Assembly Select Committee on Biotechnology and Medical Technology

Well, good morning everybody. I want to welcome you to this Assembly Select Committee on Biotechnology and Medical Technology for the hearing on Wednesday February 18th for Members of this Committee. We are in room 127 at the State Capitol and today's hearing is titled California's Medical Technology Landscape.

I think you all know California life sciences sector encompasses over 12,000 biotechnology and medical technology companies. It generates more than $470 billion to the economic output of the state and supports over 1 million jobs for Californians.

These companies, from startups to industry giants, not only drive life changing advancements but they also invest deeply in our local communities fueling some economic growth and attracting significant venture capital. Now last year the select Committee added medical technology to our title.

And the purpose of this hearing is to better understand what is and the impacts and contributions that it brought to this biotechnology industry. Medtech organizations provide groundbreaking technologies and significantly impact society and our individuals health and well being. So today our Committee will be hearing from representatives of the medical technology industry.

We want to welcome up our panelists. We are going to be in two panels today. For the first panel I invite to the presentation table Greg Theyel, the biomedical from the Biomedical Biomedical Manufacturing Network who's previously testified before our select Committee. He's gonna help give us a big picture on medical technology and the bigger picture as well.

I wanna welcome up John Wegner, a legislative advocate for Avamed. When you're ready, you may begin your presentation.

Great, thank you. I'm Gregory Theyel and I'm the Director for the Biomedical Manufacturing Network. And it's a pleasure to be back again to talk with you. I wanna talk about three things today and it'll help define the differences between medtech and biopharma. And those differences are important because they apply to policy, economic development, jobs and land use.

So we'll talk a bit about the differences in the technology and we'll talk a little bit about how they develop over time as new innovations. And then finally we'll talk about the geography. As you know I love talking about maps and so we'll have some maps as well. So. So first the differences.

So when you think medtech, think hardware. Think either hardware that's in your body, a pacemaker or stent. Think surgical robots, operating tables, any type of hardware technology, even software and wearables, where biopharma, which we talked about in earlier testimonies is really about chemicals and biologics.

And so that starts the kind of conversation about the differences between the two. Right. Because they're developed quite differently. So first of All Medtech is incremental.

It's engineers in a garage developing a prototype and maybe 3D, printing it and then trying it out with a surgeon or trying it out in a hospital setting and gradually building it, making it better and better, getting it through a regulatory process that's much quicker, maybe about a year or so.

And oftentimes just bootstrapping this, putting, pulling their money together and getting it out to market, getting some traction and then getting acquired by a larger company like Boston Scientific or, or some of the other Bard or some of the other bigger companies, they help with the distribution throughout the state, the world.

So that's the path quite different from Biopharma, which is very lab based, often research university based, very expensive with clinical trials, PhD scientists, a much different kind of, we'll call it science oriented, Maryland oriented kind of set of people who are working on this.

A path to market of over 10 years in many cases, and millions and millions of dollars, sometimes close to a billion. So these differences are really, really, really important as far as development goes. But then here's where it all comes to play with the people who are listening. And that's the geographic differences.

The geography for Medtech is lower cost locations, manufacturing, people who have high school and maybe a two year degree, many more people employed. Supply chains matter, so there's more of a ripple effect to the local economy. In other words, machine shops and component providers and even raw material providers that are nearby.

So that supply chain is really important. And so when you think of a place like Fremont, it's surrounded by engineering machine shops, suppliers that are really legacy suppliers from other industries, other electronics industries, but also supply things like the electric vehicle industry. And so they fit really nicely into this manufacturing ecosystem.

Biopharma, quite different research hospitals, ucsf, ucla, City of Hope, that's a much different setting. And Again, grad students, PhDs, scientists working in clean labs, a much different setting than the medtech companies.

And so it's almost like up in the ethosphere is biopharma and down on the ground where there are middle skill jobs and land use issues, that's where Medtech is. And so in some ways you could argue it's the people's segment of the industry.

And it's relatable too because it's tangible, it's hardware that's quite different than the mystery of chemicals and biologics. The reason this is so important is because like I said, it plays out in policies.

You have smaller companies who need space, need tax breaks on their equipment, need training and engagement with community colleges and the Cal State system more than the UC system, it's land use issues. So it's available space instead of high rise lab spaces at high rents like we see in San Diego and in South San Francisco.

Instead it's in places like Carlsbad, it's in Fremont, it's Hayward, it's in Irvine, it's in those types of places and with the potential to be in other places like Manteco or Modesto or other places as well. So the spread and the potential for spread for MedTech is different as well.

So it's a land use issue, economic development issue and a policy issue. So let me dig in a little bit more. We've talked about some of the key differences, but the state is the epicenter in the world for medtech and that's in part because of the expertise we have, legacy engineering and software.

But it's also because we have these other industries here. If you're having most. Let me give you an example. If you have a test kit, that test kit is likely to have a biological aspect but a drop of blood on it.

It has a electronic aspect, it has a software aspect and it has a hardware, you know, maybe a 3D printed or a plastic or metal hardware. All of those types of industries are leading edge here in California. And that's what makes California such an important place for this.

In addition, we have the demand side, which is cutting edge hospitals that are willing to trial these technologies. And we have surgeons who are often leading the innovation, coming up with some of the ideas frequently, they're frequently founders of these companies. And so we have the right ecosystem for it.

And, and just to give you a sense of the spread too, so, So in, in the Bay Area there are 800 medtech companies which make up about 40% of the companies there. There's about Los Angeles, about half the companies are med tech. And in San Diego about about a third of the companies are medtech.

So San Diego, as I've talked to you about before, is very biopharma oriented with about a third of their companies being MedTech. And so they then are affected more when we talk about some of these federal cuts, some of the big grants, some of the big venture capital funding, where Los Angeles is more focused in on Medtech.

And so they're more susceptible to issues around small loans for companies, startup space, a skilled workforce to help with the manufacturing of medtech. So different needs for different geographies because of MedTech versus BioPharma. Here's some of the cities let's talk a little bit.

Irvine is one of the leading places close to now 300 companies, many of them in Medtech. And so there's a real cluster here in large part because of a supply chain that's nearby. All right, same thing with Fremont, it's moved up even towards Hayward.

