| --- |
| language: |
| - en |
| license: mit |
| pretty_name: Pharma Reimbursement Path Optimization Forecasting v0.1 |
| dataset_name: pharma-reimbursement-path-optimization-forecasting-v0.1 |
| tags: |
| - clarusc64 |
| - pharma |
| - market-access |
| - payer |
| - HTA |
| - RWE |
| task_categories: |
| - tabular-classification |
| - tabular-regression |
| size_categories: |
| - n<1K |
| configs: |
| - config_name: default |
| data_files: |
| - split: train |
| path: data/train.csv |
| - split: test |
| path: data/test.csv |
| --- |
| |
| What this dataset tests |
|
|
| Whether a system can forecast a robust reimbursement pathway |
| from payer pressure, evidence constraints, and pricing limits. |
|
|
| Required outputs |
|
|
| - optimal_endpoint_mix |
| - RWE_generation_plan |
| - pricing_stability_zone |
| - access_probability |
| - restriction_burden_forecast |
| - coverage_stability_horizon |
| - confidence_score |
|
|
| Use case |
|
|
| Phase III design for reimbursement success. |
| RWE planning that closes payer gaps. |
| Pricing posture and restriction forecasting. |
|
|
