Head of Radiopharmacology, Champion Oncology

Denis Beckford Vera

Denis Beckford Vera, head of Radiopharmacology, Champion Oncology explains how patient-derived xenografts improve drug biodistribution studies and first-in-human dose accuracy.

Why PDX Models Improve Radiopharmaceutical Biodistribution Studies

Denis Beckford Vera, Head of Radiopharmacology, Champion Oncology, makes a case for incorporating patient-derived xenografts (PDXs) into the early stages of radiopharmaceutical development. He argues that doing so leads to more accurate, clinically relevant results and fewer costly setbacks down the line.

At the core of Vera's argument is the value of biodistribution studies conducted in PDX models rather than traditional immortalized cell lines. PDX tumors more faithfully replicate the architecture, vascularity, and receptor density of real patient tumors. They give researchers a far truer picture of how a radiopharmaceutical will actually behave in the body. Vera explains, "If you start early in the development using these patient-derived xenografts to evaluate the biodistribution of your radiopharmaceutical, even to choose lead compounds, you're going to have the real assessment of how your radiopharmaceutical is behaving."

One of the distinctive advantages of radiopharmaceuticals, is their inherent visibility. Researchers can directly observe where a compound travels and how it accumulates, making biodistribution an especially powerful tool for optimization. This real-time insight can streamline the path from preclinical research to first-in-human trials.

A major concern he raises is the tendency to overestimate first-in-human doses when relying on conventional cell line models, which often exhibit artificially high and homogeneous receptor expression. PDX models, by contrast, capture the heterogeneity seen across and within patients. Vera explains, "If you, from the beginning, use clinically relevant, preclinical models like patient-derived xenografts, you will have a real understanding of how much this drug is going to the tumor, and then that will directly impact the first-in-human dose estimation."

Ultimately, Vera's message is one of efficiency and precision, building on clinically relevant models from the outset reduces the likelihood of having to return for costly re-optimization later in development.

Editor's note: This transcript is a lightly edited rendering of the original audio/video content. It may contain errors, informal language, or omissions as spoken in the original recording.

I'm Denis Beckford Vera. I am the head of radiopharmacology at Champion Oncology. This is very related to clinical translation. So if you start early in the development using these patient-derived xenografts to evaluate the biodistribution of your radiopharmaceutical, even to choose lead compounds, you're going to have the real assessment of how your radiopharmaceutical is behaving. Moving from biodistribution, I think biodistribution should be the first type of assessment that you do preclinically in these, clinically relevant models, to understand where target engagement, for instance, in the tumor. How this tumor heterogeneity, and how this, tumor architecture, that mimics the patient's tumor, can really affect the biodistribution of the radiopharmaceutical, which is very tied to vascularity, for example. It is different in immortalized cell lines than in real patient samples. The receptor density and how the receptors distribute between the tumor and between, different patients and the lesions between the same patient as well. So you're going to get an idea of how this can really distribute. More importantly, you can really save time because with radiopharmaceuticals, you have something that you don't have with other modalities. You can see, you can see your real molecule. So if you are able to see where it goes and how it behave where it goes. So then you can optimize the process for later efficacy studies in this same tumor model. Even further, if there is a biologically relevant species, you can also identify off-target toxicity as well doing biodistribution studies, which is very important, very relevant to, to these types of treatments. From the beginning, you are evaluating your compound in clinically relevant models. You later don't have to come back and do optimization, what happens many times. So this is what happens, when you use biodistribution to assess a first-in-human studies and to estimate first-in-human doses. So many times, this dose is overestimated, based on these regular cell line-derived xenografts. We have high receptor expression, in many cases, has more homogeneous receptor expression. And then you're saying, you are getting a wrong understanding on how much your drug is really accumulating in those tumors. So if you, from the beginning, use clinically relevant, preclinical models like patient-derived xenografts, you will have a real understanding of how much this drug is going to the tumor, and then that will directly impact the first-in-human dose estimation. So you will not have to go back and do, or you will have the probability that you will have to go back and do so much optimization to improve in human doses and things like that, will be less likely, than if you went right.

