627 - The Future of Biopharma: AI, Automation, and Clinical Trial Breakthroughs at BIO2026

0:10Peter Birch: Welcome to the Talking Health Tech podcast. My name is Peter Birch. I'm here in San Diego at Bio International and I'm joined by scientists, founders, investors, pharmaceutical leaders, technology innovators, manufacturers and healthcare decision makers from around the globe. During the event, I had a chance to sit down with people who are addressing some of the biggest challenges and opportunities in life sciences today. We explored topics like AI-powered drug discovery, manufacturing biopharmaceuticals at scale, accelerating clinical development, bringing new therapeutics to market, improving access to innovative treatments, and the growing role of data and technology across the biotech ecosystem.

0:52Peter Birch: In this episode, you'll hear a handful of the conversations I've had during BioInternational, but head on over to our YouTube channel because there'll be a special playlist featuring all of the discussions that I had here during the event. Collaboration starts with the Conversation Team Health Tech. Let's make it happen. I'm Jaden Rogers, CEO of Linear Clinical Research. Excellent. Thanks, Jaden. Tell us a bit more about what you guys are up to. Yeah, Linear is an early phase clinical trial site. We're based in Perth, Western Australia. We're over here in the US catching up with our customers.

1:21We run early phase trials for biopharma from the US, China, and elsewhere in the world.

1:26Peter Birch: Yeah, amazing. What are the operational things that are required in running a trial, particularly in Shrek? Well, yeah, first in human trials, it's not a small feat. You're giving an investigational drug to people for the first time. You need world-class facilities. You need high-quality staff. You need great doctors, nurses, and then quality management systems. at the end of the day you're asking someone from the US that spent 20 years discovering new science that could potentially change people's lives and you're asking them to trust that with you so yeah it's got to be a quality product and is that like the full end-to-end because there's um you know a lot of the conversations I'm having here at bio are about you know finding the right patients for a trial and just getting that that kind of process there's um it's one thing to start a clinical trial, but often, you know, many won't even get out of the gate.

2:19Peter Birch: So yeah, tell me a bit more about like the challenges in actually operationalizing the thing. Yeah. Oh, look, it's incredibly complex. It's a bit of a double-edged sword. So science is advancing. We're getting more knowledge, we're getting better at it, but that makes things trickier. And so we're very fortunate in Australia, we've got a well-developed ecosystem, we've got all the providers, we've got a great healthcare system, we've got the right regulatory environment. It's cost effective. And that means a company from the US can come to Australia, choose their partners. We might be a partner.

2:47There's other groups. And then we can put together the clinical trial. We can deliver that, make that trial available to local patients. But what we're seeing is the drug development world is evolving. So it's becoming more targeted, more precise, and being able to access patients is an incredibly important part of it. There's also another part where you're recruiting healthy volunteers. But where it really gets exciting in my mind is when you start giving these therapeutics to patients and we've had a great a lot of experience in cancer uh and this is taking some of the best breakthroughs to people who are very unwell and in some cases we're seeing remarkable outcomes so

3:22Peter Birch: yeah it's a bit of a glimpse into the future of medicine yeah 100 no you get to see see all of it before it um comes out the uh another theme in a lot of the conversations i'm having here at bio is how popular australia is for clinical trial so i assume it's going to be a busy period for you at the moment yeah you can probably tell by my voice it's not usually this croaky that's from all the meetings and also the parties as you know but it's really nice yeah I came here 10 years ago actually to San Diego and I had to get the map out show everyone where Australia was where Western Australia was now I'm getting told what to do by the Americans and learning about Australia from them so yeah the reputation is very strong for good reason and there's a big Australian contingent here so yeah it's really nice to see uh really see that uh respect and the brand awareness that's developed but it's only looking like it's going to get stronger what kind of advancements or like innovations or different ways that you do things at a trial site have kind of evolved over the the years as well because like every part of the industry everyone needs to do more with less and also just continue to evolve and um you know expand into other areas are there any kind of innovations or advancements that you can talk about?

4:35Yeah, absolutely. I think as an industry in Australia, we've got a really good setting for a start. So the regulatory environment really does support companies coming to Australia. So it's a really good starting point. But then the way the ecosystem has developed, we've got a lot of providers and we all sort of invest and specialize in slightly different areas. In our case, we're very much driven by our purpose to get therapeutics to patients to fast track that development. We've been able to innovate in technology and facilities in particular. We launched Australia's first ever private hospital, solely dedicated to clinical trials.

