Combination Product Universe: PDA Conference Recap with Keynote Speaker Stephen Perry
Memorable Quotes:
“I think the real entrepreneurs know that you want to collect all the data because you're not sure exactly what data are going to be important.” - Stephen Perry
“I think if we can find biomarkers that we can measure and then feed it back into a system. And have algorithms that allow changing the dose frequency or the dose amount. I think they could really transform the whole patient experience.” Stephen Perry
Transcript:
Intro - 00:00:03: Welcome to The Factor, A global medical device podcast series powered by Agilis by Kymanox. Today's episode is hosted by Shannon Hoste, Vice President of HFE at Agilis by Kymanox. And she's joined by the CEO and Founder of Kymanox, Stephen Perry. Recently, Stephen delivered the keynote address at the 2023 Universe of Pre-Filled Syringes and Injection Devices Conference. The address was called The Inspiring Evolution of Parenteral Combination Products from 2004 to today from an Entrepreneurial Perspective and a peek at what is coming. Stephen and Shannon unpacked this keynote and some of the surprising revelations Stephen's uncovered in his research. And one of those revelations, that progress isn't happening nearly as fast as some might expect. Here's Stephen.
Stephen Perry - 00:00:51: So what's crazy, Shannon, I think you and I talked a little bit about this when we spoke. Help prepare for that keynote. Insulin pump, it's from the 1970s, which is just flabbergasting. And then really the revolutionary kind of introduction of a reusable pen injector. That was 1985, the Novo Nordisk Novopen. And then later came like pre-filled syringes. It was almost like insulin was innovating in reverse. So the first thing they came up with in the 1970s was an insulin pump. And if you can think of like, of all the rental combination product dose delivery systems, the on body injectors are kind of the last on the scene. And it was the first for insulin, which is really just kind of dumbfounding as a, as an engineer, as a practitioner in this space. It's interesting actually to see what additional innovation is going to happen in insulin. And then maybe we're getting a 10 year or 20 year look ahead of, of what's coming next for the rest of the space.
Shannon Hoste - 00:01:56: That's a good point.
Stephen Perry - 00:01:57: Yeah, and then there were some other really fun things like the technical committees that govern some of the ISO specifications that we know and love. Those were actually formed in the 1950s. So even though we were kind of like focusing on a 20-year look back, I think we try to go back a little bit further to understand really the origins of the universe, the origins of technology. This really interesting space that we all play in every day.
Shannon Hoste - 00:02:22: Absolutely. And what are you seeing in that evolution?
Stephen Perry - 00:02:26: Yeah, so I think right now, the current era, half of these governing standards and regulations are kind of still in draft form. People are still waiting to hear additional comments before things are finalized. And as you know, the FDA takes a good amount of time to issue draft guidance and then make that guidance kind of formal and finalized. So we're kind of living in an era of uncertainty to an extent. And a lot of people are playing, I think, as much defense as they are playing offense. So this evolution, I think, is partially guided by our external regulatory body environment. You don't want to start a modern medicine development program and then not have a clear regulatory roadmap. That regulatory uncertainty we're seeing actually really shut down funding for companies. So if companies don't have that clear roadmap, it's very difficult to raise money. Some of the evolution I think is really interesting is the people capitalizing on digital health. It's been a big disappointment in terms of it revolutionizing the industry quickly, but it is happening. And so we're seeing more and more solutions have a digital component to it.
Shannon Hoste - 00:03:50: You mentioned disappointment. Why do you use that word?
Stephen Perry - 00:03:54: Oh, I thought digital health was going to have a breakout year in 2023. And instead, some of the top 20 biopharma companies completely shut down their digital health departments. There's been a lot of layoffs and staff reductions and budget reductions. A lot of programs have been canceled. So that's where the disappointment comes in. However, I think we're still seeing some of the winners. And I think the entrepreneurial spirit of just knowing that this is going to eventually win, but it's innovation and innovation is hard. And so the companies that are just plowing forward and collecting data on their use cases, the way people are using auto injectors, and injectors, different injection systems. That data is going to be invaluable later on.
Shannon Hoste - 00:04:50: That's a good point. There is quite a bit of a timing component to innovation. I think of projects I worked on back in the early 2000s on home health. That had a lot of challenges because the infrastructure and the payers weren't set up to support home health. Flash forward to 2020, and all of a sudden now there is a need that that technology can meet. So you bring up an interesting point with digital health. And some of the advancements on it are more on the technology advancements than the solving a very specific need. But as you mentioned, the data collection, what are you envisioning when you're thinking about that data collection and what future need that might meet?
