Pharmaceutical Sector Undergoes Transformation Using Data Visualization
Pharmaceutical sector suffers from declining success rates and a stagnant pipeline. Data Visualization and the analytics that go with it could be a key element of the cure. After transforming customer-facing functions such as sales and marketing, Data Visualization is extending its reach to other parts of the enterprise. In research and development, for example, Data Visualization technology is being adopted across industries, including pharmaceuticals.
A prominent business research institution estimates that applying Data Visualization strategies to better inform decision making could generate huge revenue volumes annually across the global health-care system, by optimizing innovation, improving the efficiency of research and clinical trials, and building new tools for physicians, consumers, insurers, and regulators to meet the promise of more individualized approaches.
The opportunity of Data Visualization and Analytics 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.
Utilizing its immense potential to the maximum, 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.
Further, patients may be 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, such as genetic information, into account to target specific populations, thereby enabling trials that are smaller, shorter, less expensive, and more powerful.
And finally, Data Visualization and Analytics ensures that 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 events and unnecessary delays for the pharmaceutical sector.
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