And so if this is your district or this is where you live, there are tremendous opportunities and many of these jobs go to people that who have high school and two year trainings. And so there's real opportunities for those mid skill jobs. I think that's an important difference between Medtech and Biopharma.

And then Carlsbad's another hotspot location in the state for Medtech. And finally Silicon Valley which has its fingers in everything but in large part because it has all of these other cutting edge, cutting edge industries. Right. And so let me kind of tie this all together with two examples.

This is a company called Penumbra Penumbras and Alameda, you may be familiar with their recent purchase by Boston Scientific. They decided to keep their manufacturing in the state and what they need is they have a pipeline of people coming from Laney College, which is a two year school in Oakland that's been critical for them.

They've got suppliers nearby, they have distribution with the ports and the Oakland airport. And so they use all of this expertise within California. And it really shows how policymakers can support them by having strong infrastructure for distribution, having land use policies that make it possible for them to grow.

They grew from when I first started working with them. They had 100 people, they have thousands now. And so having space to grow, credit to the city of Alameda to help them. So it's a very good example of having the resources in place to help grow this medtech companies.

And then the second case study is really interesting too. Varian Medical Systems is a company that has reshored their manufacturing. They're an example of companies that have said things are changing in Mexico, in China. The tariff landscape is, is challenging for us. We're, we're at a higher risk and so we're going to bring it back.

And so they brought their manufacturing back to Palo Alto and to Manteca and now they're manufacturing locally. So they need help with that pipeline of, of people at the two year level or high school level. They need help with land use, they need help with economic development and policy as well.

So two really good examples that highlight what Medtech really needs. So I'll stop there. But as always, if you need data, if you need Maps. Any companies that can help you with more insight, I'm happy to provide that for you.

All right, thank you for putting me after Dr. Thiel. I don't really even have a couple slides, but they're more just graphics. John Winger here for the Advanced Medical Technology Association. Apologies my client couldn't be here. She had business in other state. But I've had this.

Been representing them for the last 10 years here in California, so I'll do the best I can. So avamed is the world's largest trade association representing the full spectrum of medical technology innovators and manufacturers. Our Members are the device, diagnostics and digital technology manufacturers, transforming healthcare through early disease detection, less invasive procedures and more effective treatments.

And our Members range from the smallest startups to the largest multinational national corporations, which was just laid out Dr. Thiel's testimony for the medical device technologies. We are what doctors, nurses and patients really rely every day on to prevent disease, diagnose conditions, deliver treatment, and manage care over time.

Our industry includes everything from traditional medical devices like imaging equipment, surgical tools, even band aids. Band aids are technically an approved medical device, but we also include implantable devices, digital technologies and software which is more commonly embedded with AI that can help Clinicians make more informed decisions.

So MedTech really sits at the intersection of patient safety, innovation and access to care. I think it's important to note that these products, everything from the device itself to the packaging, are highly regulated at the federal level by the Fda. This is because they directly affect patient outcomes and access.

So I know as state legislators, you don't want to hear that. From our perspective, we generally believe imposing additional state regulation could risk compliance with the FDA and result in layered patchwork of regulation among states that interfere with our ability to to ensure patient safety and timely access to care.

And I'll get into that a little bit more later on. So how big is the medtech pie? Most of that was just discussed, but just to put a bow on that, California is the biggest med tech center nationwide in revenue, jobs and payroll. We are $32.6 billion industry here in California and we are 83,600 jobs in California.

And I'm a poli Sci major, so don't hold me to the math, but by my rough calculations, that's 8% of the biotech revenue and 18% of the biotech jobs. Those jobs average $118,000 a year for annual salaries. And California is home to 196 AdvaMed Member company sites and 70 AdvaMed Excel Members, which are Small emerging companies.

So medtech is kind of broken into three different risk classification systems. And this is kind of the whole pre market, post market process right here. So class one is the lowest risk. So those are just subject to General controls. Most are exempt from pre market notification.

So band aids, again, elastic bandages, manual stethoscopes, exam gloves, things of of that nature. Class 2 is more moderate risk. So that requires General controls and special controls. So performance standards, post market surveillance, things like that.

I think it was on one of the slides that usually Requires like a 510k submission, which is sort of a pathway to approval. So these examples would be powered wheelchairs and fusion pumps, blood pressure monitors, continuous glucose monitors, things like that.

The third class is the highest risk and those are devices that sustain life, are implanted, or just present a high risk of illness or injury. So this requires premarket approval and a lot of special controls. And so that would be everything from pacemakers, heart valves, deep brain stimulators, things of that nature.

Another category of medical devices that are, well, not exactly medical devices, but another category of devices that continues to be talked about lately is the consumable consumer wearable products such as the Apple Watch, the Garmin watch.

So for these devices, they include specific features that have been reviewed by the Fda, such as the heart rate monitoring, the respiratory rate monitoring, and the blood oxygen monitoring or measurements. But the hardware of the product itself is not technically a medical device.

So the software of these devices is typically authorized as a Class 2 device, but the overall device marketed as a consumer product and is not itself broadly FDA authorized as a medical device. So there's a little nuance there to go back to just FDA issues and regulatory issues.

And as it relates to kind of the legislative and regulatory landscape, I would reiterate, from a broad perspective, medical devices are heavily regulated by the FDA and should not be included in broader state policy.

So this means from an advocacy perspective, our General position is that medical devices should be excluded from various broad state regulations in order to protect patient access to medical technology. So this would generally apply to kind of broader plastics laws, broader chemical laws, and most recently broader AI laws.

We feel like we, we are heavily regulated in the FDA and we have that process and that's been the easiest for us to navigate. And like I said before, it really preserves patient access and patient safety for us. So getting into kind of the AI issue in, in medtech, AI is being used across three applications in healthcare.

So there's research and development, there's Administration and efficiency, and then there's diagnosis, monitoring and treatment, which are all which diagnosis, monitoring and treatment is is regulated by the FDA. Our first actual FDA approved device was back in 1995. So the FDA has been doing FDA regulation or AI regulation for a long time.

There's currently over a ousand FDA authorized AI enabled medical devices that are being used in the diagnosis, monitoring, treatment of medical device or of medical conditions. 80% of all AI embedded devices used in the medtech space are typically in radiology. So that'd be image and data analysis tools.

A real world example of AI enhancing patient care would be a patient sitting for an MRI with the AI enhanced technology.

