What was your inspiration for going into the life sciences industry?
I was raised in a family of physicians and life sciences PhD’s. Life sciences was part of our dinner conversations—sometimes not the most appetizing! But I really got catalyzed and deeply embedded in this industry through the work I did with large health provider systems beginning in the mid-1990’s.
My respect, admiration and motivation all deepened when I saw the level of commitment displayed by the clinicians and healthcare professionals working hand-in-hand every day to improve patient outcomes. I was hooked when I realized the impact the industry could have on the life of a patient and his or her family. There just isn’t another industry like this one.
What did you do prior to joining Accenture?
I have been involved in Life Sciences now for almost 25 years. Prior to joining Accenture in January 2012, I was a co-founder of two diagnostics and two therapeutics companies focused on oncology, diabetes and Parkinson’s. I was also the global COO and senior vice president for strategy at Novartis Institutes for BioMedical Research — the R&D operating division of Novartis. Prior to that, I was a Life Sciences partner at McKinsey.
Tell us about your role at Accenture.
I am a managing director in Accenture’s Boston office and the global lead for Accenture’s Predictive Health Intelligence practice. As the lead for Predictive Health Intelligence, I am working with several of the largest global pharmaceutical companies to help them evolve their business models to become evidence-based and focused on delivering improved patient outcomes in affordable, measurable ways.
In this capacity, we are bringing our pharmaceutical and medical device companies together with healthcare providers, payers, leading clinical data and analytics companies, cloud-enabled data and technology companies, as well as numerous services companies to look at the full patient experience from all angles. This level of collaboration enables us to aggregate and analyze data collectively, creating new insights from disparate data sources to illuminate how therapeutics, devices and diagnostics can bring more value to patients and health systems around the world.
What is the most exciting change you have seen in the industry over the last 5 years?
Today, I can sit in a meeting with biomedical researchers and clinicians, engaged in questions about strategy, the current standard of care, or what actions clinicians take for specific patient populations and we can get to an answer for these types of complex questions in almost real-time.
We also now have the technologies—e.g., big data infrastructure such as hadoop—and access to a variety of data sources such as electronic medical records that enable us to model and analyze patient information at scale and with incredible immediacy.
What about over the last year?
We are now creating insights into what therapeutic approaches work best and for whom. We can use human and machine-driven analytics to predict which patients will respond to a new therapy, or those who may fail to respond. We can accelerate our understanding of why they are responding. We can see the combinations of approaches that work best for one patient but not another.
The scale of the data we can access today is twice what it was last year alone. And we are just beginning to scratch the surface. Within three to five years we’ll be able to answer critical questions about clinical research at a ‘population’ level versus at a ‘sampled trial’ scale. Soon, we will be able to measure and improve the value realized for a therapy on a precise population in a predictable and accelerating manner.
As pharma business models evolve from being volume focused to patient/value driven—what do you see as the biggest barriers for the industry to overcome?
Today, life sciences companies are ‘stove-piped’ or ‘hyper-functional’ in their operating models. Data is captured and often marooned within these silos. The future of value management and delivery is a ‘team sport.’ It requires cross-enterprise and cross-discipline analytics and collaborations.
The first big challenge is to break down these silos and create collaborative organizations where data and analytics are shared and integrated across all functional areas. The second challenge is to break down the silos externally across the health ecosystem—between payers, providers, pharma companies, and so forth—to align around the common goal of delivering an improved patient outcome in an economically viable way that has clear benefit for all parties.
What areas will the consumer be most surprised to see “big data” impacting them directly? What will they have to do differently?
We have become accustomed to websites and other technologies “knowing” who we are and what our patterns of behavior are—Amazon recommendations, Google searches, iSpotify, etc. Yet today, very few of these predictive capabilities are making their way to consumers in healthcare.
Patients will soon carry all of their medical data with them in their pockets, so to speak. Many companies are looking to partner with consumers to make it easier for the health consumer to do the ‘job’ of managing their own health and data in an effort to streamline the process and avoid expensive trips to the doctor’s office.
While the process is awkward today, in the next few years we will see big data, analytics, and new tools making it easier for individual health consumers to handle the risks and increased expenses that the health system is asking them to take on. It will enable consumers to be more intelligent buyers and users of health services. It will create a whole new industry of staying healthy with real personal, emotional and financial rewards for doing so. Healthcare will become as personal and individualized as we’ve experienced in other aspects of our lives, transformed by the digital and mobile revolutions.