- Why Us
Should you have patent protection for your medical device technology? Should you keep your secret sauce via the trade secret route? Perform due diligence to stay ahead of the competition.
In this episode of the Global Medical Device Podcast, Jon Speer talks to Kevin Buckley and Neil Thompson from Torrey Pines Law Group. Their biotech-focused legal firm specializes in artificial intelligence (AI) applied to medical devices.
Together, they discuss intellectual property (IP) with software as a medical device (SaMD) and AI and machine learning (ML) powered technologies.
“If you look at it in a way that solves that problem first—do you want to patent or not—then it becomes less tricky.” Kevin Buckley
“With coronavirus out there, a lot of our clients are trying to come up with new ways to...help people with the disease by utilizing technologies that are novel and unobvious.” Kevin Buckley
“The secret sauce, which is your trade secret, if that is generating something that is detectable, typically, our advice is to get a patent on it. Don’t keep it a trade secret.” Kevin Buckley
“Don’t get caught with your ‘patents’ down.” Kevin Buckley'
Announcer: Welcome to the Global Medical Device Podcast, where today's brightest minds in the medical device industry go to get their most useful and actionable insider knowledge, direct from some of the world's leading medical device experts and companies.
Jon Speer: We've talked, in previous episodes, on the Global Medical Device Podcast, about artificial intelligence, AI, machine learning, talked about software as a med device, we talked about regulatory- related items on those topics, but we never have talked about the intellectual property or the IP side of things on AI and software as a med device. And we're going to change that. So starting with this episode. So enjoy this episode of the Global Medical Device Podcast. I talked to Kevin Buckley, the founder, and Neil Thompson, a patent agent, with Torrey Pines Law Group. And we talk about IP, with respect to AI and software, and a few other tips and pointers for a med device in general, so enjoy. Hello and welcome to the Global Medical Device Podcast. This is your host and founder at Greenlight Guru, Jon Speer. And one of the things that is kind of a hot topic in, well, everywhere these days it seems, is AI, artificial intelligence, machine learning, specifically in the med device industry and other hot topics that sort of piggybacks on the AI side of things. Not always, but sometimes, is software as a med device or SAMD, there's lots of twists and turns, and nuances, certainly from a regulatory perspective. And if you've been a listener of the Global Medical Device Podcast in the past, then you probably have heard some of the regulatory- related conversations that we've had on these topics. But I thought we would take kind of a little bit of a twist today, and I don't think we've done anything on IP or intellectual property, ever, on the Global Medical Device Podcast, and we certainly haven't done IP related to AI and software as a med device, so I thought this would be great topic to dive into. So joining me today are two gentlemen who are from the Torrey Pines Law Group, Kevin Buckley, he's the founder, and Neil Thompson is a patent agent. So Kevin, Neil, welcome to the Global Medical Device Podcast.
Kevin Buckley: Thanks, Jon.
Neil Thompson: Thank you.
Jon Speer: Absolutely. So typically, when we get into these episodes, kind of a first place to start is you maybe give people kind of a high level overview of who Torrey Pines Law Group is and maybe some of your areas of specialty. And then we'll dive into this topic of IP with software as a med device and AI.
Kevin Buckley: All right, well, the history of Torrey Pines is mostly focusing on healthcare, life sciences, which includes medical devices. So the firm has represented medical device clients for seven years, and in that seven years, we've formed a really nice specialty which focuses on artificial intelligence as it's applied to medical devices. So we represent a lot of clients that are working on software implementation of medical devices. Pure software, as well as hard medical devices combined with software, a lot of SaaS clients, and we are really moving in a direction toward machine learning, deep learning, and a lot of different nuances related to this type of software.
