We met with Dr. Sébastien Couraud, DEEP-Lung-IV Scientific Committee member and Head of the Pulmonology and Thoracic Oncology Department at Hospices Civils de Lyon, to talk about his participation in SOPHiA GENETICS’s DEEP-Lung-IV study and reflect on the benefits of multimodal approaches to transform precision medicine and improve patient outcomes.

Watch the spotlight:

Hello Sébastien, thank you for receiving us here at Lyon Civil Hospitals (HCL). You are the biggest recruiter of the DEEP-Lung-IV study that we launched a few years ago and also a member of the scientific committee. I would like to have your perspective on why you joined the study, and then your vision on the project in general.

Hello Marion, thank you very much for the invitation. I am very happy to welcome you here and to have a discussion on the DEEP-Lung-IV project.

And I think that is really what we are going to discuss together today. This very multimodal, very ambitious side immediately won us over. In addition, it is true that we have had quite a few strong relationships with the members of your team from the start. We already knew each other before, so it was quite logical for us to finally support you on this new project.

Could you tell us more about the objective of the DEEP-Lung-IV study and how this study will meet the objectives of precision medicine in the future?

The objective of the DEEP-Lung-IV study is really to go, collect quite a massive amount of data on patients who are treated in different investigation centers and who are treated for lung cancer.

Concretely, it manifests itself in a quite simple way - in reality, when we take care of a new patient, these are patients where we will ultimately integrate all of the data that we have generated for this patient. And collected in a database.

The multimodality here comes from the fact that we will collect radiology, pathology, and molecular biology data, and connect it with clinical data.

For the future, how do you see the next steps of the study and the collaboration with SOPHiA GENETICS?

For the future, obviously, the first step is the results. We were talking about it earlier, we need to have these results, see precisely the type of results that we have, the tools that have been generated, and we will then have to ask ourselves the question of whether we can use and integrate these generated tools into practice, how to do it and evaluate it.

We are finally at the beginning of a collaboration, and it would be a shame to stop on such a good trajectory. The objective is to continue the collaboration with SOPHiA GENETICS because it is indeed really important, from now on, to enter a partnership a little more operational, if I dare say.

You previously told us that artificial intelligence (AI) was expected in real routine practice. In your opinion, what would allow us to bring this to routine?

This step towards the clinical routine of integrating AI, that really is a very good question and I think it's really, if I may say, the golden question to which ultimately no one really has an answer today. We all think that AI will have a strong impact on medicine, in several dimensions of medicine. Obviously, when we talk about lung cancer, the decision of which today is very multimodal, and is a field of knowledge that is expanding almost hour by hour.

And that's the important element and what we're missing today. And what we're missing today are studies that will allow us to show that compared to the absence of artificial intelligence, the addition of it improves patient care on very specific events, such as survival, progression-free survival, treatment tolerance, the choice of a more suitable treatment, etc. So really the next step is prospective evaluation studies that will allow us to integrate these tools into real life and compare them to the outcome and current care.

Sébastien, let's think about the first day of the launch of the project and, with hindsight over these 4 years. If we had to do it again, would you join in?

That's a good question. Yeah, I think so. Yes, I think there was a bit of a crazy side indeed when you came to see me and you told me “We are going to take all the data from your patients, integrate them, and you're going to send everything to us”. It still required a lot of organization for us, but finally, I think we would do it again the same way. The collaboration was really pleasant in reality, that is to say, that it was done in a fairly simple, fairly flexible way. And in reality, with a little bit of organization on our side. Objectively, it went well, so I think that I would do it again. Yeah, I would sign again.

We have been working together, HCL and SOPHiA GENETICS, for several years. Could you tell us about the perception you have of SOPHiA GENETICS as a company?

Yes, so it's true that we've been working together for years.

That is to say that when we met at the very beginning, you were really in biology, in genetics. And I remember conversations that date back a very long time. You managed to really open up your field of possibilities by integrating this notion of multimodality and by very quickly understanding the interest of multiple modalities, instead of staying in a single field, in which you were nevertheless quite an expert, but to take a risk by exploring other fields and opening up to other possibilities. And I find that this risk-taking is interesting.

So, there is really a fairly innovative side to your company.

Sébastien, today, the treatment decisions for a patient are processed in Multidisciplinary team meetings (MTBs). What do you expect from an algorithm and the machine learning tool in general?

In fact, at the risk of surprising you, the idea is to perhaps be a little less human. You have to understand that today when we take care of a patient, we take care of them based on our instinct, we take care of them based on their story - the patient's story - we know them, we know their story. And then we have our experience - the experience of whether we have other similar patients or not, that we have taken care of. And so that's what ultimately constitutes the decision that we're going to make in the MTB.

It's obviously science, right? There's no doubt about it. We have guidelines, and we rely on these guidelines, but then it's ultimately a collective of clinical experiences, good and bad, that will allow us all together to make the decision that we think is most appropriate for the patient.

Certainly, it's good since it's been working like that for years, and today, we're still practicing good medicine.

Now, what I'm saying is going to seem very odd, but in fact, it will allow us to tell ourselves that science in this situation, specifically for this group of patients, is telling you that. The human will then come and modulate the scientific decision and will say: the machine's decision is this. I will adapt it with the knowledge of my patient, but at least I will start from something very current, very factual, very scientific, and I will articulate based on it. This is perhaps where it will change things a little.

In practice, this machine support, how do you view it in MTBs? What does it look like?

It looks like a very intuitive interface. In fact, we must not forget that we still have a lot of work. We are increasingly solicited, we are asked for more and more things. The MTBs are becoming very, very heavy. I think all colleagues see that the MTBs are becoming more and more complicated, there are more and more patients. Patients are surviving more and more, which is an excellent thing, but it obviously increases the volume of MTBs.

All this requires us to be very simple and very pragmatic.

What is also important is that we can vary the parameters a little because sometimes we will hesitate between two strategies. We will say to ourselves: “Here, do I use this molecule or that molecule? Or do I use this diagram or that diagram?” and that finally can be done in one click. Add or remove a therapeutic option and immediately visualize the effect it can have in a cohort. That will help us greatly in our decision making.

We thank Dr. Couraud for his time and for sharing his experience. To learn more about the DEEP-Lung-IV Study, visit the dedicated page .

SOPHiA GENETICS products are for Research Use Only, not for use in diagnostic procedures unless otherwise specified.