The Apple Watch – Tipping Point Time for Healthcare

I don’t own an Apple Watch. I do have a Fitbit. But the Apple Watch 4 announcement intrigued me in a way no other product has since the original IPhone. This wasn’t just another product announcement from Apple. It heralded the U.S. Food and Drug Administration’s (FDA) entrance into the 21stcentury. It is a harbinger of the future of healthcare and how the FDA approaches innovation.

Sooner than people think, virtually all home and outpatient diagnostics will be performed by consumer devices such as the Apple Watch, mobile phones, fitness trackers, etc. that have either become FDA cleared as medical devices or have apps that have received FDA clearance. Consumer devices will morph into medical grade devices, with some painful and well publicized mistakes along the way.

Let’s see how it turns out for Apple.


Smartwatches are the apex of the most sophisticated electronics on the planet. And the Apple Watch is the most complex of them all. Packed inside a 40mm wide, 10 mm deep package is a 64-bit computer, 16gbytes of memory, Wi-Fi, NFC, cellular, Bluetooth, GPS, accelerometer, altimeter, gyroscope, heart rate sensor, and an ECG sensor – displaying it all on a 448 by 368 OLED display.
When I was a kid, this was science fiction.  Heck, up until its first shipment in 2015, it was science fiction.

But as impressive as its technology is, the Apple’s smartwatch has been a product looking for a solution. At first, positioned as a fashion statement, it seemed like the watch was actually an excuse to sell expensive wristbands. Subsequent versions focused on fitness and sports – the watch was like a Fitbit– plus the ability to be annoyed by interruptions from your work. But now the fourth version of the Watch might have just found the beginnings of “gotta have it” killer applications – healthcare – specifically medical diagnostics and screening.

Healthcare on Your Wrist
Large tech companies like Google, Amazon, Apple recognize that the  multi-trillion dollar health care market is ripe for disruption and have poured billions of dollars into the space. Google has been investing in a broad healthcare portfolio, Amazon has been investing in pharmacy distribution and Apple…? Apple has been focused on turning the Apple Watch into the future of health screening and diagnostics.

Apples latest Watch – with three new healthcare diagnostics and screening apps – gives us a glimpse into what the future of healthcare diagnostics and screening could look like.

The first new healthcare app on the Watch is Fall Detection. Perhaps you’ve seen the old commercials where someone falls and can’t get up, and has a device that calls for help. Well this is it – built into the watch. The watch’s built-in accelerometer and gyroscope analyze your wrist trajectory and impact acceleration to figure out if you’ve taken a hard fall. You can dismiss the alert, or have it call 911. Or, if you haven’t moved after a minute, it can call emergency services, and send a message along with your location.

If you’re in Apple’s current demographic you might think, “Who cares?” But if you have an aged parent, you might start thinking, “How can I get them to wear this watch?”

The second new healthcare app also uses the existing optical sensor in the watch and running in the background, gathers heart data and has an algorithm that can detect irregular heart rhythms. If it senses something is not right, up pops up an alert. A serious and common type of irregular heart rhythm is atrial fibrillation (AFib). AFib happens when the atria—the top two chambers of the heart get out of sync, and instead of beating at a normal 60 beats a minute it may quiver at 300 beats per minute.

This rapid heartbeat allows blood to pool in the heart, which can cause clots to form and travel to the brain, causing a stroke. Between 2.7 and 6.1 million people in the US have AFib (2% of people under 65 have it, while 9% of people over 65 years have it.) It puts ~750,000 people a year in the hospital and contributes to ~130,000 deaths each year. But if you catch atrial fibrillation early, there’s an effective treatment — blood thinners.

If your watch gives you an irregular heart rhythm alert you can run the third new healthcare app – the Electrocardiogram.

The Electrocardiogram (ECG or EKG) is a visual presentation of whether your heart is working correctly. It records the electrical activity of the heart and shows doctors the rhythm of heartbeats, the size and position of the chambers of the heart, and any damage to the heart’s muscle. Today, ECGs are done in a doctor’s office by having you lie down, and sticking 10 electrodes to your arms, legs and chest. The heart’s electrical signals are then measured from twelve angles (called “leads”).

With the Apple Watch, you can take an ECG by just putting your finger on the crown for 30 seconds. To make this work Apple has added two electrodes (the equivalent of a single lead), one on the back of the watch and another on the crown. The ECG can tell you that you may have atrial fibrillation (AFib) and suggest you see a doctor. As the ECG is saved in a PDF file (surprisingly it’s not also in the HL7’s FHIR Format), you can send it to your doctor, who may decide no visit is necessary.

These two apps, the Electrocardiogram and the irregular heart rhythms, are serious health screening tools. They are supposed to ship in the U.S. by the end of 2018. By the end of next year, they can be on the wrists of tens of millions of people.

The question is are they are going to create millions of unnecessary doctors’ visits from unnecessarily concerned users or are they going to save thousands of lives?  My bet is both – until traditional healthcare catches up with the fact that in the next decade screening devices will be in everyone’s hands (or wrists.)

Apple and The FDA – Clinical Trials
In the U.S. medical devices, drugs and diagnostics are regulated by the Food and Drug Administration – the FDA. What’s unique about the Apple Watch is that both the Electrocardiogram and the irregular heart rhythms apps required Apple to get clearance from the FDA. This is a very big deal.

The FDA requires evidence that medical devices do what they claim. To gather that evidence companies enroll volunteers in a study – called a clinical trial – to see if the device does what the company thinks it will.

Stanford University has been running a clinical trial on irregular heart rhythms for Apple since 2017 with a completion date in 2019. The goal is to see if an irregular pulse notification is really atrial fibrillation, and how many of those notified contacted a doctor within 90 days. (The Stanford study appears to be using previous versions of the Apple Watch with just the optical sensor and not the new ECG sensors. They used someone else’s wearable heart monitor to detect the Afib.)

Nov 1 2018 Update – the design of the Stanford Apple Watch study published here

To get FDA clearance, Apple reportedly submitted two studies to the FDA (so far none of the data has been published or peer reviewed). In one trial with 588 people, half of whom were known to have AFib and the other half of whom were healthy, the app couldn’t read 10% of the recordings. But for the other 90%, it was able to identify over 98% of the patients who had AFib, and over 99% of patients that had healthy heart rates.

