Welcome to Pharma Talk Radio. This podcast is focused on designing clinical trials balancing simplicity and complexity from the twenty twenty five Chief Medical Officer Summer three sixty. For more information on the CMO Summit, editorials, podcasts, or webcasts, please visit CMO three sixty dot org. Thank you and enjoy the podcast.
We thought it would be really helpful to get the cmos and data input onto how do we actually physically do this and what the challenges are to being able to do that. And part of it is that we live in a complex world, so it's quite challenging. So let's start out by doing introductions. Chris, why don't we started that and we'll work this way.
Yeah. Thanks. I'm Chris Morribido.
I'm the Chief Medical officer at a company called Astrio Therapeutics.
It's allergy and immunology.
We have one phase three asset, one phase one asset, and I'm incredibly sobered up by the conversation since that we heard this morning.
Hello everyone, I'm Eric Scalfrow, CEO and founder Rivia. I found a Rivia to help sponsors stay in control when trials get complicated by helping them bring all their data together to bring clarity and momentum. I'm really excited for the conversation today, in particular to understand how we can improve outcomes with smarter oversights, and that smarter oversight starts
at the design stage. We're seeing over twenty active trials at RIVIA right now, and I'm excited to share some of these observations I've had over the last couple of years.
Wonderful. Hi.
I'm Judy Nung Cash and I'm the chief medical officer of Novotech, where CRO really focused on serving the biotech community. While I'm at nov Tech now I can say I've had twenty years in the industry across large sponsors, small biotech and larger CRO. So I hope to bring kind of a balanced perspective to our topic today.
Great, Thank you.
Hi everyone. I'm Bertillion Markham, the chief medical officer of Bicopharma. We're a Scandinavian biofarma focusing on IPF and angiotens into type two receptor agonists, which is quite unique. I think everyone can do anything complex, but doing it simple, simply and simple, that's the trick.
And Buru, what phase are you in?
We're in phase two with the compound. So we're starting a big two hundred and seventy patient study in IPF, so lots of things to coordinate and ninety seven sites.
Great.
So, you know, Ken talked a lot about pivotal and phase three trials and we're gonna I'm going to kind of break this down into the challenges we see with earlier phase trials and what we need to do with biotechs and with vendors, answer key questions we need to get for how do we risk manage our programs, make investors happy and be able to fund our company and also move things forward, and then we'll switch over to
the pivotal at the end. Although with development right now in particular in a lot of these phases are kind of blurring in the biotech world, so a lot of the.
Questions are the same.
So let's talk a little bit about what the challenges are in early phase trials of what you're trying to solve for first and how that makes your trials complex and how you deal with that to be able to.
Make them more doable. So what you know, do we want to start with the Let's start with the christ.
And will work away across.
It's I mean that's a key question. We have so many stakeholders, and I mean all of us are incredibly curious people, and we're scientists by heart, and we want to do the right thing for patients by heart, and we want to do the right thing for our company and for investors, and for the FDA and for the EMA. So many stakeholders, and there are only so many questions one can ask or one should ask in early phase trial.
So you know, one thing that we've started doing is asking the hard questions, what are these data for?
Who are these data going to be shown to, what is an expected expectation of these data? And what kinds specifically, what kinds of questions must we answer versus what kinds of questions would be to answer? And for a lot of us in biotechnology, we live and breathe by our data. That's what funds us. And uh, you know, it's it's often difficult to have to ask the question, how do I get the right data for an investor versus the right data to get this in front of an end
of phase two meeting. So the FD is going to be happy with our selection of our clinical trial designer for phase three.
It's a tough. It's a tough intellectual balance. So you know, it's.
What we've what we've opted to do is work through this step by step in in fact, in fact hierarchy, hierarchical, hierarchically rank who we're trying to please and who we're trying to address with our data, such that we could design the most simple trials. Almost always has been said, and as we learn from Ken this morning, simple is better, but simple isn't always best.
So it's it's uh.
Limiting to the most precise questions that we can ask in order to please the right stakeholders.
Maybe if I could just react to that, you know, I think you can't simplify what you can't see, right, I think there's a gap between the designs and the reality operationally that they bring. Bettiel had some eloquent way to put it before that they're very theoretical.
And I just had one anecdote.
I was speaking to a CMO on Friday who has an open label phase two in a variant of IBD, and in this dose escalation, he first needs to review every patient before they're escalated and then discuss that with the PIS and make a joint decision if that makes sense right now, that actually brings quite a lot of operational burden, right, fifty patients, each patient takes a couple
of hours to do that. That's already several hundred hours to do that review on paper, pretty simple, and so bridging that gap of considering the operational reality with the designs, I think is a is an important step.
