Inside Oncology Drug Development: Overcoming Resistance with Science

Hello, everybody. Thank you very much for listening in today. Welcome to Crowncast. This is the new podcast from Crown Bioscience that aims to discuss the emerging trends, breakthroughs, and viewpoints in oncology drug discovery and development. I am the host for today's, podcast, and it's my honor to bring you, conversations with scientific experts from around the globe. My name is Johnny McMichael. I'm Trawn's VP of client experience and enablement. I'm based in Edinburgh in Scotland, having spent the last ten years with Crown Bioscience. I do apologize for my accent. If you're not used to the Scottish accent, I'm not making my accent up to sound a bit like William Wallace or Mel Gibson. So hopefully, bear with us, throughout the accent challenges. Today's episode, I'm delighted to be joined, by my good colleague, Enrico Vicente, who is Crown's, executive director of client engagement based in Milano in Italy. Enrico has been with Crown for the last two and a half years, working in leading our scientific engagement and consultancy groups. Prior to joining Crown, Enrico's had a long and distinguished career in the drug development industry, spent a number of years in leading scientific roles, with pharma companies, including Pharmacia, Neriano, and also spent ten years as the CEO of Excela, a regulatory preclinical CRO in Italy. And today's podcast, our topic is drug resistance, a topic very close to Enrico's heart and scope of expertise. So, Enrico, welcome to Crowncast. It's it's a pleasure to have you on today. How are you? How is how is Milan? Yeah. A bit cold, but it's nice, and we are waiting for Christmas. No doubt. This is called the Scotland Enrico. So, enjoy enjoy enjoy the sunshine. Enrico, thanks for coming on. Really appreciate your time. And I guess, as a start, would you like to just give us a little bit of background to yourself and how you ended up where you at Crown Bioscience? Yeah. Sure. You can see from my ear that I'm gray, so I'm I'm on on this job since a long time. And I started very I was always working oncology, yeah, search and, mainly in pharmacology. So as you mentioned, I spent many time on my career in working in pharma, in drug development. I had, despite being old, I had, I was lucky to to see the the start of what was sort of molecular oncology and new therapy with target therapy. We had a very strong program of kinase inhibitors, and two of these are are actually at the moment at the market. So also some tangible results of what we have done. Then along the career in big pharma, then I as I said, I spent almost ten years as CEO of, a cellular. It's a preclinical CRO, so I I I I start to get experience in in, like, CRO worlds and to see drug development for the other side. And then after this, I end up in in ground trying to bring my experience and my my knowledge, especially in pharmacology, helping Crown and and our clients. And, yeah, today, the topic is, is a resistance. I think it's something, to say is, in some way, the dark side of our work. And in one side, I'm still very still amazed when I see when I I learn more and more the complexity of cancer, and I still see that continuous progress we we are making and standing this space. Especially with with the new technology, we understand much more molecular pathogenesis. And what I see and make me really, away, happy is the that the what we were always thinking about on making personalized medicine is becoming true. It's it's actually there. We are doing personalized medicine. And this because in the last, like, twenty year, we have seen the development of different cancer therapy modality, including small molecule inhibitors, kinase inhibitors, I mentioned before, but up to monoclonal antibody and checkpoint inhibitors, cell based therapy. I think in the last ten years, there were something more than two hundred, three hundred new drugs per FDA and I think one third of these are new new methods of action. And all these drug now are part of the standard care alone or most most frequent complications. So that's really there's a real impact, and this is something that make us, I can say, proud of our work and our small pieces that we are doing each of us contributing in different way. And you see the impact on patient is there. I was reading yesterday the the the numbers of the decreasing of the death rate from some cancer in United States, breast cancer, lung cancer. Of course, it's not only treatment, it's prevention, early detection, changing our lifestyles, but new therapy are having impact. And I'm thinking when I started, there was only basically only chemotherapy and lung tumor. Only therapy was cisplatin. Now you think about nose muscle lung cancer, we have, I don't know, tens of drugs. Each drug specific for each specific notation, for each specific patient of different lipid line. Another example is melanoma. They were also on dacarbazine, basically not active. Now we have immunotherapy specific molecules. And I think this year was the tumor tumor infiltrating lymphocyte based therapy for melanoma. So it's a big, big advance. Yes. We're we're certainly a long a long way off what was once the one size fits all approach to cancer treatment where a patient would come without Yes. It's true. But as a Yeah. Yeah. But as I said before, there is also the dark side that most of these patients, especially the one that they enter treatment with advanced disease or metastatic disease, they experience resistance and that is manifested as local or distance relapse. So cancer is relapsing. And relapsing after basically all the available therapeutic modalities. This is common. And, and this is because every therapeutic modalities leave behind some cells that are not affected. So what is called minimal residual disease that is it's basically a a reservoir from which relapse emerges. So it's clearly that the ability of mammalian cells to develop resistance to initially