Arsalan Arif: Hi, everyone. Arsalan Arif here with Endpoints News. We hope you're enjoying our programming today at ASCO. I'm excited for this next session, How to Accelerate Development in Novel & Advanced Oncology Therapies-- From the Starting Line. We're sponsored by Novotech, and I'm excited to introduce our expert panel today.
We have joining us Vishal Navani, the Staff Medical Oncologist and Professor of the Tom Baker Cancer Centre, University of Calgary in Calgary. We have Kedan Lin, the Senior Vice President at Harbour BioMed in South San Francisco, USA. Michele Gerber, the Chief Medical officer at Myeloid Therapeutics in Cambridge, USA. Jayesh Desai, Professor and Medical Oncologist and Clinical Research Head, early drug development at the Peter MacCallum Cancer Centre in Melbourne, Australia. Of course, Patricia Mucci LoRusso, the Director of the Early Phase Clinical Trials Program and Associate Center Director, Experimental Therapeutics of the Yale Cancer Center in New Haven, Connecticut.
This webinar and all of our sessions at ASCO will be available on demand to rewatch or to share with your colleagues. Let's get started with our discussion session. Let's start by sharing insight on the ways that we are seeing technology such as CAR-Ts, ADCs, immunotherapies, and mRNA advance and innovate oncology development. My first question is to you, Patricia and Jayesh. What do you consider the most innovative areas, and where do you consider the real opportunities for advancement in oncology development right now in your view?
Patricia Mucci LoRusso: First of all, that's a million-dollar question. If we had the magic ball, we would probably be able to cure cancer. I think there are a lot of really exciting areas currently that we should all take note of. First of all, I still think that targeted therapy is exciting, and more and more we're coming up with drugging the undruggable targets, which to me is extremely exciting. I think the challenge will be in how we can advance some of those agents forward, especially in combination therapies because of the multiple pathways that are involved in several of these tumors and upregulation once you inhibit one pathway, et cetera. I also like antibody-drug conjugates.
I think that we are going into a really exciting time with antibody-drug conjugates. Although right now, I think last year, there were 454 antibody-drug conjugates in oncology that were in clinical development. Although the payloads are cytotoxic agents, I think that ADCs give us the opportunity to deliver those cytotoxic agents in a unique way that we did not have previously, almost akin to giving continuous infusion or continuous administration, altering the kinetics of the cytotoxic agents, delivering it more specifically to select targets, and hopefully, enhancing the therapeutic benefits of those payloads. I'll stop here. I'm sure that Jayesh has more to offer. I will give him a few minutes to tell us about what he feels.
Jayesh Desai: Sure. Thanks, Pat. For us, as Phase 1 investigators, there's no question that some of the new technologies really excite us. I think it's the precision in which things can be done now as far as the drugs are concerned, and ADCs are a great example of that. They've been around for a long time, but there's been this real inflection point that we've managed to get over in the last couple of years. Some of that is about the drug and the technology. Again, as I said, the precision and that balance between the warhead and the payload and how we might deliver that in the best way possible. I think that's really exciting.
One thing I will come back to, though, is-- If I think back to when I was training in drug development, there was a line that really resonated with me that came from some of my mentors, and people like Pat are included in that. That is that, it's all about the target, meaning that you can come up with the coolest drug possible, but if we don't understand the context in how we're using that drug in the patient that we're treating, we're not going to get anywhere, or the impact we're going to have is not going to be anywhere near as good as what it needs to be.
That's why, Pat, again, coming back to the comment you made about targeted therapies, all of these approaches, for them to work need to have an understanding of how we're going to do this in the patient, understanding the target, understanding the context in terms of how that patient is going to manage that. Those principles have not gone away. In fact, I'd argue that they're probably even more important now than they were before. I think that for us as the industry, as biotech, as CROs, as pharma, and as of course, as the investigators that are working with our patients, those comments are going to be things that I think we will keep coming back to, right, during the discussion.
