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The dataset viewer is not available for this split.
Cannot load the dataset split (in streaming mode) to extract the first rows.
Error code:   StreamingRowsError
Exception:    CastError
Message:      Couldn't cast
trial_id: string
source: string
subsidiary: string
sponsor: string
official_title: string
success_prediction: double
economic_effect: double
duration_prediction: double
success_composite: double
-- schema metadata --
huggingface: '{"info": {"features": {"trial_id": {"dtype": "string", "_ty' + 470
to
{'symbol': Value('string'), 'datetime': Value('string'), 'success_prediction': Value('float64'), 'economic_effect': Value('float64'), 'duration_prediction': Value('float64'), 'success_composite': Value('float64'), 'class': Value('string')}
because column names don't match
Traceback:    Traceback (most recent call last):
                File "/src/services/worker/src/worker/utils.py", line 99, in get_rows_or_raise
                  return get_rows(
                         ^^^^^^^^^
                File "/src/libs/libcommon/src/libcommon/utils.py", line 272, in decorator
                  return func(*args, **kwargs)
                         ^^^^^^^^^^^^^^^^^^^^^
                File "/src/services/worker/src/worker/utils.py", line 77, in get_rows
                  rows_plus_one = list(itertools.islice(ds, rows_max_number + 1))
                                  ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/iterable_dataset.py", line 2431, in __iter__
                  for key, example in ex_iterable:
                                      ^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/iterable_dataset.py", line 1952, in __iter__
                  for key, pa_table in self._iter_arrow():
                                       ^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/iterable_dataset.py", line 1975, in _iter_arrow
                  for key, pa_table in self.ex_iterable._iter_arrow():
                                       ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/iterable_dataset.py", line 503, in _iter_arrow
                  for key, pa_table in iterator:
                                       ^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/iterable_dataset.py", line 350, in _iter_arrow
                  for key, pa_table in self.generate_tables_fn(**gen_kwags):
                                       ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/packaged_modules/parquet/parquet.py", line 106, in _generate_tables
                  yield f"{file_idx}_{batch_idx}", self._cast_table(pa_table)
                                                   ^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/packaged_modules/parquet/parquet.py", line 73, in _cast_table
                  pa_table = table_cast(pa_table, self.info.features.arrow_schema)
                             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/table.py", line 2272, in table_cast
                  return cast_table_to_schema(table, schema)
                         ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/table.py", line 2218, in cast_table_to_schema
                  raise CastError(
              datasets.table.CastError: Couldn't cast
              trial_id: string
              source: string
              subsidiary: string
              sponsor: string
              official_title: string
              success_prediction: double
              economic_effect: double
              duration_prediction: double
              success_composite: double
              -- schema metadata --
              huggingface: '{"info": {"features": {"trial_id": {"dtype": "string", "_ty' + 470
              to
              {'symbol': Value('string'), 'datetime': Value('string'), 'success_prediction': Value('float64'), 'economic_effect': Value('float64'), 'duration_prediction': Value('float64'), 'success_composite': Value('float64'), 'class': Value('string')}
              because column names don't match

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Dataset Information

Weekly clinical trial outcome predictions for global pharmaceutical sponsors, provided by SOV.AI. Each row represents the latest modelled view for a trial on a given week, combining regulatory success probabilities, time-to-completion expectations, and an economic impact index.

  • Coverage: Pharmaceutical and biotech trials with mapped corporate tickers (where available)
  • Update cadence: Weekly (~1,052 new trials evaluated each week)
  • Performance: Ensemble models delivering 87% ROC-AUC on held-out validation data
  • Outputs: Success probability, composite success score, predicted duration (days), economic effect index, and sponsor class

Data Source

Data provided by SOV.AI. Access programmatically via:

import sovai as sov
df_clinical = sov.data("clinical/predict", full_history=True)

Notes

  • Probabilistic scores (success_prediction, success_composite) are in the range 0–1.
  • duration_prediction is expressed in days.
  • economic_effect is a unitless index indicating the magnitude of expected market response.
  • class identifies the sponsor type (e.g., INDUSTRY, NIH, OTHER).
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