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Denis Beckford Vera, head of Radiopharmacology, Champion Oncology, discusses PDX models preserving tumor architecture and heterogeneity, yielding clinically relevant data for more accurate radiopharmaceutical translation.

Improving Clinical Translation of Radiopharmaceuticals Using PDX Models

Denis Beckford Vera, head of Radiopharmacology, Champion Oncology, discusses the critical role of patient-derived xenograft (PDX) models in advancing radiopharmaceutical development. PDX models are created by implanting fragments of a patient's actual tumor into immunocompromised mice, a process that preserves the tumor’s original architecture, molecular characteristics, and inherent heterogeneity.

Vera emphasizes that traditional, simplified cell lines often fail to capture the complexity of human cancer, which can lead to biased data and an overestimation of drug uptake. To ensure accurate clinical translation, researchers must utilize models that mimic real-world conditions rather than relying on oversimplified systems.

Vera further explores the importance of biodistribution studies, which are fundamental to developing radiopharmaceuticals. By utilizing a larger cohort of PDX models, researchers can account for heterogeneity between different patients. This approach provides a much clearer picture of how a lead compound will behave in a human clinical setting.

As Vera explains, "The more that you involve this patient-derived xenograft, the biggest the cohort or the biggest the number of patient-derived xenograft that you use, even within one disease, is going to give you way better and more information on how your compound will really behave in a real scenario or in the clinic." Ultimately, the interview underscores that the power of PDX models lies in their ability to provide the biologically relevant data necessary for successful clinical translation.

I'm Denis Beckford Vera I am the head of radiopharmacology at Champion Oncology. Patient-derived xenograft model are created by implanting, fragments of real patient's tumor into immunocompromised mice. What is very relevant of this model is that this approach research preserves much of the tumor's original architecture, heterogeneity, and molecular characteristics, which it is very important when you are translating targeted drugs, and in this case, targeted radiopharmaceuticals. Because, as we know, cancer and these diseases are very heterogeneous. And, most of the time, we really use very simplified, tumor models or cell lines that really don't express the real architecture of patient samples. Therefore, using patient-derived xenograft can really mimic what may later, later happen in the clinic, if you are assessing your radiopharmaceutical of your, lead compounds, in patient-derived xenograft. Let's say, rather than mentioning specific examples, I'm going to say in general, when patient-derived xenograft can really, change the development plan or the clinical translation, and again is similar. So if you have, cell lines that have very homogeneous receptor expression, for instance. So you may overestimate your drug uptake or your drug behavior in preclinical models. While if you have patient-derived xenograft, and I like to repeat that because it's very important that it keeps the architecture, the receptor heterogeneity expression, and as well a molecular characteristic of patient samples. Between patients and within a patient, if these samples are taken from the same patient or from different patients, you are really, getting the behavior of the drug that you really need in the, in the clinic. Basically, if you are oversimplifying your model, your animal model, you are basically lying to yourself. So you don't have the opportunity to really see which, the real behavior you sample. More importantly, the patient history. The patient history in those tumors. If you are already targeting a specific disease, you are going to be able to see if a standard of care of other drugs have not been working for that particular tumor or for that particular set of patient populations. So this is gonna be very powerful in translating your radiopharmaceutical, for example. So biodistribution studies are key to developing radiopharmaceuticals. And this is because with radiopharmaceuticals, you have the ability to see. You can treat what you see, and you can see what you treat. So biodistribution studies are probably one of the main components of, developing radiopharmaceuticals. And then we go back to the model. If you are developing, your radiopharmaceutical doing biodistribution, which biodistribution is tied to biology. So if you are oversimplifying your biology, again, you're lying to yourself. You are not really getting the real outcome. You are biasing the outcome. Whether if you use preclinical model with real clinical samples or clinically relevant, animal models, you are really getting the data that you need. The more that you involve this patient-derived xenograft, the biggest the cohort or the biggest the number of patient-derived xenograft that you use, even within one disease, is going to give you way better and more information on how your compound will really behave in a real scenario or in the clinic. You can not only evaluate the heterogeneity of this disease between patients, but also within the patient, if these samples have been taken from the same patient, but from different part of the disease or different part of the patient as well. So it's gonna be very powerful because it is all related to biology.

Denis Beckford Vera

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