Redefining the MedTech Landscape - Precision Medicine

Expert Profile

Section 1: Why is this technology redefining MedTech?

1.1. To what extent has this technology disrupted the way we deliver healthcare?

Precision medicine in general fights against the historical way we tried to approve novel treatments. The old paradigm of treatment development is that we looked at developing drugs based on basic understanding of how a disease works and try it in patients to learn from the use of the drug how the drug works.

With precision medicine, the opposite is true. When we develop a drug, we have an anticipated knowledge of how that drug or therapy is going to work which maximizes the chances for patients to have benefits rather than having to learn from an undefined population of patients, and then infer our understanding from that initial experience.

Take chemotherapy, it is very specific and creates a lot of toxicity, it has dominated any other cancer treatment. Now there has been a massive growth of precision medicine in oncology. We were able to develop targeted therapies that specifically block certain mechanisms in cancer cells without destroying the body or causing harm.

Disruption has been dual fold. We have become more capable of developing new drugs, spending less time and less money; on the other hand, it changed the way we understand diseases. If you think about lung cancer, there were only two types: non-small cell lung cancer and small cell lung cancer. Now, we have at least 15-20 types of the same type of cancer based on each individual mutation. Hence, we have been able to increase our visual capacity when it comes to detecting diseases, which has been disruptive in cancer medicine, but also in other diseases.

1.2. Why should healthcare providers use this technology more?

The main reason is because it has shown to improve outcomes. It improves the patients’ experience throughout treatment and patients tend to benefit longer from treatments that are specifically targeted. Other aspects, for instance, the identification of patients that will suffer from harm from specific treatments. If you’re able to identify the patients that will have harm from treatment, then you can spare them from a drug that might or might not be effective but is likely to give rise to very severe side effects.

Before medicine is precise, you need to know what you’re looking for. I think that’s one of the challenges that is still present. There are certain disease areas, such as neurology, brain diseases, neurodegenerative disorders, those are diseases where we kind of know what happens, but do not fully understand it.

1.2.1. What opportunity does this technology unlock?

There is a societal benefit, having more precise therapies allows a lot of patients to be treated with oral therapies. For a lot of cancer patients that has been revolutionary because original chemotherapies all had to be intravenous drips. Patients can now have treatments at home, and not in a hospital. This enables a lot of cost reduction for healthcare systems as it doesn’t require stringent follow-ups within the hospital.

It is important to likewise consider the broader healthcare systems, the taxpayers, and how we fund our own healthcare. Precision really has got a lot to do with treatments that can be easier to deliver and less expensive. A common criticism against precision medicine is that precision comes at a cost. If a box standard treatment can be given to everyone at fairly low cost, but low benefit, to achieve high benefit in a selected population of patients, you’re basically leaving a lot of patients untreated with the precise approaches and therefore leads to increased costs to identify the patients that will benefit.

However, what we have learned is that identifying patients that benefit most leads to broader, positive implications for the pathway of care for these patients. Patients survive much better and they have less side effects.

1.3. Are there any barriers to successfully implement this technology?

I think there are internal and external barriers. The first barrier is knowledge. The discovery of precision approaches is really based often on years of science. Over the past 20 years, we have had to develop and deliver several biomarkers to check whether patients truly have that biomarker that will enable a precise approach.

This is obviously a barrier because it requires us to implement a turnaround time for a specific test to be linked to the treatment of interest. Hence, this is not something that can be taken for granted and it needs to be implemented at a scale that is compatible with routine clinical life. Hospitals must be equipped with the right laboratories and with the right expertise. Doctors have to be able to interpret the test they’re reading.

The other barrier is the fact that drugs must be available. In certain healthcare systems, you have instances where there is very unrestricted access to drugs. Perhaps the payment is funded by private healthcare insurance, or you rely on a public sector instead. Health economic evaluations are often done by the public bodies approving the drugs before they can be implemented, which can take time.

1.3.1. Where is it most important to invest in the future in order to be implemented more widely?

I would say in the knowledge aspect. Precision medicine has opened up a number of doors, we are also very aware that there are issues around resistance and the fact that not all patients would respond.

One example is melanoma or non-small cell lung cancer, where you have specific alterations that now define a very specific subgroup of patients, what we have seen is that after being treated with one type of drug that is meant to be hitting that precision medicine biomarker, there is adaptive resistance. Therefore, there are now second, third, and fourth generation drugs that are linked to the same mechanism.

Only through that process of continuous research into the same mechanism, has it been possible to create a number of therapy lines. The same is true for breast cancer and the same is true for many other disease areas. It’s still important to define what it is that we could do to improve our understanding of how precision medicine works even beyond resistance to treatment.

1.3.2. Do you expect the overall future healthcare to be much more personalized and targeted towards each individual?

Yes, I think that’s really the future. I don’t think there is coming back to a stage of us not using the scientific knowledge that we have accumulated so far to develop new drugs and to develop new therapies. There are a lot of areas outside of cancer medicine that are still characterized by a number of unmet needs.

Even areas where we thought we had conquered, the field for instance in infection, which are now really troubled by the lack of novel antibiotics. We have also seen with the COVID pandemic novel emerging viruses are really on the horizon. Yet, even with the pandemic, we were able to develop a precise approach by utilizing an RNA technology that has revolutionized the way we develop vaccines. Hence, you can see that even with new and emerging threats that were not present before, the future really stands in the opportunity of trying to deliver a precise healthcare and the challenge will be to make it increasingly relevant to the individual patient, to the unique human being that we’ve got in front of us as a patient.