The second data set Apple sent the FDA was part of Stanford’s Apple Heart Study. The app first identified 226 people with an irregular heart rhythm. The goal was to see how well the Apple Watch could pick up an event that looked like atrial fibrillation compared to a wearable heart monitor. The traditional monitors identified that 41 percent of people had an atrial fibrillation event. In 79 percent of those cases, the Apple app also picked something up.

This was good enough for the FDA.

The FDA – Running Hard to Keep Up With Disruption
And “good enough” is a big idea for the FDA. In the past the FDA was viewed as inflexible and dogmatic by new companies while viewed as insufficiently protective by watchdog organizations.

For the FDA this announcement was as important for them as it was for Apple.

The FDA has to adjudicate between a whole host of conflicting constituents and priorities. Its purpose is to make sure that drugs, devices, diagnostics, and software products don’t harm thousands or even millions of people so the FDA wants a process to make sure they get it right. This is a continual trade-off between patient safety, good enough data and decision making, and complete clinical proof. On the other hand, for a company, a FDA clearance can be worth hundreds of millions or even billions of dollars. And a disapproval or delayed clearance can put a startup out of business. Finally, the rate of change of innovation for medical devices, diagnostics and digital health has moved faster than the FDA’s ability to adapt its regulatory processes. Frustrated by the FDA’s 20th century processes for 21st century technology, companies hired lobbyists to force a change in the laws that guide the FDA regulations.

So, the Apple announcement is a visible signal in Washington that the FDA is encouraging innovation. In the last two years the FDA has been trying to prove it could keep up with the rapid advancements in digital health, devices and diagnostics- while trying to prevent another Theranos.

Since the appointment of the new head of the FDA, there has been very substantial progress in speeding up mobile and digital device clearances with new guidelines and policies. For example, in the last year the FDA announced its Pre-Cert pilot program which allows companies making software as a medical device to build products without each new device undergoing the FDA clearance process. The pilot program allowed nine companies, including Apple, to begin developing products (like the Watch) using this regulatory shortcut. (The FDA has also proposed new rules for clinical support software that say if doctors can review and understand the basis of the software’s decision, the tool does not have to be regulated by the FDA.)

This rapid clearance process as the standard – rather than the exception – is a sea-change for the FDA. It’s close to de-facto adopting a Lean decision-making process and rapid clearances for things that minimally affect health. It’s how China approaches approvals and will allow U.S. companies to remain competitive in an area (medical devices) where China has declared the intent to dominate.

Did Apple Cut in Front of the Line?
Some have complained that the FDA has been too cozy with Apple over this announcement.

Apple got its two FDA Class II clearances through what’s called a “de novo” pathway, meaning Apple claimed these features were the first of its kind. (It may be the first one built into the watch, but it’s not the first Apple Watch ECG app cleared by the FDA – AliveCor, got over-the-counter-clearance in 2014 and Cardiac Designs in 2013.) Critics said that the De Novo process should only be used where there is no predicate (substantial equivalence to an already cleared device.) But Apple cited at least one predicate, so if they followed the conventional 510k approval process, that should have taken at least 100 days. Yet Apple got two software clearances in under 30 days, which uncannily appeared the day before their product announcement.

To be fair to Apple, they were likely holding pre-submission meetings with the FDA for quite some time, perhaps years. One could speculate that using the FDA Pre-Cert pilot program they consulted on the design of the clinical trial, trial endpoints, conduct, inclusion and exclusion criteria, etc. This is all proper medical device company thinking and exactly how consumer device companies need to approach and work with the FDA to get devices or software cleared. And it’s exactly how the FDA should be envisioning its future.

Given Apple sells ~15 million Apple Watches a year, the company is about to embark on a public trial at massive scale of these features – with its initial patient population at the least risk for these conditions. It will be interesting to see what happens. Will overly concerned 20- and 30-year-olds flood doctors with false positives? Or will we be reading about lives saved?

Why most consumer hardware companies aren’t medical device and diagnostic companies
Historically consumer electronics companies and medical device and diagnostic companies were very different companies. In the U.S. medical device and diagnostic products require both regulatory clearance from the FDA and reimbursement approval by different private and public insurers to get paid for the products.

These regulatory and reimbursement agencies have very different timelines and priorities than for-profit companies. Therefore, to get FDA clearance a critical part of a medical device company is spent building a staff and hiring consultants such as clinical research organizations who can master and navigate FDA regulations and clinical trials.

And just because a company gets the FDA to clear their device/diagnostic/software doesn’t mean they’ll get paid for it. In the U.S. medical devices are reimbursed by private insurance companies (Blue Cross/Blue Shield, etc.) and/or the U.S. government via Centers for Medicare & Medicaid Services (CMS). Getting these clearances to get the product covered, coded and paid is as hard as getting the FDA clearance, often taking another 2-3 years. Mastering the reimbursement path requires a company to have yet another group of specialists conduct expensive clinical cost outcomes studies.

The Watch announcement telegraphed something interesting about Apple – they’re one of the few consumer products company to crack the FDA clearance process (Philips being the other). And going forward, unless these new apps are a disaster, it opens the door for them to add additional FDA-cleared screening and diagnostic tools to the watch (and by extension a host of AI-driven imaging diagnostics (melanoma detection, etc.) to the iPhone.) This by itself is a key differentiator for the Watch as a healthcare device.

The other interesting observation: Unlike other medical device companies, Apple’s current Watch business model is not dependent on getting insurers to pay for the watch. Today consumers pay directly for the Watch. However, if the Apple Watch becomes a device eligible for reimbursement, there’s a huge revenue upside for Apple. When and if that happens, your insurance would pay for all or part of an Apple Watch as a diagnostic tool.

(After running cost outcome studies, insurers believe that preventative measures like staying fit brings down their overall expense for a variety of conditions. So today some life insurance companies are mandating the use of an activity tracker like Apple Watch.)

The Future of SmartWatches in Healthcare
Very few companies (probably less than five) have the prowess to integrate sensors, silicon and software with FDA regulatory clearance into a small package like the Apple Watch.

So what else can/will Apple offer on the next versions of the Watch? After looking through Apple’s patents, here’s my take on the list of medical diagnostics and screening apps Apple may add.