5:08That's been in operation for two years now. And that's where we deliver our cancer clinical trials to very sick patients. I've had the privilege of taking Big Pharma through there and some of the leading CROs and BioPharma. And it's consistently been described as one of the best centres in the world. So, yeah. And then we're very fortunate in Australia. We've got great clinicians. So you innovate around the clinicians because at the end of the day, you need someone that knows what they're doing. You need a really great clinician as principal investigator, but they become a key opinion leader. And the biopharma companies, they need to influence them.

5:40So they prescribe the drug if it eventually becomes successful.

5:43Peter Birch: I'm going to imagine this is not my, you know, it's becoming my area of expertise. But my last kind of question or thinking about, you know, those that are looking to run a clinical trial, if you had the opportunity to because I guess there would be a lot of opportunity a lot of circumstances in clinical trials where for unavoidable reasons we weren't able to get you know treatments into the hands of patients but there's there may be other avoidable situations that if things were done differently at some point in the process we could have got perhaps some innovative new care to patients are there any kind of key things you hope that or you would give advice to say, let's get this right.

6:24Peter Birch: So we've got more chance of success later on. Yeah. Look, absolutely. Discovering drugs is a very expensive process. It's circa$2 billion to get a new drug all the way through. I think you mentioned earlier, the success rates are not great. 90 % will fail through development. It takes 10 years on average to get a drug developed. So yeah, that's too long. So yeah, there's definitely ways that we can fast track that. I think from the Australian perspective, with really leveraging the advantages we have, particularly in the startup timelines and that regulatory environment that I described here, continuing to stimulate the industry.

6:58It's great to see the support across government, non-government industry. Building that out is really important. But then I think I'm really excited. I'm somewhat nervous about what AI is going to do to this industry. That holds huge promise. There's a lot of, yeah, there's a lot of duplicated effort. there's a lot of inefficient effort in drug development for very good reasons but yeah this is where we're starting to see some real promise ourselves um some of the pilots we're rolling into our operations and we're seeing it with our clients too and and i think we're going to get a good glimpse soon um just there's a whole lot of drugs that were discovered um with the support of ai um starting to go through early clinical trials and yeah the hope is that they'll have a higher success rate the better design molecules so i think we're going to start to see the innovation but I think it's incumbent on everyone to sort of keep pushing the envelope.

7:44And we've got to do it for the right reasons because, as you sort of picked up, it's a patient at the end of the day and people need it. And I think the other thing is we look at it a lot in a range of areas. Cancer has been a good example, but less than 5 % of patients in Australia get access to a clinical trial. But if you go to a leading cancer centre anywhere in the US, there's 60 % of patients go on to some form of trial. So we're on a mission to change that. And it's not just cancer. There's a whole range of other areas. We're seeing a lot of excitement in immunology, cardiometabolic fields, neurology.

8:16But our hope is that as we get better at drug development, we get these therapies to patients sooner.

8:25I'm Stacey Collad-Thompson. I lead business development at NVIDIA for pharma labs and manufacturing.

8:32Peter Birch: Thanks, Stacey. Tell us a little bit more about what NVIDIA does in the life sciences space. Yeah, so we work across the ecosystem with pharma and biotechs that are building on AI and data and enabling sort of the next generation of drug discovery. So I'm working across that ecosystem. We have just launched our BioNemo agent toolkit. So this is taking the last decade of research and products that NVIDIA has been working on in life sciences. so models that understand the language of biology and chemistry we've packaged them up now so that agents can have access to them it's all documentation that you can point your agent at our at our github and now your agent can use those tools those skills to be able to build pipelines that help you in your own drug discovery pursuits yeah for those that wouldn't be totally like that may be familiar with nvidia generally and then going away hang on a second we're talking about enabling agents and drug discovery life sciences that's like very much in this world of like this industry vertical like why why for those that may be thinking just of nvidia is like i don't know the behind the scenes or like the infrastructure powering stuff that what you just described is a lot more involved than all of that but can you help fill that gap a little bit yeah so we want to make it easier for people to use and consume compute.

