Innovation Under Pressure: What Will Drive Progress in the Life Sciences?

1. When we spoke about precision medicine a few years ago on a small stage at the Omniturm, much of it still seemed a distant prospect. Which developments have advanced more rapidly than expected since then, and which have progressed more slowly?

Personalised precision medicine has advanced considerably, particularly in oncology. Many newer approaches, including cell therapies and cancer vaccines, are now genuinely personalised and tailored to the individual patient. When we spoke at the Omniturm, these approaches were still largely stratified, targeting groups of patients rather than individuals. Personalised therapies are also expanding beyond oncology. Significant progress is being made, for example, in the use of cell therapies to treat autoimmune diseases, and other indications are likely to follow. Cost remains an unresolved issue, as personalised therapies will inevitably be more expensive than one-size-fits-all approaches. At the same time, efforts are under way to keep costs within reasonable limits, including the development of allogeneic cell therapies and the industrialisation and optimisation of the underlying processes.

2. The pharmaceutical and biotech industries are investing more in innovation than ever before. Nevertheless, many people feel that genuine breakthroughs are taking longer to emerge. Has innovation become more difficult?

• Are the scientific questions becoming more complex? Scientific questions have always been complex because biology itself is complex. Although the volume of available data, including clinical data, continues to grow, it remains far from sufficient to capture the complexity of human biology. Credible scientific estimates suggest that we would need approximately 1,000 times more clinical data than is currently available to achieve even a reasonably accurate representation.
• Have regulatory hurdles increased? Regulatory hurdles have not increased, but unfortunately they have not decreased either. During the pandemic, many new procedures were introduced that enabled the first vaccine against SARS-CoV-2 to become available within 11 months, compared with the usual vaccine development timeline of seven to ten years. Regulatory authorities contributed to this achievement, for example by conducting rolling reviews, in which data were assessed as they became available rather than only after the full dataset had been completed. These procedures were introduced in response to a crisis, but they could certainly also be applied to conventional drug development.
• How is AI changing the situation? AI will revolutionise pharmaceutical research and development, and the first signs of this transformation are already visible. One example is AlphaFold, which can predict the three-dimensional structure of proteins from their amino acid sequences. Since its publication in 2021, countless other data-driven tools have emerged that can design new proteins, small molecules, RNA therapies and even gene therapies. They can also predict interactions with other molecules, including those naturally present in the human body. Systems for assessing the druggability of molecules, including their safety, pharmacokinetic properties and potential drug interactions, have existed for even longer and are already well established. At present, however, AI is used primarily to accelerate decision-making within companies rather than the entire value chain. This is partly due to the understandable caution of regulatory authorities, which continue to require conventional procedures for the approval of clinical trials and manufacturing processes. Over time, this too will change as AI-based approaches repeatedly demonstrate their validity and, in many cases, their superiority. In the medium term, we can therefore expect the entire research and development process to accelerate.

3. If you were to lead a global R&D organisation again today, which areas would you prioritise immediately?

• AI and data: Definitely, for the reasons outlined above.
• Talent: Definitely. Without the right talent, we will not be able to overcome the challenges ahead. However, the talent profile will change. Until now, R&D has been shaped primarily by pharmacologists, biochemists, chemists, physicians and pharmacists. In future, data specialists and computer scientists, among others, will also play a major role. Ideally, universities would reflect this shift in their degree programmes, which are currently still housed separately across different faculties.
• Collaboration: Another clear priority. We need to recognise that novel ideas are far more likely to originate in academia. What is often missing there, however, is the expertise required to turn ideas into molecules and molecules into products. That is where industry can make a vital contribution. This clearly calls for cooperation between public institutions and the private sector through public-private partnerships. Collaboration between large pharmaceutical companies will also become increasingly important. With the cost of developing a single drug often exceeding €2 billion, even for relatively small patient populations, it will become increasingly unattractive for one company to bear the investment alone.
• New organisational models: To a lesser extent. Virtually every organisational model has already been tried at some point over the past few decades.

4. Will the future of the pharmaceutical industry be shaped primarily by individual companies or by ecosystems comprising pharmaceutical and biotech firms, technology companies and healthcare providers?

• Perhaps you could answer from the perspective of your experience in industry and on supervisory boards. The future will undoubtedly be shaped by ecosystems linking universities, non-university research institutions such as the Max Planck, Fraunhofer, Helmholtz and Leibniz organisations, start-ups, SMEs and large companies. These ecosystems will probably extend beyond the pharmaceutical industry itself because tomorrow's patients will no longer expect a medicine alone, but a personalised solution to an individual problem. This will include an accurate diagnosis, a drug, a device, since many modern medicines cannot be administered orally, and the data and algorithms that connect these elements. This is known as the 4D concept: Diagnosis, Drug, Device and Data. Industries that have traditionally operated separately will therefore need to converge much more closely.