Sleep Tracking and Sleep Apnea Detection
Compared to the Fitbit, the lack of a sleep tracking app on the Apple Watch is a mystery (though third-party sleep apps are available.) Its absence is surprising as the Watch can theoretically do much more than just sleep tracking – it can potentially detect Sleep Apnea. Sleep apnea happens when you’re sleeping, and your upper airway becomes blocked, reducing or completely stopping air to your lungs. This can cause a host of complications including Type 2 diabetes, high blood pressure, liver problems, snoring, daytime fatigueToday diagnosing sleep apnea often requires an overnight stay in a sleep study clinicSleep apnea screening doesn’t appear to require any new sensors and would be a great app for the Watch. Perhaps the app is missing because you have to take the watch off and recharge it every night?

Pulse oximetry
Pulse oximetry is a test used to measure the oxygen level (oxygen saturation) of the blood. The current Apple Watch can already determine how much oxygen is contained in your blood based on the amount of infrared light it absorbs. But for some reason Apple hasn’t released this feature – FDA regulations? Inconsistent readings?  Another essential Watch health app that may or may not require any new sensors.

Respiration rate
Respiration rate (the number of breaths a person takes per minute) along with blood pressure, heart rate and temperature make up a person’s vital signs. Apple has a patent for this watch feature but for some reason hasn’t released it – FDA regulations?  Inconsistent readings?  Another essential Watch health app that doesn’t appear to require any new sensors.

Blood Pressure
About 1/3rd of Americans have high blood pressure. High blood pressure increases the risk of heart disease and stroke. It often has no warning signs or symptoms. Many people do not know they have it and only half of those have it under control. Traditionally measuring blood pressure requires a cuff on the arm and produces a single measurement at a single point in time. We’ve never had the ability to continually monitor a person’s blood pressure under stress or sleep. Apple filed two patents in 2017 to measure blood pressure by holding the watch against your chest. This is tough to do, but it would be another great health app for the Watch that may or may not require any new sensors.

Sunburn/UV Detector
Apple has patented a new type of sensor – a sunscreen detector to let you know what exposed areas of the skin of may be at elevated UV exposure risk. I’m not big on this, but the use of ever more powerful sunscreens has quadrupled, while at the same time, the incidence of skin cancers has also quadrupled, so there may be a market here.

Parkinson’s Disease Diagnosis and Monitoring
Parkinson’s Disease is a brain disorder that leads to shaking, stiffness, and difficulty with walking, balance, and coordination. It affects 1/% of people over 60. Today, there is no diagnostic test for the disease (i.e. blood test, brain scan or EEG). Instead, doctors look for four signs: tremor, rigidity, Bradykinesia/akinesia and Postural instability. Today patients have to go to a doctor for tests to rate the severity of their symptoms and keep a diary of their symptoms.

Apple added a new “Movement Disorder API” to its ResearchKit framework that supports movement and tremor detection. It allows an Apple Watch to continuously monitor for Parkinson’s disease symptoms; tremors and Dyskinesia, a side-effect of treatments for Parkinson’s that causes fidgeting and swaying motions in patients. Researchers have built a prototype Parkinson’s detection app on top of it. It appears that screening for Parkinson’s would not require any new sensors – but likely clinical trials and FDA clearance – and would be a great app for the Watch.

Glucose Monitoring
More than 100 million U.S. adults live with diabetes or prediabetes. If you’re a diabetic, monitoring your blood glucose level is essential to controlling the disease. However, it requires sticking your finger to draw blood multiple times a day. The holy grail of glucose monitoring has been a sensor that can detect glucose levels through the skin. This sensor has been the graveyard of tons of startups that have crashed and burned pursuing this. Apple has a patent application that looks suspiciously like a non-invasive glucose monitoring sensor for the Apple Watch. This is a really tough technical problem to solve, and even if the sensor works, there would be a long period of clinical trials for FDA clearance, but this app would be a game changer for diabetic patients – and Apple – if they can make it happen.

Sensor and Data Challenges
With many of these sensors just getting a signal is easy. Correlating that particular signal to an underlying condition and avoiding being confounded by other factors is what makes achieving medical device claims so hard.

As medical grade data acquisition becomes possible, continuous or real time transmission will store and report baseline data on tens of millions of “healthies” that will be vital in training the algorithms and eventually predicting disease earlier. This will eventually enable more accurate diagnostics on less data, and make the data itself – especially the transition from healthy to diseased – incredibly valuable.

However, this sucks electrons out of batteries and plays on the edge electrical design and the laws of physics, but Apple’s prowess in this area is close to making this possible.

What’s Not Working?
Apple has attempted to get medical researchers to create new health apps by developing ResearchKit, an open source framework for researchers. Great idea. However, given the huge potential for the Watch in diagnostics, ResearchKit and the recruitment of Principal Investigators feels dramatically under resourced. (It took three years to go from ResearchKit 1.0 to 2.0).  Currently, there are just 11 ResearchKit apps on the ITunes store. This effort – Apple software development and third-party app development – feels understaffed and underfunded. Given the potential size of the opportunity, the rhetoric doesn’t match the results and the results to date feel off by at least 10x.

Apple needs to act more proactively and directly fund some of these projects with grants to specific principal investigators and build a program of scale. (Much like the NIH SBIR program.) There should be as sustained commitment to at least several new FDA cleared screening/diagnostic apps every year for Watch and iPhone from Apple.

The Future
Although the current demographics of the Apple Watch skews young, the populations of the U.S., China, Europe and Japan continue to age, which in turn threatens to overwhelm healthcare systems. Having an always on, real-time streaming of medical data to clinicians, will change the current “diagnosis on a single data point and by appointment” paradigm. Wearable healthcare diagnostics and screening apps open an entirely new segment for Apple and will change the shape of healthcare forever.

Imagine a future when you get an Apple Watch (or equivalent) through your insurer to monitor your health for early warning signs of heart attack, stroke, Parkinson’s disease and to help you monitor and manage diabetes, as well as reminding you about medications and tracking your exercise. And when combined with an advanced iPhone with additional FDA cleared screening apps for early detection of skin cancer, glaucoma, cataracts, and other diseases, the future of your health will truly be in your own hands.