10:02And we do that by making open source models that are able to be used by many in the community. And I think at this next inflection point of agentic AI, it's going to be democratizing access so that you don't necessarily need to be a computational chemist or biologist to understand how to use all these tools. It is something that's going to be more accessible to you know people like just chemists or biologists that uh that have ideas and have hypotheses and are looking to access more tools and uh and using agents enables them to do that so for us at nvidia if we make it easier for people to use compute make it more accessible then people are consuming more compute and that ends up on a gpu usually

10:51Peter Birch: somewhere that makes a lot of sense the and i guess if i think about it too because we've been talking a long time well for recently about how with all of this data that's collected probably not humanly possible to do it all with uh humans that's where the role of artificial intelligence comes in to be able to look at what we can do with um the data that's been collected but then you know it's not just your average person that's say um trying to do something with you kind of need to know what you're doing with the information and what you need to ask but then if you're getting professionals to utilize ai you don't want them spending all of their time in training the ai on what they're looking for if you know what i mean am i kind of in the right direction here you're kind of enabling like you're taking the computery bits out for the scientists to allow them to do more sciencing?

11:45Yeah, I think, I think what these tools are is enabling like a new co-worker to join your team. And that's how I think of it. It's, it's, you know, right now, they might just be like a really, a really smart sort of PhD student, a grad student that's, that's fresh off, fresh off of their degree, that's still learning the ropes, but, but they have an understanding of a lot of the tools and capabilities. So part of it is treating them as, you know, a new intern that you're going to help teach how you want to be able to progress through a drug discovery program, for instance, or find, you know, that new biological target or refine that new molecular structure.

12:32and then it's going to have tools that it can call on to help you refine some of your journey as well.

12:40Peter Birch: What I'm learning through my time here at Bayer International is there are a lot of players that kind of hone in on those specific parts that you mentioned, like the drug discovery part or on the molecular side. If you're kind of building this base, is that in competition? Are you collaborating? How does that kind of all come together? We see, you know, all of our tools are open source. So we want to make these broadly available. And we're still supporting people that have commercial models. Those are amazing models. They make it easier to consume as well than somebody that's trying to integrate an open source.

13:15So we want people to consume wherever they can and however they want to, however they're most comfortable with, whether that's through one of our commercial partners that has built on top of our stack and made something that is easier for a scientist to use or whether that scientist wants to build something themselves with all of the tools that are in our toolkit.

13:38Peter Birch: And I hear also, I was reading through about the BioNemo toolkit stuff. There's like also, it's across the anthropic side and open AI as well. Yeah, so any agent can be pointed at the GitHub and pull out any of our tools. So we love working with OpenAI and Anthropic. We also have some of our own LLMs, like our Nemetron model and agent harnesses and NemoCon, OpenShell, if people want to build their own and sort of control their own destiny that way as well. Very cool. if I think about all of that kind of enabling the ecosystem which is so cool it's kind of like at the same time if you've got everything available to you and the world is the the oyster so to speak it's kind of like what what do I do with this like how have you found the whole let's enable the ecosystem in order to in this new world and all those other cliches there's so many things are possible if if everything is possible you don't actually know what you can kind of focus on how do you work with the different kind of stakeholders to fully uh make use of some of this great capability you're building?

14:45I think this is where like our startup ecosystem has amazing ideas and often very specific ideas of, you know, where a product is needed because they understand the ecosystem as well. So we'd love to partner with them because they're building more specific solutions that can solve more specific problems. And that's what then, you know, prevents somebody from having the, from us boiling the ocean and having this not knowing where to start, I guess.

15:16Peter Birch: Yeah, 100%. So here at Bio International, I've seen, you know, NVIDIA's busy doing the rounds and connecting with the ecosystem. What have been the key conversations or the most relevant you found or interesting that you can share? Yeah, so one of my roles, I'm here focusing a lot on the translation from, you know, agentic AI and that understanding of biology and chemistry into now, how do we take that into the lab and validate some of those predictions? And how do we make the lab not the bottleneck in this design, make, test cycle now? So a lot of lab automation companies and data platforms and AI scientists are coming together in that ecosystem to enable faster lab in the loop cycle times.

16:06And so those are a lot of the conversations I'm having here on people that are interested in building out that automated lab, on thinking about physical AI now as the next frontier so that, you know, the agents are not just making predictions, but now are connected to an orchestrator that understands the layout of your lab, that understands all of the laboratory information management system, what supplies and reagents you have, what starting materials you have, and then based on your hypothesis can then formulate an execution plan. And then being connected to all of your laboratory instruments and automation systems can then execute that.

