Big Analytics in Biopharma: Transforming Care

Rethinking Big Data Strategies in Biopharma: From Platforms to Engagement

Most biopharmaceutical companies have spent the last few years focused on a Big Data strategy targeted at reducing costs and increasing effectiveness. Big Data platforms have been built—but did they, “they” being the patients and physicians with whom we need to engage, come? The impact has been mixed. Today, the approach to addressing core business questions has not changed despite investments in Big Data.

Patient journey and physician segmentation approaches remain largely unchanged at the core. How do we use the tremendous volume of customer data, including attitudes and behaviors, to allow biopharmaceutical companies to deliver effective, personalized, multichannel communications to individual stakeholders? How do we resource differently based on physician treatment patterns? How do we engage differently with physicians and patients to support appropriate diagnosis?

Big Analytics is the answer.


Analytics provides insights and strategies, not just data. Artificial intelligence (AI) platforms offer high-value, cost-effective solutions that maximize the commercial potential of therapeutic innovation by revealing patterns, trends, and associations, especially those relating to human behavior and interactions. Big Analytics that leverages machine learning can take a broad range of claims data and be used to fundamentally change how we approach our two core customer groups—patients and physicians—in a more nuanced and impactful way.

Where are our patients?

The biopharma industry strives to help clinicians recognize and diagnose diseases earlier to expedite the diffusion of therapeutic innovations to improve patient outcomes. Biopharma companies have started to embrace Big Analytics, including AI and predictive analytics, to address these challenges. Analytics can accelerate the process of getting the right therapies to the right patients by using AI-based algorithms that harness the power of patient-centric datasets to produce actionable results.

Patient-finding solutions employ predictive analytics and AI-based algorithms to examine real-world data to identify patients with difficult-to-diagnose diseases, facilitating earlier treatment by clinicians.


Patient-finding solutions that enable patients to be mapped to clinician practices where they are currently being managed for other conditions increase the actionability of the results considerably. The ability to find undiagnosed patients along their disease journey, as well as understand the healthcare professionals (HCPs) who are currently treating them, has the potential to dramatically change physician and patient engagement.

Which Physicians Should We Target?

Certain clinicians impact the decision-making of others in the health care community. Network-mapping analytics identifies not only those highly influential clinicians, but also the strength and breadth of their impact. These clinicians are imperative to the success of your brand. Understanding the existing relationships among HCPs not only optimizes your ability to connect with them, but also maximizes the impact of marketing communications in achieving the desired clinical behavior change. Targeting influential clinicians dramatically impacts prescribing rates among peers within their network. Studies have shown that the recommendation of an influential peer had many times greater impact than that of sales rep interactions with physicians. Big Analytics can identify those clinicians who drive behavior change. These experts have the unique ability to impact the care of patients well beyond their own practices. As network leaders, these highly regarded and influential clinicians measurably impact the clinical behavior of peers within their networks and thus have the power to facilitate the adoption of therapeutic approaches to optimize patient outcomes. With a keen understanding of the power of scientific leadership within a network, AI-based network mapping in combination with natural language processing can identify national key opinion leaders and local clinical leaders. These physicians have the greatest measurable ability to impact clinical behavior. Collectively, these solutions help optimize patient care by facilitating the diffusion of therapeutic innovations.

It is clear that companies with data-driven cultures do more with less.


They’re able to turn data-driven insights into action, which allows them to deliver products and services efficiently and effectively to exceed customer expectations and achieve operational excellence. However, Big Analytics offers much more. Data analytics allows companies to create a strategic road map for innovation and engagement. Analytics does not just provide information, it guides action. “Without data, you’re just another person with an opinion,” noted W. Edwards Deming, a leader within the quality improvement movement. Today, every company has access to Big Data. Without analytics, you are just another company with data.

To see how we use AI to assess key market stakeholders, go to

To see how we identify clinical leaders and map their networks, go to

To see how we use AI and RWD to find undiagnosed patients and their HCPs, go to

To see how we answer your business challenges leveraging Real-World Data

To see how to identify and manage interactions with influential Thought Leaders