Patricia: I think, Jayesh, please correct me if I'm wrong, but don't you think that immunotherapy is challenged with that currently? We're developing very exciting and naval immunotherapeutics. Unfortunately, the preclinical models are not there, and we haven't really identified in a prospective fashion biomarkers that are actual targets for delivery of many of these drugs. Although we're developing many immunotherapeutics targeting many novel targets in the immunology of cancer, I think right now the greatest challenge is who do we give those drugs to? How do we administer them in combination or in monotherapy? What is guiding us as to what the best IO therapies, monotherapy, or combination are for specific patients in diseases?
Jayesh: Yes, absolutely.
Arsalan: Wonderful. Michele Gerber, I want to bring you into this conversation now. Could you share some of the insight into the focus at Myeloid Therapeutics and where you may be seeing some of the opportunities and innovations similarly?
Michele Gerber: Yes, absolutely. Thanks to Novotech and Arslan for having Myeloid join you. As you know, we're in the field of immunotherapy. We do know that the other modalities that you discussed, the CAR-T cells, ADCs, and other immunotherapies are providing great examples of clinical activity, especially evident in hematology. However, they lack durability in solid tumors. We believe that also the immune checkpoint inhibitors and ADCs have improved outcomes in solid tumors, but only for a limited subset of patients. At Myeloid, we're looking forward and we have several objectives to meet the improved outcomes for many patients receiving immune therapies.
The first objective is we believe it's very important to access the tumor microenvironment. Next, once within the TME, a key objective is to overcome the immunosuppressive environment and drive a sustained immune response. Finally, a third objective is to preserve accessibility, including manufacturability and value for the patient and society, including the availability of off-the-shelf products. At Myeloid, we are meeting these objectives by using RNA to genetically modify myeloid cells. Myeloid cells are known to be the primary orchestrator of the immune response. We know that the medical field has been harnessing myeloid cells in the form of infectious disease vaccines for well over a 100 years. More recently, the approach is extended to cancer.
We observed in the recent trials that Moderna with Merck and BioNTech with Genentech have targeted myeloid cells with their personalized vaccines and yielded promising clinical results. However, these modern vaccines deliver neoantigens derived from the patient's own tumor as the mechanism to support an immune response. In principle, the effort to isolate and present the neoantigens makes sense from a canonical immunology perspective. However, the identification and prioritization of neoantigens using ex vivo laboratory methods also relies on predicting correctly whether the presenting peptide sequence can successfully induce an immune response.
Overall, the identification of neoantigens from patient samples is complex and time consuming. As I will describe next, these approaches may be suboptimal, relative to the in vivo approach that Myeloid Therapeutics is developing. Furthermore, these vaccines do not address the earlier objective of penetrating the TME. As an immunologist by training, I'm still hoping for convincing data that merely activating T cells in the periphery will be useful beyond the adjuvant setting. Here at Myeloid, we are using
the in vivo delivery of mRNA-encoded chimeric antigen receptors that program tumor-associated suppressive myeloid cells to induce an innate immune response with recognition and killing of tumor cells.
This allows the liberation of novel neoantigens for natural in situ presentation to T cells. To summarize by this approach, we allow human biology to take on the task of neoantigen identification and prioritization, and thus to present all the available neoantigens. We see this as an optimal and more rapid approach to personalized therapy, all occurring within the patient. Myeloid has illustrated this approach in rodent models and safety studies have been performed in non-human primates. The findings all support our clinical trial targeting Trop2-expressing tumors, which we expect to initiate in August of 2023.
Arsalan: All right, thanks for sharing that. Kedan, I'd like to move on to you and to learn a little bit more about the breakthrough medicines and your focus at Harbor BioMedicine.
Kedan Lin: Wonderful. Thank you and also thank the Novotech for inviting me to this very interesting discussion. In Harbor Biotech, we as a company really facing the same challenges as all the other company. In this oncology space, how do we combat resistance, how do we utilize the existing target? Our approach, we're using the so-called, basically a heavy chain-only platform generating a fully human antibody. This characteristic of this type of platform is that this is a fully human and a very small size can achieve much better penetration compared to other antibody.