Outside the U.S., China is plowing into this with government support, private and public funding, and a China FDA (CFDA) approval process that favors local Chinese solutions. There are well over 100 companies in China alone focusing in this area, many with substantial financial and technical support.

Let’s hope Apple piles on the missing resources for diagnostics and screening apps and grabs the opportunity.

Lessons Learned

  • Apple’s new Watch has two heart diagnostic apps cleared by the FDA
    • This is a big deal
  • In a few years, home and outpatient diagnostics will be performed by wearable consumer devices – Apple Watch, mobile phones or fitness trackers
    • Collecting and sending health data to doctors as needed
    • Collecting baseline data on tens of millions of healthy people to train disease prediction algorithms
  • In the U.S. the FDA has changed their mobile and digital device guidelines and policies to make this happen
  • Insurers will ultimately will be paying for diagnostic wearables
  • Apple has a series of patents for additional Apple Watch sensors – glucose monitoring, blood pressure, UV detection, respiration
    • The watch is already capable of detecting blood oxygen level, sleep apnea, Parkinson’s disease
    • Getting a signal from a sensor is the easy part. Correlating that signal to an underlying condition is hard
    • They need to step up their game – money, software, people – with the medical research community
  • China has made building a local device and diagnostic industry one of their critical national initiatives

The 7 Deadly Healthcare Startup Sins

Todd Dunn is the Director of Innovation and runs the Intermountain Healthcare Transformation Lab, which is working to foster innovation in the healthcare industry. Todd DunnHe’s now run several Lean LaunchPad classes and has seen a ton of healthcare startups. Here’s his advice for startups in this space.

———

I have spent the last 10 years in the Healthcare space. Over the past couple of years as Director of Innovation for Intermountain Healthcare I’ve mentored and worked with many Healthcare-focused startups. During that time I have seen teams that really seem to understand the industry and those who are relatively uninformed.

Our healthcare system is complex, under intense regulatory pressure, the pressure of the aging population, reimbursement changes, and an oncoming shortage of clinicians, among other challenges. It is in need of innovation on many fronts and is also trying to embrace the amazing amount of innovation happening with early-stage companies.

Yet, I have noticed that many healthcare startups make “leap of faith assumptions” as they try to build their businesses. Let me highlight the 7 deadly healthcare startup sins!

Sin 1: Healthcare startups assume hospitals will let them host patient data in “their portal.” The reality is that healthcare customers know that startups’ portals are likely hosted by AWS, Azure, or Google, and therefore pose security and privacy concerns. My reference points on these startups are digital health startups and small device startups that gather data from patients remotely. Many startups make the key assumption that hospitals will trust their data to a startup’s “cloud” for the long term. For a proof of concept or pilot this may be OK. For the longer term it may not be. The only way to know for sure is to test that assumption by getting out of the office and talking to customers.

Sin 2: Startups assume that clinicians will be willing to access yet another portal for their data. Basically, startups make assumptions about clinicians’ workflow that may be myopic. In completing their Business Model Canvas some startups assume that a clear value is having their solution hosted in the cloud but often overlook the workflow impacts from a value perspective. The challenge is that many of them haven’t done enough “get out of the office” work to understand how their proposed solution will or won’t fit into a healthcare provider’s workflow. Doctors and nurses want more time with patients. In addition, doctors have many data points for making decisions. Having to go to multiple places for data about one patient reduces the time they can spend with each patient and complicates sound decision-making. The “job to be done” is to diagnose and prescribe. One pain that doctors and nurses want to avoid is going to multiple locations to get the needed decision support data. Clinical decision support needs to be simplified. Going to another portal for patient data is simply onerous. If your solution reduces the time a clinician can spend with a patient or makes it harder to make a decision you have reduced the value.

Sin 3: That one doctor or hospital lends enough credibility for other organizations to simply accept a startup’s solution. Many startups believe that if they have a doctor on their team or as an advisor (the idea of having a KOL – Key Opinion Leader), or if one hospital has written a letter of support, they have credibility. The reality is that it doesn’t suffice. More homework needs to be done. Healthcare regulations, processes, and delivery approaches often vary from system to system. A broader base of KOL’s would simply lend credibility to the solution’s applicability across multiple customers.   “Getting out of the office” and talking to customers is a necessary endeavor to get these deep and broad insights from KOL’s.

I recommend that teams get a least five KOL’s to support their value claims. This isn’t just about conducting 100 customer interviews. This is about getting evidence that Key Opinion Leaders agree that the value proposition offered by the startup can be realized. As Steve recommends, use an MVP to get evidence that validates those opinions.

Sin 4: Believing that ONE key leader inside a hospital is the decision-maker, influencer, etc. all in one role…. The Startup Owner’s Manual clearly articulates the need to understand “how” a company buys a product. ….Most startups I see want to go directly into a pilot and many want to speak directly with the C-level clinical leaders. Part of the weakness is that most startups aren’t asking learning questions … they are making statements vs. being curious enough to test their assumptions.

Sin 5: Thinking that conducting a “proof of concept” and/or pilot is a simple endeavor. In working with eight early-stage companies in the last two months I have consistently asked, “What do you want from us?” Oddly I found some teams did not have a crisp answer. However, all of them wanted to hop directly into a proof of concept within an extremely short time. In wanting to do so, they overlooked

  • the need for an IRB (institutional review board,) (especially where patients are involved)
  • a security review (especially if they are in “the cloud”)
  • a compliance review
  • the time needed to design a study
  • and last but not least signing a contract!

All of these are easily in the “Activity” portion of the Business Model Canvas and few early-stage companies fully understand these needs, especially when working with a large IDN (integrated delivery network) like Intermountain Healthcare.

Sin 6: There isn’t anyone else out there solving the problem. A large percentage of startups struggle to answer the question, “Why do current solutions fail?” This suggests that they haven’t completed a petal diagram to look at the existing offerings, or analyzed the “job” that someone needs to hire a solution for. As an example, a med-adherence solution approached us recently and offered that there wasn’t “anyone” else with a technology like theirs. That may be true…not likely. I suggest that teams thoroughly think through this.

Sin 7: Believing that startups need to have more answers than questions. Almost unanimously startup teams want to have an answer for every question. I understand their desire to appear knowledgeable. But you don’t get out of the office to have answers – you get out of the office to ask questions. This goes back to a fundamental that I believe all startups need until they truly know: curiosity.

hypotheses experimentMy advice to healthcare startups.