effective therapy is the major obstacle that we see now in cancer treatment and and and definitely in in with a big impact in patient outcomes. And is the also one of the biggest or the biggest challenge ever in fact. That is the general picture where resistance is and the value of this small world. Got you. Exactly. And so, yeah, really to to kick off, you've you've touched on it already a little, but, you know, would you be able to talk a little bit about what you see as the the main current challenges in in oncology drug development? Oh, yeah. Let let let's start with the with the definition, you know, being scientist like definition, because make your the word the complex is giving some order to the complexity. So blood resistance is is the ability of cancer cell to survive and proliferate despite the treatment you are giving. Treatment, they are meant to kill or to grow, to inhibit that growth. And and this is done through a very broad spectrum of mechanism. You will see later on. Maybe we can discuss about this. But in generally, the definition is that resistance can be primary or or intrinsic or secondary or acquired. Primary means that, basically, there is no object to response to the treatment following therapy. And the secondary, you have response, but then you have. So this is clearly classification based on on the medical aspect. If if you change your point of view from a biological point of view where, right, it's much more complex, plus in this case, despite the the the several mechanisms behind resistance can be categorized into major group. The one where resistance therapeutic resistance is is a result of a genetic evolution, a selection of genetic mutation that it is enabling cells to escape through therapy. So, basically, there is one cell or a group of mammalian cells that they have already or they acquire specific genetic mutation that give the cancer set the capability to escape treatment. It's a kind under therapeutic pressure. It's a kind of, Darwin concept. Pressure, selection under pressure. And only the few clones that have already have many time they already have. It's very similar to the resistance to antibiotics, whatever. But what is very interesting and and open up some some some different point of view is is emerging that there is another kind of resistance that is not genetically based. Is what is called is an adaptive mechanism. Is so we have cells, a subset of cells that basically under therapeutic pressure, they enter a status of, let's say, drug tolerant. They are called they are called persistent cells, and this is done by post transcriptional reprogram. And, couple of example, chemotherapy can is very well known phenomenon. It was called epithelial to mesenchymal transition cell under from different cancer. Epithelial cancer can can change their their their phenotype, acquiring a different phenotype. It's more undifferentiated like mesenchymal, and this is connected to to chemo resistance. It is pretty interesting in melanoma where the the these these two two status, these two phenotype can can basically switch back and forth by the cells depending on the pressure of the of the of the treatment. And one of these phenotype, what is called invasive, the mesenchynal one, is is is resistant to map k treatment. So it's giving specific risk. And under pressure, you see most of the cell are positioning to this status. So under the under the the the pressure, under the stress of the treatment, cells are changing, assuming a status that is basically not responding. That is very interesting. And and behind, basically, there are it's like the the cells tumor cell is hijacking many of, normal mechanism of survival of the and and transforming this in a mechanism of these systems. And this is one of there is activation of different pathway or as also for immunotherapy, you see activation of different checkpoint, and as response to one t p d one therapy. So it's it's very complex and sometimes intrinsic of of the of the basic mechanism itself. And and what is emerging is interesting is a bit a contradiction of what is our theory of Darwin therapy is that many at the beginnings, these phenomena, these adaptation phenomena are reversible. But under therapeutic pressure, they become they can be irritable. So cell stay in this status, and then and they can and and proliferate maintaining this status. So that is a kind of it's it's pretty interesting, but it's open up also new new avenues of therapy, of course. And and what I'm thinking talking about drug development, I would say that that side is a kind of yinga. Yeah. You have new drugs, but you have also cells tumor cell adapting to the new drug. So you get one, and then you get the response of the cells. So it's something and and it's well known from the early days. I was I I was not I was not born yet, but, at the beginning, with even with the first use of radiation, then I think at the beginning of nineteen hundred, there were cell, not tumor, no more responding, but the the real emerging of resistance was with the introduction of chemotherapy. After the second World War, we have the first patient treated with with chemotherapy more or less. And it was pretty clear that using methotrexate, cyclophosphamide, the or the the new chemotherapy at the time, it was clearly initial response, but then relapse. Nothing was patient. So the next step was to use combination therapy. So putting together different mechanism of action, and this was very effective for leukemias, lymphomas, or whatever. But also in this case, it was relapse. But until, can say, the early eighties, it was not very clear the mechanics. And one of the third mechanisms, I remember very well because when I start to work in the lab, it was my lab focused on the multidrug resistance. The group that was basically, that there was the docuserubicine was discovered in in Durbanua where where I was lead working, and and so there was a long tradition of, evolving the chemotherapy and resistance