Most of all, it actually can achieve very versatile functionality. Basically, you can plug and play into multiple platforms. For example, you could actually use this HCAb fused to antibody and protein and then generate IgG-like bispecific antibodies. This bispecific antibody can actually generate a new novel biology. The second application for this HCAb, you can actually attach to the cells, and those can be utilized in the bispecific CAR-T cells, in the CAR-T NK cells. The third application of our platform, you can conjugate it to the payload, and as mentioned earlier, for the cytotoxic payload, for radioactive payload, and this also for PROTAC.
Again, this can target a protein degradation, can target a tumor microenvironment. This is really amplified its application. Lastly, our platform can also pair with nanoparticles. This, again, can deliver mRNA and LNP expression and caps and all biospecific antibodies and conjugated to nanoparticles for targeted drugs delivery to various cargoes, including gene editing and other things. By and large, we're basically addressing key questions in the oncology field, and then present additional flexibility and also a new versatility. A versatile tool for targeting novel therapeutics. Thank you.
Arsalan: Wonderful. Thanks for that. Vishal, I just want to quickly bring you into the conversation before moving on to our next topic. Vishal, tell us what do you find most attractive or interesting in a new therapy.
Vishal Navani: Thanks, Arsalan, for the question, and Endpoints, and Novotech for having me. It's a pleasure to be on this panel with these colleagues. Firstly, unmet need is this compound active in an area with poor prognosis, lack of other therapeutic agents, or asymptomatic burden. Is there a biomarker that's ideally easily identified even putative biomarker, because we know from the data that having a biomarker that's accessible, easily identifiable increases the chance of success at every phase of clinical development.
I think as we move into this new world of new mechanisms of action, we need to think slightly differently from using old measurement schemes such as resist, for example. Historically, we've used resist and resistors, didn't use a lot successfully to determine early phase promises of success or activity. Ask a patient, do they care if a tumor shrinks by 29% or 31%? Is this a partial response or
or stable disease, probably they won't care, and probably they want long-term disease control, toxicity free and durable.
As we use new agents that have new tumor kinetics like T-cell engagers to Tebentafusp-tebn and uveal melanoma, or Belzutifan, your HIF-2α inhibitor in renal cell that have long episodes of stable disease control, potentially, without imaging response. That's meaningful to patients, and I think we have to get more flexible and up-to-date in our assessments of patient benefit with novel time-to-event endpoints, like a stable disease or duration of response.
I also think that medicinal chemistry capabilities are exploding. We can now target transcription factors at the cellular level in renal cell carcinoma, for example. Lots of these mechanisms are exciting. As a field, we need to update our own early surrogate endpoints to be able to keep up with the dynamism of the underlying improvements in medicinal chemistry and in their therapy.
Arsalan: All right. Wonderful. Let's move on to my next topic. Let's talk about clinical trial design and how a clinical trial should be set up. Patricia, I'd like to discuss with you early phase clinical design and your experiences here. In particular, what ways have you seen clinical trial design being an impediment to regulatory success? Any tips on how that might be avoided in your view?
Patricia: First of all, I've been doing this quite a while. I can honestly tell you that in the 20-some years that I've been doing this clinical trial design in early phase, Phase 1 or early phase clinical drug development has really changed and really morphed. The trials, I believe, are becoming more complex. We're trying to pack more and more into one trial. We're trying to get multiple answers, whereby back when I first started, the primary objective was primarily identifying the recommended Phase 2 dose.
It's still a primary objective but with many of the drugs, we're not pushing to maximum tolerated dose, or some of the drugs don't really have a maximum tolerated dose. It may be a maximum financial dose or a maximum biologic dose. Although we're trying to identify what that dose is, and that hasn't changed what dose we're going to carry forward, because of the complexity of the science that's involved in many of these novel agents, the trials have become much more complex, and the demands and the data points have become significantly greater.
In some ways, that does present a regulatory hurdle. However, you must keep in mind that regulators' primary responsibility, especially with early phase trials, is first and foremost, safety. We have to assure safety as we're trying to answer pivotal questions. Like I said, we're trying to bring more and more answers within the context of a single trial with limited patient numbers. The number of exploratory endpoints has really exploded in many of these trials relative to what we used to see several years ago. Jayesh, what do you think about that?
Jayesh: Absolutely, Pat. I think it has to come back to, as you said, there are some very basic things that we have to meet as part of that Phase 1, the dose escalation part of it.