Jon Speer: I mean, I know, and in Greenlight's world, I mean, Greenlight is a SaaS platform, obviously, that works with medical device companies and it's tricky from an IP perspective, right? I mean, because... I mean, I'm probably over simplifying this and maybe misstating this, but it seems like, from a patent perspective, it's easier to kind of wrap your head around something that is more of a tangible good. And it seems to be a little bit more tricky to protect your software from an intellectual property perspective. Is that something that... I don't know if you would agree or disagree with that or have some other thoughts or ideas that may counter what I'm suggesting.
Kevin Buckley: Yeah, I think... So, I mean, really, the answer to your question is it is tricky. But if you look at the problem to be solved, and that usually is first determining whether you want to protect your technology as a trade secret. Do you want to protect it under copyright and just the code? Do you want to patent it? So if you look at it in a way that solves that problem first, do you want to patent or not, then it becomes less tricky. For example, if you wanted to patent a technology, there are a lot of things that you need to determine first. And the first step, usually, is doing a patent search. This is pretty good advice for anybody, for a couple of reasons. If you do a patent search and we use professional third party vendors all the time to do these kinds of searches, if you're finding that your competitors are out there and they have claimed some invention that you might be infringing upon or you could work around, well, that's just good information to have. It doesn't matter if you're trying to patent anything or not, doing these types of searches are really informative.
Jon Speer: It makes a lot of sense. I mean, I just chime in there because... See if I can connect some dots that you're proposing. So I guess one way to think about this is if I'm trying to figure out, do I patent this, do I protect this as a trade secret, what have you, regardless of the situation, it's good to know sort of the prior art, if you will, that's out there. So I can say," What are other people thinking about this?" It's good from a competitive landscape. Am I connecting the right dots?
Kevin Buckley: You are. Yeah, competitive intelligence is one of the key areas in which we focus. And you can imagine that if you are thinking about licensing this technology, if you're thinking about getting acquired as a company, if you're thinking about getting an investment to enhance your R& D, this kind of question will pop up in due diligence. If somebody's looking at working with you, you really need to know where you stand with respect to your competition. If there is a freedom to operate problem, in other words, if somebody has a claimed invention which you might be stepping on and you might not know it, well, that's going to be a problem if, for example, an investor finds it before you do. Another situation is if you are looking at these technologies for potential patenting and you find a blocker, you want to know how to work around it. And this is something that Neil and I do all the time. We look at these professional searches, we see if there're any blockers, we see if there's any whitespace between two claimed inventions, where our clients might have some wiggle room to claim their invention. So it's just really good business sense to get these types of searches completed.
Jon Speer: I kind of introduced this as we're going to talk a little bit about AI and software as a med device, and how to navigate from an IP perspective, are you finding a lot of interest in this particular topic?
Kevin Buckley: Yeah. So, again, we're focused on life sciences, healthcare, and we have numerous clients that are developing these technologies from scratch, De Novo. We also have a lot of clients who are adapting artificial intelligence, machine learning, deep learning, etc., to more conventional technologies. Our clients are looking for better ways to skin the cat. And a lot of times, that is done with machine learning, with the deep learning, and what we're finding now, especially with Coronavirus out there, a lot of our clients are trying to come up with new ways to, number one, help people with the disease, but utilizing technologies which are novel and unobvious. And it is such a hot area right now, Jon, and Neil, and I have been working seven days a week for the past 13, 14 years.
Jon Speer: Oh my goodness.
Kevin Buckley: Yeah, it's been crazy.
Jon Speer: Wow. I realized that I'm asking probably a proprietary question here, but any, I guess, stories that you can share that the listening audience might be able to relate to?
Kevin Buckley: Huh. Well, that's interesting because, yeah, I can imagine that your audience is representative of so many different technologies, but if we're going to talk about a little bit about software, a little bit about the AI, I think that, again, first question is, do you want to patent it or not, or do you want to keep it a trade secret. A lot of that would be determined based on a search. If somebody's competing with you and they are blocking you somehow, and you can work around that, well, then maybe you want to keep your technology a trade secret. So that's just kind of general good advice. Yeah. There are a couple of other things though, Jon. I mean, when you're getting into a deep dive into how to really flesh out your technology so that it can be patented, for example, there's just a lot of different things that need to be considered. And they all relate to the law, the patent laws, and these are all international laws by the way, so Neil and I are handling these things not only in the US, but Europe, Canada, Mexico, Brazil, etc., etc. All over the world. So yeah, there's just a lot of advice that we can give. I don't know how long we have Jon.
