5 big questions on innovation

My team operates in Silicon Valley with three goals: bring Silicon Valley perspective and knowledge into our company; find and incubate new partners (especially start-ups) to demonstrate the power of new technology and approaches, and build a West Coast presence that leverages technology as well as life science leadership.

My team sits in IT, so we serve all therapy areas and functions. Technology is changing the game in many industries – or eating the world, as Marc Andreessen might say. We look for innovation that can bring medicines to market more quickly, or make therapies more effective. This could be re-imagining how we recruit or operate clinical trials, delivering mobile services that complement our medicines, or applying machine intelligence for clinical or patient support.

Our industry is complex, so we work closely with internal teams for the necessary scientific, clinical, and business domain expertise. We are a catalyst, empowering innovation rather than trying to own it in our team. This requires new technology skills in areas such as data analytics or IoT, as well as soft skills in communication, influencing and teamwork. We prioritize based on the importance that differentiating new technology plays in the opportunity, whether the potential value is incremental or transformational, and how closely the company matches our current needs and therapy area focus. 

Healthcare and drug development are highly regulated environments, with enormous - often literally life-and-death – impact on people’s lives. This makes innovation all the more important, but it has to be done carefully and respectfully.

Regulators have a very difficult job to keep up with impending changes, and sometimes lag the “state of the art” in areas like social media, or machine learning. How will a regulator assess a machine learning algorithm that doesn’t offer a clear rationale for a diagnosis, for example?

Another challenge is the complexity and deep specialization required across multiple scientific and technological domains. We need people with deep knowledge in both technology and science or clinical areas – or who have exceptional ability to work with together. 

The healthcare environment is a complex and fragmented system with many regional variants, and even though we are a large multinational, our impact on the overall system can be limited. People like to say it is easy to pilot a healthcare innovation, but hard to scale it.

Finally, we have a very successful core business. It can be hard to convince highly accomplished people of the need to change - especially when many aspects of digital health are still generating clinical evidence, or have very different operating models.

One of the hardest parts about embedding innovation is moving from a successful proof-of-concept into widespread adoption. 

Ideally, at a grass-roots level, we work jointly with highly motivated internal stakeholders at a very early stage, so that if we are successful there is a home for the project to land and grow. This is a balancing act – at times, we need to push the envelope too!

However, top down executive visibility and endorsement is critical. When our leaders understand technology trends and potential impact on our business, they provide invaluable recognition and support of projects that might otherwise “fly under the radar” or be seen as optional. Executive support has also helped to embed innovation objectives for employees more broadly – moving everyone from innovation “if and when I have time” to “a core part of my job, which I’m accountable to deliver.”  

There are huge advances in the way we store, transfer, use, and think about data, software and devices. The real change is driven not by a single technology, but by the combination of several: cloud computing, increasing digitization of healthcare, more personal and linked data, connected devices in the hands of patients, and changes in the ways we interact with computers.

We are arriving at a new class of data-empowered healthcare tools. Formerly invisible factors involving behavior, diet, environment, genetics, omics, or early cancer risk can now be measured and assist in risk assessment and diagnosis support. The cost of sensors and medical grade devices is decreasing, improving our ability to monitor continuously. Machine intelligence is exceeding human ability to recognize patterns in medical images and data. This opens possibilities to identify patients at risk, understanding disease progression, and analyzing historical and real time data and making appropriate recommendations.   

At the same time, issues like cybersecurity, privacy and cost sustainability must be addressed if we’re to realize these benefits without introducing unacceptable risks.  

I am most excited by companies that surprise me and challenge the way I think – bringing fresh approaches to some of our industry’s longstanding challenges. I believe there is huge potential in combining the rigor of science with the power of human-centered design. One company is using sensors and data analytics to quantify the degree of control in asthma patients, which could help predict an attack days before it would otherwise have happened. I’m also fascinated by “doctors on demand” services and the degree to which smart logistics, advanced teleconferencing, conversational UI and machine learning-enabled clinical support could improve the experience of healthcare while dramatically lowering costs. And I am excited about companies who are thinking about the whole ecosystem – for example, one that is looking to create an “app store” for genomics, challenging potential partners to offer value at a very personal level to their customer base. 

The variety and impact these companies will have is part of what makes my role such an exciting and rewarding one!