Instead of the doctor only receiving kind of the raw image, they would receive an AI enhanced image that is a little cleaner, higher quality image and may enhance or draw attention to certain aspects of the scan in a quicker manner. It also reduces the time for the patient and sometimes can reduce that time by 50 to 80%.

And as somebody that's due for an MRI, I'm very happy about that. Imaging is not the only use case. We are seeing advancements in patient care in cardio, neuro, diagnostics, maternal health. Some examples would be surgical planning tools, blood loss estimation tools to detect maternal hemorrhages and cardiac monitors.

Clinicians maintain the oversight and the final say on treatment pathways. But AI has been a very powerful tool that facilitates the process for these professionals. With the example of a blood pressure cuff gathering Millisecond by Millisecond, physiological data, ECG and heart sounds.

These devices are leveraging AI to enhance the accuracy efficiency while also rapidly analyzing this data to provide physicians with better information, sometimes in ways not possible for humans. That leads to better diagnosis and treatment recommendations.

And to orient you to the type of procedure areas our systems are used for. These are the different procedure categories which are normally referred to as soft tissue procedures. This is different than an orthopedic system or a knee replacement, or any of those.

Since 2000, robotic assisted surgery has enabled certain procedures to become standard of care using RAS that includes prostatectomy.

And our impact over 30 years is reflected in the more than 20 million patients served with more than 3 million procedures performed last year alone in California, there are more than 500 systems placed across major health health care systems as well as VAs that are serving Californians.

We recognize that our reach and impact means we have to be we've become an integral part of healthcare delivery, a position we take seriously to ensure that hospitals and healthcare systems we work with can rely on our tools to be safe and effective.

And to give you a sense, this is what our systems look like in the OR setting. On the far right you see a surgeon who's in complete control of the system the entire time while sitting in the console gives them an ergonomic way to perform the procedure while viewing an enhanced 3D vision.

In the middle you see the patient's side cart, which is often referred to as the robot. It is where the end effectors are inserted into the body. And once again, although it is a robot, it is not acting autonomously.

Lastly, the vision tower on the far right is the brains of the system, where the computing power is located and a vision into what the surgeon is seeing as well, so that the care team can control critical variables for the procedure foundationally.

The way Intuitive has thought about innovation and improving the future of care is centered on our commitment to patients.

And we do that by delivering technology that enables clinicians to deliver better patient outcomes to their patients in alignment with the quintuple aim first started as the Triple Aim, Healthcare's quintuple AIM is our North Star and is embedded into the design, development and implementation to assure that our value is synonymous with the healthcare system's goals.

What does that really look like in practice? It starts with understanding the problem first, and we can't do that without talking with those closest to the hard problems in health care. Since the beginning, surgeons and care teams have been an integral part of informing the problems and initiatives we seek to solve, choose to pursue, design and implement.

And that means more than delivering just proven technology, it means providing an entire ecosystem to set these programs up for success. So the first being the technology we have systems, instruments, data, software. Second is effective and comprehensive education and training provided to surgeons, care teams, clinicians at any point of their career.

And the last is evidence backed program optimization where our teams can provide insights to surgeons and hospitals to improve workflows, reduce redundancy and help reduce total cost to treat. But we're always seeking improvement of that whole ecosystem.

Most recently this is reflected in the digital tools we are integrating into our platforms, including tools that may utilize machine learning or AI. And for us, machine learning and AI applications, like all product innovations, need to be evaluated through the lens of the quintuple aim and the meaningful value they provide.

The development and the design of these tools is also rooted in good machine learning practices which is an international consortium of experts who have come together to lay out a set of principles on best practices when it comes to the design of medical devices that integrate machine learning and AI.

All our applications continue to rely on providers and Clinicians final decision making while augmenting their skills or improving safety by providing them the clinical context necessary to make more informed decisions.

We envision using the system data and user experience across 20 million procedures combined with AI or machine learning capabilities to better understand which surgical techniques and movements create better patient outcomes. In doing so, surgeons can reduce their own learning curve herds safely and quickly, allowing the benefits to reach more patients.

I'll end with a real example of machine learning and AI enabled application in one of our current systems. This was approved by the FDA just last fall. This update addresses a key challenge expressed by pulmonologists using our ion system called CT to body divergence.

This is when the lung nodule changes location during the procedure as a result of the patient's lungs expanding due to respiration. This can make it more difficult to accurately reach that nodule.

So this update will build on the original machine learning enabled ion technology which uses the patient's own scans to map a precise pathway to the nodule, allowing pulmonologists to use the ultra thin catheter you see there to take a precise biopsy without excessive trauma to the body.

With this recent update, the system will now utilize AI to compare live images to those original scans, allowing the user and pulmonologist to adjust alignment of the pathway in real time. This increases their ability to perform a gentler and more precise biopsy, all while expanding the opportunity for early detection of cancer, increasing chances of remission and survival.

When large updates to our software are made such as these, we always work with our regulators to ensure the safety and reliability. As we think towards the next 30 years, we imagine a world where healthcare delivery is less invasive than ever.

Our role in health care is one that will always rely on the clinical knowledge and skills of health care providers. And we'll continue working with them and regulators to deliver insights and tools that meaningfully improve outcomes, hospital workflow and expand access to minimally invasive care.

Thank you for having me and I'm so happy to be a resource to you all moving forward. Thank you.

Good morning, Chair, Ward and esteemed Committee Members. My name is Ida Garakhani Good. I'm actually a co-founder and chief operations officer with a company called Cerevia Neurosciences, but I've been a founder and operator within MedTech for over 15 years and prior to that was involved with biotech and biopharma.

So I have sort of straddled both sides of this equation, if you will. Cerevia is actually an early stage neurotechnology company and we are looking at how to actually approach and treat neurological degenerative diseases, particularly with dementia. I wear my Alzheimer's pin with pride today as that is our patient population that we're going to be treating.

If we all make it there. It's a very innovative approach and I'll go into that in just a little bit.

But really, we were founded on a really bold question, but a very responsible question, which is can advances in neuroscience, imaging as well as medical physics be used to actually approach a very dramatic health crisis taking place not only within our state and within the country, but really globally?

And with the numbers that we're seeing to continue to increase with dementia cases, particularly with Alzheimer's disease, can we actually restore cognitive function as opposed to just managing the symptoms and helping to hopefully slow the decline of its inevitable end?

