Project Optimus Series | Operationalizing Dose Optimization

In this episode, we continue our exploration of Project Optimus and the evolution of dose optimization in oncology drug development. Following our discussion on regulatory expectations in the previous episode, we now turn to the operational challenges and strategies required to implement optimized dosing in real-world settings.

Host Dr. Wael Harb is joined by Patrick Melvin, Vice President, Oncology & Hematology and Global Head, Novel and Emerging Therapies at Syneos Health, to discuss the complexities of operationalizing Project Optimus. Together, they examine how drug developers, investigator sites and patients are affected by these changes, the role of adaptive study designs, and how AI-driven technologies and digital health innovations are helping to streamline dose optimization.

Tune in to gain valuable insights into the future of precision dosing and the long-term benefits of this industry shift, from improving patient outcomes to enhancing drug development efficiency.

The views expressed in this podcast belong solely to the speakers and do not represent those of their organization.

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Transcript

SPEAKER_01 0:00

Welcome to another episode in our podcast series on Project Optimus, where we explore the evolution of dose optimization in oncology drug development. In our previous episode, I spoke with Zura Lamri, a regulatory expert, about the regulatory expectations and challenges introduced by Project Optimus. Today we're shifting our focus to the operational side of dose optimization. How companies can implement optimized dosing strategies in real-world settings and what challenges they face in the process. I am honored to have Patrick Melvin, Vice President of Therapeutics Strategy and Innovation at Project Delivery, join today. Patrick brings extensive experience in operationalizing clinical strategies, and we're going to explore what implementing precision dosing means for sponsors, investigator sites, and patients. Operationalizing dose optimization. Next on the Sineas Health Podcast. Patrick, welcome to the show.

SPEAKER_02 1:05

Thank you, YL. It is indeed great to be here. Thank you for the invitation. And I'm glad to be joining your second part in your series here. The podcast you did with Zora Lomery, our regulatory expert, was fantastic, very informative. And pleased to be here with you today to talk about operationalizing Project Optimus. You know, this is a time of discussion, indeed, as many, many companies, both in the US and abroad, are trying to understand how to transition from traditional dose escalation models that we have used for decades to optimize dosing strategies and managing the operational complexities that come with this transition.

SPEAKER_01 1:45

Let's start by defining what really means by operationalizing Project Optimus. We often discuss the scientific and regulatory aspect as we discuss with Bombera, but when it comes to making this work in real-world drug development, what does it entail?

SPEAKER_02 2:02

Operationalizing Project Optimus means sort of taking the FDA's guidance on dose optimization and translating that into practical, executable strategy in the management of early phase oncology clinical trials. It genuinely impacts every facet of our industry in when we talk about early phase oncology drug development. And by that I mean regulatory interactions, manufacturing, clinical trial design, of course, patient recruitment, data cleaning, data collection, and all the way out through commercial planning. For decades, the traditional approach focused on identifying a maximum tolerated dose, an MTD. And this meant trials often escalated dosing without fully considerating the dose response relationship. Now, under Project Optimus, companies need to evaluate multiple dose levels in parallel. This requires adaptive study designs, very heavy PK and PD modeling that we didn't see under those MTD designs. And we also see expanded cohorts in early phase oncology trials. In all of that, it genuinely does impact all of those functional areas, both within the sponsor companies, the drug developers, CROs, all of the vendors that are included, and also the sites. And it's not something that's a level of complexity that is insurmountable. It's just, you know, there's a bit of a learning curve. And as we go into each of these, we find different pieces and different segments across all of those different functional areas and stakeholders need different levels of support. It's a very exciting time, and I think everybody's fully embracing it.

SPEAKER_01 3:42

That's a great overview, Patrick. But this shift comes with the real challenges. What are the biggest operational hurdles that companies face when they're trying to implement dose optimization according to Project Optimus?