Jon Speer: Well, why don't we maybe start into the practical tips and pointers, and maybe here's a good place to start. So what advice would you give engineers and researchers, and inventors and scientists, etc.? What advice would you give them when deciding to seek patent protection on a technology.
Kevin Buckley: Yeah, you want to tackle this Neil?
Neil Thompson: Sure. So when it comes down to this, the idea of what to patent, it's really important, especially when you're dealing with software and AI- type inventions, that you have to follow what's called the Alice two- step process. And it stemmed from a Supreme Court case which essentially made it a little bit more difficult to claim these types of inventions. You have to go through this process to determine whether your invention's even patent- eligible. And so, for instance, if you have an invention that's claiming a law of nature, a natural phenomenon or an abstract idea, and if that's the case, then, essentially, the invention that you have has to build, I guess, has to have significantly more than just those three things to be considered patent- eligible. And that's where a lot of people get tripped up on the definition of what significantly more means. In Europe, they've done a bit of a better job in defining this than in the US, in that they deem the answer to this to be a technical solution to a technical problem. And so if you're able to determine... Or your invention actually has a more detectable solution, as opposed to just a lot of code or something that's not even associated with any type of hardware, that type of thing, than it's going to be a lot more difficult to patent that than if it were to be, as I said, associated with some sort of hardware.
Jon Speer: So that's called the... You said Alice two- step framework.
Neil Thompson: Yeah.
Jon Speer: All right, maybe we'll go over that here in a few moments because that raises some questions. It sounds like a new dance step or something, I'm not really sure, but any other thoughts that you had? I mean, I know, Kevin, you mentioned maybe a couple of times and, so far, that we have a choice. Should I seek patent protection or should I go the trade secret route? Assuming that some folks may not understand the pros and cons of each, can you maybe elaborate on the pros and cons of IP versus trade secret?
Kevin Buckley: So this is an interesting problem because, usually, the real quick response is just keep it a trade secret because it'll never publish and it's unlimited duration. You can have a trade secret forever. Well, it may be in a perfect world. But the difference, the real key difference is a patent you get for 20 years from the date of your first non- provisional file. It's limited duration. After 20 years, it's essentially given to the public. You're no longer able to enforce your patent rights. The real problem that we see, especially in quick moving technology areas like a medical device, and it's an iterative process, software is always changing and AI is happening and changing so rapidly that the big problem is, even if you're keeping something trade secret, somebody can develop it independently of you. So a lot of our clients, they think about this in a really nuanced way. If they've got something, a software, for example, that provides an output, and it's a unique output, a certain type of score, or some type of visualization on a picture, or something that you can detect as its output from an algorithm, for example. If it's detectable, our clients are usually opting for patent protection, especially if it's something truly unique. One of our clients, they developed a score for certain parts of X- rays, and those scores relate to detecting cancer. So patenting a score or a system to generate a score was really important for that client. The alternative would have been to keep it trade secret, but then, a competitor could've independently developed another way to generate a score on a X- ray and the client would've been stuck, and they would not have been able to keep that competitor away from their technology. So, Jon, it's a really nuanced question. It's a real gut check. And if you think that you can keep certain things trade secret, even though they're being displayed, so that the trade secret itself isn't being displayed, but the secret sauce which is your trade secret, if that is generating something that is detectable, typically, our advice is you get a patent on it. Don't keep it a trade secret. Somebody's going to work around you.
Jon Speer: Yeah, that makes a lot of sense. Any other tips or pointers that you can think of that engineers and vendors, researchers, etc., should be doing to, I guess, prepare their case, if you will, for patentability?