Most people think of dementia as being a cognitive problem, which it starts out being, but it's actually a life sentence for people who get diagnosed with it, because it stops the brain from actually interacting neurologically with the rest of the brain. It may start in the memory center of the hippocampal networks, but it actually extends beyond that.

And when we see the brain scans of dementia patients, you start to see the atrophy of those neural pathways to the rest of the brain. Our approach is actually to look at it from a neurological standpoint and not look at it from a pharmacological standpoint.

So it's really been rooted in scientific precedent, but guided with some really clear values that we hold very dear to, which is patient first and patient safety first, evidence before expansion and rigor overhype, because you can get a lot of hype in this arena.

And we really do want to make sure that we stay away from that and look at the rigorous work that we're doing. The challenge we face is really in MedTech, not a lack of promising scientific discoveries, nor is it in the ability for us to find ways to bring capital to scaling.

Our problem that we have in MedTech is really that translational phase in between, which is a very long process, I think from the previous panel with Greg and John speaking about just the lay of the land with MedTech and how that differs in the discovery phase. Our discovery phases can be very quick.

They can take a long time as well, depending on what you're working on. But the end result of where we're actually talking about getting to the end result can also be very arduous and rigorous as well, because we still have to meet a lot of the same safety and patient requirements.

But it's really that translational phase that I'm going to be focusing on today.

And Dr. Patel asked a question on the last panel as to what we can do and I hope that after this presentation I can give you a little bit of a foundation of what you can do, coming from our point of view as being a founder and innovator as well as an operator within this space, as you consider all of your decisions for policy, I want you to also take into consideration the many MedTech innovations that never come to be and the discoveries that go into what we call the valley of death, which is a reality for a lot of the innovations that are out there.

It's actually upstream is really where we live and whereby companies like Danaher and Abbott and Intuitive and Boston Scientific and Medtronic, they're all relying on companies like us to be able to get it right because we have to actually be able to provide them with the ability to have tested the market, tested the product, and have done the due diligence that's required to then be able to become acquired and to and to bring that technology to the masses.

Because as a founder of a small early tech or early stage tech company, I can tell you that that work is very challenging, but we certainly don't have the ability to scale it the way that the larger MedTech companies can.

So I'll use Cerevia as really an example today of the broader early-stage med tech reality and kind of share what's on the horizon and also where the system creates some friction, and then hopefully be able to bring you some, some real foundational ideas as to what you can start to look at in your policy recommendations.

So I use this slide, really just to kind of highlight just how big the problem is with dementia. It is still one of the largest medical crises in the globe, that we're in the world that we're dealing with.

But imagine watching a loved one slowly fade, where memories are lost, recognition is gone, and disconnections are now a part of their everyday life. That's the reality for tens of millions of families that are living with dementia affecting one in two adults. It really devastates the patients and the caregivers alike.

What do I mean by one in two? You're either caring for a patient in your family, or you're wondering if you're going to be getting it yourself or you might already be diagnosed with it. Right. So it's one in two adults that are affected with someone around them, and that number is going to continue to grow.

By 2060, we expect the 7 million people that are just diagnosed with Alzheimer's disease and 10 million with all of dementia in general will be doubled by 2060. Once you get diagnosed, there is no cure, there's no reversal.

The best that you can offer are current treatments that only slow the progression, but have some very undesirable side effects, including brain hemorrhaging and death, because all of these pharmacological products actually have to cross through the blood brain barrier. And that opens up a whole host of other problems that come with it.

The total cost of dementia by category is also staggering. We spend nearly $800 billion a year in the US in direct and indirect costs. It's over $246 billion spent by Medicare and Medicaid alone.

If you calculate the number of loss of hours of caregivers that need to take time away to care for their loved ones, we're talking in the billions, near $50 billion a year of lost wages just from the indirect cause of a diagnosis and dementia.

So families are just told to prepare for the worst when they get a diagnosis, because we really don't have great options. So the world really needs, and it's desperately needing a different way to look at how do we treat dementia. And we believe that we need to look at restoring cognitive health as well as.

As opposed to just preparing for the inevitable. So our answer is what we affectionately call the ladybug.

The ladybug was really born out of medical physics and imaging and looking at how we can actually use what's currently available with transcranial magnetic stimulation, which is called TMS, and advancing that system to be able to reach the hippocampal networks of the brain. Now, the hippocampal networks of the brain are actually very deep in your brain.

It's difficult to reach that area of the brain. And what we can best do right now is with TMS is maybe offer one to three coils. Our system offers 144 coils, which essentially means we can reach anywhere in the brain that we want to.

We also have integrated live brain imaging using functional MRI so that we actually get real time, actionable insight at the time of treatment.

Included in that is their AI driven therapy, which essentially accelerates that image construction, as well as being able to create a digital twin of each patient where then we can personalize that therapy, optimizing that session or the length of time, and then be able to use those as an aggregate over time to create biomarkers.

My brain will respond differently than Chair Ward's will with the stimulation. And so we need to better understand how can we map the brains of each of our patients in real time to optimize that care and see how the brain is responding. We're also then able to make this very compact and mobile.

We can outfit it onto a van and take it to rural areas, which my colleague here spoke about the challenges of rural areas being able to get access to proper treatment. And it's also very important with this particular patient population, because this is a very vulnerable and fragile patient population.

They do not like to be moved and they're all probably already in some sort of assisted living or in a memory care center. So we can actually go to them to deliver this treatment.

And we do not need them to come into a hospital setting for a static MRI, which other systems, other TMS systems currently on the market require you to do that. TMS is very well tested to be safe. It's currently being used for major depressive disorder very effectively, as well as other neurological diseases.

Our system has been able to advance the current treatment options that are available because we can electronically steer the TMS system in real time. You do not need to go back into the hospital to get another MRI. In fact, our first session is our mapping session.

Essentially, the patient is wheeled out from their place of care and brought to our van, loaded up to the van. They get pictures and music that they enjoy, pictures of their family members, which also helps us to be able to keep them stable and comfortable for a 15-minute session.

But it also lets us see how the brain is responding to those that stimulus as well. And then from there what we can do is bring up, I'm glad you're appreciating it, Dr. Patel. Then from there you can also then get the.

The technologist is also then able to get the brain life scanning to see how the brain's responding before we actually place them into sessions. So our technology is actually rooted in some scientific precedent here. So this is not some crazy idea that we've come up with.