SPEAKER_02 3:57

Yeah, there are a few, you know, a handful of complexities and challenges that come. And it's different depending on the structure of that drug developing company. So we work with what we call sponsor companies, drug developers, across all different sizes, from large pharma to small to mid. And a lot of them, particularly in the oncology clinical drug development space, are very, very small biotechs. And I think across that paradigm, the small biotechs are really the ones who have the biggest learning curve here, and in some cases, sort of resource constraints or expertise experience constraints. And so, you know, I would put the four challenges that I see in four buckets. And the first is a manufacturing complexity. Having to produce multiple dose drinks increases CMC demands in early phase on college trials, again, which we didn't always see in those smaller MTE. And so manufacturing those different dose formulations requires additional stability testing, regulatory approvals, supply chain adjustments, and all of this can increase cost and result in delays or timeline extensions. I think that's the biggest change for the sponsors is that these small, I mean, great improvements under this dose optimization project optimus, it is going to require a little bit more time and in some crazy costs. Another key challenge is increased patient recruitment. These dose optimization studies often are going to require more patience in that early phase development, the phase one space, as opposed to what we used to see in traditional MTV models, which were much more streamlined and just require fewer patients. So a few more patients going to sometimes require a little bit more time, a little bit more cost in that early phase space. But gosh, the benefit on the other side is tremendous to the sponsors, and they're all, as I said, fully embracing that. Trial zone complexity is in there for sure. And it's interesting, as opposed to what we used to do with the traditional three plus three dose escalation models. You know, the sponsors, of course, now need to plan for these slightly larger phase one studies, more PK, PD, but it really takes us to a point of data-driven dosing decisions, which is fantastic. And the last piece I would say is regulatory uncertainty. The FDA has been very clear over the last few years about dose optimization and what their expectations are. They're giving guidance and really suggesting and encouraging drug developers and sponsors to come and talk with them and have a dialogue. But outside of the US, you look at, say, EMA or PMDA, et cetera, they're not fully aligned on Project Optimus yet. I think they probably are moving that way and we'll get there, but it's sort of a different space. A lot of our sponsors are from outside of the U.S., maybe they're based in Japan or South Korea or somewhere in Europe and coming to the U.S. to run a phase one trial. So we can help them through that process, which makes it a little less painful for them. You know, I was at a conference, a small industry conference about a year ago, and there was one of these fireside chats. At the end of that fireside chat, I had a panelist of a couple of biotech CEOs, and then there was a senior director from one of the divisions in the FDA. And at the end of that fireside chat, the moderator asked, What is your takeaway message for today? And this director from the FDA said three simple words, but repeated it multiple times. And those three words were communicate with us, communicate with us, communicate with us. And that's a common theme thread if you read up on Project Optimus. The FDA is very much encouraging the drug developers to come and engage with them in early discussions around trial design. And they will provide that guidance. And we can from the CRO side as well.

SPEAKER_01 7:40

Yes, indeed. The FDA is always encouraged to have early discussion about Project Optimus. Patrick, we'd like to understand better what is the impact of these changes in the main stakeholders, which are the drug developers or the sponsors, the investigator sites, and the patient. How does this Project Optimus affect each of these groups?

SPEAKER_02 8:00

You're absolutely right, Weil, that those are the three main stakeholders in clinical drug development. There's the sponsors, there's the sites, and there's the patients. And through a lot of different methods and systems and processes and technology, we've moved a long way over the last couple of years and mindfully making efforts to reduce site burden, but most importantly to reduce patient burden in clinical trial drug development. So we try to marry that up with Project Optimus. And so when you look across those three stakeholders, the biggest impact really is to the sponsors, the drug developing companies, where they are having to genuinely rethink their trial design strategy in that early phase space. There's also for them, gosh, manufacturing considerations, that early regulatory engagement that we talked about. If they don't embrace this, if they don't integrate dose optimization in this early phase development, they're going to risk post-market dosing issues and potential regulatory setbacks. And so we're very much encouraging those early engagements. For the investigative sites, not a huge challenge by any means, but a couple of things that are different. The main thing I think is more patients in an early phase, a phase one design, and then the multiple dosing and the randomization into multiple doses in a phase one space. And then the heavier than we had seen before PK and PD data collection. We're asking them to collect a little bit more data than we used to, and so they're having to adjust patient monitoring protocols to help kind of track and collect those data, like the early, early extensive PK, et cetera. The last of the three stakeholders are the patients. And the impacts here are all positive. And the biggest impact is better tolerability at the end of the day. Project Optimus ensures that patients receive the most effective dose without unnecessary toxicity. So no more just increasing doses to a maximum tolerated dose, but really getting to that most effective dose. You know, it leads to better adherence, fewer dose reductions, and an overall improved quality of life.

SPEAKER_01 10:11

I have a question regarding, you mentioned earlier, small biotech companies. And as we know, the majority of early phase oncology trials happen with small biotech. How these operational changes are handled? Because it can be overwhelming. How can they navigate the resource constraint while implementing those optimizations?

