Founder Spotlight #3: Cailin Hardell @ Segmed
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Cailin Hardell is Co-Founder & CEO @ Segmed. Cailin has her masters in bioengineering from Stanford & experience in product management/healthcare as a Biodesign NEXT Fellow, Verily Life Sciences, & Apple Healthtech.
Segmed, a health care startup based in San Francisco, CA, provides high quality data for companies developing medical AI.
What prompted you to pursue a career in healthcare/life sciences (HC/LS)? Was there a specific moment in time or influence you can remember? What drives you to work in this space?
Growing up I always imagined being a doctor, because I wanted to help people. I actually did my undergraduate in physiology and was pre-med. However, after doing internships in health-tech and seeing trends towards digital health, personalized medicine, and data driven insights in healthcare, I switched course. Later choosing to pursue a technical master’s degree because I thought I could be more impactful by developing technologies that would help products get to patients and clinicians faster.
How did you get your training if any to be able to build your company? HC/LS increasingly has interdisciplinary academic backgrounds, while other founders take the plunge & jump straight off the deep end. Which one are you & why?
As far as training for entrepreneurship goes, I got very lucky. I interned in the Apple Health Tech department during my undergrad, then worked at Verily Life Sciences as an Associate Product manager during my masters. Working alongside some of the brightest minds in health tech at companies that are pushing boundaries showed me that even grand, vast, revolutionary ideas start out with someone saying ‘let’s try it’, taking a calculated risk, and working hard to make it a reality. And that this is how change is made. At Stanford, I participated in the Biodesign for Digital Health and the Stanford Ignite programs along with taking courses in the d.school, which taught me how to iterate quickly, put users first, and the basics of starting a company.
Can you tell us a little bit about your background & career thus far? What were you doing before you started running a high potential venture backed startup?
I did my undergrad at the University of Miami in exercise physiology. I loved physiology and learning about the body. Part of the reason I pursued exercise physiology at Miami was because sports have always been a huge part of my life — water polo in high school, competitive triathlon and ultimate frisbee in college, and now rock climbing. Sports have taught me perhaps better than anything else how to be patient, persistent, a teammate, a leader, and how to face your fears (of heights, in particular!). A few summers ago I climbed a 12 pitch, 1200ft wall.
Though I originally wanted to be a doctor, I switched trajectories and pursued bioengineering at Stanford for my masters after doing an internship at Apple and falling in love with health tech.
What problem is your company solving?
Segmed solves the problem of getting high quality, labeled training data for medical AI. We make it easy for companies to come to one place and get diverse datasets that they can use for AI training, testing, and validation. Right now, medical AI companies have to make individual data partnerships themselves (6+ months), then transfer and process the data (2 months), and get it labeled (3 months+). Additionally, they only have the bandwidth to partner with a few institutions each, so we are seeing algorithms being developed on data that isn’t representative of everyone, which could lead to bias in the future.
How did you become motivated to tackle this particular problem?
My co-founder, Dr. Martin Willemink, used to consult for an AI radiology company in the Bay Area, CA. He observed the struggle this company went through to get data labeled for developments (>9 months for one dataset!), and as we dug in to the problem we realized that solving this issue would take months off of companies’ development timelines, getting algorithms to patients, faster.
Quite simply, what does your company do?
Segmed provides high quality data for companies developing medical AI. We have started by selling licenses to AI Radiology companies, who use our data for training and validating their algorithms.
What are the specifics of what your company does?
We make contracts with hospitals, then transfer their (anonymized) data in whatever way they are comfortable with — cloud transfer, VPN, or sending them disks. Then we run our de-identification checks over the data, which work for multiple modalities (text, image, video), to make sure there is no PHI. At this point we start our standardization work, extracting metadata from the medical files and indexing it along with the files in our database so that it can be queried in the future. We perform a variety of labeling on the data depending on what it’s being used for (everything from NLP through ground truth labels performed by radiologists).
Why does your solution matter for the world when you get it right?