was the problem. So we we started to understand the mechanism behind. So MDR mainly was, which came with two p glycoprotein, efflux. So, basically, cells is is, again, is a is a defense use of cells from from from chem external chemicals. So you pump immediately out, and you decrease the constant intracellular concentration of. But then with with target therapy, we saw that we understood much better what is genetic based use resistant that is kinase inhibitor or the point mutation, kinase structure that are given to the to the to the prod the kinase kinase domain. Basically, the inhibitors are no more active for different point. Point mutation that can keep the protein, the the kinase domain in active status, or they can block the the assess to the ITP binding. So different mechanisms are giving specific specific, resistance and error record making a lot of in vitro model bring bearing all the different mutation and testing hundreds of compounds and and a lot of interaction between cell biology and MedChem at the moment. A way in the interest is that this kind of study they brought also change also some dogma. Chemists, they were avoiding completely any covering binders at the time, But then they discovered that maybe some some covering binding on the on the kindness domain was a way to overcome resistance. It was in there to be a piece one of these, for example. So it's interesting how you learn lab the things, and and things are evolving. And then, of course, now we have, as I mentioned before, your therapy, other breakthrough. Each of new therapies bring a new problem, so a new mechanism. And and this is the base, can say also in this case, complexity is is is a challenge, but it's bringing us opportunity. So understanding mechanism open up therapeutic approach, and we can we can discuss about that. Like, if you want later, we can go. Yeah. Yeah. Absolutely. That's fascinating. I've I've actually learned quite a lot in those ten minutes, Enrico, about drug resistance. I mean, of course, resistance means different things depending on which area of biology or drug development you you work in. My my first experience when I worked in industry was not drug resistance. It was I was a medical microbiologist, and my focus was on cystic fibrosis. And there, the main problems were multidrug resistant, microorganisms, bacteria that pharmaceutical companies back in back in that day, like, so Pathogenesis Corporation were working on, subverting that resistance and getting around it to really try and improve patient patient outcomes because it is a very that that level of resistance is very debilitating and really prevents your ability to to to to treat the condition. So that kinda leads me to to ask you you've talked a little bit there about the the impact of, drug resistance on the development of new drugs and and what it means for, drug development approaches. What what would you comment on the the main challenges we see in the in the in the clinic related to resistance? What are the, you know, the the patient impacts? Oh, that that that that's a real the real question because at the end, we are we are talking about patient always saying that yeah. And clinics, the major problem is pretty obvious. You you you have, the outcome the clinical outcome is is impaired. So if you see the numbers of of leakings in tumors, see, breast tumors, for example, most of the patient responded to have two diabetes become resistant. Yeah. They want to hear. So the same happened to as soon in in like, lung as soon a a resistant emerge that immediately the the performance status of patient is weighted. So the outcome is really really poor for patient. And one example, if you take pediatric tumor, I I think there is neuroblastoma that is is a rare tumors, but relatively frequent pediatric tumors. And I think the fifty percent of patient, they have relapsed. Even if they are responding pretty well and and a complete remission, and these patient are patient that are going through radiotherapy, complete ablation of bone marrow, of chemotherapy, immunotherapy. They got all through different line of therapy and then become relaxant. And and this is telling also how cancer cell can adapt. Also, in this case, with different point in different to to frame way of treatment that is really say, I would say, not amazing, but it's really impressive. And then, of course, there is an effect of not only to the to the disease outcome also on patients, if you think that impact on psychology of the patients. So it's not only a matter of medical or biological problem. It's a real problem for for psychology of the patient that become immediately no more responsive. But also from a medical point of view, you run out of option. And even in clinical research, when you get resistant within a clinical trials, then the the response become very difficult to interpret also the biomarker. So it's really is effect is really really affecting in a profound way all the outcome looking. And and this is, again, why it is so important to find the right strategy both in clinics but also in in this corner. Yeah. You know? What we are doing with that in our research to find the right strategy to to overcome resistance. Yeah. Perfect, Enrico. That's that's fascinating, and I really enjoy hearing your insights around the real impact to to patients because we get so often very focused on the the the drug development aspects and and and forget the ultimate aim is to to make the lives of patients easier and more more manageable. So in that regard, you mentioned strategies. Are are there any new strategies being developed to overcome, drug resistance that you could touch upon? Yep. There are many and and and and say before, there are many opportunity both in the bench and in the bed and and vice versa. Because from from the clinic experience, we are learning a lot and and dissecting the the the the patient response or no response, we can learn more and more and more. And this is basically