},
  author={Wang, Zifeng and Theodorou, Brandon and Fu, Tianfan and Xiao, Cao and Sun, Jimeng},
  journal={arXiv preprint arXiv:2306.04018},
  year={2023}
}