1.4. How does this technology reshape what the future of healthcare will look like?

One of the aspects that is still lacking is truly individualized medicine. What we tend to do very well these days is to identify something that we call stratified medicine. Meaning, that we know on the basis of certain traits, certain biomarkers, that there is a group of patients that is likely to respond on the basis of molecular alteration, but then within the same group of patients who have that alteration, we know that not everyone will respond. Perhaps some 80% of the patients will respond, but not 100%.

Perhaps the next step will be to have technology available at the patient’s bedside that would look at the other traits beyond the presence of particular traits that are also involved in influencing response, survival to treatment and be able to have a real-time approach, have the possibility of really telling the patients purely on the basis of the quick test, maybe done at the bedside or in the clinic that yes, they have all the green lights for that particular precise treatment to be successful. This is still something that we cannot do to the point of the individual patients. We know very well that the patient group will be potentially easily identifiable, but within that group, we still struggle. This would be a really good way to further broaden the reach of precision medicine.

Section 2: The Future of Digital Disruption in MedTech

2.1. What other MedTech innovations are you most excited about?

I think there are a number of innovations. Precision medicine is really a label that encompasses a mission rather than a specific technology. Hence, artificial intelligence is a methodology that can very easily fit within the remit of precision medicine as such. We now have very potent computerized models that on the basis of complex algorithms can interpret traits, scans that the patients have had, medical notes, or blood tests that patients would’ve had even before there is a proper diagnosis of a disease being made. The potential for these technologies is not just to treat disease, but also to prevent it. Consequently, I think it’s very important to look at many different technologies, but under the same aim. Precision medicine really isn’t just a simple one-dimension technology, but it’s trying to use technology to a purpose.

2.2. In which area do you expect the biggest breakthrough/ innovation in the next 5-10 years?

I think AI is definitely an area of active investigation, which allows the combination of many different domains. Even if we think about, for instance, human pathology, and human disease as such, we know that now with the sequencing of the genome and also the understanding that the genome itself is not sufficient for us to give us the blueprint of everything, of the fate of our body in terms of whether we will catch a disease or how quickly will get the disease. We have started to appreciate that we kind of need to combine many different technologies together to generate an answer and generate new treatments. And I think this is one of the reasons why I think artificial intelligence can really enable us to upscale the capacity to compile and contrast a number of different sets of data.

We call it big data research, sometimes even blue-sky research, because it’s not driven necessarily by a hypothesis, but by trying to look at trends, how big numbers change, and how those changes in big numbers basically change towards the appreciation of what a disease state is going to be in the real patient. In my mind, artificial intelligence is really fairly high up in this process.

2.3. If MedTech is set to grow significantly, how do you think MedTech providers can create a competitive advantage?

I would point out two aspects. One is, certainly, about knowledge of a novel mechanism of disease. In answer to your question, pure and basic research around the mechanisms of a specific disease is really what gives a competitive advantage. The story of development of precise approaches in med tech has really been that of knowing where to go first and trying to validate that concept in patients rather than, as we said before, doing the opposite. That’s perhaps the key point.

The second point is targeting groups of patients where there is no valid standard of treatment. There are still a lot of rare diseases where there is completely uncharted territory when it comes to treatments. Those have essentially been ignored by medical technology and by drug development, because the potential revenues for the invention of novel therapies in very disease areas are very small. Now there are government programs and research programs that tend to prioritize the discovery of treatments for deprived or orphan diseases. So, there is an incentive in terms of patent laws, but at the same time, this commercially and strategically is also a very good territory to have that level of competitive advantage. So, concentrating in disease areas where there is a very high rarity.

2.3.1. Are there any security concerns? (Or data protection?)

The key issue and question is ownership of the data and how the intersection of all this human biological data can be utilized to the advantage and not to the disadvantage of people. Anyone of us who is on social media will sometimes feel a little bit uncomfortable about how these clever algorithms are able to suggest a specific ad that is tailored based on our internet research and our preferences, popping up in the different technologies that we have: our computer, our telephone, etc. If we think about healthcare, there is a very important risk here, which is that of trying to maintain the patient themselves as true protagonists, main characters in the story, making sure that we as individuals have our human rights and our data rights protected and preserved so that for instance, potential commercial interests that might arise from the use of our biological data are actually done with our own consent and not behind our backs. There is clearly a very important aspect here that needs to be explored if, for instance, the use of big data of AI needs to be brought forward to the clinic.

2.3.2. Are you concerned about the potential misuse of data by the owner of the data?

We have to think about the fact that if we live in democracies, then, our rights to access data should be protected. There is an issue around the integration of healthcare data and the potential of profiling patients on the basis of their own personal or healthcare information. We can imagine that if this information is used against us, we might be denied healthcare insurance if our profile is in a situation or in a state where the risks will be too high. So personally, I’m quite concerned about what the potential societal implications might be for the use of AI. And I think it’s very important that we don’t discourage research in this area, but that we accept the potential risks and we govern them.

Hence, there has to be a legal framework that enables us to control this data and to protect it. And I think the point is that in situations where we are not part of a democracy, obviously, the state might potentially come across as a threat in the use of healthcare data. And I think this is why to a certain extent, it’s very important that at an international level, there is an agreement in terms of how the use of this data and these paradigms can actually be used for good of the promotion of the healthcare agenda in mind and not certainly from the point of view of disadvantaging people or depriving them or liberties.

2.4. Overall, what role will MedTech play in the healthcare industry in the next 10-15 years?

I personally think so. The only problem is the reimbursement. If you’re thinking about precision medicine, trying to implement a new paradigm always clashes with the old ones. And I think novelty always brings the need for investment. And so, if I’m thinking about the overall global landscape, there are a number of precision medicine approaches that are, for instance, approved in Western countries that are not available in more sort of economically or socially deprived areas of the world. So again, this is another challenge that is worth insisting on, the fact of creating affordable precision medicine approaches across all the indications that are suitable for this approach.