Kevin Buckley: Because of Alice, and it's funny, Jon, it's a funny nickname but there's a Supreme Court case from 2014, that's where the name Alice comes from. Our Alice was one of the parties in that Supreme Court case and that's where that framework came from. But, because of that case, what we're seeing is there's a lot of homework, and vendors need to do, in helping patent attorneys and law firms, just like Neil and me, get these applications fleshed out in such a way that you can beat Alice. So to overcome Alice rejections, what we're seeing is when our clients can describe a number of working examples, some of them can be things that you've already done in the lab or at the bench, but others can be what we call prophetic. If you can describe a way that your medical device or software, anything AI- enabled can work and alternative embodiments to things working, that's how you're going to do two things. You're going to enable your invention. That's one of the things that is required. And, as well, to keep your patent in force after it issues, you can expect challenges. And one of the challenges that's commonly used is you're not enabled. So by putting these working examples in, even if you're making it up kind of, it just needs to teach, one, a skill in the art, how to make and use the invention without undue experimentation. So in other words, flesh it out with working examples. So Neil and I are getting a lot of really good input from our inventors before we even start drafting the application, and that really helps us get these things, number one, drafted, but number two, issued. And then the second thing, really, with, especially software, if you're going to be claiming not only a system, so if it SaaS, if it's something on a server, if it's cloud- based, what have you, there's probably a method of using your medical device, using your software that you're going to be claiming. So a lot of the homework which our inventors do, again, before we even start drafting the application, is getting flowcharts ready. So a flowchart images on how the process is utilized, how the system is utilized, the type of input, the type of output, the different routines, subroutines. It's really easy to describe things pretty generically in flow charts, so that when you claim your invention, you're getting some additional breadth there, which you might not necessarily get if you're not providing the flowcharts, not providing the drawings, and other images of how the software works. So those are two really good steps for any patent attorney to take, a medical device software especially, to take it and draft a really killer patent application.
Jon Speer: Yeah, I like that a lot. And, in my world, those steps are part and parcel with just good development practices anyway. So this does seem to be, I guess, in a good way, overlapping or dovetailing very nicely with what a medical device company is expected to be doing on the regular anyway, to support their claims from a regulatory perspective. And I want to talk about that in a moment too because I know your firm does a little bit of work in that space too. So I just want to remind folks, I'm talking to Kevin Buckley and Neil Thompson. Kevin and Neil are with the Torrey Pines Law Group. You can find out a whole bunch more about their firm and their service areas by visiting torreypineslaw. com, and it's T- O- R- R- E- Y- P- I- N- E- S- L- A- W. com, all one word, no hyphens, no spaces, none of that. And again, you're listening to the Global Medical Device Podcast hosted by Greenlight Guru, as you probably know. And if you don't, I would encourage you to check out what we do at Greenlight Guru. Greenlight Guru is a SaaS platform, we are the only medical device quality management system on the market today. We were designed specifically and exclusively for the medical device industry, and that the platform's actually been designed by actual medical device professionals who have our fingers on the pulse of what's happening in the EU and FDA, and so on and so forth. So check it out, go to www. greenlight. guru to learn more. And if you're interested, reach out to us and we'd be happy to connect with you and share more about how we might be able to help you with your quality system, and your go- to- market strategies and things of that nature as well. All right, so getting back into Neil and Kevin, let's talk a little bit more about AI- enabled inventions. And I think this is a true statement, but, pretty much, when we talk about AI, we are probably talking about software. I know it's a hot topic. Every time it seems you're reading something in the news or every commercial these days... I think my water bottle that I bought the other day has AI- enabled in some way, shape or form. So it is a buzz- worthy topic and there are some really cool things that software companies are doing to enable AI. You mentioned that the X- ray imaging and being able to take that and develop some sort of score for cancer detection. So that's really cool, right? But what are some other tips that you might provide, and to those listening, for what they should be doing for their invention that has AI?