  1. Use the Lean Startup tools! Regardless of where you start, it comes down to your value proposition as a starter or non-starter. Use Alexander Osterwalder’s Value Proposition canvas and Steve’s guidance to “get out of the office.”
    value prop map
  2. This often tries the patience of entrepreneurs. I cannot overemphasize the need to use the learning loop in every single part of the Value Proposition and Business Model canvases. The only way to do that is to GET OUT OF THE OFFICE!
  3. Be curious about workflow and how large IDNs (integrated delivery network) like Intermountain Healthcare are thinking about the integration of patient data into a workflow. Be empathetic to your user.
  4. Study the industry more deeply. While you may have a great value proposition for one or two hospitals, how does your solution fit into the regulatory landscape, workflow, etc. of multiple hospitals?
  5. Listen! Assume you don’t have enough evidence to scale your business yet. Act like you don’t know enough. While an entepreneur’s “go get ’em” attitude is appreciated, it isn’t appreciated when the entrepreneur isn’t open to feedback, seems to have all the answers, and has a condescending attitude toward the way “jobs” get done today. Test your assumptions! Come loaded with questions that are related to your assumptions.
  6. Last but not least, structure a learning plan. Embrace the Lean Startup tools and methods. Following this structure will cause you to write a learning plan. A foundational question to guide your learning plan in every part of your business model is “What do we need to learn before we invest more time and money?”

Best of success! Healthcare needs innovative startups and innovative startups need the knowledge and access that Healthcare can provide.

I’m on the Air – On Sirius XM Channel 111

Starting this Monday, March 9th 4-6pm Pacific Time I’ll be on the radio hosting the Bay Area Ventures program on Sirius XM radio Channel 111 – the Wharton Business Radio Channel.Untitled

Over this program I’ll be talking to entrepreneurs, financial experts and academic leaders in the tech and biotech industries. And if the past is prologue I guarantee you that this will be radio worth listening to.

On our first show, Monday March 9th 4-6pm Pacific Time join me, as I chat with Alexander Osterwalder – inventor of the Business Model Canvas, and Oren Jacob, ex-CTO of Pixar and now CEO of ToyTalk on Sirius XM Radio Channel 111.

Oren Jacob - CEO ToyTalk

Oren Jacob – CEO ToyTalk

Alex Osterwalder - Business Models

Alex Osterwalder – Business Models

On Monday’s show we’ll be talking about a range of entrepreneurship topics: what’s a Business Model Canvas, how to build startups efficiently, the 9 deadly sins of a startup, the life of a startup CEO, how large companies can innovate at startup speeds. But it won’t just be us talking; we’ll be taking your questions live and on the air by phone, email or Twitter.

On April 27th, on my next program, my guest will be Eric Ries the author of the Lean Startup. Future guests include Marc Pincus, founder of Zynga, and other interesting founders and investors.

Is there anyone you’d like to hear on the air on future shows? Any specific topics you’d like discussed? Leave me a comment.

Mark your calendar for 4-6pm Pacific Time on Sirius XM Radio Channel 111:

  • March 9th
  • April 27th
  • May 11th
  • June 29th
  • July 13th
  • Aug 24th in NY

Life Science Startups Rising in the UK

Stephen Chambers spent 22 years in some of the most innovative companies in life science as the director of gene expression and then as a co-founder of his own company. Today he runs SynbiCITE, the UK’s synthetic biology consortium of 56 industrial partners and 19 Academic institutions located at Imperial College in London.

Stephen and SynbiCITE, just launched the world’s first Lean LaunchPad for Synthetic Biology program. Here’s his story.

—-

Why did you come back?
This is the question I most often hear, having now returned to the UK after leaving 24 years ago to work in the US. The answer is simple. The reason I came back is the same reason I left – to be where life science startups are happening.

Hard to imagine now, but in the late ’80s the life sciences startup landscape in the UK was almost non-existent. One or two companies existed which at the time were described as startups, but in reality were government-backed small companies attempting, and ultimately failing, to execute business plans.

At that time for any life-scientist wanting to work in the commercial sector there were few, if any, jobs in the UK. Along with the rest of British industry, the pharmaceutical sector was under going massive re-organization and mergers creating much of today’s big pharma in the process. These where the Thatcher years: when we were told to  ‘get on your bike’ and many of us did.

I left the UK joining a newly formed startup, Vertex Pharmaceuticals in Cambridge, Massachusetts, as one of the founding scientists. There were few alternatives then, if you wanted to work in a startup you had to go to the US. Fortunately, Vertex became one of the most successful US pharma companies in recent history. But even if it hadn’t, in the rich life-science ecosystem around Cambridge and Boston, there are plenty of other opportunities. Or you could start your own company, which I did after Vertex.

So what has changed in the UK?
Probably the biggest change was the UK government’s recognition of the importance of synthetic biology. (Synthetic biology engineers biologically based chemicals, drugs and materials.) The government designated the field as one of the UK’s Eight Great Technologies (along with advanced materials, agri-science, big data, energy storage, regenerative medicine, robotics, and satellites) that the country would focus on. The UK invested ~ £150 million in synthetic biology research and training through the Research Councils and Innovate UK.

To focus the national synthetic biology effort the UK created SynbiCITE, as the public-private partnership responsible for taking synthetic biology from the lab bench into commercial products in the UK.

And this is what has drawn me back. Looking at the UK, I saw a hotbed of startup activity, especially among companies looking to exploit the latest developments in synthetic biology.

I jumped at the opportunity to be the CEO of SynbiCITE, where I can pursue my passion of working with scientists and entrepreneurs who want to create and build something spectacular in the UK.

The Foundry
SynbiCITE provides financial aid for Proof of Concept and collaborative research, and logistical support in the form of access to a state-of-the-art ‘Foundry’ for DNA synthesis, assembly and verification.

Often the limiting step in synthetic biology innovation is the generation of the prototype, the model or the data: the Foundry seeks to bridge the critical gap between ideation and physical product in synthetic biology. Think of it as a “maker-space” specifically designed to support the commercialization of synthetic biology allowing startups to prototype new biologically based chemicals, drugs and materials.