Jayesh: If we can't come up with an appreciation of dose and schedule, and at least some idea about how to do that in a safe and manageable way for patients, then we're never going to get the chance to do that again. That's a message that we constantly feed back to our colleagues as we're working on trials. I think that part is absolutely critical. The second is, how much burden can we put onto a patient who is participating in a trial?
I think if that's justified, what we are doing is something that we can learn something from, I think our patients are really happy to go along that journey, but if we're doing things for the sake of it, I think that starts to become really, really difficult. I think all of us around the call need to continually question everything that we are asking in that trial, what are
we really trying to achieve, and are we going to achieve that? Does it look good on paper? We're actually going to get that data and we're going to learn from it and really interrogate ourselves in being able to do that. I think that's really key.
Arsalan: Wonderful. Vishal, let's get you also in this part of the conversation too. How about any early phase of protocol considerations in your view that could reduce any enrollment barriers?
Vishal: There's been some recent FDA guidance on improving eligibility and minority representation in trials and expanding access to trials so that they already reflect the populations that the end putative drug may serve. I think that's really important. I think that sponsors need to work hard in helping a broader panel of potential patients recruit onto trials and deal with the language, communication, health literacy barriers that may prevent the patient from enrolling onto an early phase trial.
When a protocol comes across my desk for feasibility, I'm just looking for red flags early on to say, "Why could I not do this?" To Jayesh's nice points about schedule of assessments that may be particularly onerous, red flags like mandatory fresh tissue or repeat on-treatment biopsies or onerous peak over 48 hours, I've seen all of these in protocols. We need to think really hard about why we're doing that because not only is that going to make an investigator not likely to open, but a patient unlikely to stay on the trial for long enough so you can collect the precious data that you need to know about this drug.
I also think we need to think as a field more broadly about expanding inclusion criteria, especially in the early phase setting. These highly selective patient populations at large academic centers, like Pat's, Jayesh's, and mine, often don't represent the underlying patients that may be served by the drug if it gets through to regulatory approval. We need to be pretty engaging in expanding the access to early-phase trials across different types of center.
I would encourage sponsors to work with cooperative groups to increase community oncology representation in that regard. That's great from a patient volume point of view too, if they have early phase capabilities and thinking hard about baseline organ function and performance status requirements to try and broaden the inclusion criteria and help the enrollment.
Arsalan: Very good. Patricia, let me ask you about any new recommendations in your view around study design from the regulators, from the FDA in this context. For example, any, like a three-by-three study design, moving away from that now, what other new recommendations from the regulators in your view?
Patricia: Well, there have been several guidelines that have come forward, some being biostatistical guidelines, but also identification of the most relevant recommended Phase 2 dose, such as Project Optimus, at least in the United States. Many of these drugs go on to get FDA approved in the United States, I think implementing guidelines or recommendations like Project Optimus that are actually going to be required is going to actually impact drug development clinically globally.
Project Optimus is trying to identify what the right dose is instead of giving too much of a dose because it's the maximum tolerated dose. Perhaps less of a dose that can allow the patient to maintain on that agent more chronically without dose interruptions or dose reductions is one of the recent driving forces within the FDA guidelines. Trying to maximize efficacy but minimize toxicity.
There's been a big push for that, not only by the FDA, but advocacy groups have pushed for it in hopes that we're no longer pushing a drug so high that you have to have so many interruptions that it may actually, in the long run, be less efficacious. Also, there's a lot more input into more novel biostatistical designs. BOIN designs are becoming more commonplace in early phase trials, like type BOIN designs as an example with immunotherapy or Bayesian designs. Trying to maximize the information across the patients
spectrum and not just within three patients within one dose and I think that these are novel biostatistical designs that actually lend us to be able to get as much information as possible from each patient.
