Health / Pharma

How big data can revolutionize pharmaceutical R&D

The big-data opportunity is especially compelling in complex business environments experiencing an explosion in the types and volumes of available data. In the health-care and pharmaceutical industries, data growth is generated from several sources, including the R&D process itself, retailers, patients, and caregivers. Effectively utilizing these data will help pharmaceutical companies better identify new potential drug candidates and develop them into effective, approved and reimbursed medicines more quickly.

Imagine a future where the following is possible:

  • Predictive modeling of biological processes and drugs becomes significantly more sophisticated and widespread. By leveraging the diversity of available molecular and clinical data, predictive modeling could help identify new potential-candidate molecules with a high probability of being successfully developed into drugs that act on biological targets safely and effectively.
  • Patients are identified to enroll in clinical trials based on more sources—for example, social media—than doctors’ visits. Furthermore, the criteria for including patients in a trial could take significantly more factors (for instance, genetic information) into account to target specific populations, thereby enabling trials that are smaller, shorter, less expensive, and more powerful.
  • Trials are monitored in real time to rapidly identify safety or operational signals requiring action to avoid significant and potentially costly issues such as adverse events2 and unnecessary delays.
  • Instead of rigid data silos that are difficult to exploit, data are captured electronically and flow easily between functions, for example, discovery and clinical development, as well as to external partners, for instance, physicians and contract research organizations (CROs). This easy flow is essential for powering the real-time and predictive analytics that generate business value.

That’s the vision. However, many pharmaceutical companies are wary about investing significantly in improving big-data analytical capabilities, partly because there are few examples of peers creating a lot of value from it. However, we believe investment and value creation will grow. The road ahead is indeed challenging, but the big-data opportunity in pharmaceutical R&D is real, and the rewards will be great for companies that succeed.

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