due to the to the new technology we have now. What I like very much, for example, now one of the approach is using precision medicine and air biomarker. And now this is possible mainly what what technology I like very much is the single cell multi omics technology. So it is the response of what we this is one of the major problem. I was not mentioning that is tumor regenerative genicity. If you think about the different resistant mechanisms within the same cells, if you multiply this for the million cells per tumor, you you get immediately idea of our altered heterogeneous cells with different the tumor, with different cell population, with different grade of adaptation, with different grade of making different mechanisms that I forgot to say that all these mechanisms, sometimes they're happening at the same time, and not only in the cells, but also the interaction of what is around the cells that is normal. So it's a really dynamic situation, dynamic and plastic situation. So tumor heterogeneity is really the one of the major others challenge that we have with the tumors and understanding the tumor biology. But with for example, I I think the sample of single cells multiomic technology or single cells or or single nuclei technology. That is really revealing, make us to understand much better the tumor's progenity, pointing out the different tumor population or identify rare resistance cell population. That is very important for resistance where maybe, the the mutation or the adaptation of treatment occurs in a very, very few cells. But with this kind of of technology, you can identify this and have a map of also the different status. The for example, as I said before, the the transition between the the epithelium and mesenchymal status can occur at different stage, at different time of different cells. And with this kind of analysis, you can identify the different stages. There is I was mentioning before the neuroblastoma. There is a very, very recent published this month's paper from the John Maris group of the of the children hospital in Philadelphia. They were analyzing, I think, more than twenty case of, neuroblastoma with single nuclei technology. They they identified identified, I think, at least four different subpopulations of cells with different phenotype as result of the treatments. And between the these two, they identify some specific pathway, for examples, MIG inactivation or or nuclear fat or kappa b activation pathway that are typical of resistance. So having the possibility to do this kind of very in deep analysis that we're analyzing, I think, more than two hundred thousand sales is giving you insight of the mechanism and open up therapeutic possibility. Even if, for example, on NF kappa b, we know that it's a pathway that's very difficult to touch because of, it's an essential intrinsic cell pathway in the cell can lead to toxicity and so but you can then look to downstream pathway of the activation beta. So it's it's it's it's open up new rights or no for treatment. And connected to this, what I like very much is the now we we are adding the third and the fourth dimension of the two loss with special transcriptomics. Okay. We see the the three d, But, also, we have possibility to insert also the the timing. So there is the possibility of evolution during the time. So it's it's becoming more and more detailed, plus the typical multiplex immunofluorescence that you can see of the protein marker. So whatever. Especially very important within this is very important within cells and interaction between tumor cells, immune cells, and tumor macron. So that's the what I like very much in terms of, analysis technology applied to biomarker or analysis of clinical results. But from our side, say for experimental models, of course, I think, having PDX or patient derived xenograft or in generally patient derived tissues of sampler is a real balance. PDX, NVivo, everybody knows, especially in crown. We know this and some of our our strength points. And then in vitro, we have the organoids and all the other cultural system using patient derived patient derived tissues. And and this, for example, if you take organoids, the possibility to study also an interaction with the tumor microenvironment and the other cell, not only immune cells, but also fibroblast, tumor associate fiberbias. So and in using coculture technology. And sorry. And you have also a a kind of throughput screening. You can discuss if I I'll to put medium or low throughput screening in vitro to test, for example, combination and personalized combination to the patient. That's that's really advanced. And, I go on. So other technology, like, very much is all the tech the the the the genomic editing possibility with CRISPR. So you can one example, you can create some specific model or with specific notation or and we have some example of my sparing different notation of Keras notation. But one of the problems coming is is the massive amount of data that we are seeing. And so at this point, what is so is where computational and AI driven, approaches are entering. So once I now now I think every pod podcast at some point are mentioning AI, but I think it is very forced to understand what we are machine learning and and and calculation power is very important to analyze and and and make some deep analysis of the massive amount of data we have. And there is one example I like very much is, you can also actually for example, in the case of kinase inhibitor, you can actually predict the the the the weak point, the the the most probable point of mutation conferring resistance. And then you can do this in the lab, not in the clinic after some years. So that is you can understand now how how this connect which kind of impact can have this because you bring immediately to the patient a drug or you know already what is gonna happen, so you you you have not to wait five, six year to to study the next basic combination that you get. And and it was applied, for