Medical AI will power healthcare in the 21st century and has the potential to help millions of people — some of whom do not have access to high-quality healthcare today. In order to develop algorithms that will work for everyone, we need an abundance of real-world patient data. At Segmed we care about making this happen sooner rather than later, to help these technologies get to patients faster, and also to make sure that everyone is accounted for in the training datasets, to avoid bias in systems that are life or death.
What is your company’s founding story? How did everything come together?
My co-founders and I met in the Stanford Ignite program in January of 2019. We discovered that we liked one another and had super complementary abilities. My CTO, Adam is a software engineer with 10 years of experience. Martin is an MD PhD radiologist and researcher, junior faculty at Stanford. And Jie is an ex-Facebook AI engineer, currently finishing up his PhD at Stanford. We decided it wasn’t going to get better than this team-wise and we thought we could make a real difference. We incorporated after the Ignite program ended.
Was there a specific moment when you knew you should pursue this as a business idea? If so, what was it?
When we dove into the labeled problem in medical AI (getting images labeled by experts for training), we discovered the magnitude of the problem. We spoke with researchers who had spent 2 years getting access to a single dataset for training. Realizing the impact we could have on the field by fixing this turned Segmed from a project into our personal missions.
Timing is everything — how did you know the timing was right?
Computing power, availability of AI resources, and increasing hospital modernization is allowing us to begin seeing algorithms be FDA approved and clinically deployed, and there’s been a boom in the medical AI field (growing 50% CAGR!). As things like the reimbursement pathway and ethical questions in the field are sorted out in the next few years, this will only increase. The companies with who are the fastest and have the best data will be poised to be market dominators, and the companies who work with Segmed can move the fastest and develop the most robust algorithms.
What are some of the notable milestones your company has achieved thus far?
We’ve made data partnerships that allow us to access data from >500 institutions worldwide. We’ve onboarded ~25 million images to our library, and have begun serving customers (in just 9 months as a B2B healthcare company, this is huge!).
What are some of the biggest hurdles ahead? How do these create points of value inflection?
We will face technical challenges as we develop pipelines to increase our labeling and scaling capabilities. Every time we succeed we create more value for our customers.
Pay It Forward
Throughout the journey, what have been some of your biggest takeaways thus far? What advice/words of wisdom would you share from your story for other founders?
Persistence is key! Find a way to connect with your “why” every day. Take care of yourself and set boundaries — you can’t sprint a marathon.
What are some of the must haves for an early stage HC/LS startup in your eyes? (Key critical components like team, academic papers, industry know-how, etc.)
Team! We are lucky enough to have technical, clinical, and product perspectives in our founding team. We don’t always agree, but usually the middle ground is where the answer lies, anyway. We have also seen a huge boost in inbound leads after publishing our first paper in Radiology. Never discount the power of proving you can do what you claim to be able to do.
What are some of the traits that make a great founder? What type of risk profile/archetype does someone need to have to be a founder in your opinion?
Ability to zoom out and look at the big picture, in addition to being detail oriented. Being able to think from your users’ perspective, feel their problems, and understand why they will derive value from your solution. I wouldn’t have described myself as someone who loves taking risks in the past, so I don’t think you need to be an adrenaline junkie to be a founder. I think it’s more important to know how to be vulnerable, to put yourself out there, and to really believe that what you’re doing can make a difference in the world.
For folks coming out of academia, what advice would you share?
Move faster than you’re used to. Don’t underestimate sales, marketing, and relationships because those are the tools that will make or break you. Learn them even if you don’t want to.
Not everyone knows everything. Often founders have to learn either the science or the business side better. What advice would you give for someone picking up a new skill set such as this?
Stay humble, curious, and google is your friend! Don’t be afraid to seek out mentors and ask questions.
Can you demystify the process of what it was like to raise VC funding? What were the highlights & low lights? Any advice or words of wisdom for future founders?
Don’t get too discouraged by the ‘no’s’, you only need a few ‘yes’s’. I came out of my masters and had to immediately start raising money so I could get paid (and pay for the expensive education I had just received). The first couple months were the hardest — pitching for the first time, getting told no again and again, and having just left the comforting nest of Stanford behind. I wanted to give up many times. But I never did, and things got way better!
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