Kevin Buckley: Yeah, so... And it is. It's all software there, of course. I keep on saying the word nuance, Jon, but it's true, there are so many nuances to AI and actually getting a device, an existing device or a brand new device, working with machine learning, deep learning, the algorithms, all of the neural networks, etc. So the first thing that we look at as patent practitioners is how are we going to get something issued as a patent? And we mentioned Alice. The real kind of big picture idea with describing and claiming these types of technologies for patent purposes is to think of it as a system. And when you're thinking of AI implementation of devices as a system, you're not talking about something super abstract, you're not talking about just a mathematical formula. What you're doing is putting some really good physical parameters on what AI is doing in conjunction with the device or even separately from the device, or within a system. I guess that's another way to say it. So when you're describing the invention, I guess the recommendation would be do it as a system, not as an AI software routine. AI software routines are... It's looking a bit too much like exclusive software. And your audience probably has heard that getting software patents is more challenging now than it probably ever has been. They're still allowable, people are still getting issued patents, but it's harder now. When you couch the entire invention, as a system, you're just going to get a lot more attraction. You're going to get a broader claim as well. AI, you can imagine, it's based on training models and models require a lot of data. So machine learning, that requires a lot of data which has been a marked up by human beings. So, for example, if, I don't know, you're looking at a bunch of images on Google and you're trying to determine which one is a cat. And, believe me, this is not as hypothetical an example is as you think it is. These are the subjects of contests. How accurate can someone look in a random sample of images on Google and how accurately can you find a cat? That's a really tough problem. So, you can imagine, the data sets. You have to train a model to recognize a cat in this hypothetical. So that could require millions of images of cats in all shapes and forms, in all positions, all colors, and in all states of what cats do. So that is a huge challenge right there. Machine learning, if you have humans marking up those datasets, that's one thing. Deep learning, on the other hand, requires huge amounts of data because a human isn't marking up the data. It's a computer learning on its own and telling the user what a cat is. So all of that, it's a long way of saying that data is going to be very important to every medical device company which is implementing AI. Whether it's, again, an old technology which is newly implementing AI, or it's some new AI technology itself, that's going to be a huge thing for any of your audience members to look at. And that is going to be very important for we patent professionals to really understand. That the next thing is, once you've got all the data set out and you're you're adequately able to describe it to people like Neil and me, there are a lot of algorithms out there. I mean, you can't count them on five hands. The algorithms are being developed so rapidly right now and improve so rapidly that I think a lot of the members of your audience, they'd really get a lot of value out of looking at what those algorithms are, what the neural nets are out there, how they're implemented, how they could be combined to more effectively operate with the existing software or hard device. There are a lot of ways to optimize software- optimized devices using artificial intelligence. That is what is patentable. It's the optimization of how the system works. It's the optimization of the output, what a user sees, how a user can interpret that optimized output. That is all going to be critical, not only for your audience members to implement AI into device, but also to get a patent.
Jon Speer: Yeah, a lot of great stuff there. I was looking at the Torrey Pines Law Group website and I know you do a lot of work in the IP space, but I also see that it looks like you do a lot of work in the regulatory space. And you mentioned De Novo earlier too, and this conversation's kind of got the gears turning. And I think the challenge, sometimes, or the perception anyway, is like IP and... It's almost like IP and regulatory pathways, they're almost can be diametrically opposing of one another. And I guess let me elaborate a little bit further. So a lot of people seem to gravitate toward, in the US, the FDA 510( k) pathway because it's the most clear pathway and the most predictable, etc., etc. However, more or less, a 510( k) is more or less saying," Hey, I got a me- too product." Because I'm comparing my thing to something that's already been cleared. From an IP perspective, that seems to be a challenge. Can you speak a little bit to some of your experiences with that?