I think the way forward is going to be away from 3+3 and more towards these designs so that we can maximize the data that we're obtaining from each individual patient into a collective amount of data so that we can hopefully get it right as early as possible within the context of a Phase 1 trial. It's a well-known fact, especially with targeted drugs, that we would get a recommended Phase 2 dose, and 45 to 50% of the time conservatively it's been shown that that dose is not the right dose in Phase 3 and that's a very expensive error. 9% of Phase 3 trials had historically been aborted because the wrong dose was chosen to advance forward and it's not only financially expensive, but it's horrifically bad when you think of the potential outcome of the patients. I think trying to get it right as early as possible by adding additional cohorts as we have been recently with Project Optimist as an example, is very, very important.
Arsalan: Very good. Jayesh, I wanted to ask you about Australia actually and in terms of Australia and the regulators. Just simply put, is Australia aligned with the FDA and the FDA's recommendation for early-phase oncology research?
Jayesh: Yes, it's a good question and the answer is very much so. Pat put it so well in the sense that I think we don't think that the changes that have been made by the FDA for example, as a regulatory agency have been…. For the most part they've actually been really positive. We want to move into an era where we are using more risk-adapted study designs. That's what we do in clinical practice every day. We don't look at things in a black-or-white way. Most of what we do is pretty gray actually and the field for how you interpret how a patient is responding to treatment or toxicity they might have or the issues they might have.
I think the way we see it is that these adaptive designs are now allowing it us to an extent. To actually bring that into practice in a, what was traditionally, a pretty hardwired space as far as our 3+3 designs. The difficulty has been essentially aligning how the statisticians view this and how us as clinicians view it. We can both understand things in the same way and I think that's happening much more so now.
I'd say 10 years ago, Bayesian designs were probably something we struggled with a little bit more. I think we've adapted pretty quickly now and we've got a good understanding of why we are again, not looking at something as being a yes or no, but actually there's a lot in between. Using that information, we are learning from each patient as Pat described. To be able to help us in making the right decisions. I think that's critical.
Patricia: When we're discussing cohort escalation and toxicities, et cetera, within an individual cohort, the biostatistician is reviewing that information with us but there's still the human component or the clinical researcher component to this assessing whether or not, it is safe to advance to the degree that the biostatistician feels based on what we have seen in our clinical practice when we're treating these patients on these trials. What I find is, as a result of these novel designs, we recognize more importantly than ever the team approach to early phase trials is in the team approach to understanding the complexity of escalating doses and also identifying the most relevant dose or doses to advance forward.
Arsalan: All right. Wonderful. I want to move on to my next topic here And Pat, you were actually just addressing a little bit ago about the Bayesian trial designs over here, but I just wanted to double-click on that a bit
here and allow you to expound a bit and Vishal please too if you can, what role do you see in these Bayesian data playing in the early phase trial design moving forward?
Patricia: We're seeing, it's not just the Bayesian designs, there are other designs that are also very important such as BOIN, as I stated before. Honestly, especially with some of these novel agents, these designs are becoming more and more important. I don't know that we can answer all of the questions we need to. As I stated before, these trials are becoming more and more demanding in terms of the questions that they want answered, even if many of the questions are exploratory. That's why I think many of these designs are going to be pivotal to helping us at least preliminarily coming up with answers to many of these questions. I think that these designs are here to stay. I don't know. Jayesh or Vishal, what do you guys think is clinical research?
Vishal: Well, I was a resident at the ACORD Trials Workshop when Pat LoRusso came and gave the lecture on early phase trial design. I'm going to differ a lot to Pat, but really I think that there are so many endpoints needed from these early phase trials and so much data required that using a Bayesian approach or a BOIN approach gets the most out of each patient's kind voluntary time that they spend with us on a trial.
Using what you believe to be prior knowledge and integrating that into the trial outcome, and then getting an updated belief that's what Bayesian approaches are is much more encompassing than just the normal frequentist approach which is just looking at the data in a silo and not knowing what came before it which to me always seems more muddy and less elegant.
I like model-assisted designs like BOIN because they're flexible. Let's say for example, you have a bispecific trial and you're worried about a specific toxicity like cytokine release and everyone's anxious a bit about that at the moment. Well, you can set a dose-limiting toxicity rate of 10%, let's say, for argument's sake with BOIN. Whereas using a rule-based design like 3+3, you can't really do that.