Yeah.
Well, you know, it's funny.
I'm from Philly and uh you know we have a famous basketball uh thing where Alan Everson said practice, I don't need practice, right, And what we find is that sometimes you win these before you start. And Judith, you know, as somebody that's a cro how much up front work does it take to get your trials to be simplistic even in a complex world.
I think that's a great question. And I think, you know, Chris got to the heart of it. I think, you know, coming from a big pharma background where you know you're really designing for the health authorities right for approval, you're looking at this long long development program and trying to do things in a stepwise fashion. And what's very different working with biotech is all the stakeholders, right, and I think what we observe with our early phase biotech.
Sponsors, is it.
That prioritization is rarely done right, and so you're trying to please everyone, which just adds more endpoints, because what's meaningful to the regulators might be different than what is going to be a value inflection point for you with investors. And so I see, I do observe sponsors trying to add everything in but not appreciating the potential operational risk that they incur and that that ultimately might result in
a problem with your data integrity. So it is a conversation when you have a biotech who doesn't have operational experience in it to really say can we can we trade off? And it's a lot of work, and depending on the background of who you're interacting with, that sort of conversation may or may not hit well yeah.
Yeah, no, I think there is kind of many many flavors of complexity, avoidable and unavoidable because you start with the drug and you start in therapeutic area, so you have some kind of complexity to begin with, but then you add on and I remember many years back in ASTRA people suggested that we have a cutting manager that actually tried to cut down on the number of things that people heaped up on studies. So I think that
mindset is extremely important. So you make it as simple as you possibly can while still answering the key questions. And then I think there and there's a degree of blindness because the companies often try something new and already in the design phase, you are kind of blind to the problems that you will anticipate. Actually the pis and
the sites might actually help you. And then of course we spoke about the patients and the sort of simplicity that understanding the patient bird brings, So I think there are those things that can help.
Yeah, it's a great point. I think Ken talked about it a little bit this morning.
I'd be interested to hear how when you start to think about your programs you start to think about patient burden, site burden, do ability. Are you designing programs that are actually people are able to do? And how do you take that into account and what kind of feedback you get to be able to achieve that?
So look, you hear left from the group.
So yeah, yes, absolutely.
From the beginning, as a patient orient in company, we take a lot of time and care to talk with the patient groups. We've established patient advisory councils working closely with patient advocacy organizations. And the advocacy organizations have been incredibly helpful by themselves, but the advisory councils.
Are one step better.
These are people that we can talk about strategy with but then talk about operations with as well. And you know, when we propose clinical trial operation elements, these are the number of site visits.
This is what we want to do.
At each side visit, they come with pencils and pens and they mark it up and they give us the feedback and this is not going to happen or you need to do that.
It's incredibly helpful because if we can.
Then go to our sites and said, we designed this with input from your patients, and this is what they feel like they can do in a clinical trial. Operational burden therefore is therefore is decreased, so please help us enroll this trial.
So far that seems to work. It's an evolving landscape.
Though, I think there what's important is that you know, complexity is a choice, not a consequence, in the sense that right we saw mister Getz's staring numbers on more endpoints, more procedures, et cetera. Now, what does that really imply operationally?
How does that compound risk and variability? Right? I have several of our sponsors are now undertaking decentralized trials, and what I hear is there is a discordant reduction in burden decentralized trials the premise that it reduces patient burden for the people running the trial, it actually potentially increases it because instead of just doing the monitoring at the site, you now have to do monitoring at the site and at the patient's home, and you have to make sure
the data is collected in consistent ways, and so there the complexity is perhaps more of a consequence than a choice, or maybe not fully thought out. So I think it's important to reflect on those different compounding elements of complexity.
I think that you know, especially for you know, our biotech sponsors, the the technologies that are being studied are by definition super complex. Right, So there is operational complexity that you can't like what you were saying, virtiularly, that you can't avoid there maybe there's a cold chain, supply
chain or something like that that is unavoidable. But I think when you can, I think the complexity from the sponsors is often driven by a risk aversion, right, that we're going to not collect the right data, that someone's gonna one of our many stakeholders is going to ask for data we didn't collect, and why don't you collect that?
And I'm not going to invest in your company.
And I think taking a risk based approach to what must we have and can I accept the risk that maybe someone down the road some day is going to ask for this other thing?
And let's omit that.
I think it's hard math when you're a physician scientist and you just want more data because it's convention that more data.
Is better, right.
Yeah.