example, for for a track inhibitor. That can can really, let's say, go much more in detail, identify patterns that maybe we we cannot do with the simple microscope. So it it's it's incredible. I think it's really exciting. But sorry. Last point in then in the cleaning, in the practice, what what what is the result of every what we say is they do a combination. So we we have tens, hundreds of drugs we are learning to use in the best way and in a personalized way. So now we have biomarker that can drive the the personalization of the medicine, and we have also, research tools like Bito, as I mentioned, Organo ISO, and algorithm to analyze to to to make combination much more effective and personalized to the specific, where is some pattern that are for the for the patient. We tend you tend to see the general picture. I like very much when you see all the pieces coming together. And, and and then you get a bit with this. Also, some observation that you have done maybe twenty years ago that are coming back and with a different. There are a number of themes there as as as as the drug development has evolved over the decades that there will be themes that will, you know, come back. Yeah. They'll be modeled Sure. Come back into that. Yeah. Exactly. I mean, I I guess I've really only got, one one more question for you from what you've said. So you talked about the, you know, the important approach the the the importance of approaches to to model or or try and develop strategies to to to predict and also deal with the implications of resistance. You mentioned things like, you know, modeling the TME is important. The more translational the model, the better using AI as an approach to, again, direct that modeling. So as a CRO, we have a lot of companies come to us who are not experienced in in certain areas or with less experience or moving into an area for the first time. So what advice would you give to a a company coming to us telling us that resistance is a concern for them or they're wishing to target an indication or or a therapeutic modality for which resistance is a is a challenge? That's a good that's a good question, Johnny. The first thing is that I learned is that even if my several of my bosses were already asked about this, that the clear experiment doesn't exist. Zowar is a complex word, and and it's never black and white. It's never yes or no. But what is important is to have in mind yeah. Try to keep in mind your general picture, your your calls at the end, where you wanna go. And as you mentioned, I want to to explore and dissecting a specific clinical situation, specific indication. I want to position my new drug in specific setting to be, I don't know, second line, third line. So I mean, a strategy helps in the general picture. And then based on this, you you you choose the right path going there. So the right experiments and the right path. And being a CRO, what we we need to give is the two put on the table all the possibility. So we need to have all the technology, but at the same time, we need to have the capacity together to find the right way to use it and the right path. And because at the end, what we want first, yeah, we need to clear win win situation. The the success of the driver, the product is also our success, but definitely, ultimately, it's the success of the of the patient that we get this job. That's been fascinating. As I say, I will watch this podcast back myself to to learn more myself about drug resistance because I've learned a lot there already. So do you do you have any, closing remarks or comments on drug resistance? Yes. More in general than drug resistance. Last month, we we had a roadshow in Switzerland. We were making some presentation, meeting clients, and and collaborators. And I I had a couple of slides showing all the our model, especially model focus on on on resistance. So it means, sample coming from patients where we know the story of the patient. We know different therapeutic data got. Some of them are, a longitudinal sample so we can see the evolution here at the time. But then I was really looking at each single patient that of of course, for us are numbers, but behind there is a patient, there is some there's a person. And you see that the what this patient have to do. And so some of them, they were they they had eight line of therapy. And anytime we knew therapy because there is response or labs, new therapy, that I thought. So it's it's it's some way touching because it's, when when you made the translation you mentioned at the beginning from from from the left to the there is a there is a person behind. And at the same time, give you give you the strength The motivation. Motivation to move forward. Yep. That that's this something was touching me. So now I'm when I'm seeing these these lies with the long table now, always thinking about this. Absolutely. Exactly. We have to bear with us. The patient is waiting, and that's the that's the important thing. Here's here's to hoping that, all of these novel approaches and and, all the the ways in which we're able to model resistance, in the preclinical and clinical phases will allow us to find new approaches to subvert resistance and and and find those therapeutics that will make a major difference to people's lives. So thank you very much, Enrico. That's, it's been a pleasure speaking with you as always. I could sit and listen to you all day. My wife won't let me do that. So thank you very much for your time. Love you, my wife. You too. Really appreciate it. So thank you. And thank you for everyone, listening into this, this podcast. As we set out on on on Crowncast, it's a fairly new venture for for Crown. And if you've listened to this, we're really great. Really appreciate you Support again. I'll send this and hope that you've that you've got something out and enjoyed it. If you have enjoyed, today's episode, please do, be sure to hit subscribe on Spotify or on YouTube. 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