You can help allay investigators' fears and clinicians fears about specific toxicities which is really nice. Also time-to-event endpoint BOIN, for example, immunotherapy has late toxicities. A lot of these novel immunotherapies may have late toxicities and they can be impactful and need a lot of input. If you use a rule-based design, you may not capture that.
Your late toxicity may not be captured. If you use a time-to-event point, it can capture toxicities throughout the entire time the patient's on therapy, rather than just waiting for one
experience of dose domain toxicity. That's it. That's all the data that you can extract. I think it's more elegant and more efficient from that point of view.
Another piece about novel trial approaches I guess to move away from patient is, we're using circulating tumor DNA so much now in both the response to therapy piece in the metastatic setting, and that's moving earlier and earlier into the clinical trial development paradigm. Normally we're all very used to looking at waterfall plots for recess defined response.
Well, I think looking at the way the data and the field is going, it won't be long before we look at molecular waterfall plots before we look at ctDNA reductions, hopefully in log quantities like the hematologists get to do and look at these molecular waterfall plots similarly to our imaging waterfall plots to identify particularly promising novel therapies.
Arsalan: Great. Wonderful. Actually Michele, I wanted to ask you. I understand myeloid, you've incorporated this Bayesian study design into your program, why?
Michele: Yes, absolutely. I think for all of the reasons that Pat and Vishal have mentioned, as you know the 3+3 design was really designed for chemotherapy and for determining the maximum tolerated dose. With gene and immune targeted drugs, we really need to find out what the optimal doses
which may not be at the maximum tolerated dose. We believe that the Bayesian designs were the best way forward for our project. We believe that they improve the precision of the safety profile and allow earlier information on the therapeutic index.
As also was mentioned, there's really two main Bayesian designs, one on model-based and the other model-assisted design. Which one you choose is dependent on operational feasibility, including the expertise and infrastructure with the model-based designs being much more difficult to implement. The model-assisted designs include the BOIN design, which everybody has discussed. That's what we've chosen to use in our in vivo program.
Choice was really dependent on financing, the really ease of implementation and desire to define our safety profile with precision and to begin to understand that therapeutic index very early in development, so that we can optimize and understand the efficacy to the safety or the therapeutic index of our product. When we're ready to go into large Phase 3 programs, we already have a very good idea of what the therapeutic index will be for our product.
Arsalan: Similarly, Kedan, I'd like to ask you, is this Bayesian study something that Harbor Biomed has considered?
Kedan: We have not implemented that in our study, but the overall principle are pretty much, very much identify with the speakers here. We definitely need to incorporate that in our design. At this stage, we are addressing it in a much more pragmatic way. For early programs, we want to achieve proof of concept stage very quickly. We have those endpoints in mind and we remain very flexible. In addition to a traditional 3 +3 design, we incorporate those parameters in there and it really fits for purpose design and we are open to all different level, different kind of design and incorporate that in there as well and it remained flexible.
Arsalan: Wonderful. Okay. Let's move on to our last topic here. Accelerating clinical development timelines here. Michele and Kedan, I'd like to get your perspective here first. From a sponsor's perspective, from where you sit, what aspects need to be considered in defining a really full clinical program?
Michele: Go ahead.
Kedan: Okay. Sorry, I can take a shot at that first. I think for a company like the Harbor, we're a small company, we have limited resource. There is really for our considerations, we want to achieve right to a place very quickly. It really depends on the target and therapeutics we are dealing with. It's again, fits for purpose. For example, for molecule with novel mechanism, which has first-in-class molecule, we want to achieve quick design of quick experiments. We selected an indication, it may eventually, may never be approvable indication, but we wanted to prove this biologically make sense.
The pre-clinical data can be adequately authentically translated to clinical efficacy. Those are the indications we wanted to target. Those are for first-in-class molecule. On the other hand, for best-in-class molecule, for…molecule, and those are the ones we need to identify a niche indication. Those niche indication can enable us to quickly identify a regulatory approval pathway. For example, we have a second generation CTLA-4 molecule. This one in our molecule, we believe because it's the enhanced ADCC, it's better than AP, but as you know, AP has occupied a tremendous approval landscape.