The Foundry accelerates the translation of synthetic biology research into the marketplace. Small and medium-sized companies, startups or virtual companies can use the Foundry as a remote laboratory. We provide automated end-to-end design, construction and validation of synthetic biologic components. It is the generation of these parts, devices and systems, and the diversity of products they can produce and the range of functions they perform, which is creating the enormous excitement around this technology.

Another change in the UK, is the growing acceptance that startups are the true engines of not only economic and job growth but also the medium by which innovation most efficiently takes place. While there are still universities in the UK that would rather not have to deal with messy, cash-strapped entrepreneurs and startups most are beginning to realize that licensing doesn’t create jobs, startups do.

Lean LaunchPad to Accelerate Commercialization
The goal of our Synthetic Biology consortium is to turn our world-class scientific research into commercial products. This is why we’re excited about offering the Lean LaunchPad at SynbiCITE. Our goal is to help would-be scientist/entrepreneurs translate their ideas and research in synthetic biology into the marketplace. We want to teach them how successful startups really get built – and do it with urgency.

If you can’t see the video click here

The goal is to provide them a route from coming up with an idea for a product, through generation of business model canvas via the Lean LaunchPad program and in parallel, harness the Foundry for the production of prototypes, models and data all the while providing evidence of commercial potential.

The program gives those involved direct hands-on experience of identifying a product that the customer really needs and is prepared to buy. I want the participants in the program to have the excitement of finding their first customer, shipping that first product and in doing so learn about all the other aspects of building a successful business.  The Lean LaunchPad does that it in 12 weeks.

Going forward this initial Lean LaunchPad cohort at SynbiCITE will be the first of many. The course is the most important of all the innovation programs we are providing.

This will be the first time in the UK, scientists in the field of synthetic biology have being given the unique opportunity to learn how to become would-be entrepreneurs, by getting out of the lab, talking to potential customers and partners, and identifying what’s needed to turn science into commercial products.

Lessons Learned

  • The UK has established a national effort in Synthetic Biology
  • The Lean LaunchPad is being used to rapidly turn science into commercial products

Getting out of the building…by staying in the building!

The landscape for how to turn life science and health care technologies into viable companies has changed more in the last 3 years than in the last 30. New approaches to translational medicine have emerged. Our Lean Launchpad® for Life Sciences is one of them. But a new class of life science/healthcare co-working and collaboration space is another.

———–

The National Institutes of Health recognizes that Life Science/Health Care commercialization has two components: the science/technology, and the business model. The Lean Launchpad® for Life Sciences (the I-Corps @ NIH) uses the Lean Startup Model to discover and validate the business model.

two parts to commericializationThe class provides Life Science/Health Care entrepreneurs with real world, hands-on learning on how to rapidly:

  • define clinical utility before spending millions of dollars
  • understand who their core and tertiary customers are, and the sales and marketing process required for initial clinical sales and downstream commercialization
  • assess intellectual property and regulatory risk before they design and build
  • know what data will be required by future partnerships/collaboration/purchases before doing the science
  • identify financing vehicles before you need them

This user/customer-centered approach is a huge step in the right direction in the life science/health care commercialization. However, one of the bottlenecks in actually doing Customer Discovery for medical devices/health care is testing how minimal viable products work in-context. Testing hypotheses with doctors, patients, payers, providers, purchasing departments, strategic partners is hard. It can involve traveling hundreds of miles and can consume months of time and loads of money. Scheduling time to look over a surgeon’s shoulder in an operating room is tough. Getting time to brainstorm with payers or experts in clinical trials is hard.

It would be great if there were a way to first test these hypotheses and minimal viable products in a realistic setting locally. Then after a first pass of validation, take them on the road and see if others agree.

A new life science/healthcare co-working and collaboration space
It looks like someone is actually pulling this together in a life science/healthcare co-working and collaboration space in Chicago called MATTER.

Co-working spaces seem to be evolving into the startup garages of the future. It’s a shared work environment (typically a floor of a building) where individuals (or small teams) rent space and work around other people but independently. Yet they share values and hopefully some synergy around topics of mutual interest (same customers, or technologies). Incubators are designed for teams with an idea. They add mentors and additional services and some offer free space in exchange for equity. Accelerators take teams with fairly focused ideas and offer a formal 3-4 month program of tutoring/mentoring with seed funding in exchange for equity.

The MATTER co-working space will have five unique things specifically for life science/healthcare companies:

  1. It’s focused exclusively on life science/health care (therapeutics, medical devices, diagnostics, digital health, health care IT, etc.)
  2. Key stakeholders in the broader healthcare ecosystem will be co-located under one roof: entrepreneurs, universities, established companies and strategic partners, providers, payers, hospitals, service providers, associations, advocacy groups, government and more.
  3. It will have a simulated procedure space that can be configured as an Operating Room, Emergency Room, Intensive Care Unit and other clinical/procedural settings. The space will include authentic lighting, equipment and other features that very closely resemble the look, sound and feel of these environments in the “real world”.
  4. It will have a clinician and patient studio configurable as a doctor’s office or a home care setting to simulate clinician and patient interactions. It will serve as a test bed for software, services and other technologies to improve the clinician/patient dynamic as well as improving workflows in the clinic.
  5. It will have a fabrication space where device startups can build minimum viable products and iterate on their designs while in the facility.

By building a co-working space that includes all of these stakeholders, MATTER allows startups (and companies) to get in front of customers and other members of the value chain first, before they leave the building.

The team at MATTER also realizes that facilities alone will not do the trick. In order to get the healthcare community to collaborate with each other to bring new ideas to market they will need some help to catalyze  the “co” part of co-working.

“The life sciences community is still warming-up to the value of customer development in the early stages of building new ventures”, says David Schonthal, MATTER Co-founder and Clinical Assistant Professor of entrepreneurship & innovation at the Kellogg School of Management. “Many of them aren’t yet clear on who their customer actually is – and as a result – what value they should be focused on creating. Essentially, through programming and content, we will need to teach many of our members the importance of understanding the needs of stakeholders and customers – we just aim to make it easier by bringing these people into the building.”

The procedure space and clinician and patient studio allow startups to test and demo medical devices, diagnostics, software and other technologies, with real clinicians, to validate hypotheses, their technologies, and discover the “unknown unknowns” that they wouldn’t learn until the product was used in a real clinical setting (meaning: after years of development and regulatory clearances).