The clinical data was actually published in a peer reviewed journal in JAMA in 2024. So it's pretty recent. These were randomized patients that we had a sham controlled study with our treatment group as well. The patients received four weeks of MRI guided TMS in patients that had mild to moderate cognitive impairment associated with Alzheimer's.

As you can see there, the blue graph is the sham graph. The purple line is our treated graph. ADS scores and cognitive scores that actually are lower scores are better in this environment. You want a lower score to be able to say that you've got better cognitive functioning.

As you can see, immediately our treated group started to do better than baseline. They continued to four weeks and at the end of four weeks we assessed them as well. And you can see still doing better than baseline and better than at the immediate.

And then treatment stopped at four weeks, eight weeks, they were assessed again to see the durability of our treatment and they continue to do well. Now the other part to this is the Sham Group did what we expected it to do, is that it continues to decline.

The other part to this study that was so elegantly described and studied is there was a correlation between the cognitive clinical outcomes to the patient scans of our treatment group. So there is a mechanism of action taking place.

We can say that, that there is a correlation to how your brain functions, to how well you do clinically in these particular cognitive subscales.

All right, so that brings me to the challenges. So this is all great stuff, right? This is all breakthrough technology that needs to be further studied and we need to get it out to the market very desperately.

But because of the challenges that are currently in the med tech space and in the market, we may never ever get to see a single patient treated with the ladybug. And that is because of all of the hurdles that we have to get through. Now my job here is as an operator not to tell you to do away with any of the patient safety. That rigorous requirement is in place for a reason, and we embrace it, we welcome it.

The challenge again is not here in terms of the scientific promise because more than ever today we're seeing great technology come and being emerged through all of the discoveries that we're getting because of all of the work that's been done.

Intuitive, for instance, you know, leading the way with robotics. AI, bringing a lot of that great technology into play and making it a lot more interesting for us to explore. The challenge is also not in the post revenue phase, because once you get to revenue phase, that's easy.

You have a lot of investors who are interested in helping you scale. That's not a problem. The problem is getting through this transitional phase, which is a very structured, safety critical process of moving from that scientific innovation that's very promising to actually getting validated, regulated, and then into the market.

So that's the phase that I'm going to be speaking about. It is a requirement of every med tech company. It's not a milestone, it's not a convenience. It is a requirement. And again, we embrace that because we want the patient safety implications at every stage of the way to be, to be maintained.

But it is the most rigorous, it is the most risk concentrated, and it is the most capital intensive phase of med tech. And it's multifaceted. It's linear. I can't bring something to the market without doing the clinical trial. I can't get a coding or CMS approval without the FDA approval. So there is a linear pathway, but we are working it parallel pathways. And I'll kind of describe what that is.

But if we lose innovations during this process, no matter how good the science was, it doesn't matter because we'll never see it. Because large medtech companies will never acquire the technology, they'll never bring it to market, and we'll never know whether that discovery could have been the world's next breakthrough technology.

So where does California lie in all this? Well, I think we've already mentioned it today and you've probably heard from previous testimony from your panels. But California is actually one of the strongest, if not the strongest, discovery and scale states. We do a great job in those places. Our opportunity lies in strengthening the bridge in between.

So here's where our gap is. Our gap is really about the lack of meaningful capital from private investors into this particular phase. So it actually doesn't come to us until the companies have achieved post FDA approval, post CMS approval, and or being revenue positive.

I'll say that again. It does not happen until we meaningfully, right, until we have post FDA approval, post CMS approval, and revenue positive. So imagine what has to happen until we get to that point. That's why founders often feel that this middle phase is under instrumented in California, and we are swayed to move outside of California.

So we talked about keeping the jobs here. We've talked about how do we actually get a lot more interest from investors to invest during this phase. And this is how we think that you can help, which is actually to bring a single state funded direct translational fund that provides non dilutive checks to medtech startups for prototype to clinical bridging to retire critical milestones that the investors need to see to bring private capital into play.

We are not talking about the state running as an investor. We want to be supported by the state in this very critical phase so that the investors who are looking to de risk companies to invest are able to get that de risk company to a state where in these early stages it matters the most.

So really in our $4.2 trillion economy in the state, this is actually a precision instrument. We're talking basically less than 100, I'm sorry, 1 in 1,000% of what we would probably need to be able to fund anywhere from 15 to 20 companies, maybe even 30, depending on what we need.

The strength of our robust ecosystem is really being, we can actually address this specific gap. Most other states can't. And they're trying. They've already done this in Maryland, Michigan, Wisconsin, North Carolina, as well as Texas. We are missing that gap here in California.

It actually ensures that California remains at the forefront of moving through this stage by bringing those breakthrough technologies from discovery to delivery. And we can be the state that actually delivers those breakthrough technologies that the world truly does need. And so really what I'm talking about is medtech doesn't need the AI billions. We really don't.

AI is requiring billions of dollars of investment. In fact, when you look at where the investment dollars went last year. And when you read the headlines it looks like, you know, the investors are back and the dry powder is being used up. But it's being used up with AI and AI tech and not so much in med tech. And really all we need are millions. We don't need billions.

We need somewhere between $15-50 million to be able to take discovery to post market translation. So that is a translational fund that similar in spirit to other states, could really unlock that private capital that we're looking for and it removes that execution friction. And we don't have to touch anything with patient safety. We actually will.

We're working within the system of the FDA and all of the state regulations within med tech and making sure that we actually bring a technology forth for all of our patients. Really with your leadership and with this particular committee that's looking at what you can do to affect policy and make recommendations, that is the one gap that I can point to.

Because we are so strong everywhere else. We have no shortage of really great innovations that come out of California. We really have great private capital within California. It is the hub of where a lot of our capital can come from. But where the investors are choosing to go is where the companies are de risked enough where they are willing to make those investments.

And unfortunately that's an AI that does not involve any life science, that doesn't involve any patient care. And it's in medtech where it's post approval and they are ready to scale. And I can assure you that we want to get there and we want to bring the ladybug to, you know, to the world. But we've got to be able to support that kind of bridging of that gap. Thank you very much.

All right, I'll do my testimony without slides. First of all, thank you, Mr. Chairman and Assembly Members of this Committee, for the opportunity to present a startup perspective on manufacturing in California.