For us, we really need to find an indication that it's not being occupied, but yet we have quickly show our advantage. Meanwhile, I think that one of the key consideration in all of that is seeking feedback on regulatory. Previously,Pat and other people mentioned Project Optimus, all of those things. We need to be able to have the end game in mind and encode those component in our study design. Don't do it too early because we don't have the resource to do it. To do that, once we have the POC data, we engage in there and remain flexible.
FDA does not necessarily have a very prescribed way of when you should do it and how you should do it. They're very open. They're very open to the suggestion, to the feedback. And they're also going to address it case by case, right? We have experience bringing our study design to FDA and they had some questions. They wanted more data, we show it to them, it's not necessary feasible. They actually show the great level of flexibility.
You can also, in addition to the data, we have the modeling approach, the integrated full-on-- Just the modeling and simulation could make up the deficiency in the data itself and get us there very quickly. Again, and like said, it's really target and therapeutic-dependent fit-for-purpose design and integrated with the regulatory feedback. Those are the things that we have experienced on our end.
Arsalan: Michele, anything to add?
Michele: Yes, so for our company, really having a very strong scientific and early clinical foundation, which will provide assurance to the regulatory agencies, to the patients, and to our clinical partners that we have the foundation for a good development plan, which will lead to a safe and effective product for patients with unmet medical needs, so really having that strong foundation right from the beginning.
Arsalan: Okay, wonderful. Jayesh, I just want to ask you another quick question about Australia. Here, we talked about the early phase oncology, but what about any regional advantages in accelerating a Phase 1 study? What might the US regulators think about Phase 1 data from Australia?
Jayesh: Yes, sure. It's a good question. Look, in Australia, we've had good alignment between investigators' sites and our regulatory agencies as well and obviously, our ethics committee in between that. It's been an environment where we've managed to get things going very quickly. Our activation timelines are very good and I think that's been attractive for industry.
I'd like to hope that industry comes to Australia because of the quality of the investigators and the sites, not just because we do things quickly. Look, I'll start by saying trials are global, and Phase 1 trials are largely global as well. That's why we know each other well on this call, for example. To date the strategy of beginning a first time in human trial in Australia and then, for example, moving that to the US, as you move through dose escalation or even towards the latter parts of dose escalation. That's something that we've done many, many times and I'm not aware if there'd been any issues with the … trust or the integrity from data that's come from Australia, and New Zealand for that matter. We work a lot together. I think it's certainly a good option. It's a good pathway that exists. As I said, I think it's because of the quality of the work done here rather than just because we do things quickly.
Arsalan: Oh, wonderful. Michele and Kedan, I want to ask you through site selection rationale for your current trials, and if you are actually using any Australian or AsiaPac site to support your current clinical program. Maybe Kedan you could start first.
Kedan: Sure, we have. As a matter of fact, I totally identify with what Jayesh just said. We actually have opened up sites in Australia. It actually does have advantage. We kept having a very quick start and the data quality, the….quality is excellent. We have wonderful experience with Australia and then it also serve our purpose. You allow us time to initiate other sites in US, in other region of the world. Using its timelines, much more, much delayed and we can actually leverage the data we obtain from Australia to open up the site trials in US or in China or somewhere else.
This has been, but again, it's dictated by your overall global development strategy and Australia can really provide a pivot point and engage you, then hit at the milestone, which is the first patient dose very quickly and it get you to hit to the escalation stage very quickly. I also wanted to mention, because of the diversity in Australian population, now you have a huge input of Asian population in addition to indigenous people and then the Caucasian, all that.
That actually can help meet the requirement of FDA in terms of the diversity, the genetic and complexity, everything. This actually, overall, serves the very good purpose. You have companies, CIOs, like Novotech can actually help us get there because they have very strong presence in Australia. They help the sponsor get to the key decision point very quickly. I emphasize the speed because at the end of day, this is the money, and this is also the time that bringing those much needed therapeutics to meet unmet medical needs, to meet the patient's needs. We have had a wonderful experience in Australia.
Arsalan: Michele, how about you are using Australian AsiaPac sites?