16:48The data comes off of those instruments, then back into your data platform, and it's ready to refine those predictions and models so that you can make your next hypothesis. Yeah, amazing.

17:00Peter Birch: And lastly, any other final thoughts, reflections and stuff coming away from bio or even things that you'd hope the rest of the ecosystem will start to think about or now realize is possible? Yeah, I think we're at this inflection point of agentic AI now, and it certainly is permeating a lot of conversations that I'm having. Big pharma are across the spectrum. Some are early adopters that are leaning in and are really at the bleeding edge with building their own AI capabilities and agentic capabilities and infusing that in every step of the process. And others are looking to partner in this space because they're wanting to sort of leak frog into the front here.

17:45So everybody's leaning in in different ways, and it's exciting to see here.

17:54My name is Arjun Bhatt. I'm one of the co-founders at ClinRoll. We're a patient management software and platform company where we help clinical trial sites make their life easier when it comes to recruitment and patient management.

18:06Peter Birch: Yeah, amazing. And you're, I'm sensing the strong Australian accent for once here and some of these conversations we've had here on the podcast. So it's good to see Australian representation. Yeah, absolutely. Brought up in Sydney and we're an Australian born company. All of our founders are Australian and we're proud to help sites, especially in Australia, build this platform from the ground up, just really understand the pain points that they have, especially when it comes to recruitment, patient processing and just speeding things up when it comes to engagement, retention and the trial operations.

18:39Peter Birch: No, nice one. We'll come to the international opportunity near the end of the chat, but just more on the challenges in Australia. So patient recruitment. So finding, you know, with clinical trials often, as I understand it, clinical trials often have a really particular requirement when it comes to patients, depending on what the trial is about. And sometimes it can be like finding that proverbial needle in the hay sack type thing. But also at the same time, it's a lot of patients that if they were aware of a trial, they'd probably be all over it. So is that kind of directionally the challenge we're addressing?

19:12Peter Birch: Exactly. Yeah. so we we kind of do it in multiple factors or tackle the problem multiple factors so we have a patient matching aspect where a patient can go onto our platform there's a bunch of studies or a lot of studies they can basically using natural language type in what study they're looking for their demographics what condition they have and they'll basically be matched with various studies that fit their criteria. And then on the site side, we have a platform where, for example, there's a lot of studies these days where things are getting popular, like things like GLP-1 studies where a site might get a thousand interested leads.

19:53And that takes a lot of time to process all those leads. You know, some of these sites only have one or two staff that do patient recruitment. So our platform automates that process, engages with interested patients, checks their eligibility automatically, and then schedules them for a screening visit.

20:10Peter Birch: Yeah, right. Am I understanding it right then? So, you know, it's not even the finding the patient's kind of, well, yes, that's a challenge, but then like there could even be situations where there's a big pool of patients who've been identified and there is further credentialing or eligibility checking that needs to be done. It's just that at that end that that checking needs to be done, sometimes there's not enough capacity to do it. So there'll be a big pile of patients that could have gone through, but they just didn't, there was that tiny kind of pipe to get them through. Yeah. So, I mean, the best example I can give you is we were running a central recruitment campaign for endometriosis, and we were sending good referrals, but there was one site that essentially didn't follow up with a patient until two months later.

20:57And it wasn't because that patient wasn't a good fit. It just simply was a case that they didn't have enough time to reach out to that patient. They were preoccupied with, I guess, more important aspects of clinical trial conduct. So that's why we built this platform from the ground up. We have automation and engagement tools that automatically reach out to patients once they register. It keeps them in the funnel. It allows them to understand where they actually sit in the recruitment funnel. it provides automated information as they progress through the different stages of recruitment

21:31Peter Birch: i feel like that's going to become increasingly important too if the vibe i'm getting here at bio is that um the big appeal in this industry of australia is the opportunities that exist in doing clinical trials and if we're presenting ourselves as a great place to do clinical trials we we want to be able to do clinical trials well exactly yeah so i mean everyone talks about the R &D incentive and good regulatory pathways or the quick regulatory pathways. But I think Australia is great operationally. We have great sites. We have great staff. Quality is always excellent. And ClinRoll, our job is to, you know, make things more streamlined for sites, especially when it comes to engaging with patients, processing patients, checking that they're eligible and they just understand where they sit in the whole trial process.