But the real benefit for a Lean Startup is that unlike a traditional OR/ER, technologies/devices used in these spaces can be minimum viable products. They can be crude, non-sterile prototypes tested at any phase of their development (from sketch to machined parts), to answer any number of important questions that innovators might have about how, when, why and by whom a technology is used.

(Think of a startup building a diagnostic display designed for an operating room that discovered it was virtually unreadable and inaudible in the bright lights and loud sounds of a real operating room. Finding this out late in the development process can burn cash and time in a med tech company.)

MATTER is funded and supported by a broad range of private sector partners including established companies, providers, payers, service providers and others; as well as public sector support from the State of Illinois and the City of Chicago.

It Takes a Village
“This has been nearly a 4-year journey,” said Schonthal who prior to moving back to Chicago in 2011 had been working in healthcare venture capital in San Diego.

“One of the noticeable things about the San Diego health tech community is that it feels like a community. It has density,” he said. “People bump into each other, seek each other’s advice, make connections and collaborate on projects. In Chicago, despite having a lot of talent, companies and great research, we are a big, spread-out city. As a result we needed to design some of that density inside of MATTER so that serendipity can occur”.

Schonthal found that others in Chicago saw the vision. He enlisted the help of serial medical device entrepreneur Andrew Cittadine, biotech startup veteran Jeffery Aronin and Patrick Flavin and Steve Collens who was a major force behind the development of 1871 – Chicago’s digital co-working space. Together they recruited the support of the city, state and private industry who all agreed that frequent and early community collaboration to support young companies would be key to Chicago’s future in healthcare entrepreneurship.

Others Are Doing this As Well
MATTER is one of many organizations supporting life science/healthcare entrepreneurship across the country. In New York there’s Blueprint Health and Startup Health, in Denver there’s Stride and Princeton has Tiger Labs. Other incubators and accelerators in the health tech space include Health WildCatters in Dallas, RockHealth in Silicon Valley, Iron Yard in North Carolina, HealthBox Accelerator, Athena Health MDP in Boston and others. And probably the most important will be the Lean LaunchPad @ Life Science Angels class for early stage life science companies. Each of these has their own approach to supporting the creation of new ventures – but all are working to help young startups solve big problems.

Lessons Learned

  • Our knowledge of how to efficiently turn life science/health care technology into companies is rapidly increasing
  • Lean Methods are one such tool
  • Healthcare co-working and collaboration space is another

I-Corps at the NIH: Evidence-based Translational Medicine

If you’ve received this post in an email the embedded videos and powerpoint are best viewed on www.steveblank.com

We have learned a remarkable process that allow us to be highly focused, and we have learned a tool of trade we can now repeat. This has been of tremendous value to us.

Andrew Norris, Principal Investigator BCN Biosciences

Over the last three years the National Science Foundation I-Corps has taught over 700 teams of scientists how to commercialize their technology and how to fail less, increasing their odds for commercial success.

To see if this same curriculum would work for therapeutics, diagnostics, medical devices and digital health, we taught 26 teams at UCSF a life science version of the NSF curriculum. 110 researchers and clinicians, and Principal Investigators got out of the lab and hospital, and talked to 2,355 customers. (Details here)

For the last 10 weeks 19 teams in therapeutics, diagnostics and medical devices from the National Institutes of Health (from four of the largest institutes; NCINHBLI, NINDS, and NCATS) have gone through the I-Corps at NIH.

87 researchers and clinicians spoke to 2,120 customers, tested 695 hypotheses and pivoted 215 times. Every team spoke to over 100 customers.

Three Big Questions
The NIH teams weren’t just teams with ideas, they were fully formed companies with CEO’s and Principal Investigators who already had received a $150,000 grant from the NIH. With that SBIR-Phase 1 funding the teams were trying to establish the technical merit, feasibility, and commercial potential of their technology. Many will apply for a Phase II grant of up to $1 million to continue their R&D efforts.

Going into the class we had three questions:

  1. Could companies who were already pursuing a business model be convinced to revisit their key commercialization hypotheses – and iterate and pivot if needed?
  2. Was getting the Principal Investigators and CEO out of the building more effective than the traditional NIH model of bringing in outside consultants to do commercialization planning?
  3. Would our style of being relentlessly direct with senior scientists, who hadn’t had their work questioned in this fashion since their PhD orals, work with the NIH teams?

Evidence-based Translational Medicine
We’ve learned that information from 100 customers is just at the edge of having sufficient data to validate/invalidate a company’s business model hypotheses. As for whether you can/should push scientists past their comfort zone, the evidence is clear – there is no other program that gets teams anywhere close to talking to 100 customers. The reason? For entrepreneurs to get out of the building at this speed and scale is an unnatural act. It’s hard, there are lots of other demands on their time, etc. But we push and cajole hard, (our phrase is we’re relentlessly direct,) knowing that while they might find it uncomfortable the first three days of the class, they come out thanking us.

The experience is demanding but time and again we have seen I-Corps teams transform their business assumptions. This direct interaction with potential users and customers is essential to commercialize science (whether to license the technology or launch a startup.) This process can’t be outsourced. These teams saved years and millions of dollars for themselves, the NIH and the U.S. taxpayer. Evidence is now in-hand that with I-Corps@NIH the NIH has the most effective program for commercializing science.

Lessons Learned Day
Every week of this 10 week class, teams present a summary of what they learned from their customers interviews. For the final presentation each team created a two minute video about their 10-week journey and a 8-minute PowerPoint presentation to tell us where they started, what they learned, how they learned it, and where they’re going. This “Lessons Learned” presentation is much different than a traditional demo day. It gives us a sense of the learning, velocity and trajectory of the teams, rather than a demo day showing us how smart they are at a single point in time.

BCN Biosciences
This video from team BCN Biosciences describes what the intensity, urgency, velocity and trajectory of an I-Corps team felt like. Like a startup it’s relentless.

BCN is developing a drug that increases anti-cancer effect of radiation in lung cancer (and/or reduces normal tissue damage by at least 40%). They were certain their customers were Radiation Oncologists, that MOA data was needed, that they needed to have Phase 1 trial data to license their product, and needed >$5 million and 6 years. After 10 weeks and 100 interviews, they learned that these hypotheses were wrong.

