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Case Studies

Expanding patient access to a proven therapeutic by leveraging diverse data collections in the Global Data Partner Network

Expanding patient access to a proven therapeutic by leveraging diverse data collections in the Global Data Partner Network


A leading biotech’s approved therapy has shown that optimal treatment path is associated with improved prognosis, but only a limited patient group has access. A registry-based study was undertaken with the goal of expanding the applicable patient population and identifying a novel approach for patient identification / stratification. This study was to be carried out in one country but needed to be verified in another population.


  • In order to meet research goals, drug developers required a large amount of clinical and genomic data (>100k patients) to re-estimate the patient population and identify treatment-eligible subsets.
  • Drug developers did not have access to this level of data and would need to develop a database from scratch, incurring significant time and cost
  • The drug developers also wished to include patient level genetic data to increase study novelty


Data Feasibility:

    • BC Platforms worked with the client to assess the availability of the required set of clinical data across BC Platforms’ Global Data Partner Network
    • Three key sources were identified: two university hospitals and one biobank across two European studies. Hospitals (n=112 471) were targeted as the initial study location; the biobank was targeted for validation of results and as a key source for novel patient stratification (n=10 051)
    • BC Platforms served as a trusted broker and ensured data access that would not have been granted to the drug developer independently

Secure Patient Level Analysis:

    • BC Platform’s researchers accessed biobank data and conducted individual site level analysis via BC Platforms’ unique technology and federated model. This approach eliminated regulatory patient data use risk to the biopharma client, as data was not transferred from original premises
    • Descriptive statistics were applied to the data based on researcher questions


Expanded Patient Pool & Label: Real-world patients at greatest risk and most eligible for targeted treatment were identified and the data used to support label expansion discussion with health authorities

Improved Patient Care: Polygenomic Risk Score created and shown to support patient identification and personalized  treatment path for the given drug

Disease Insights: Client was able to clarify incidence and prevalence of the disease and patient characteristics (e.g., comorbidities, medications, treatment paths)