| --- |
| pretty_name: Stocks Weekly PharmaClinicalPredict |
| language: |
| - en |
| license: other |
| task_categories: |
| - time-series-forecasting |
| - tabular-regression |
| tags: |
| - finance |
| - quantitative-trading |
| - backtesting |
| - algorithmic-trading |
| - stocks |
| - equities |
| - weekly |
| size_categories: |
| - 10K<n<100K |
| extra_gated_prompt: "This dataset is free to browse and gated for download. Approval is tied to a Papers With Backtest subscription, which also covers the other datasets in this organisation and the strategy catalogue at https://paperswithbacktest.com. Plans and what each one includes: https://paperswithbacktest.com/pricing" |
| dataset_info: |
| features: |
| - name: trial_id |
| dtype: string |
| - name: source |
| dtype: string |
| - name: subsidiary |
| dtype: string |
| - name: sponsor |
| dtype: string |
| - name: official_title |
| dtype: string |
| - name: success_prediction |
| dtype: float64 |
| - name: economic_effect |
| dtype: float64 |
| - name: duration_prediction |
| dtype: float64 |
| - name: success_composite |
| dtype: float64 |
| splits: |
| - name: train |
| num_examples: 91981 |
| --- |
| |
| # Stocks Weekly PharmaClinicalPredict |
|
|
| Modelled outcome, duration and economic impact for pharmaceutical clinical trials, one row per trial. |
|
|
| **91,981 rows**, 9 columns. Updated by Papers With Backtest. |
|
|
| ## Why It Matters |
|
|
| A biotech's value is a probability-weighted pipeline, and the probabilities are what this dataset estimates: |
|
|
| - **Event odds ahead of the readout:** `success_prediction` is a modelled probability that a trial reaches its endpoint. Priced against the sponsor's market capitalisation, it is a view on how much of the outcome is already in the stock. |
| - **Timing:** `duration_prediction` estimates how long the trial still has to run, which is what decides whether an event is inside or outside a holding period. |
| - **Size of the move:** `economic_effect` scores how material the trial is to the sponsor, separating a phase III lead asset from a minor indication. |
|
|
| ## Load It |
|
|
| **Installation/Upgrade:** |
|
|
| ```bash |
| pip install --upgrade pwb-toolbox |
| ``` |
|
|
| **Load the Dataset:** |
|
|
| ```python |
| from pwb_toolbox import datasets as pwb_ds |
| |
| predictions = pwb_ds.load_dataset("Stocks-Weekly-PharmaClinicalPredict") |
| trials = pwb_ds.load_dataset("Stocks-Weekly-PharmaClinicalTrials") |
| |
| # The predictions carry no ticker; the trial register is what maps them to one. |
| linked = predictions.merge( |
| trials[["trial_id", "symbol", "datetime"]].drop_duplicates("trial_id"), |
| on="trial_id", |
| how="inner", |
| ) |
| ``` |
|
|
| ## Columns |
|
|
| | Column Name | Description | |
| | :--- | :--- | |
| | **trial_id** | Registry identifier for the trial. The join key to `Stocks-Weekly-PharmaClinicalTrials`. | |
| | **source** | Registry the trial was read from. | |
| | **sponsor** | Sponsoring organisation. | |
| | **subsidiary** | Subsidiary running the trial, where it differs from the sponsor. | |
| | **official_title** | Registered title of the trial. | |
| | **success_prediction** | Modelled probability, between 0 and 1, that the trial meets its endpoint. | |
| | **success_composite** | Composite score combining the success model with trial characteristics. | |
| | **duration_prediction** | Modelled remaining duration, in days. | |
| | **economic_effect** | Unitless index of how material the outcome is to the sponsor. | |
|
|
| ## What This Data Does Not Cover |
|
|
| **There is no ticker and no date column.** The file is one row per trial, keyed by `trial_id`, and it carries neither `symbol` nor `datetime`. Mapping a prediction to a listed company means joining `Stocks-Weekly-PharmaClinicalTrials`, which holds both. Anything that needs a point-in-time view has to take its timestamps from that side too. |
|
|
| ## Access |
|
|
| Browsing the card and the schema is open to anyone. Downloading the files needs an approved request, tied to a subscription: [what each plan includes](https://paperswithbacktest.com/pricing). The same subscription covers the other datasets in this organisation. |
|
|
| ## Elsewhere |
|
|
| - [Dataset page and coverage charts](https://paperswithbacktest.com/datasets/stocks-weekly-pharmaclinicalpredict) |
| - [The strategy catalogue](https://paperswithbacktest.com/strategies), 3,806 papers and 4,837 replicated strategies |
| - [`pwb-toolbox`](https://github.com/paperswithbacktest/pwb-toolbox), the loader used in the snippet above |
| - [`awesome-systematic-trading`](https://github.com/paperswithbacktest/awesome-systematic-trading), the replicated strategies with their measured Sharpe |
| - [Every dataset in this organisation](https://huggingface.co/datasets/paperswithbacktest) |
|
|
| Papers With Backtest publishes 32 datasets on the Hub and codes the papers that use them. Every strategy in the catalogue is run over its own full history before it is published, which is where the numbers above come from. |
|
|