Michele: We are actually initiating our trial for our in vivo program in Australia. We have decided to go there first and foremost because of the excellent medical system that exists there and the very strong Phase 1 units. Also, we are using a lot of academics to support our translational program. In addition, the regulatory pathway is very well defined. It's easy to navigate and very efficient. Lastly, very importantly for a small biotech company, the trials are less expensive than in the US, and that supports our needs to really conserve funds. We are very much looking forward to opening our trials in Australia. I am working very closely with some sites now to get it up and running.
Arsalan: I wish both those trials, lots of luck. For my final question here, Pat, I would love to get your take first on this, please. For a biotech or pharma that is entering the clinic now and wanting to build the best possible program. Another broad question for you here, Pat. What's your one key piece of strategic advice?
Patricia: If you don't get it right in the beginning if you're a small biotech, it's hard to go back and start over. I've very much appreciated what the biotech, Kedan, and Michele have said today. It's important to have sites where the investigators are invested in the trial, know their patients, and know the study. Where the support teams are consistent, the turnover is not that as great.
We did have turnover issues with COVID, but institutional memory or protocol memory is very, very important. I can honestly tell you that I've really enjoyed working with Australian sites, outstanding investigators. Outstanding investigators as well in the United States. You want investigators that are going to be engaged, that are going to know the patients, that are going to know the protocol, and are going to know the drug because if you're a small biotech and you don't get it right, many times you can't repeat it. Maybe both people, Michele and Kedan, maybe you can agree or disagree with me, but it's very important to choose your investigators wise.
Kedan: Absolutely. Not only small biotech, even big company. I used to work at Genentech, if you don't get things right, there's no second chance, so ship has sail. We really need to think very hard, very early on what the design is, how you're going to conduct your study. Absolutely. Totally agree with you.
Arsalan: Yes. Michele, any other comments from the sponsor side over there before I turn it over to the academics again?
Michele: No, absolutely we have to have the right trial design and I think the emphasis on working very closely with our investigators who know the patients, who understand our product is really critical, and so far I've found in Australia that those investigators are available and committed to bringing these therapies and understanding these therapies in the full spectrum of what's available.
Patricia: I have a saying that I tell people, all that is investigator and all that is Phase 1 site is not created equal.
Arsalan: That's sage advice. What else do you have to add over there, Jayesh or Vishal for other doctors on the panel here?
Jayesh: Look, you can tell I'm itching to say something. I couldn't find a better way of saying it than what Pat did. I completely agree with that. Remember, when you're doing a Phase 1 trial, the Phase 1 trials that work really, really well are the ones in which we truly come to this as partners. As equal partners and partner means responsibility
as well. I think a really good Phase 1 trial is one, and this is particularly with biotech, but even with bigger companies. When we approach it as being like an investigator initiating trial, you want your investigator to think that this is their baby. This is their thing that they're actually taking care of and that they're working in partnership with you, with the patients to really bring that forward.
That engagement is what's really critical because that's something you can control. There's a lot you can't control in what goes on, but you can control that dialogue and exchange of information and that shared responsibility that goes with that as well. The reason why we do Phase 1, part of it is we are really interested in the science. We want to work with the great scientists and they often will come from biotech, for example, or industry. We want to do that in partnership as well. It's a really important part of it.
Patricia: Arsalan, one thing I recently had to give a talk about my journey and what I've done and I had to list all of the drugs that I had been involved in that subsequently became FDA-approved. I called them my babies.
Arsalan: Yes, yes. I can imagine.
Patricia: They're our children. When they become FDA-approved, it's almost like they've grown up, graduated from high school and went to college, and got a job.
Arsalan: Yes. That's wonderful. That's going to be our time for today. Let's just leave it at that Pat. That's just really wonderful. Thank you, Vishal and Jayesh, and Kedan and Michele, it was really wonderful moderating this discussion. Clearly, you guys know each other over here fairly well over there, and I wish you all the most success.
Thank you for taking your time and sharing your expertise with Endpoints audience, and joining us virtually for ASCO. I just want to remind everyone in the audience if they want to rewatch this session or share it with your colleagues, a link for on-demand viewing will be sent to you all next week.
I'm Arsalan Arif for Endpoints News. Thanks for joining us and we hope to see you at a future event. Thanks again, everybody.