I guess if you like a clinical study with going on an expedition, you kind of you can't pack everything, so you have to unpack and limit and that's a hard choice. And I guess the complexity has three time segments in a way, it's before the study, is during the study, and it's after the study. One of the key aspects that I'm quite interested in is the data
and the access to data. At least my experience is that sort of there is a little bit of a power game sort of who accesses the data and who can really understand the data in depth in a clinical trials, both during the trial blinded data and after the data when you try to connect this to the next sort of phase in the program. And I think accessing blinded
data during studies is extremely important. I know that Rivia is working with that Capacious and other companies that you will see here where you can have sort of data dump and actually understanding the data during the trial because that helps you actually plan for the next segment. And I think that's super important to reduce complexity.
So, Chris, you talked about site and Bernald you talked about this to cite and patient input and having you know, folks review your protocols. Any of you institute actually walking through your visits and looking at your visits and seeing
what you're asking patients to do with your visits. Have you done that in your child I'd be curious to folks in the audience as well of actually having your folks just pretend they're a patient or a coordinator and actually make them do a visit, as has anybody on this panel thought about her?
Have they done that to see what the burden really is.
I've asked my clinop's team to do it, but I haven't done it myself.
Yeah, yeah, I think I think you see that happening at sponsors.
Not really, but it's a great idea because I think, you know, that experience really helps you understand what's necessary, what's not necessarily, what's a burden. I think asking people is a good idea. And you know, one thing, you know,
this conversation is making me think. You know, it's so competitive to enroll the patients, and the sites feel it, the sponsors feel it, and so anything you can do to like hit the easy button for both of those populations might actually give you a competitive advantage in a crowded you know, indication.
Yeah, I think the idea of walking through a visit or the visits is really important. The number of visits and the complexity is extremely important. And I was starting to think of a clinical study as a board game basically, because you do you have the the sequence of events, but you also have the the what if kind of questions that will that will happen during a trial that you don't spend enough time to walk through.
And eric you help folks think through their databases but also their data entries, So do you do that with sponsors where you actually have them sit through and simulate a patient and have them entered their data or think through that.
Sure.
More so, we have two chief medical officers in our founding team and did pretty much the exercise you're describing with their teams, more so on a softer side, to humanize the trial, to really understand because a lot of people, including myself, are very far moved from the patients and the reality of the data collection at the site and you just becomes a lot of emails and data points, and so they've brought them for a few visits to
really understand the reality of what it takes. More from really an empathetic, humanizing perspective, I think it softened a little bit to the frustrations when things are or when things are maybe not the quality that they desire, because there's there's a tough reality.
To it as well.
So, Chris, you I'm going to shift this a little bit because we've been talking about patient burden and site burden, but you raise another thing at the beginning, and that's all the stakeholders you have to answer questions for and be able to produce clinical trial results for. And I'd love to hear from the four of you. Who where you think your biggest challenge of complexity comes from. Does it come from your self, does it come from the from the board, does it come from your investors, does
it come from the regulators? Where do you think or does it come from the scientific community. Where do you each think that the complexity arises from? If you had to pick a point where it comes from, where would you think that comes from?
So I think each of those and those stakeholders that you identified wants a simple trial. The challenge, of course, is that they want a simple trial asking different questions. So ultimately the complexity is on us because we're trying to put all of those questions into one trial. You know, it's it's no longer sufficient just to say I'm going
to do a safety study in phase one. You know, you're throwing in biomarkers, You're throwing into all these exploratory things to look for some efficacy signal that will translate into potentially a value inflection. And that makes it very complex even for a phase one study, which are generally operationally simple. So you know, this is why we do this. Prioritization is trying to, you know, try to limit the number of people that are forcing us to ask these complex questions.
Yeah, and so from my perspective, what becomes challenging is deciding what's essential and cutting what's not and seeing how that priorization might change as the trial's unfolding, right, and responding to various stakeholders. So kind of being like by analogy, you know, the bird at thirty thousand feet or a hulk and knowing at the right time to go and
peek down and then come back up and resurface. I think that's tremendously difficult, but also where there's a lot of potential and opportunity.
If I had to pick one of the stakeholders that the one stakeholder that drives complexity, I might say the investors, only because what they want out of an early phase trial is so much right. And you know, for what when we used to do phase one, it was just healthy volunteer sad mads and simple and let's move on to the next phase. But the funding pressure and the time pressure, I think drives adding all this other stuff
in that drives complexity. So even though we'll say this is not powered, it's exploratory, people want something at the end of that right because they invested and they want to turn around and or you know, an increase in value or whatever it is. So I think that on the sponsor side, especially for the CMO population, we're just trying to do a good trial that is safe or has the appropriate risk benefit for the people who are you know, volunteering to be in this experiment.
And then you add on from that.