22:16Peter Birch: And I guess too, if I was thinking about the, you know justifying the return on investment obvious i mean it makes a lot of sense to me just being able to give access to more patients to to clinical trials but there's got to be um huge commercial opportunity and or like that's left on the table or that there's is kind of seen as waste when we're trying to use humans on tasks that probably ai is more helpful exactly time is money right so you know if we can harness technology especially ai to do those repetitive low i guess oversight required items and just get ai to do it it means that we actually get side staff humans freed up to take care of more important aspects like patient care yeah so you know we've we've seen recruitment teams at sites spend eight hours a day just trying to follow up you know a bunch of patients and then a week later those bunch of patients aren't even eligible so if we can kind of use ai to automate that whole process so at clinroll we do ai outbound pre-screening calls which a lot of sites are now using which really helps them with that high volume so yeah it just frees up more time what's been the um reception like from a patient receiving a ai phone call you know like we might already all be receiving ai sales calls and it's you know, we've had our own previous experiences years and years ago with automated IVRs.

23:48Peter Birch: And I know that's very different technology, but what's, has there been any early indications on people's acceptance of it? Yeah. I mean, it's 80 % completion rates. Our methodology is we don't pretend that it's a human. We are upfront that it's an AI call and the interested participant or patient actually needs to schedule the AI call. So they know it's coming. We would never do, you know, an out of the blue call to a person because, you know, that's just when things go wrong. And it's just about giving that optionality. So some people, you know, they obviously work nine to five. Clinics are open nine to five during the week.

24:23So, you know, the opportunity for an interested participant to receive a call, an eligibility call on the weekends or after five just makes sense. So, yeah, it's just using technology to make the experience much better.

24:36Peter Birch: 100%. If I, you know, if I receive an AI phone call out of the blue, I'm it's gonna be a lot of work to do to kind of keep me on that phone call but if it's a I'm scheduling something in and I can make the call at three in the morning because that's when I'm available because I'm traveling or whatever then amazing you know like that's I'm all for it so I can see the the real opportunity that exists there and so um you're here at Bio in San Diego yeah um what what brings you to the event just to meet people um spread awareness about how we're using technology at clinical to solve you know a real issue in in clinical trials which is obviously recruitment and patient management and retention.

25:11Had some great conversations with all three stakeholders. So sponsors, CROs and sites and site networks as well. We continue to notice that, you know, a lot of clinical trials and sites aren't using the right type of technology. They're using, for example, CRMs that are built for sales and other tools that have, you know been built 20 25 30 years ago and they're basically sticky taping things together so it's really refreshing to have a conversation with someone um whether that's you know a sponsor or a site and just explaining that we've built a centralized platform specific for clinical trials uh we're also you know going through all of the security standards and privacy um aspects and yeah really excited to continue the conversation with as many people as we can as great awareness Yeah.

26:03Peter Birch: And lastly, what's on the horizon then, you know, as you come back home, always work to be done. What are some of the priorities for ClinRoll? I think just kicking goals with roadmaps. So we've launched the ClinRoll Connect at the start of this year and we've received a lot of good feedback. And based on that feedback, we can continue to add to the roadmap. really kicking more goals in terms of filling those pain points with sites and site networks, using AI technology to get rid of those mundane, repetitive tasks and giving more time back to the sites. That's our goal. And we'll continue to do that.

26:45We love feedback and exciting times ahead, I think.

26:51Thanks for having me. My name is Tran. I'm a general manager at Hippocratic AI. I lead our lifeline solutions, especially in clinical trials. Before this, I was the co-founder and CEO of a company called Grove AI. We were the first to market with AI agents to run clinical trials. So we helped clinical trial sites, CROs, as well as pharmaceutical sponsors to run clinical trials faster with pre-screening and recruitment through these agents. Very cool. So very excited to be here at Bio and share a bit more about how we help our pharma customers run trials faster. Yeah.

27:24Peter Birch: Okay. I was going to ask about what is the role of then AI in clinical trials? Yeah. So I started off working as an AI researcher at Stanford Medicine, so a hospital. And essentially what my job was before ChatGPT came out was to really think about how we can run clinical trials and do clinical services faster. And I remember when GPT-2 came out and the very beginning of these models, I was like, oh, my gosh, we can start to do calls to people and actually interact with them and say, hey, Peter, can I educate you about trial? and it was no longer, you know, this chatbot. You can actually have an interactive conversation and be there 24-7.