My name is Luca Springer, and I'm the CEO of Numen, a Y Combinator backed venture funded startup based in San Francisco, right next to the UCSF Parnassus campus. We are innovating at the intersection of synthetic biology and artificial intelligence to bring lab grade diagnostics and biomarker tracking into every American's home.

We're a team of 16 exceptional scientists and engineers deeply focused on research and development that will unlock a future in which all cancers are detected as early as possible and every patient receives timely life saving care. My co-founder, Dr. Thomas Carroll and I started the company four years ago in London in the United Kingdom.

After graduating from the University of Oxford, where we both studied as Rhodes Scholars. We believe that the future of cancer research lies at the intersection of computation and biology, and this conviction led us to move the company to the Bay Area in 2023.

There's no better place to build a company like ours than in the very ecosystem that initially gave rise to modern biotechnology in the 70s, and where the likes of Anthropic, OpenAI, and Google are rewriting the rules of what can be accomplished when compute is leveraged intelligently today.

Our partnerships with Y Combinator, exceptional academic and clinical centers, as well as strategics and corporate partners have enabled us to dream bigger, move faster, and innovate much better here.

Over the past six months, we've made significant efforts exploring where to manufacture the diagnostics, the diagnostic devices that we will distribute at scale once we have cleared the appropriate regulatory channels. Our plan is to initially work with a CMO and eventually establish our own manufacturing side as we continue to scale.

In this effort, we're actively looking for manufacturing capacity in California because we believe that proximity between R&D and manufacturing is of immense value, speeds up iterations, avoids costly logistical concerns, and ensures that transfer to manufacturing goes smoothly.

I will admit that personally I'm not an expert in manufacturing, but I'm learning as fast and as much as I can. And to be quite frank, the past couple of months exploring manufacturing in California have been quite daunting. Permitting timelines can stretch for years. Zoning restrictions, while I know that this is often a local issue, not a state issue, make it difficult to find appropriate space.

The regulatory complexity for standing up even a small pilot manufacturing line is enormous compared to other states. And as a result, there are very few competitive local CMOs, and the timeline on setting up our own sites is prohibitive. It's important to keep in mind that we're not talking about smokestacks and heavy industry here.

Our kind of manufacturing is about clean rooms, semiconductor fabs, and biotech labs, which is exactly the kind of advanced manufacturing that I would assume California wants in its state. We are more than willing to pay a premium for the access to the incredible talent that lives here. That's why we moved here, that's why we left Europe, that's why we're in the United States. And also the ecosystem, obviously, that I already highlighted.

Ultimately, however, I think all of us here have a fiduciary duty to our shareholders, and unless the gap in manufacturing between California and the other states is narrowed, it is extremely difficult for us to justify manufacturing here to our investors. As I trust you know, this is by no means a novel concern.

I'm sure you've heard this before. But California has already lost multiple unicorn deep tech companies to other states. In the YC community alone, Solugen, which is a $2 billion industrial biotech, has moved to Houston. Boom Supersonic. I mean it's not a biotech, but they're building really cool aircraft. They have moved to Colorado.

Gecko Robotics in Pittsburgh. May Mobility in Ann Arbor. And the list goes on and on and on. These are billion dollar companies with hundreds of high paying jobs that were initially created here in California, but then have been lost because of this lack of manufacturing ability.

I firmly believe that supporting companies wanting to manufacture in California is crucial in ensuring the state's competitiveness in the long run. It seems to me that the US is in the early stages of a re-industrialization wave due to federal policy, competition with China, and a new generation of founders who want to manufacture domestically.

California can choose to either lead the wave or watch it happen elsewhere. My ask to this committee would be to support streamlining of permitting, removal of red tape for manufacturing, and the creation of incentives for companies that commit to creating manufacturing jobs in California.

For us, as Numen, the question whether we can manufacture here long term will depend whether the state makes it viable for companies like ours to scale without being priced out or slowed down. Thank you so much for your attention.

Great. Well, thank you everybody for your overviews of the work that you're doing. We often use the word innovative, and it is, but you know, it's amazing that, you know, you're taking some, you know, pretty ingenious thought and actually connecting that to some of the problems that people are having with their daily lives and disease that has plagued so many that we love for so much time.

I wanted to maybe start with an overview question for anybody that, and I actually probably meant to ask this for the previous panel. But the RD tax credit is something that's talked about here pretty often. Unfortunately, because of our state budget scenarios, it's something that fell short over the last two years.

I'm sure it'll be up for discussion again this year. Can anybody comment to anything specifically that we have missed out on in the last two years? How has that challenged, I guess, you know, the either preservation or expansion of job opportunities?

I suppose I'll add in the same spirit of R&D tax credit, advanced manufacturing tax credits as well have also been incredibly, I think to Luca's point, at Intuitive, we often say, you know, we were starting today, would we be able to manufacture in the same capacity that we do given the price and the landscape. So when it comes to those advanced manufacturing tax credits for those of us who are investing in manufacturing here, that goes a long way, I think.

Is that separate and distinct as something you see in other states as they...

Yes, we have seen it in some other states. I don't think it's something that, I think it's something that California has done before. But in the past when budget constraints come in, it can be something that in the same spirit of the R&D tax credit, can be put to the side.

Okay, anybody else?

Yeah. What I will say is I think that the challenge has been, is because the tax credits are not there and there isn't a safety net either, that it's sort of a double whammy because there's really then no incentive.

And that's why the translational fund is what I was talking about because that can actually help offset what may be a concern for manufacturing to stay in California. Because there's no tax credit. Because ultimately, yes, you would want, you want the tax credit.

But I think what we've gone for a while now without the tax credit that I think it's had an impact on decisions that have already been made, and I don't know if that can be walked back in a lot of situations.

Well, no and yes. Right. It's like it can inform just in a two year period how that has affected decisions around whether somebody's going to move, whether someone's going to locate here or move here. Actually, we'd love that.

But that might also help us to project the, give us the argument, the evidence that we could use going forward as we're thinking about our state budget this year might be in better situation than last year about trying to resurrect this because we've got very current real time data.

This is happening so fast, you know, the evolution of companies in this space. But we can all know, and I welcome anybody out there as well to continue to engage with myself and other Committee Members as well, as we're thinking about this heading into budget season.

