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feat: Clinical trials lookup function #52

Merged
merged 13 commits into from
Aug 28, 2024
Merged

feat: Clinical trials lookup function #52

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7d9614f
function to grab clinical trials data for drug searches. includes che…
Aug 16, 2024
10ab373
ruff fixes
Aug 16, 2024
eeef142
more ruff fixes
Aug 16, 2024
a45c4f0
ruff format
Aug 16, 2024
c94bdc3
PR fixes for clinical trial data representation
Aug 26, 2024
1a30322
more PR fixes, ruff format
Aug 27, 2024
68eac98
underscore fix
Aug 27, 2024
5864b52
log things
jsstevenson Aug 27, 2024
844eec7
isort
jsstevenson Aug 27, 2024
6d6d069
remove if/else for pediatric?
Aug 28, 2024
bb5f5eb
ruff police
Aug 28, 2024
5542606
Merge branch 'main' into clinical-trials
mcannon068nw Aug 28, 2024
8a8bef9
ruff again
Aug 28, 2024
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2 changes: 2 additions & 0 deletions src/dgipy/__init__.py
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Original file line number Diff line number Diff line change
Expand Up @@ -2,6 +2,7 @@

from .dgidb import (
get_categories,
get_clinical_trials,
get_drug,
get_drug_applications,
get_gene,
Expand All @@ -20,4 +21,5 @@
"get_gene_list",
"get_drug_applications",
"generate_app",
"get_clinical_trials",
]
72 changes: 72 additions & 0 deletions src/dgipy/dgidb.py
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Original file line number Diff line number Diff line change
@@ -1,5 +1,6 @@
"""Provides methods for performing different searches in DGIdb"""

import logging
import os

import pandas as pd
Expand All @@ -9,6 +10,8 @@

import dgipy.queries as queries

_logger = logging.getLogger(__name__)

API_ENDPOINT_URL = os.environ.get("DGIDB_API_URL", "https://dgidb.org/api/graphql")


Expand Down Expand Up @@ -220,6 +223,75 @@ def get_drug_applications(
return result


def get_clinical_trials(
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terms: str | list,
) -> pd.DataFrame: # TODO: Better error handling for new_row?, use_pandas=False
"""Perform a look up for clinical trials data for drug or drugs of interest

:param terms: drug or drugs of interest
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are there any guarantees about what form a given term takes? are we hoping that the label provided by the normalizer is the term used by the trial? I just tried imatinib vs gleevec and I think they are both returning the same results

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In its current state, yes just essentially hoping that the label the normalizer gives is the correct search term to use. I imagine whether or not it works on clinical trials end (i.e. imatinib vs gleevec) will be determined by how well the clinical trial entries themselves have been tagged/organized for the appropriate interventions? The imatinib and gleevec example I can see someone remembering to associate both of those names with any clinical trial just because its so well studied, but maybe this isn't always the case and maybe some aliases will differ in results.

:return: all clinical trials data for drugs of interest in a DataFrame
"""
base_url = "https://clinicaltrials.gov/api/v2/studies?format=json"
rows_list = []

if isinstance(terms, str):
terms = [terms]
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for drug in terms:
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intr_url = f"&query.intr={drug}"
full_uri = base_url + intr_url # TODO: + cond_url + term_url
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what's the story here?

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Also, I wonder if we can reduce the size of the response with the fields param in case there's anything that we aren't using

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https://clinicaltrials.gov/data-api/api#:~:text=Studies-,Studies,-Returns%20data%20of

ClinicalTrials.gov api allows you to submit a bunch of different parameter types through the Studies API. For this implementation, I just had the Studies API as the base URL then wanted to leave room for constructing more specific queries if needed just by adding strings together basically. So intr_url corresponds to the query.intervention parameter, but I could also see a world where someone is also interested in supplying the query.condition parameter, or maybe just additional terms as a parameter.

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For now, just have the intr_url working.

All this being said, if there is a better way to do this I am all open for it

try:
r = requests.get(full_uri, timeout=20)
except requests.exceptions.RequestException as e:
_logger.error("Clinical trials lookup to URL %s failed: %s", full_uri, e)
raise e
if r.status_code == 200:
data = r.json()

for study in data["studies"]:
new_row = {}
new_row["search_term"] = drug
new_row["trial_id"] = study["protocolSection"]["identificationModule"][
"nctId"
]
new_row["brief"] = study["protocolSection"]["identificationModule"][
"briefTitle"
]
new_row["study_type"] = study["protocolSection"]["designModule"][
"studyType"
]
try:
new_row["min_age"] = study["protocolSection"]["eligibilityModule"][
"minimumAge"
]
except:
new_row["min_age"] = None

new_row["age_groups"] = study["protocolSection"]["eligibilityModule"][
"stdAges"
]
new_row["Pediatric?"] = "CHILD" in new_row["age_groups"]

new_row["conditions"] = study["protocolSection"]["conditionsModule"][
"conditions"
]
try:
new_row["interventions"] = study["protocolSection"][
"armsInterventionsModule"
]
except:
new_row["interventions"] = None

rows_list.append(new_row)
else:
_logger.error(
"Received status code %s from request to %s -- returning empty dataframe",
r.status_code,
full_uri,
)
return pd.DataFrame(rows_list)


def _process_drug(results: dict) -> pd.DataFrame:
drug_list = []
concept_list = []
Expand Down
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