28:03And so then I, you know, I ran to my co-founder, Soit, who also works there at Stanford Met, and said, so we can actually speed up the hundreds of thousands of hours that are manual in clinical trials and do a lot of this work through agents. So that's really the premise of it.

28:18Peter Birch: Yeah, right. And so is that the recruitment side of things, like finding the right people to jump onto trials because that's part of the challenge? Often there's like really specific niche requirements. that to find those needles in haystacks can be difficult. Yes, definitely. And so what our tech does is before a patient or a participant enrols in a trial, there can be tens of thousands of folks who are interested. They express their interest through Facebook ads, community events, in person, their doctors. And a lot of times, because clinical trials is not a part of central clinical services, it gets, you know, take an overlook, go to ct.gov, find it yourself, find your own sites.

28:55What these agents do is we'll contact you, will say, hey, Peter, I saw you were interested. You consented to receiving more information. Can we tell you a bit more about the trial? Can we ask you a few questions so that we can see which trial is the best match for you? Great. We found a great match. Where are you located so we can find the closest site? Can we help you book your transportation? Can we help you warm transfer to the site? These are all things that the agents does on demand. So you can think about it like Amazon customer service, but maybe on steroids. Yeah, got you.

29:25Peter Birch: And is that the big block in now because I think about the reason you deploy agents to do that is because if you were to get a bunch of humans to do that you'd need a lot of humans and a lot of time whereas agents you could deploy all at the same time so is that the challenge that there's an opportunity to engage with a lot of people who potentially might be a fit but you've got to kind of really hit a lot of people at the same time am I understanding that correctly yes we just did the math for one of our clients, a phase three trial arthritis trial that we just ended up recruiting for. They needed about 750 participants across 89 US locations, and they needed to speed this up.

30:04And so essentially enrolled our agents, we trained it on the protocol, got the script, IRB approved, went through everything, deployed the agents out to pre-screen 25 ,000 potential participants. We ended up enrolling about one eighth of their trials in a span of four months. And we compared that to the normal industry rates for the same therapeutic area. And we were about 168 % faster in randomization just because we were able to provide this full concierge. And so that was a team of about 28 or 30 folks. But we did that span of work with, you know, like one or two engineers doing that agent behind the clinic staff.

30:44Peter Birch: And directionally, where does this go? Like if this is the demonstration of the potential of it in the clinical trial space, where are you seeing the ball going? Yeah, so today I'm here at this panel actually with the FDA commissioner, another person from a different hospital system. And really it's to talk about some of the results that we've been seeing for the past two years and now to push the boundaries of where this can be possible in trials. So now the question is, great, we support with pre-enrollment. What else can we do? Can we support with concierge in trials? Can we help folks with adherence?

31:15Can we help folks after the trial ends? What else is possible out there? At Hippocratic, we're now also launching solutions for agents to support within patient services on the commercial side, as well as to educate doctors, playing like an MSL support role for a medical science liaison to go out and help doctors understand the latest tests and trial results. So we're doing a lot of cool work generally, and I think this will be very helpful for the community at a whole.

31:42Peter Birch: Yeah, nice one. And lastly, because this is my first bio, if there was something I should be really keeping an eye out for other than AI and clinical trials, or maybe that's the hottest topic, I'm not sure. What should me or other people checking out bio, what do you think we should keep our eye on? I think I'm here just to learn the science, go read all the cool research papers that are being published. I think a lot of times at these conferences, researchers come with posters and findings that are exclusively just at these conferences and not posted anywhere else online. Can't find it on PubMed or elsewhere.

32:16And at the heart of bio and in these life science companies is the assets, is the research. clinical trial operations is one part, but having a very successful candidate and an asset that you can take to market that works well in folks with high efficacy rates is definitely very helpful. So I'm very excited about seeing all the new compounds and new researchers that are coming here. And I think everyone else should be too. We hope you enjoyed this episode of Talking Health Tech. Make sure you like and subscribe and share this episode with someone who might find it valuable. For more information and resources about healthcare innovation, visit TalkingHealthTech.com.