Patricia Zilliox has spent her entire career working in ophthalmology, including 30 years at American-Swiss medical company Alcon. Now she’s running a tech startup that aims to improve treatments and prognoses for some of the most common eye diseases.
In 2017, Patricia became CEO of Eyevensys, a biotech company founded nine years earlier in Paris.
Eyevensys is in the clinical stage of making a drug delivery system to inject DNA plasmids directly into the ciliary muscle with the goal of producing a consistent supply of antibodies to fight various eye diseases. The main areas of focus for the company include wet and dry age-related macular degeneration (AMD), and degenerative retinal diseases.
Patricia is working to bring Eyevensys to big pharma companies in the U.S. But first, she has to navigate some challenging regulatory hurdles.
Eyevensys’ technology has been classified as a combination biological device by the U.S. Food and Drug Administration (FDA). This means the company has to meet the agency’s requirements for selling a biologic (a type of drug) and for selling a medical device.
“That's what starts to make it more complex, because when you raise money, the first thing investors are going to ask you is, Are you a device company? Or are you a biologic?” she says. “We are a biologic, but from a device point of view, we have to follow all the rules as if you were developing a device.”
In this interview, Patricia gives advice for navigating the complicated world of regulatory affairs, the dos and don’ts of planning clinical trials, and why raising capital is the most frustrating part of her job.
Patricia Zilliox, PharmD, spent three decades managing clinical development programs for eyecare giant Alcon, followed by five years at the Foundation Fighting Blindness. Since 2017 she has been the CEO of Eyevensys, a French biotech startup working on an ophthalmology device that can inject DNA plasmids into the ciliary muscle.
Key Learnings from Patricia’s Experiences
- Be strategic in the early stages of developing your technology. Choose a suitable indication for your device, and when planning your timeline, take into account that it may take longer to collect data on how it works in some conditions versus others. And make sure you can repeat your results!
- Find advisers who have experience in drug and device development, preferably in the specific condition you’re trying to treat. You need experts to rely on for questions ranging from clinical trials to quality control and the regulatory pathways.
- Fundraising can be very challenging. You can have the best technology in the world, and the data to back it up, and still pitch over and over again with no success. It’s not necessarily your fault, and you usually won’t find out why investors said no.
Don’t Overcomplicate Your Job in the Development Stage
Before Patricia became CEO of Eyevensys, the small R&D team in Paris chose a complicated indication for their technology. Specifically, they were testing it as a potential treatment for noninfectious uveitis: inflammation of the part of the eye called the uvea.
The issue, Patricia says, is that this is a systemic condition, meaning it involves the entire body, not just the eye. It is believed to be caused by inflammation triggered by the immune system.
When you’re trying to test an ocular device, targeting a condition that affects the whole body can make it much more difficult to prove the effectiveness of your technology.
Your product may do exactly what it’s supposed to in the eye, only for the patient to show no signs of improvement, because the issue might be elsewhere in their body.
The other problem was that noninfectious uveitis is a relatively rare disease. This makes it harder to find patients for clinical trials, which can extend your development timeline and increase your burn rate.
Patricia understands why the early team chose this condition. “Patients were going blind, and there was no treatment for them,” she says. “Gene therapy at that time was still science fiction. So there was a logic to going after that indication.”
However, she says that if she had been CEO at that time, she would have started measuring the technology’s impact on something more straightforward, like wet age-related macular degeneration (AMD), from the start.
Three Pieces of Advice for Planning Clinical Trials
Based on Patricia’s experience, here are the top three pieces of advice she would give to people in medical device and drug technology who are at the stage of planning their clinical trials.
Never forget who your patient is.
When you’re building your target product profile (TPP), remember that your patient is a person who feels pain, and has opinions about things like needles and delivery mechanisms. Especially in an area as sensitive as the eye.
“If you have a treatment that you know is going to work, but [the patient would] have to have an injection in the eye every day, forget about that: it’s not going to work,” Patricia says.
A treatment that is highly effective in a lab setting, but cannot be delivered in a tolerable manner, or which has to be used too frequently, won’t translate to real patients.
Build a realistic timeline.
Different conditions require you to wait different amounts of time before you can confirm whether your device or drug has been effective. You need to factor this into your timeline, and if possible, find ways to demonstrate your technology’s effectiveness while waiting on the final study results.
For example, Eyevensys’ priority is to treat dry AMD. It’s the most common form of AMD, affecting approximately 80% of AMD patients, as opposed to 20% who have wet AMD. As with wet AMD, the current treatment involves an anti-VEGF injection every month, and the patient will still lose their vision eventually. Eyevensys’ shots only have to be taken once every six months, and will hopefully delay vision loss.
However, it will take one or two years to get the results back on the dry AMD clinical trials, whereas the wet AMD clinical trials produce results in three months. That’s why Eyevensys is studying its technology in both dry and wet AMD.
You can’t always move up your timeline, but you can find creative ways of maintaining momentum while you wait.
Make sure your data isn’t a fluke
Your high school science teacher was right: repeatability is the holy grail of scientific experiments.