Kevin Buckley: Yeah. Yeah. Yeah. And we have this conversation. You know what? I have this conversation at least once a day with our clients. And so the predicate device is a... It's a challenge. First of all, you have to find a predicate to show some kind of an improvement. And that's a that is a very patenty word, improvement, because improvements are patentable. But here's the challenge, and this is why we work so closely with our clients in the med device space. Let's say you choose a predicate which has a pending patent claiming the predicate. So the question is, are you infringing that patent on the predicate device, to go 510( k)? Let's just say that if you are cleared through 510( k), the moment that you hit the market with your device, whether it be a heart device software or what have you, are you infringing somebody's patent? Well, in my recommendation would be take a close look, here's where patent searching comes in, by the way, take a close look at your competitors, see if they have any patents pending or even patent applications submitted, and maybe they'll get a patent on that device that they're applying for in the future. Really important that Neil and I work very closely with our clients, and figuring out kind of the kind of the dance that we do. Looking at not only the regulatory pathway, but the IP pathway as well. So you can imagine working with our clients. Let's just say that, I mean, everybody wants to avoid PMA. It's expensive and it's uncertain. But if they want to go 510( k), the one good way to look at that is," Okay, you are me- too, you are an improvement, but maybe our improvement is a work- around to what other competitors are doing." So it's different enough so that you potentially avoid the IP problems. So you get your clearance, but there is a way to do things which avoid blockers, which are pending patents, which claim the predicate device. It's always a question that we look at. The second thing that we do is," Okay, well, if you can work around that, you can claim something potentially in your own patent application, which avoids your competitor." That is something that we try to patent. It's what I mentioned before is the whitespace between patent claims and in this kind of a patent landscaping that we do. So you can also imagine that things change, Jon, as you know. So as you're developing a device, you're going 510( k) for sure, you will almost certainly, somewhere along the process of developing that device, there are going to be changes even.
Jon Speer: Oh, yeah. Yeah.
Kevin Buckley: I mean, so let's just say, even if you patent version 1. 0, version 2. 0 is probably something that you didn't include in the patent application itself. So the question is, how do you keep your IP strategy going in the right direction through version 1. 0, 2.0, 3. 0, etc., while you're getting regulatory approval? So that is something that we, again, we work very closely with our inventors in the space, so that if they do choose the patent route, we are always refreshing things based on the changes that are inevitably going to happen, not only in the clearance process, but in the technology development process.
Jon Speer: Yeah, that's really good insights. Really good insights because I know this is always something that folks challenge. And I know some things, I've got a couple of folks that I've talked to quite a bit about this in the past, that are more regulatory- oriented, but some of the recent, and when I'm saying recent, I'm talking within the past five years or so, updates with FDA, the De Novo path is becoming more and more attractive to companies I'm guessing. And that allows me to claim more novelty than if I'm going to go that 510( k) path.
Kevin Buckley: Yeah. Yeah. Well, the company I mentioned earlier, I was fortunate to be on a team which got 510( k) De Novo clearance for that cancer detection system. And I believe it was the first device cleared for.... At least for breast cancer detection and mammograms, and I think it went further. I can't remember the exact label. Yeah, I think a lot more people are using that, and like you said, Jon, it allows more wiggle room, more space to get a cleared product, and again, potentially keep your competition at bay using that De Novo process. But again, going back to the IP part of it, when you're going De Novo, there is usually something that is protectable by way of patent, by way of trade secret protection. We haven't talked about know- how yet, but there are any number of ways to think about how to work with patent counsel on protecting something that is going through that De Novo process.
Jon Speer: Absolutely. So I guess as we're wrapping up today, Neil, Kevin, any final thoughts that you think are important to share with the listening audience?
Kevin Buckley: What do you think Neil?