5. Artificial intelligence is currently the subject of intense debate. Where do you see its greatest tangible benefit for patients, and where is its influence being overestimated?

• Drug discovery: This is where the greatest potential lies, particularly in identifying new biological targets. At present, AI is still used mainly to design molecules for known targets. The preceding step - identifying the right target in the first place - remains comparatively underrepresented in current applications of AI. (See also the attached manuscript.)
• Clinical development: There is potential here too, although to a lesser extent, for example through the use of digital twins. AI is currently expected to shorten clinical development timelines by approximately 25%, but probably no more. (See also the attached manuscript.)
• Diagnostics: AI can help to identify and validate new biomarkers. There is particularly strong potential in liquid biopsies. In radiology, AI is already part of standard practice.
• Access to therapies: AI will also play an important role here. However, I believe that even in the long term, patients will be more likely to trust a physician than an AI system.

6. In your view, what distinguishes companies that innovate successfully from those that struggle to sustain innovation despite sizeable budgets? I consider all four factors mentioned below to be important, although their relative significance varies by company. Multinational pharmaceutical companies face different challenges from nationally focused SMEs or start-ups.

• Culture: This is an important factor, particularly in the way an organisation responds to mistakes. Employees are far less willing to take risks if every mistake is severely punished. What matters is a culture that learns from mistakes and avoids repeating them.
• Risk tolerance: Portfolios must be balanced and should consist neither exclusively of high-risk projects nor entirely of me-too products. The decisive factor is intelligent portfolio management and, consequently, intelligent risk management.
• Speed of decision-making: The speed of internal decision-making matters, but external factors, such as the speed at which regulatory authorities reach decisions, are often just as important to an organisation's capacity to innovate and accelerate development.
• Team diversity: This is certainly a positive factor that can promote innovation, although it is rarely decisive on its own. Individuals, too, can be highly creative and innovative.

7. Today, you advise companies from a variety of perspectives. Which challenges do you encounter repeatedly across different industries?

• Translation into practice: A long-standing challenge in Germany is translating the findings of outstanding basic research into practical applications. There are too many cautionary examples, beginning with the MP3 player. A similar pattern can be seen today in cell and gene therapies. German basic research is on a par with that of China and the United States in terms of high-impact publications and patents, yet 94% of the corresponding clinical trials are conducted in the United States and China.
• Shortage of skilled professionals: This is not yet an acute problem, but it could become one. New education and training models will also be needed, as outlined above.
• Digitalisation: This will remain a challenge and will require collaboration. The pharmaceutical industry cannot drive digitalisation entirely on its own; it needs the right partners from the technology sector.
• Leadership culture: A more collaborative style of leadership is gradually gaining ground, particularly in European companies. In the United States, the leadership culture associated with the Trump administration is undergoing a period of change, while in China, corporate culture continues to be shaped by the Party.

8. If we meet again in ten years, which development in healthcare do you think will surprise us most?

• Prevention: We need a fundamental shift towards prevention - essentially a revolution in our healthcare system. Today, approximately 90% of healthcare expenditure goes towards treatment and only 10% towards prevention; ideally, those proportions should be reversed. That will not happen within ten years, but perhaps the first meaningful steps will have been taken by then.
• Longevity: This is currently overhyped, partly because of the attention it receives from prominent advocates such as Mark Zuckerberg and others.
• Gene and cell therapies: These will initially deliver spectacular advances in rare diseases, although there will also be setbacks. Nevertheless, they will undoubtedly become an important part of the therapeutic landscape.
• AI-assisted healthcare models: AI will have an impact on research first and only later on healthcare delivery models.
• Digital medicine: If by this we mean telemedicine, we will see significant growth, as is already happening in many Scandinavian countries. Telemedicine can also help to reduce the number of in-person consultations, making an important contribution to lowering healthcare costs. People in Germany consult a physician eight times a year on average, compared with only twice a year in Norway.

9. After many years in senior positions in the pharmaceutical industry, what do you believe today that you did not believe 20 years ago?

That learning processes always take far longer than we initially imagine and that progress can be reversed. The pandemic provides a striking example. We learned an enormous amount: that genetic engineering is important; that science communication can play a major role in shaping public perception; that production must be considered from the outset; that cooperation between all parties must be able to proceed without unnecessary bureaucracy; and that innovation depends on patent protection. Yet we have already forgotten almost all of those lessons.