Producing one set of incredible, technology-validating results one time is not enough to prove that your device or drug works.
“Many biotech companies are created, and cannot repeat the basic science, and then it fails,” Patricia says. “It may still fail if you repeat the data. But don't undermine that: I always say, make sure you can repeat the data.”
Get Drug Development Experts on Your Team
As with most things in life, the best advice you can get about how to take a drug or medical device to market comes from people who have already done it. Patricia specifically recommends finding someone who has experience working in device/drug development in big pharma.
“That's the first thing you have to do: Try to reach for a big pharma expert who has been around the block, who has dealt with regulatory, with quality, with clinical, with science, etc.,” she says.
She also recommends maintaining high standards when it comes to experts. Look for the very best. The better your guide, the easier it will be to navigate the difficult steps ahead.
They should be experienced in the specific area you’re looking at. “You don't develop a drug for the eye the same way you develop a drug for cardiac [disease] or for stroke,” Patricia says.
Even better if you can get someone who knows about the exact condition you’re developing for. “Even inside the eye, if you think about glaucoma versus AMD, it's a different expertise,” she adds.
Given how specific you need to get, you’ll probably end up consulting more than one expert.
This belief in choosing partners who can support growth was also why Eyevensys decided to strategically collaborate with Midwest-based manufacturers Minnetronix Medical and Phillips-Medisize.
The first iteration of Eyevensys’ technology was built in a garage, before the company transferred to a small manufacturer in France. But the aim was to break into big pharma, which required a move to the U.S. — and partners who understood the U.S. regulatory and clinical environment.
“I need to make everything as clean, as easy and straightforward on the device side, so for me, getting with Phillips-Medisize and Minnetronix was a no-brainer: I knew I was going to the best,” Patricia says.
No, it’s Not Just You: Fundraising is Hard
Coming from the world of big pharma, Patricia was used to every financial request in her business development plans being granted. The process of fundraising and pitching venture capital (VC) firms was a shock to her system.
What she finds most frustrating is that VC investors don’t appear to base their decisions on data. Often, it’s just as much about luck and other outside factors as it is about science.
“You can have the best science, the best data, the best team: You can be the best, you can be super,” she says. “[But] at the end of the day, you don't know who you have in front of you, why they would invest in you, and why they would not. It can be multiple things and you don't know: You don't know the rules of the game. You're in the dark, and it's very frustrating.”
Experience — your own or someone else’s — can help you with most of the challenges of developing medical technology. But you might need something no one has invented yet to understand investors: a working crystal ball.
Patricia Zilliox has spent her entire career working in ophthalmology, including 30 years at American-Swiss medical company Alcon. Now she’s running a tech startup that aims to improve treatments and prognoses for some of the most common eye diseases.
In 2017, Patricia became CEO of Eyevensys, a biotech company founded nine years earlier in Paris.
Eyevensys is in the clinical stage of making a drug delivery system to inject DNA plasmids directly into the ciliary muscle with the goal of producing a consistent supply of antibodies to fight various eye diseases. The main areas of focus for the company include wet and dry age-related macular degeneration (AMD), and degenerative retinal diseases.
Patricia is working to bring Eyevensys to big pharma companies in the U.S. But first, she has to navigate some challenging regulatory hurdles.
Eyevensys’ technology has been classified as a combination biological device by the U.S. Food and Drug Administration (FDA). This means the company has to meet the agency’s requirements for selling a biologic (a type of drug) and for selling a medical device.
“That's what starts to make it more complex, because when you raise money, the first thing investors are going to ask you is, Are you a device company? Or are you a biologic?” she says. “We are a biologic, but from a device point of view, we have to follow all the rules as if you were developing a device.”
In this interview, Patricia gives advice for navigating the complicated world of regulatory affairs, the dos and don’ts of planning clinical trials, and why raising capital is the most frustrating part of her job.
Patricia Zilliox, PharmD, spent three decades managing clinical development programs for eyecare giant Alcon, followed by five years at the Foundation Fighting Blindness. Since 2017 she has been the CEO of Eyevensys, a French biotech startup working on an ophthalmology device that can inject DNA plasmids into the ciliary muscle.
Key Learnings from Patricia’s Experiences
- Be strategic in the early stages of developing your technology. Choose a suitable indication for your device, and when planning your timeline, take into account that it may take longer to collect data on how it works in some conditions versus others. And make sure you can repeat your results!
- Find advisers who have experience in drug and device development, preferably in the specific condition you’re trying to treat. You need experts to rely on for questions ranging from clinical trials to quality control and the regulatory pathways.
- Fundraising can be very challenging. You can have the best technology in the world, and the data to back it up, and still pitch over and over again with no success. It’s not necessarily your fault, and you usually won’t find out why investors said no.
Don’t Overcomplicate Your Job in the Development Stage
Before Patricia became CEO of Eyevensys, the small R&D team in Paris chose a complicated indication for their technology. Specifically, they were testing it as a potential treatment for noninfectious uveitis: inflammation of the part of the eye called the uvea.
The issue, Patricia says, is that this is a systemic condition, meaning it involves the entire body, not just the eye. It is believed to be caused by inflammation triggered by the immune system.
When you’re trying to test an ocular device, targeting a condition that affects the whole body can make it much more difficult to prove the effectiveness of your technology.
Your product may do exactly what it’s supposed to in the eye, only for the patient to show no signs of improvement, because the issue might be elsewhere in their body.
The other problem was that noninfectious uveitis is a relatively rare disease. This makes it harder to find patients for clinical trials, which can extend your development timeline and increase your burn rate.
Patricia understands why the early team chose this condition. “Patients were going blind, and there was no treatment for them,” she says. “Gene therapy at that time was still science fiction. So there was a logic to going after that indication.”
However, she says that if she had been CEO at that time, she would have started measuring the technology’s impact on something more straightforward, like wet age-related macular degeneration (AMD), from the start.
Three Pieces of Advice for Planning Clinical Trials
Based on Patricia’s experience, here are the top three pieces of advice she would give to people in medical device and drug technology who are at the stage of planning their clinical trials.
Never forget who your patient is.
When you’re building your target product profile (TPP), remember that your patient is a person who feels pain, and has opinions about things like needles and delivery mechanisms. Especially in an area as sensitive as the eye.
“If you have a treatment that you know is going to work, but [the patient would] have to have an injection in the eye every day, forget about that: it’s not going to work,” Patricia says.
A treatment that is highly effective in a lab setting, but cannot be delivered in a tolerable manner, or which has to be used too frequently, won’t translate to real patients.
Build a realistic timeline.
Different conditions require you to wait different amounts of time before you can confirm whether your device or drug has been effective. You need to factor this into your timeline, and if possible, find ways to demonstrate your technology’s effectiveness while waiting on the final study results.
For example, Eyevensys’ priority is to treat dry AMD. It’s the most common form of AMD, affecting approximately 80% of AMD patients, as opposed to 20% who have wet AMD. As with wet AMD, the current treatment involves an anti-VEGF injection every month, and the patient will still lose their vision eventually. Eyevensys’ shots only have to be taken once every six months, and will hopefully delay vision loss.
However, it will take one or two years to get the results back on the dry AMD clinical trials, whereas the wet AMD clinical trials produce results in three months. That’s why Eyevensys is studying its technology in both dry and wet AMD.
You can’t always move up your timeline, but you can find creative ways of maintaining momentum while you wait.
Make sure your data isn’t a fluke
Your high school science teacher was right: repeatability is the holy grail of scientific experiments.
Producing one set of incredible, technology-validating results one time is not enough to prove that your device or drug works.
“Many biotech companies are created, and cannot repeat the basic science, and then it fails,” Patricia says. “It may still fail if you repeat the data. But don't undermine that: I always say, make sure you can repeat the data.”
Get Drug Development Experts on Your Team
As with most things in life, the best advice you can get about how to take a drug or medical device to market comes from people who have already done it. Patricia specifically recommends finding someone who has experience working in device/drug development in big pharma.
“That's the first thing you have to do: Try to reach for a big pharma expert who has been around the block, who has dealt with regulatory, with quality, with clinical, with science, etc.,” she says.
She also recommends maintaining high standards when it comes to experts. Look for the very best. The better your guide, the easier it will be to navigate the difficult steps ahead.
They should be experienced in the specific area you’re looking at. “You don't develop a drug for the eye the same way you develop a drug for cardiac [disease] or for stroke,” Patricia says.
Even better if you can get someone who knows about the exact condition you’re developing for. “Even inside the eye, if you think about glaucoma versus AMD, it's a different expertise,” she adds.
Given how specific you need to get, you’ll probably end up consulting more than one expert.
This belief in choosing partners who can support growth was also why Eyevensys decided to strategically collaborate with Midwest-based manufacturers Minnetronix Medical and Phillips-Medisize.
The first iteration of Eyevensys’ technology was built in a garage, before the company transferred to a small manufacturer in France. But the aim was to break into big pharma, which required a move to the U.S. — and partners who understood the U.S. regulatory and clinical environment.
“I need to make everything as clean, as easy and straightforward on the device side, so for me, getting with Phillips-Medisize and Minnetronix was a no-brainer: I knew I was going to the best,” Patricia says.
No, it’s Not Just You: Fundraising is Hard
Coming from the world of big pharma, Patricia was used to every financial request in her business development plans being granted. The process of fundraising and pitching venture capital (VC) firms was a shock to her system.
What she finds most frustrating is that VC investors don’t appear to base their decisions on data. Often, it’s just as much about luck and other outside factors as it is about science.
“You can have the best science, the best data, the best team: You can be the best, you can be super,” she says. “[But] at the end of the day, you don't know who you have in front of you, why they would invest in you, and why they would not. It can be multiple things and you don't know: You don't know the rules of the game. You're in the dark, and it's very frustrating.”
Experience — your own or someone else’s — can help you with most of the challenges of developing medical technology. But you might need something no one has invented yet to understand investors: a working crystal ball.