Stephen Perry - 00:05:34: Yeah, so I think the real entrepreneurs know that you want to collect all the data because you're not sure exactly what data are going to be important. But one of the things that we're talking about in terms of just designing your biologic auto-injector, and everything's moving to larger volumes, is like, how long can your injection time be? And so one of the things we can measure is actually measure injection time, because there's what you're supposed to do, but there's what actually the user does. So that's something that we can record. We can record exactly how long a patient holds, say, an auto-injector to their outer thigh or to wherever they're doing their injection, and record that over time. How consistent is it? What users are maybe doing shorter injections or longer injections than necessary? Maybe something where you've got like a bent needle or some other failure mode where someone kind of injures themselves with the auto-injector. Of course, there's been so many safety advancements. Those things have really become a real rare exception. Yeah. So I would say you don't know what the important data are going to be. So you should really collect it all. And you know, even just consistency of dosing. So having the date and time of the dose, I think it becomes really important. And then I'm not an elderly person and I'm not a child, but I'm this ideal person who should be able to take my own medicine. Sometimes I'll take medicine, I forget if I took it or not. So just having that reassurance of knowing that you actually completed your dose is really going to be potentially invaluable. And then linking that all the way back to the payers, like, hey, one of the things we found out that if you don't take your medicine, you're not going to get better. So just like compliance with the prescription, I think is gonna be a really important thing.
Shannon Hoste - 00:07:30: Absolutely. So you mentioned data to the patient, data to the payers. And then I think also data back to, you know, with the development of machine learning and AI and other items I'm seeing now, for example, in the software as a medical device space, tools come on that are using healthcare record data to help more quickly diagnose or recommend diagnoses or flag, you know, potential deterioration and the like. I could imagine potentially the data being valuable for further analysis down the road.
Stephen Perry - 00:08:06: Yeah, and when... I mean, just like most of this stuff, you don't need a ton of interaction with your primary care physician, but when is it time to go check your, with your doctor? In the case of diabetes and insulin, there's always like the feedback loop, right? So you're getting your glucose measurements. So I think as other people, diseases have other biomarkers that can be conveniently measured. Maybe it's your blood pressure conveniently measured for a heart medication that you might be taking. If there's a digital loop that we can kind of close the loop on, that feedback can be really valuable. Again, not just to the patient, but to the caregiver and then all the way back to the payer. So I think everybody can win. This digital revolution, but you kind of have to embrace it. And you have to be willing and able to collect the data and then have that data available for analysis.
Shannon Hoste - 00:09:04: Another thing that this brings to mind for me is something you mentioned earlier, and that part of that is the gray space in some of the regulatory expectations right now. And what I'm thinking of specifically are EPRs, so on the FDA front, and how handy that data might be in establishing and maybe even tracking lifecycle performance of your product and your device. Yeah. Against some of those EPRs.
Stephen Perry - 00:09:30: Yeah, essential performance requirements. I think you pointed out too that everyone's following this like it's the Bible. And it doesn't really, it comes from a completely different area of life science, which is like what governs pacemakers. So it's kind of a borrowed concept. Everyone is, I think, really on board with it, but we probably need a clearer definition for the way we're using our products. So, for instance, a biologic and an auto-injector, I think, is very different than a pacemaker. And the central performance requirements kind of theory should be built around that use case so it can be as applicable as possible.
Shannon Hoste - 00:10:12: So I'm going to ask you two questions and you can decide which way you want to answer it. The first question is, what inspired you to select this topic of going back the 20 years? But an alternate question is, what did you learn or revisit as you're preparing for this discussion that you found inspiring.