If you can’t see the BCN Biosciences video click here

The I-Corps experience helped the BCN Bioscience team develop an entirely new set set of business model hypotheses – this time validated by customers and partners. The “money slides” for BCN Biosciences are slides 22 and 23.

If you can’t see the BCN Biosciences presentation click here

You Can’t Outsource Customer Discovery
What we hear time and again from the Principal Investigators is “I never would have known this” or “I wouldn’t have understood it if I hadn’t heard it myself.” Up until now the NIH model of commercialization treated a Principal Investigator as someone who can’t be bothered to get out of the building (let alone insist that it’s part of their job in commercialization.) In the 21st century using proxies to get out of the building is like using barbers as surgeons.

Clinacuity
While the Clinacuity video sounds like an ad for customer discovery, listen to what they said then look at their slides. This team really learned outside the building.


If you can’t see the Clinacuity video click here

Clinacuity’s technology automatically extracts data in real-time from clinical notes, (the narrative text documents in a Electronic Health Record,) and provides a summary in real time. Their diagrams of the healthcare customer segment in slides 15-18 were outstanding.

If you can’t see the Clinacuity presentation click here

GigaGen
The GigaGen team – making recombinant gamma globulin – holds the record for customer discovery – 163 customer interviews on multiple continents.

If you can’t see the GigaGen video click here

GigaGen’s learning on customer value proposition and who were the real stakeholders was a revelation. Their next-to-last slide on Activities, Resouces and Partners put the pieces together.

If you can’t see the GigaGen presentation click here

Affinity Therapeutics
Affinity came into class with a drug coated Arterial Venous Graft – graft narrowing is a big problem.

One of things we tell all the teams is that we’re not going to critique their clinical or biological hypotheses. Yet we know that by getting out of the building their interaction with customers might do just that. That’s what happened to Affinity.

If you can’t see the Affinity video click here

Affinity was a great example of a team that pivoted their MVP. They realized they might have a completely new product – Vascular wraps that can reduce graft infection.  See slides 17-23.

If you can’t see the Affinity presentation click here

Haro
Haro is making a drug for the treatment of high risk neuroblastoma, the most common extracranial cancer in infancy and childhood. On day 1 of the class I told the team, “Your presentation is different from the others – and not in a good way.”  That’s not how I described them in the final presentation.

If you can’t see the Haro video click here

After 120 interviews the Haro found that there are oncology organizations (NCI-funded clinical development partners) that will take Haro’s compound and develop it at their own expense and take it all the way into the clinic. This will save Haro tens of millions of dollars in development cost.  See slides 12 and 13.

If you can’t see the Haro presentation click here

Cardiax
Caridax is developing a neural stimulator to treat atrial fibrillation. Their video points out some of the common pitfalls in customer discovery. Great summary from Mark Bates, the Principal Investigator: “You don’t know what you don’t know. Scientific discovery is different than innovation. You as a prospective entrepreneur need this type of systematic vetting and analysis to know the difference.”

If you can’t see the Cardiax video click here

After 80 interviews they realized they were jumping to conclusions and imparting their bias into the process. Take a look at slides 8-11 and see their course correction.

If you can’t see the Cardiax presentation click here

The other 15 presentations were equally impressive. Each and every team stood up and delivered. And in ways that surprised themselves.

The Lean Startup approach (hypotheses testing outside the building,) was the first time clinicians and researchers understood that talking to customers didn’t require sales, marketing or an MBA – that they themselves could do a pretty good first pass. I-Corps at NIH just gave us more evidence that’s true.

The team videos and slides are on SlideShare here.

A Team Effort
This blog post may make it sound like there was no one else in the room but me and the teams. But nothing could be farther from the truth. The I-Corps@NIH teaching team was led by Edmund Pendleton. Allan May/Jonathan Fay taught medical devices, John Blaho/Bob Storey taught diagnostics and Karl Handelsman/Keith McGreggor taught therapeutics. Andre Marquis, Frank Rimalovski and Dean Chang provided additional expertise. Brandy Nagel was our tireless teaching assistant. Jerry Engel is the NSF I-Corps faculty director.

Special thanks to Paul Yock of Stanford Biodesign and Alexander Osterwalder for flying across the country/world to be part of the teaching team.

I created the I-Corps/Lean LaunchPad® syllabus/curriculum, and with guidance from Allan May, Karl Handelsman Abhas Gupta and Todd Morrill adapted it for Life Sciences/Health Care/Digital Health. The team from VentureWell provided the logistical support. The I-Corps program is run by the National Science Foundation (Babu Dasgupta, Don Millard and Anita LaSalle.) And of course none of this would be possible without the tremendous and enthusiastic support and encouragement of Michael Weingarten the director of the NIH/NCI SBIR program and his team.

Lessons Learned

  • The I-Corps/Lean LaunchPad curriculum works for therapeutics, diagnostics and device teams
  • Talking to 100 customers not only affected teams’ commercial hypotheses but also their biological and clinical assumptions
  • These teams saved years and millions of dollars for themselves, the NIH and the U.S. taxpayer
  • Evidence is now in-hand that the NIH has the most effective program for commercializing science
  • In the 21st century using proxies to get out of the building is like using barbers as surgeons

Why Translational Medicine Will Never be The Same

There have been 2 or 3 courses in my entire education that have changed
the way I think.  This is one of those
.
Hobart Harris Professor and Chief, Division of General Surgery at UCSF

For the past three years the National Science Foundation Innovation Corps has been teaching our nations best scientists how to build a Lean Startup.  Close to 400 teams in robotics, computer science, materials science, geoscience, etc. have learned how to use business models, get out of the building to test their hypotheses and minimum viable product.

However, business models in the Life Sciences are a bit more complicated than those in software, web/mobile or hardware. Startups in the Life Sciences (therapeutics, diagnostics, devices, digital health, etc.) also have to understand the complexities of reimbursement, regulation, intellectual property and clinical trials.

Last fall we prototyped an I-Corps class for life sciences at UCSF with 25 teams. Hobart Harris led one of the teams.

What Hobart learned and how he learned it is why we’re about to launch the I-Corps @ NIH on Oct 6th.

If you can’t see the video click here

Translational medicine will never be the same.

%d bloggers like this: