Member of the Board, Public Relations, Senior Project Manager ICT & Precision Medicine
Tel. +41 61 295 50 16thomas. brenzikofer@baselarea. swiss
After 20 years with the pharmaceutical company Eli Lilly, Bernard Munos set out to better understand pharmaceutical innovation – specifically what makes it possible and how to get more of it. Munos is now a Senior Fellow at Faster Cures, a Center of the Milken Institute, and the founder of the consultancy InnoThink, which advises biomedical research organizations on how to become better innovators. He also contributes to Forbes magazine, an American business publication. Munos travelled to Basel in October, on behalf of HKBB and DayOne to participate in the “Powertalk”.
Mr. Munos, precision medicine has been around for a couple of years. These days everybody seems to talk about it. Why is that?
Bernard Munos: The healthcare system is increasingly torn apart by powerful forces. On one hand, science is delivering amazing things such as protein therapeutics (peptides, monoclonal antibodies); cellular therapies (CAR-T); gene editing (CRISPR); and a growing array of technologies based on a molecular understanding of diseases. The only problem is that this is very expensive. In addition, the population is aging, and older people tend to get diseases that are costlier to treat. The result is nearly infinite demand for costly care, which is clashing with the limited resources available to fund it. But, as it turns out, precision medicine is the most promising opportunity to change the economics of pharmaceutical R&D, reconfigure healthcare, and deliver affordable care to all.
In other words: the current system is not built to distribute the benefits of the new technologies?
For decades, R&D was much simpler: We took a disease that we typically did not fully understand, threw a bunch of compounds at it and saw if something would work. If it did, you had a drug. This was crude, but not a bad strategy since it gave us drugs long before we understood the diseases they treated. Sometimes, however, it does not work. For example, we have thrown over 350 compounds at Alzheimer’s, but none has worked, and we still do not know what causes the disease. There’s got to be a better way, and that is precision medicine.
What will change with precision medicine?
Once we understand how diseases work, our capabilities are so powerful that we can often design a disease modifying molecule literally within months. Precision medicine, along with the technologies that enable it, will give us the insights we need to develop those drugs. But it translates into a smarter – and ultimately cheaper – way to do science and develop drugs –which is why it will prevail.
What do we need to establish to get precision medicine taking up more speed?
According to the Food and Drug Administration, the number one impediment to innovation is the lack of natural histories for most diseases. This means that we do not have baseline data that describes the course of the disease, and therefore we cannot measure the improvement that a therapy would bring. It really limits our ability to innovate. Many diseases progress quietly for many years before they are diagnosed. Take Alzheimer’s or pancreatic cancer: by the time they show symptoms, it is too late for an intervention. Precision medicine will change that by collecting data while the diseases progress but the patients are asymptomatic. This will advance disease discovery and give us the knowledge we need to develop better therapies. Much of this will be enabled by new and inexpensive data-capture technologies such as biosensors, apps and other plug-in devices that are advancing very rapidly.
But first of all this means new investments – who is going to pay for all this?
At the moment, public companies spend US$110 billion per year on clinical research, much of which goes to collect data. This is an enormous amount of money, and companies gather indeed vast quantities of data, but they are limited in scope and often of mediocre quality. In 2014, the company Medidata Solutions ran an experiment to test the capabilities of biosensors. They assembled a couple hundred patients and equipped them with a few low-cost biosensors such as activity trackers and heart monitors. Over a couple of months, they collected up to 18 million data points per patient and per day. That data was later reviewed by regulators and declared to be “FDA-compliant”. One key point, however, is that its collection cost was trivial. Other evidence suggests that, by redesigning trials to leverage digital technologies, we can cut down the cost of data collection by as much as 80 percent. This is big enough to change the economics of clinical research, but it does more. It also enables better research. Today, drug trials focus on homogenous patient populations, because one needs to minimize the sources of variance. But the result is trials that do not represent very well the populations that we want to treat. Biosensors, on the other hand, can collect lots of data on larger populations, and statistical significance is usually not an issue. It is also high-frequency longitudinal data which gives us a much better picture of what happens to patients.
How will this change medicine?
Today, when someone comes down with Alzheimer’s, we don’t know when it started, or why, and therefore have no way to intervene on the course of the disease before it is too late. If we had data on pre-symptomatic patients, scientists could look back and pinpoint when the disease might have started and how it progressed. With such information, we could design better drugs and intervene earlier when the prognosis is better and treatment costs cheaper. It could potentially move medicine from treatment to prevention, but implementing it won’t be easy. Our whole healthcare system is designed to treat not prevent. Changing it will require a lot of retraining, but it’s the way to go.
Crucial will be the question who owns the data and who will have access to the data?
A key requirement of precision medicine is that data needs to be connected. It will be scattered over hundreds of databases, but they need to be interfaced so that they can easily be searched. Some of the data will be public, but much of them will be collected and controlled by the patients themselves. A majority of patients has signaled a willingness to share their data for legitimate research purposes, but whoever controls data will also control innovation. Patients hold values that are dear to them – such as transparency, openness, and affordability – and they will likely expect the recipients of their data to comply with these values. This will be a big change for the culture of R&D and will have significant consequences for the design of clinical research.
This will change the Value Chain – who will win, who will loose?
Precision medicine will bring some desirable changes: Historically pharmaceutical companies have generated their own data and competed on the basis on such proprietary data. Increasingly, however, data will become a commodity. For instance, the data from the “All-of-Us” million patient cohort that the U.S. National Institutes of Health is assembling will be in public access. There are numerous other large patient cohorts around the world that are being created and whose data will also be public. This will change the basis of competition. Scientists will increasingly work from shared, public data, and their performance will depend upon their ability to extract superior knowledge from the same data used by their peers
What does this mean for the Basel Life Science Cluster?
Big corporations struggle to generate enough internal innovation. The bigger they get, the greater the bureaucracy and the more regimented they become. This creates a climate that is less hospitable to innovation precisely at a time when large companies need more of it. To sustain revenue, they must access a source of external innovation that can supplement their own. Relying on licensing, mergers or acquisitions does not work well, as companies seldom find what they want to buy at a price they are willing to pay. Innovation hubs such as BaselLaunch or DayOne are a better solution. They allow the local community to create shared infrastructure – such as incubators and support services – that can become a global magnet for entrepreneurs. They also give the local large companies an opportunity to mentor the startups and offer scientific support. For them, it is a way to seed the local ecosystem with innovation that they can harvest later on. Basel is especially suited for this because innovation tends to blossom where cultures overlap. This has been a factor in the city’s past success, and it is an asset that can be leveraged again.
Do we have enough data scientists?
You certainly have them in Switzerland. Data sciences have long been a strength of Swiss education. It goes hand-in-hand with engineering, physics and other sciences in which Switzerland excels. It is also an important advantage since there is an acute shortage of data scientists around the world. Processing the big data flows discussed earlier requires much larger numbers of data scientists that we are currently training. In America, this has been identified as a critical workforce issue. Switzerland is in a stronger position.
Would an open data platform work like a catalyst?
Scientists flock to data. In all scientific projects, a huge amount of resources – as much as 80% – is spent on data collection and cleanup, which are seldom the most interesting parts. If Basel can offer rich data that is already curated, scientists will be able to accomplish much more while focusing on the part of their work where they really add value. Having data in open free access will also help attract researchers from other disciplines who currently do not engage in biomedical research – such as mathematicians and artificial intelligence experts. Such cross-pollination is a powerful catalyst of innovation.
About Bernard Munos
Munos is a Senior Fellow at FasterCures, a center of the Milken Institute, and the founder of InnoThink, a consultancy for biomedical research organizations. He regularly contributes to Forbes and is a board member and independent non-executive director of innovative healthcare companies.
Interview: Thomas Brenzikofer, Annett Altvater