Stephen Perry - 00:10:32: Yeah, so I think it was just a really unique opportunity that I happen to have founded Kymanox. At the exact same time, the universe of pre-filled syringe conference was formed. And then we kind of both went on a journey together. And when Kymanox was starting out, we were primarily serving the biologics community for the most part, a little bit of pharmaceuticals. Then we kind of backed into device, pure medical device. And then the last thing that we dug our nails into was combination products and syringes course, from the very beginning, the pre-filled was a combination product conference. It was focused on pre-filled syringe. And then they backed into cartridge-based injection systems and then other dose delivery systems. And then I tried to make an argument that, hey, let's just make it any combination product. Including like nasal delivery, for example. And the reason is it's like how PDA in this particular community, how they approach to solving the problems is I think what's really valuable. And that approach, I think, is universal. And so it can be applied to anything. So I think when I was kind of researching the topic, this theme of insulin and diabetes really just kind of kept hitting me in the face. And shockingly, even though it's a really prevalent combination product and it's a prevalent disease, I personally haven't really worked on any insulin or diabetic or even continuous glucose monitoring programs in my entire career. So it was kind of like an entire discovery exercise for me. And went down a lot of different wormholes on the internet and found some really old articles. I even went on to eBay and tried to go buy some of these old insulin pumps and some of these old pen injectors. So I could actually have it in my hands while I was doing the research. And that was probably the most revealing thing to me was, wow, insulin and diabetes is really the cornerstone and the center of the universe. And I didn't even realize it. And so a lot of the innovation that I was working with really came from that.
Shannon Hoste - 00:12:48: And crystal ball, as you pointed out earlier.
Stephen Perry - 00:12:52: Yeah, potentially, right?
Shannon Hoste - 00:12:53: Their technologies, yeah.
Stephen Perry - 00:12:55: Of course, diabetes has figured out digital, right? So one of the things, my friends and I, we did a little wellness retreat. We were in Austin, Texas, and my friend is a diabetic, and he's Looks perfectly fit. Really good care of himself. He's a very well controlled diabetic. But we were doing really unusual things. We were doing cold plunges. We were doing salt floats. We were doing the sauna thing. Went out for a big long run, just a lot of activities that we just weren't normally doing. And we were also eating a lot of like good Texas barbecue. This is maybe not the best recipe for a well-controlled diabetic. And so that evening, my friend's blood sugar was just crashing, which is a real dangerous situation. You can go into a coma and you can die. And his wife got a text message and his wife called the group and say, Hey, Is everything okay? And then we kind of worked on an action plan to get him back, to get his blood sugar back up, make sure he's monitored before going to bed and calling it a day. And so it was just like, just to see the marvel of technology where you get not only just the digital monitoring, but the digital alerts. And then it's, it's outside of that person's realm. So it's the caretaker, And the key stakeholders were notified. And then we were able to communicate and really come up with a good plan. And so that really hit home that, wow, this technology really works.
Shannon Hoste - 00:14:30: That is a very different picture on the digital health landscape, as you mentioned, than you were describing for other drugs, other applications. Like you said, that's 10 years ahead of where we're at with other products when we think about digital and digital support tools. A very good point.
Stephen Perry - 00:14:47: Yeah, I mean, like I said, they've figured it out. And so there's definitely some innovation that's already happened that you need to figure out how to transfer it over.
Shannon Hoste - 00:14:59: Yeah. Even the physiological closed loop control systems. So now those are, there's several of those active in the diabetes space now. And still evolving in other spaces.
Stephen Perry - 00:15:14: Yeah, you can imagine too, like for something like pain management, you could have a complete closed loop system. There's a lot of biometric readings for pain and people don't want to be reminded of their pain by taking pills or whatever. They're doing. I think there's a lot of creativity where people can come up with these things, variable dosing. So you look at some of the most popular drugs like Humira, or any of these rheumatoid arthritis or autoimmune drugs, it's kind of like a one-size-fits-all dosing regimen. And of course, they do have different doses, but they're pretty chunky drugs. And I would imagine like true variable dosing where you could vary the frequency as well as the dose amount could offer a lot of benefits. The theory is you could reduce the side effects and improve the efficacy both at the same time. And so I think this idea of one injection volume One size fits all. I don't, especially for biologics, I don't think this is the case. And where I think you can make a real big splash in that type of innovation would be in the GLP-1 space. So these are the anti-obesity drugs that also treat diabetes and hypertension and potentially like reduces your risk of cancer. Obesity has a lot of other kind of secondary overflow disease conditions that it contributes to. And what they found out is that the higher the dose, you had more side effects and you had more weight loss. And a little bit lower dose, you had less side effects and less weight loss. And you could literally dial in your weight loss or dial in your side effects so that you can stay on the drug to ultimately prevent help your diet, help your obesity, but then all these other secondary diseases that obesity makes a lot worse or potentially causes. And I think you need a feedback system. You need data collection in order to warrant changing or dialing in a specific dose or changing the dose frequency.
