Is the German Life Science and Healthcare sector prepared for the AI revolution?

08 Jun 2020

Is the German Life Science and Healthcare sector prepared for the AI revolution?

With artificial intelligence set to have a game-changing effect on the global Life Sciences and Healthcare industry, will Germany keep up, or be left behind?

Silvia Eggenweiler and Veronika Ulbort, Partners in the Odgers Berndtson Germany Life Sciences and Healthcare Practice, in conversation with Soren Eichhorst, Global Head of Consulting at Siemens Healthineers.

How does Siemens Healthineers utilise AI?

Soren Eichhorst: One example is that it supports pattern recognition for the analysis of radiology images. This aids radiologists in making the right diagnosis.

The other example is a bit more advanced: We use artificial intelligence to define and support clinical pathways. We have a tool that is called “AI-Pathway Companion”, a decision support tool that integrates multiple data sources to help clinicians devise precise, personalized treatments for patients. It helps to define an end-to-end process, a clinical pathway, for different diagnoses. Thereby, we are also able to support physicians in making the right decisions and focus on what really matters: their patients.

Should a life sciences company acquire an AI startup or develop these capabilities from within?

Silvia Eggenweiler: They should do both. Startups work well because they are agile, have a certain culture and they are small. Bring them into a big company, then ensure that you do not destroy their creativity and agile way of working with overly complicated processes. And be very careful with who you put in leadership positions.

Veronika Ulbort: It is essential that companies also improve their own capabilities. With their engineering DNA and competitive edge in training their staff, German companies are well positioned to face this challenge.

Soren: Companies need to bring a powerful AI engine together with the right dataset and have deep insight into the specific policies and organisational setup required. The highest impact and easiest route for a company that has yet to develop their AI solutions, for example in the clinical space, is to work with startups who have already developed deeper insights into such processes in more detail.

Has AI changed the nature of life sciences companies?

Veronika: Life Sciences, and Pharma in particular, is a sector that ticks quite slowly.

When new product development takes 12 years on average, that does something to its people and culture.

I expect that disruption and a different pace, not typical of especially the large companies, is coming and this trend is currently being accelerated by the Covid-19 pandemic. However, leadership is crucial. For me, this requires out-of-the-box thinking when filling key positions, including e.g. the mapping of candidates from faster-paced sectors like Technology or FMCG.

Silvia: It is an evolution. Large pharmaceutical companies and the innovative startups have adopted a lot of it already. Novartis, for example, is allied with Microsoft to boost drug discovery, Merck & Co collaborates with Amazon, Sanofi with Google, to name a couple of prominent ones. And the AI teams within the pharmaceutical companies themselves continue to grow.

Soren: Currently, we are seeing an initial effect of the changes caused by artificial intelligence. But they are a game-changer. You need the right environment to fully leverage their power in terms of potential, so the full impact is still to come.

Leveraging the live data that is available from patients or processes in a hospital, e.g. via RTLS (Real-Time Location Systems) tracking technology combined with digital dashboards can have a significant impact. Think of combining this information with a “digital twin” simulation of a hospital in real-time to maximize the value of care. It is not only making the healthcare system more efficient, but also helping patients to have a better experience. It means streamlining processes, and making the right diagnosis for individual patients so more of them will receive personalised medicine. That has the ability to change healthcare entirely. Furthermore, there is tremendous opportunity and need for strategic thinking in healthcare today.

Can German life sciences companies compete with international counterparts in the AI space?

Silvia: Yes, but it all depends on how well they partner with the big technology companies and the kind of talent they attract. If these are in the Bay Area in the USA, there is the monetary part that you cannot ignore. That means having a truly global mindset and not putting these positions in an unattractive place like Frankfurt, but leaving talent to work in San Francisco and commute to Frankfurt if needed.

Soren: They can, but there are solutions in Germany that are directly focused on the national and regional space. And that means that in these cases they are not necessarily expected to compete against global players. Plus, you could always argue they need more money to fund their AI solutions.

Compare us with what China is putting into AI. It is not the same level at all.

Is there a reason why German life sciences startups fail?

Veronika: There is this rather risk-averse approach, a tax system system which does not support innovation and small companies’ lack of funding. In the next phase of growth after venture capital, emerging companies are very often in trouble because they cannot generate further investment. That is a huge disadvantage compared to the U.S. and UK.

Germany is a country of innovation, engineers and scientists, but its leaders are often too technology-focused. They lack marketing and storytelling skills, especially in front of U.S. investors.

Furthermore, they require excellent investor-relations managers, so the way they present their case can be most effective.

What kind of AI skills are needed at C- and board level?

Silvia: The C-level has to understand AI and provide the strategy, but does not need to operationalise it. At the moment, most of those positions are in middle management and typically within the IT organisation led by the CIO.

AI will have strong implications and bring new requirements for regulators, clinicians and managers that touch on complexity, technology and risk management and therefore will require upper management to have a solid understanding of it.

Veronika: It is important for executives to develop a basic understanding of the AI industry that goes beyond the “marketing jargon”. They also need to create a company culture that enables disruptive change, including more flexible and creative HR strategies that will attract top AI talent to Life Sciences.

Soren: The future will show a merging between the healthcare-oriented backgrounds and an understanding of the required technology and change management.

Thank you Soren Eichhorst, for your enlightening insights.

Odgers Berndtson’s Global Life Sciences Practice works with businesses, from start-ups to multinationals, to recruit executives with the strategic skills and mindset to deliver their business objectives in a digitally-disrupted world.