I wondered, Dr. Monroe, you talked about with your technology that I fully appreciate how this is speeding up some of the opportunities for pathologists to be able to make certain findings.

But I think on one of the schematics that you had there that you said that using this technology that pathologists may review the findings. And I was curious, are there, was I reading that correct in that it's possible the diagnoses can be made without a human, a trained pathologist to actually review that. And if so, what do we think about that?

Yeah, that's a great question. I think it's very applicable to many of the AI tools are being developed across different industries. Our position and the way that the FDA views it is that these are tools that require and will continue to require a pathologist to sign off on them. And so that's where we're investing our dollars and where we're putting our focus to have AI with pathologists in the loop.

I mean, I could see that saying, like, hey, I think that this is this kind of observation, you know, with a 96% probability. What do you... And then making sure that we've got a trained individual there who can validate that or think about other options.

Exactly, exactly. It's more, as you've heard for many fields, it's the pathologist who doesn't use AI is putting himself or herself at risk, as opposed to the pathologist who embraces AI and incorporates it into his or her practice. So that's the way we view it, that it can elevate the accuracy and the quality of diagnoses.

Great, great. Question for Ida. More kind of a technical question. Maybe I missed it in the presentation. How exactly does TMS help preserve, or I should say prevent any cellular death, is what I'm reading, as far as its beneficial use.

Yeah. So that's a great question because the mechanism of action is not very well understood with TMS, other than the fact that we're building plasticity back into the brain. So we're actually, we're able to do is to take the synaptic exchanges and be able to kind of, if you think about it as a congested highway.

And we're basically clearing a lot of the congestion in that highway so that the transmission of information through the synapses can more effectively take place and more efficiently take place. What happens with the plaques in dementia, for instance, is that it clogs that highway.

Okay. So the amyloid and tau proteins will start to clog that up. And so that creates, over time, so much congestion. If I could use that analogy, that essentially it disconnects.

Right. And that disconnection, I think, triggers cellular death.

And so what it does is that magnetic. It's non-invasive, so there's no surgery involved. It's very non-invasive. It's currently being used for a lot of neurological disorders right now and safely and effectively, and it's very well tested in the market.

So it's kind of a beautiful thing, actually, because what you can do is the brain responds to the magnetic stimulation. So it's using, that's where the medical physics and the imaging kind of comes in very well with this, is that it uses that stimulation through the use of magnetics to think of a big MRI, if you would.

But we've kind of compacted down and we're able to use that stimulation in a way where we can target very precisely the neural pathways that we're trying to stimulate. It's not a full stimulation. It's not electromagnetic. It's not convulsions of any sort. This is truly just a magnetic stimulation as you would, as you would have with sitting in an MRI, if you would.

You said that you didn't fully understand, and I know we have a lot to understand with the brain. The mechanisms that were present. Was this discovered sort of secondarily to some other work and realized that this technology actually had some benefit and you wanted to dig in more? In other words, if you don't understand the exact mechanisms that you're going after, you probably didn't create a technology specifically to do that.

Yeah. So it's so hard. I mean, they can do it. We've had it published in rat studies, for instance, where you can see. You can see what happens in rat brain. But the reason why I say that is because I'd love to see much more definitive mechanism of action studies.

But when you see very strong correlations take place and you can see the brain scan is actually lighting up in the places where it was dead, basically, or it was just not moving. That correlated with how the patient's doing clinically is really what we're pointing to.

That I can say in clinical studies. Now, we can sort of hypothesize around the fact that, yes, there is a very straight correlation between how your brain is able to exchange the synapsic exchange of information, and that's where it lies. We're not there yet to be able to say definitively that that's what's taking place. Theoretically, conceptually.

And as a secondary endpoint, if you would, in studying in these studies, you can say that. But to meet that level of scientific rigor, it's very challenging to do that. But outcomes are the outcomes, and it's working. And you can see it versus the sham groups, that it is definitely having an impact.

And one of the things that we need to better understand is how durable Is it. So the previous study went into eight weeks. Can it go into 12? Can it go into 24? Can we, maybe it's a once a year thing?

And does it relapse?

And does it relapse? Do we need to kind of go in for another set of treatments? And then within our system, do we actually need four weeks? So the previous system was using a different TMS that's not as advanced as ours. Maybe we only need one week of treatment and get the same effect.

So it's an adaptive clinical pathway that we're looking at with the FDA. And speaking with the FDA about it is we'd like to do a small little sample study to make it adaptive to say, you know, is this the right clinical protocol that we need to be using and see what the FDA is able to sort of work with on that with us. They're very open to that. As long as you're not saying that this is what we want to do and then you didn't show it.

Right. Thank you for getting a little deeper into that. I find it fascinating. It might have like, you know, been a little bit more than the high level that I think our committee likes to be able to cover. But I appreciate entertaining that. I'm just super curious about it.

Back to FDA approvals and some of the regulatory barriers that you're seeing. Do you find that medtech is any more or less impacted by, compared to biopharmacological companies, as far as their process? We know well, we've been educated well about the 10 to 12 years it takes to get a drug from concept all the way to approval. How is your relative timeline as well? If anybody wants to...

I can speak to that, as the fact that we're right in the middle of it. It's actually less than biopharma. Okay. And the reason for that is because you're dealing with a different kind of pathway. It still has the same amount of rigor that you need to demonstrate in terms of patient safety and outcomes.

But I would have to say that in comparison with the number of years and the, and the amount of capital that's needed, it's less than biopharma would be. Now, there is a caveat, which is if it is a completely new breakthrough technology, which our system is. And you probably were too, in the early days. That has a lot more oversight and that is going to be much more traditionally looked upon like a biopharma process.

And that is because it's a de novo pathway. And the de novo pathway has a lot more questions, has a lot more rigor, you having to explain a lot more. Now, it's not as much as a PMA is, because the PMA pathway is going to be much, much more lengthy and rigorous.

But a de novo versus a 510k clearance. In med tech, a 510k clearance is typically what med tech companies will use, and it's going off of a predicate. If you don't have a predicate, you're going de novo.

So we're in the middle of talking with the FDA about really, can we use TMS as our predicate? Because it's already approved by the FDA and it's already being reimbursed very handsomely by CMS. We don't know that yet. They're still deciding because we're integrating functional MRI with it. So it is. It is different.

Got it. Okay. Dr. Patel.