Shannon Hoste - 00:17:32: It's true. And even I was thinking of that same, the GLP-1 as you were talking through that. And one of the big issues right now with that is it's addressing such a persistent need, a massive need, the patient population, that there's shortages and supply chain issues. So coming at it with a bit of a more of a club approach of, this is the dose, the gross metric, rather than fine-tuning it, does that contribute to things such as supply chain shortages?
Stephen Perry - 00:18:08: Yeah, and like I said, these biologics are very powerful. And so you want to really find the minimum therapeutic dose. And whether it's a drug like Humira or these GLP-1s, I think if you can find the Goldilocks range, which is not too little, not too much. And look at our patient population. You'll have the NFL lineman who weighs 300 pounds, healthy guy, and all the way down to a 90-pound healthy woman who's just really skinny and trim and fit. But they both may have autoimmune issues, and they need these drugs. That is not a one-size-fits-all scenario. It really needs to be kind of customized. And then people have different livers. These half-lives of these products change based on people's ability to process these the drug in their body. And people with really strong, healthy livers, a lot of these drugs have a shorter half-life. Also, people live different lives. Some people are a little bit more sedentary and other people are like super active. And all that is like different variables. So I think if we can find biomarkers that we can measure and then feed it back into a system. And have algorithms that allow changing the dose frequency or the dose amount. I think they could really transform the whole patient experience. Equation in terms of treating these diseases on a personalized medicine basis.
Shannon Hoste - 00:19:39: I like that, Stephen. As you mentioned, a lot of those variables that affect and can alter what that minimum therapeutic dose is for each patient. You think of all those variables and in classic medicine, in our history, understanding how and accounting for those variables is a bit of an insurmountable problem, right? How do I account for the variation in size and health and life cycle activity and diet, right? But introducing that digital component makes insurmountable, surmountable, right? It's a way we can address them.
Stephen Perry - 00:20:15: And I think introducing artificial intelligence. So I think some of it is overwhelming. And again, if you just look at the case of a diabetic. All these things like whether or not they're sick, whether or not they're stressed, whether or not they're working out or being sedentary and exactly what types of food that they're eating and when they're eating it, how much it is. It is absolutely overwhelming. And the best thing you can do is kind of take a wild guess on what your insulin dose should be as well as the timing for that dose. Yeah. But with artificial intelligence, it can process all that information. And so you can now take a picture of your meal, and it'll tell you all your macros and what... How that's going to impact your body. And so that's not that hard to point your camera at what you're eating. It takes two seconds, pretty low friction. We know that these other diseases have similar effects. You know, data that potentially is available. If we can just record all of it and then figure out what is important later, we can then devise an algorithm that's safe and effective for these patients. You know, obviously there's the label and you need to be following the label, but then there's the really the best way to administer a drug. And those two are not always compatible. So I think companies are going to need to invest in clinical trial studies that are really adaptive, that account for how the drug should be used and not just the clinical first label use for the first approval of the drug. And we all know this, right, that doctors will prescribe things that are off-label. So I think with, let's just be open and honest about that. I mean, that's exactly how some amazing new treatments are found. It's an approved drug. Prescribed by a doctor for an unapproved indication. Of course, that's a risk to the doctor, but it's also a risk to the patient. And it's also a risk of not being reimbursed in the payer system. But, a lot of patients' lives are so much better as a result of some of this off-label use. So I think the regulatory agencies and the people who are innovating the drugs really need to have like a partnership where how they collect data and and share data and make some of the labeling flexible based on the classic risk benefit analysis. Okay, what's the risk? What's the benefit? And if the risk is really, really low and the benefit's really, really high, we need to introduce that flexibility on this labeling.
Shannon Hoste - 00:22:54: Is down to clinical trial design and real world evidence too.
Stephen Perry - 00:22:59: Yeah, I mean, this is where the CMS and the clinical worlds combine, and also just the practical side of medicine.
Outro - 00:23:13: That's where we're going to stop today. In part two, Stephen and Shannon continue their chat about PDA, progress in the market, and what's ahead. This episode was edited and produced by Earfluence. Thanks for listening, and we'll talk to you again soon on The Factor.
Like this episode?