SPEAKER_02 10:32

Yeah, it's a very real issue. As you mentioned, a high percentage of oncology early phase customers are very, very small, if not virtual biotech companies. And it can be a little bit overwhelming. They don't download the full education on Project Optimus. In some cases, not only is it a lack of experience or expertise, but as you mentioned, resource constraints, infrastructure restraints. But there are a few things that those companies of that size and type can leverage to help manage through these new uh processes and the new era of early phase oncology drug development. The first of those, of course, is where we sit, CRO partnerships, working with companies like CineOs Health and or other CROs that are specialized in these adaptive trial designs, BK and PD modeling, biomarker-driven approaches. All of these can help with their resource limitations and understanding the processes. A couple other areas where they can leverage to find additional support is in innovative trial designs themselves. What we call a model-informed drug development, MIDD and real-world evidence to supplement trial data can reduce the number of patients required. And as we mentioned, the regulators, the FDA are certainly there to engage in those discussions and give guidance, and we can do that as well. The third piece that I think can be helpful for small biotechs like that is digital health technologies. When we think about reducing burden at the site level, at the patient level, AI-driven patient monitoring tools can really streamline data collection and prove adherence tracking, as I mentioned, and provide real-time dosing insights. So there's a lot of technology that comes into play here where we can help or the regulators can help, the FDA and other vendors like ourselves can help demystify or make it easier for the small biotechs in particular to get above and beyond early expertise or experience or resource constraints, et cetera.

SPEAKER_01 12:28

Since we're talking about technology and innovation, can you elaborate more about how can AI-driven models and digital health technology improve those optimization and patient adherence?

SPEAKER_02 12:41

Yeah, it's very interesting. We didn't really see, I'll say over the last 10 years and earlier than that, we didn't see a lot of digital health and a lot of technology innovation really moving the needle in particularly an early phase in this phase one space, but we genuinely are seeing it now, and it really is providing great benefits. In this project, underneath the project optimization umbrella, the trial complexity is increasing a little bit, but these digital technologies are helping tremendously. The first I would say is AI-driven platforms. You know, we talked about the PK and PD, and these AI-driven platforms can analyze PK and PD in real time and enable sponsors to make faster data-driven dose adjustments. So digital health tools, we're seeing these more and more and then implementing these more and more into clinical trials, oncology clinical trials of all phases, wearable devices like mobile apps, well, mobile devices, patient monitoring, and side effects. It just helps with real-time, invaluable data. And when we're looking for optimizing dose response relationships, these technologies can get us there a lot quicker and cleaner and easier with less burden on the sites and the patients. And this reduces the trial and error in these dosing approaches. So, bottom line is these technologies are helping us even all the way back in this early phase on biology space, helping us accelerate timelines, reduce costs, reduce burden, increase patient outcomes, et cetera. Very exciting time.

SPEAKER_01 14:25

Indeed, very exciting. Patrick, looking ahead, what do you see as the long-term benefit of implementing optimized dosing strategies?

SPEAKER_02 14:34

A lot. It really is going to be a game changer in early phase oncology, drug development, all of these things that we've talked through over the last few minutes. The outcomes, the benefits are here to stay, and they're going to be huge in dose optimization. A few come to mind, um, lower trial failure rates, overall program failure rates by selecting the right dose early in phase one. We reduce the risk of late-stage trial failures due to those unforeseen toxicities that sometimes, now with targeted therapies that you wouldn't find in an MTD model where we know that an MTD is not necessarily the optimal biological dose. And so lower trial failure late, improved patient outcomes. Better dosing means fewer side effects, better adherence, and improved quality of life for the patient. So they're the big winners in this. Market differentiation for sure. It's an ever-increasingly competitive and crowded space, even for targeted therapies that are going into the same space. And optimized dosing can be a competitive advantage, differentiating a drug in terms of tolerability and patient experience. And so huge benefit there. And then I think the last thing in the long-term benefits that I would mention is we talked about the three main stakeholders in clinical drug development, those being the sponsors, the sites, and the patients. But there are a couple of other significant stakeholders in the process. And those are regulatory, and we talked a little bit about regulatory today, but regulatory benefits and benefits to payers, cost-effective dosing strategies, you know, they align with value-based care models. And so it makes them more appealing to both the payers and the regulators. So another significant long-term benefit for the drug developers.

SPEAKER_01 16:26

Patrick, this has been a fantastic discussion. It's clear that operationalizing dose optimization isn't just about compliance. It's about improving patient outcomes, accelerating drug development, and creating a more sustainable future for oncology treatment. Thank you for sharing your insights.

SPEAKER_02 16:44

You are very welcome, Wile. It's been my pleasure to be here. And you're right, this is an amazing space we're in. And dose optimization is all about identifying the right drug for the right patient at the right time and at the right dose. Precision dosing is here to say, and it's certainly the future of our industry. So it's been a pleasure being here with you today, and I thank you for your time.

SPEAKER_01 17:06

Our listeners, thank you for tuning in. Stay with us for the next episode where we will continue exploring how Project Optimus is reshaping on college drug development.

SPEAKER_00 17:16

See you next time. That's all for today's episode of the Senior's Health Podcast. I'm your host, Nick Kenny. If you have other topical issues you'd like to hear on this podcast, please do send us a message at podcast at Synioshealth.com. And for access to more future-focused, actionable life science insights, please visit the Senior's Health Insights Hub at insightshub.health.