Measuring one’s own life has already become part of everyday life for many people – so why would we not also make use of this opportunity in clinical trials? For years, I have encouraged the inclusion of sensors or applications in study designs, at least on an exploratory basis. One would think that by following the everyday life of a study participant, it should at least be possible to see whether life activity increases during treatment with the medicine compared with the control group. After all, digital monitoring turns into objective numbers what used to be asked of the patient, with the recorded information based on memory or opinion. If only everything were that simple. Over the years, my enthusiasm has been challenged by many highly relevant questions: What does the sensor measure? What factors could produce data that look like what we want to measure and thereby confound the results? Does the sensor function technically as intended? Does it calculate correctly what is being me

When a medicine moves forward in development, the starting assumption is usually that its potential efficacy is still believed in. I have often talked with colleagues about how our role is to recognise the risks around a medicine and look for ways to address them. The work could feel heavy if it were only about wrestling with uncertainty and setbacks, but that is also what makes it so compelling. What I find most rewarding is being part of conversations with drug development experts from many different fields. There is real respect in that collaboration, because none of us could move a project forward alone. Around the table, there are often as many perspectives as there are experts, and somehow a path forward begins to take shape—by listening carefully and building on one another’s ideas. And sometimes, just as importantly, the decision is made that there is no path forward at all. When a project has been carried forward for years, it can be especially difficult to admit that the real

A cornerstone of clinical development is looking far ahead. You can’t focus only on the next study; you also have to ensure it will properly serve what comes later in development. I’m asked whether I could design the next phase’s studies. The answer is yes—provided we also map the road beyond that. Every stage of development becomes the foundation for the next ones, and the only way to avoid wrong choices is to look far enough ahead. All prior data and results are, of course, highly decisive—they form the up-to-date knowledge used to weigh opportunities and risks. Based on knowledge and theory, we arrive at the assumptions on which the next plan is built. The theory consists of the scientific literature related to the specific drug target, which must be continually updated through discussions with experienced experts. The second key foundation for plans is understanding the environment—what treatments are already available for the disease in question, what others are developing for the

In today’s clinical trial process, we are finally allowed to focus on what truly matters. Dialogue with regulators can also move the process forward—as long as the industry doesn’t make it unnecessarily complex.

Years ago, I found myself in a working group trying to pin down what we really mean by “insight”—and what it definitely isn’t. An insight is more than a quick opinion or a standalone fact; it’s something that takes shape over time; through experience and an understanding you’ve built step by step. In drug development, that kind of insight is what helps you make decisions and keep a project moving. Opinions and data matter, of course, but on their own, they don’t do the job. When I talk with a clinician who knows a disease area inside out, I come away with a flood of smart ideas and practical perspectives from everyday clinical work. And the real value comes from talking to several specialists, because each brings a different angle that deepens the overall picture. Best would be to get them (also with patients and other experts) in the same room. In a couple of hours, you can generate an impressive amount of sharp, well-processed medical thinking. Still, for the purposes of drug develop