Financial services firms have a long history of investing in data analytics and data management capabilities. Given the high average cost per customer to acquire, retain, and grow financial services clients, understanding your customer is essential. Financial services firms must also manage credit, liquidity, and financial instrument risk, which requires complex data analytics.
While financial services firm have developed robust data management capabilities, there are other industries that are data rich. Within these industries, the benefits of data discovery are powerful, but data management capabilities remain basic. Today, there may be no greater opportunity to leverage the power of data and analytics than in life sciences and healthcare.
To understand the potential for data-driven transformation in life sciences, I spoke with Jonathan White, whose extensive history at the intersection of data and the life sciences includes leadership roles as a top executive with responsibility for Research and Development (R&D), technology, and data functions at Pfizer, Haemonetics, IQVIA, and iCarbonX. White observes, “The pharmaceutical industry has entered a golden age era of R&D productivity, with the FDA approving new products at a rate not seen the mid-1990s. It may not be fully appreciated how much this productivity gain has been a result of the emergence and exploitation of ‘Big Data’ in life sciences”.
Research and Development Productivity
According to White, though pharmaceutical executives are vaguely aware of the theoretical benefits of Big Data strategy, few have taken concrete steps to ensure that their firms are taking an enterprise-wide, or even a divisional approach, to data management. White believes that this may be changing however, as industry R&D performance becomes increasingly driven by data-centric expertise and informed leadership. He notes, “Early R&D productivity has been improved by targeting better-characterized molecular targets. The initial turnaround in biopharmaceutical fortunes was spearheaded by companies that specialized in rare diseases, where a single causative gene mutation could be isolated. Robust data and analytics capabilities provide the foundation for effective targeting”. White confirms that rich data and analytics are critical to pharmaceutical companies, as currently half of the world’s top selling drugs are in immune- or oncology-related therapeutic areas.
Real-World Evidence
White also highlights the example of Real-World Evidence (RWE), meaning evidence obtained from real world data (RWD), which comprises observational data obtained through sources such as electronic health records (EHR), medical claims, billing activities, and other patient-generated data. He comments, “There is an explosion of data in Real World Evidence resulting from the expansion of digital prescribing, the implementation of electronic medical records, and the increased use of wearable devices. While the mixed quality of data in most EHR’s has largely precluded their use in clinical trials, the use of data from medical records to design successful clinical trials is well-proven”.
It is White’s belief that data supremacy was the logic behind the recent acquisition of Quintiles, a clinical research organization, by IMS. The current new drug pipeline often requires companies to find patients with rare diseases or very selective entry criteria for the clinical trial. By screening hundreds of millions of medical records, proposed clinical trials can be modeled and validated to ensure that enough qualified patients exist for a trial to succeed.
Clinical Trials
White sees an environment today where researchers are interrogating data to better understand the experience of each patient in designing clinical trials. This is done to ensure that a drug reflects the actual patient experience and that will be tolerated in the daily context of the patients. The use of such data for monitoring the health and experience of patients is already a reality in post-approval clinical registries.
It is White’s observation that these efforts are expanding as confidence in the quality of the data increases. He comments, “In the longer term, a major drug development goal is to reduce the clinical trial control arm through the use of real-world data. This remains some way off for general use, but it is becoming a reality in leading academic centers where good process control and careful data curation has been made a priority”. White believes that we are likely to see leading hospitals surfacing high-quality anonymized patient data for use by biopharmaceutical firms, becoming important centers of innovation in the coming decade. He notes, nonetheless, that these are isolated examples, and no one has yet cracked the code.
In conclusion, White perceives an industry rich with opportunity for data-driven transformation. By way of example, Paul Hudson recently assumed the reins at Sanofi, where his experience in digital strategies and mechanism-based oncology products provides a non-traditional CEO background for a company where internal R&D productivity has struggled to deliver, according to White. Hudson has expressed his intent in building a data-driven digital organization.
It will be an interesting case study to see whether Sanofi can become perhaps the first major pharmaceutical firm to fully embrace and capitalize on a data-driven future.
Randy Bean is an industry thought-leader and author, and CEO of NewVantage Partners, a strategic advisory and management consulting firm which he founded in 2001. He is a contributor to Forbes, Harvard Business Review, MIT Sloan Management Review, and The Wall Street Journal. You can contact him at rbean@newvantage.com and follow him at @RandyBeanNVP.