Thank you very much for your presentations. Very exciting work that all of you are involved with. It lets me believe that we really are going to cross those barriers that have so far not been able to be crossed. It's very exciting. Specifically around the Da Vinci system. I'm going to get a little deep into the weeds too. Is there potential to do remote surgery?

That's a great question. Telesurgery has long been a kind of hot topic. And actually just this past summer at the SRS conference, Intuitive performed a remote procedure using our systems. I will note, though, that while we do have this capability, so in theory, yes, can we do it.

But from our perspective, Intuitive, the real question should be, can we do it correctly and at scale. Right. So I think what we have seen is that even though the capability exists, there are still systemic inputs that need to be put in place to make it a reality that is really safe, reliable, and effective and can be used broadly.

So the capabilities are there, but, you know, you still want to ensure that there is a surgeon there on the other side that can help. Right. And that there are available care teams and hospital systems that can step in as needed, and that doesn't always exist. It sounds like a really great way to solve a lot of really challenging access problems. Right. But it's actually, to set up the ecosystem, it's much more challenging.

Yeah, yeah, I understand that there will be lots of risks, obviously, and we wouldn't want to cross that until we mitigate for all those risks. But thinking of the future.

Yeah, yeah, I mean, there is absolutely. And I mean, the original funding for Intuitive actually came from the Stanford Research Institute. And it was for remote battlefield surgery initially. So that was the original. And then they said, oh well, that's a little bit harder.

And actually urologists were the ones that came to us and said, hey, we can make this is, this is great for our practice. And so, you know, that relationship is so important to understand. You know, how can you use this effectively?

Yeah. On the battlefield you would still need to ensure constant power and constant Internet.

It's a little bit more complicated.

You know, the basic things are just... Yeah, yeah, certainly. Do any of you have, have any of you done the calculation? I've been thinking a lot about the R&D tax credit, like my chair here.

We've been talking about it with several Members and how we can bring that back. It's very interesting to me. Is there a standard calculation or number that we have out there on the ROI or the multiplier of what that R&D tax credit would do for our local economies? Do you know of one?

No. But I can tell you that we can certainly look at that. If that is something that you would like to get in terms of data, we can certainly pull that. What I can say is that if you look at the milestones that med tech companies have to be able to achieve, it is you start calculating what goes away when you don't have a tax credit, what goes away when you don't have the funding that you need.

And then you start to realize that not only are we, you know, entering into this phase of really being stalled in the process and running out of capital runway, if you will. Again the valley of death, entering closer and closer.

And that is, I think that's the bigger question for us to kind of think about is how do we sustain during that process. And I do think that for a company like ours, having that tax credit in place allows us to then use the funding that we have, our non-dilutive funding from NIH and DOD and the bootstrapping that we're doing. Right.

To be able to then use the funds in very meaningful ways, which is to support the evolution of our translational phase. Bringing much more qualified talent to the table, being able to attract the manufacturing folks who are going to be able to help us basically move through the process faster.

So we could be looking at something that's going to take 20 years to something that may take five years to realize. And I think that's what, that's kind of hard to measure, but we can certainly take a look and maybe crunch some numbers.

I would say too I think we have a, prior to you joining us, we have had, I think prior testimony as well about the rough calculations and benefits of the tax credit. I believe that was a year, maybe two years ago. Certainly can go back to some of those stakeholders and ask for updates.

Yeah, I think that will help with the argument. Because my, you know, back of the envelope calculations sort of tell me that it's certainly worth the investment. Tech and biotech certainly are a huge impact to our economy and our startups certainly are as well. And my feeling is that multiplier must be rather large.

And certainly if you combine that with the ability to really push forward clean manufacturing or new manufacturing types of facilities, not the smokestacks like you were talking about. But certainly what we have in clean room technology, those are the great paying jobs we need here in California.

It's also the workforce that our higher education institutes of learning churn out on a regular basis. And those students want to have jobs in California, they want to stay in California.

And if we can create a stronger ecosystem through advanced manufacturing, through an R&D tax credit, through supports to get industry through the valley of death, I think we create that ecosystem we need to stabilize our revenue stream and create that strong economy that we all want to create here in California. You had something you wanted to add?

Just quickly add that the way we think about it internally is that by far the largest cost that we see on a day to day is payroll. So the talent that we hire, it's really specialized, really strong talent in this, in this region. And R&D tax credits, what they do is they can offset payroll cost.

And so then that may be at scale, one additional hire that we can make. But then a year later that might be two or three additional hires that we can make. And once we are 100 people company, there might be tens of talents, tens of new talented individuals that we can bring on. And so I think it flows right back into the state by those metrics. And that's how we think about it.

Yep. And I'll just add one to I think the theme here. As Intuitive, you know, our supply chain and somebody else spoke to it. The reason the majority of our supply chain is within about 100 miles of our manufacturing facility. So a lot of it is in the Bay Area and on our other manufacturing hub is in Georgia.

But looking at the talent there, you know, I think these credits, it's you have the big companies, you have the smaller companies. But those supply chains, we work so closely with those researchers, with those new innovators, and we can't do it without them, you know, so it's just as important to a bigger company to maintain that supply chain.

And, you know, I think this last year has shown all of us how much chaos that can bring. So we want to make sure it's as contained and protected as possible. And I think that it can do that.

And thank you for bringing attention back to the supply chain. I know we've talked about it a lot in biopharma and how important that that is, you know, protecting that supply chain. But I think making that a talking point around the medical device manufacturing is also important. So thank you for reminding me. Yeah, thank you.

Great. We covered a lot of ground today. Well, I want to thank all of you for your time to be able to join us and really share your individual companies' perspectives and how that there are threads together with what we can do in the state through our policy and our work to be able to support not just your success, but those like you as well. And thank you again for the ingenious advancements that you're helping to provide for not just Californians, but the rest of the world.

Thank you all for your time. Really, really appreciate it. Thank you.

Thank you. And at this point in the agenda, we do have opportunity for public comment if anybody, members of the public want to be able to address the committee. We have a microphone over here. And as we have caucus coming up pretty soon.

You should feel free to join us at the microphone. Yes. No. No. Okay. All right. I see we have no public members wishing to make comments today to committee. And with that, again, I appreciate everybody's time. We'll go ahead and conclude this select committee's agenda here today day and certainly make an announcement when the next hearing is to be scheduled. Thank you all very much.