Neil Thompson: Yeah, well, it was mentioned earlier on, but it really is important for inventors to take into account, I guess, the path, going forward, when it comes to patenting software and AI- affiliated innovations. Making sure that there's a... I mentioned earlier that there's a technical solution to the technical problem. And, specifically, when dealing with AI inventions, that you're obviously dealing with an input and making sure that the training of the input is mentioned in the specification or mentioned in the patent application. In fact, what exactly that training is and how it relates to the output that the invention eventually spits out, and just being mindful of all of these things and just know that you know of what's to come ahead during the whole process.
Kevin Buckley: And, Jon, I just kind of got to reiterate what I was talking about before, with respect to due diligence. I think the most salient point we can provide your audience is don't get caught with your pants down. Even if you choose not to patent whatever you're doing, somebody eventually is going to ask you," Well, who's got a patent on it?" You need to nail that. If you're talking with licensors, licensees, collaborators, acquirers, investors, any sophisticated third party is going to want to know what your challenges are with respect to IP. So I guess the most salient point, the best recommendation is see what your competitors are doing. Doing patent searches is relatively cheap, it's something like 600 bucks. That money is very well spent if you can explain to investors, for example, how you don't infringe somebody's patent, how you've avoided it, you have looked at it, and you're not blindsided by these types of due diligence questions. Again, don't get caught with your pants down.
Jon Speer: I wrote down a few points that I wanted to wrap up with and you hit point number one much better than I was going to focus the other points that I picked up from the conversation with Kevin and Neil is there is this... There are tradeoffs, there are pros and cons with respect to considering whether or not to go the trade secret route or the patent route. So something that you want to be very conscious about making that decision. The novelty piece that's really important. And I think it's really important to realize that your product strategy or your IP strategy, or however you refer to this, it's got to dovetail really well with your regulatory and your go- to- market strategy. So you want to make sure that all of these things are flowing and connected to one another because they all sort of feed off of one another or feed into one another in some way, shape or another. So Kevin, Neil, thank you so much. I appreciate you taking time to talk a little bit about the importance of IP, with respect to AI, and software as a med device, as well as some of the other key tips and pointers. What are the best ways for those listening to get ahold of you? Is it just simply go to the torreypineslaw.com website and fill out a contact us page or do you have some other preferred way for people to reach out to you?
Kevin Buckley: Yeah. Through the website, it's easy. Our number, if anybody wants to call, 858-869-1250. And we really enjoy talking, fleshing things out with potential clients, so please don't hesitate to call. We have free consultations, so it won't cost you anything. And you know what, Jon? The thanks actually do belong to you, this is such a cool platform that you're providing and we're just really lucky to have met you and talked to your audience.
Jon Speer: Oh my pleasure. And you should also thank Neil because I know he was like,"I think we've got a good message to share." And once we finally connected, I'm like," Absolutely. We've never covered this topic." So how about this, how about we make a point to follow up with maybe some other IP- related topics on a future episode?
Kevin Buckley: Yeah, sounds cool.
Jon Speer: All right. Well, folks, again, check out torreypineslaw.com. Reach out to Kevin, reach out to Neil, they're happy to help you. You heard it here, they're willing to get on the phone and give you a free consultation, just to give you some tips and pointers, and some things that you should be considering with respect to your novel product and your AI-enabled software. So check it out. Again, Greenlight Guru, we're here to help too. So if there's something that you need a little bit of help with, figuring out your quality management system, that go-to-market strategy, the things that you need to be doing to meet the FDA criteria, 13485, we're here to help. www.greenlight.guru to learn more. And, as always, thank you for being listeners of the Global Medical Device Podcast, the number one podcast in the medical device industry. And as always, this is your host and founder at Greenlight Guru, Jon Speer.
The Global Medical Device Podcast powered by Greenlight Guru is where today's brightest minds in the medical device industry go to get their most useful and actionable insider knowledge, direct from some of the world's leading medical device experts and companies.
Nick Tippmann is an experienced marketing professional lauded by colleagues, peers, and medical device professionals alike for his strategic contributions to Greenlight Guru from the time of the company’s inception. Previous to Greenlight Guru, he co-founded and led a media and event production company that was later...