Yeah, I think it's easy to kind of blame everyone else, but I think the cmos are driving complexity as well. And obviously you have you have your guiding star with the regulators and the science and the drug and you try to get that into package. But actually then there are kind of some kind of inertia and some kind of momentum that builds in company where you add stuff, but you have to restrict and keep yourself a bit calm, even as a CMO.
I think and do you think that.
It's a good point. Do you think that getting involved earlier in the program, when the prequinical programs are designed would help you streamline some of the things that you're trying to collect or target so that you get that one answer out of your phase one two that's meaningful when you've thought about it when they put the drug into a mouse or or.
A monkey or something like that. Thought about that about.
Our companies bringing cmos in too late to think about the holistic design their programs.
Is that adding to it?
Yeah?
Maybe, But I think honestly that kind of question that you're asking goes with every single phase change. I mean, I think that we should be thinking deeply along the way of all of the data that informed a high pos in the clinical trial that you're about to start. And I think that absolutely does include the pre clinical space. One of my former mentors that actually is in the audience today taught me a long time ago that you should never ask a question you don't really know the
answer to. You should pretty much be sure you're going to get an answer that you've predicted. And there are lots of tools like doing more translational research, enabling model informed drug development and pharmacometrics to give you confidence in the question that you're about to ask.
So yeah, absolutely.
But it is also, though, Chris my observation that with smaller companies with constrained funding, that up front.
Pre clinical work is.
Not thought of as a must have to get into the clinic. It's a nice to have, and it's unfortunate because that helps you do a better early phase trial.
Well, I happen to be lucky because we are extremely close with the pre clinical guys, and you know, the whole question about sort of exposure, exposing humans to a drug. I think that's so so serious and so interesting that you need to absolutely understand what's going on, both in terms of in terms of potential side effects and potential exposure and the drug concentrations and everything. So you need to really hook up with the pre clinical guys and work closely.
So we'll shift over to pivotal a little bit because Ken talked about that this morning, and I think, you know, a couple folks made some comments about learning from early phase and are we getting enough out of our early phase studies to be able to target and design much more simplistic pivotal trials that ask the questions we need to get approval and access and whatever, or we you know, asking too many questions out of our early trials and
not getting enough to be able to design simplistic pivotal trials.
Is that what's contributing here. My observation is that.
Complex early phase studies lead to complex pivotal studies exactly because there's not enough data with all those exploratory and points to make people feel confident that they can start eliminating them. So they just continue that on because we already measured that in phase one, so let's keep measuring it.
And were just in the face of designing a sad MAD with the kidney disease cohort, and we were thinking, okay, okay, should we just do PK, should we do PK tol ability?
Should we do eight days?
Should we do like a month? And then you start thinking about the underpower, the risk of underpowering all these things, so you need to limit and we started thinking esoteric blood flow measurements and stuff like that. But then we were advised, well, they're not that that sort of high precision, so you may end up with just a gray cloud of uncertainty. And of course, the more stupid uncertainty you bring with yourself, the more questions you might be asking in the next phase.
So it is tough. It is tricky.
I think the answer to your question isn't so simple. I think it's complex. I don't mean to make a pun about it. I think I've seen lots of examples of phase retrials that have been simple despite lots of complexity early development, and I've seen the converse. I've seen companies push the difficult questions to phase three because they want to get through phase two faster to get to a value inflection to fund phase three, making FACE three
is more complicated. And on top of that, the payer market right now, the pero dynamics right now are really complicated, and you have to throw in all kinds of quality of life and other pyros into your assessments that add complexity.
I think part of this is the regulatory burden. If you're going into a rare.
Disease, the regulatory pathway may not be as well defined for you, which, no matter what you do in early development, makes FACE three complex.
So ultimately, I don't know the answer to your question, but I.
Would say that it is on us to do whatever you possibly can to make phase three as uncomplicated as it possibly can, just to make sure that trial gets done well.
So I love the end sessions with if there's one bit of advice to make your trials simple, what would it be? So why don't we start down there? We'll start down this.
I'd actually go to sites and ask them what makes this the most sort of competitive study that that that would would help us run.
I was going to say the same thing. Thanks for still in my thunder. I think coming back to the beginning of this conversation, when engage early with your patient population and your investigator population to understand what really makes sense and what they what do they want to participate in, I think that's a good start.
Yeah, just to bring it back to my three observations, which were, you can simplify what you can see. Simplify simplification needs discipline, and make complexity choice not a consequence. And with that in mind, consider designs with the operational reality that they bring exactly what that Deal and Judith are talking about, right.
And then mine would be make sure you know your company's primary objective before you put pen to paper on their protocol.
Great, and I think we're out of time. I don't know if we have time for no questions. Okay, great, Well, thank you very much, this is great.
Thank you.
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