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May 26, 2019
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Healthcare by 2028 will be doctor-directed, patient-owned and powered by visual technologies

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Visual assessment is critical to healthcare – whether that is a doctor peering down your throat as you say “ahhh” or an MRI of your brain. Since the X-ray was invented in 1895, medical imaging has evolved into many modalities that empower clinicians to see into and assess the human body.  Recent advances in visual sensors, computer vision and compute power are currently powering a new wave of innovation in legacy visual technologies(like the X-Ray and MRI) and sparking entirely new realms of medical practice, such as genomics.

Over the next 10 years, healthcare workflows will become mostly digitized, with wide swaths of personal data captured and computer vision, along with artificial intelligence, automating the analysis of that data for precision care. Much of the digitized data across healthcare will be visual and the technologies that capture and analyze it are visual technologies.

These visual technologies traverse a patient’s journey from diagnosis, to treatment, to continuing care and prevention.They capture, analyze, process, filter and manage any visual data from images, videos, thermal, x-ray’s, ultrasound, MRI, CT scans, 3D, and more. Computer vision and artificial intelligence are core to the journey.

Three powerful trends — including miniaturization of diagnostic imaging devices, next generation imaging to for the earliest stages of disease detection and virtual medicine — are shaping the ways in which visual technologies are poised to improve healthcare over the next decade.

Miniaturization of Hardware Along with Computer Vision and AI will allow Diagnostic Imaging to be Mobile

Medical imaging is dominated by large incumbents that are slow to innovate. Most imaging devices (e.g. MRI machines) have not changed substantially since the 1980s and still have major limitations:

  • Complex workflows: large, expensive machines that require expert operators and have limited compatibility in hospitals.

  • Strict patient requirements: such as lying still or holding their breath (a problem for cases such as pediatrics or elderly patients).

  • Expensive solutions: limited to large hospitals and imaging facilities.

But thanks to innovations in visual sensors and AI algorithms, “modern medical imaging is in the midst of a paradigm shift, from large carefully-calibrated machines to flexible, self-correcting, multi-sensor devices” says Daniel K. Sodickson, MD, PhD, NYU School of Medicine, Department of Radiology.

MRI glove-shaped detector proved capable of capturing images of moving fingers.  ©NYU Langone Health

Visual data capture will be done with smaller, easier to use devices, allowing imaging to move out of the radiology department and into the operating room, the pharmacy and your living room.

Smaller sensors and computer vision-enabled image capture will lead to imaging devices that are being redesigned a fraction of the size with:

  • Simpler imaging process: with quicker workflows and lower costs.

  • Lower expertise requirements: less complexity will move imaging from the radiology department to anywhere the patient is.

  • Live imaging via ingestible cameras: innovation includes powering ingestibles via stomach acid, using bacteria for chemical detection and will be feasible in a wider range of cases.

“The use of synthetic neural network-based implementations of human perceptual learning enables an entire class of low-cost imaging hardware and can accelerate and improve existing technologies,” says Matthew Rosen, PhD, MGH/Martinos Center at Harvard Medical School.

©Matthew Rosen and his colleagues at the Martinos Center for Biomedical Imaging in Boston want liberate the MRI.

Next Generation Sequencing, Phenotyping and Molecular Imaging Will Diagnose Disease Before Symptoms are Presented

Genomics, the sequencing of DNA, has grown at a 200% CAGR since 2015, propelled by Next Generation Sequencing (NGS) which uses optical signals to read DNA, like our LDV portfolio company Geniachip which was acquired by Roche. These techniques are helping genomics become a mainstream tool for practitioners, and will hopefully make carrier screening part of routine patient care by 2028.

Identifying the genetic makeup of a disease via liquid biopsies, where blood, urine or saliva is tested for tumor DNA or RNA, are poised to take a prime role in early cancer screening. The company GRAIL, for instance, raised $1B for a cancer blood test that uses NGS and deep learning to detect circulating tumor DNA before a lesion is identified.

Phenomics, the analysis of observable traits (phenotypes) that result from interactions between genes and their environment, will also contribute to earlier disease detection. Phenotypes are expressed physiologically and most will require imaging to be detected and analyzed.

Next Generation Phenotyping (NGP) uses computer vision and deep learning to analyze physiological data, understand particular phenotype patterns, then it correlates those patterns to genes. For example, FDNA’s Face2Gene technology can identify 300-400 disorders with 90%+ accuracy using images of a patient’s face. Additional data (images or videos of hands, feet, ears, eyes) can allow NGP to detect a wide range of disorders, earlier than ever before.

Molecular imaging uses DNA nanotech probes to quantitatively visualize chemicals inside of cells, thus measuring the chemical signature of diseases. This approach may enable early detection of neurodegenerative diseases such as Alzheimer’s, Parkinson’s and dementia.

Telemedicine to Overtake Brick-and-Mortar Doctors Visits

By 2028 it will be more common to visit the doctor via video over your phone or computer than it will be to go to an office.

Telemedicine will make medical practitioners more accessible and easier to communicate with. It will create an all digitized health record of visits for a patient’s profile and it will reduce the costs of logistics and regional gaps in specific medical expertise. An example being the telemedicine services rendered for 1.9M injured in the war in Syria.4

The integration of telemedicine into ambulances has led to stroke patients being treated twice as fast.  Doctors will increasingly call in their colleagues and specialists in real time.

Screening technologies will be integrated into telemedicine so it won’t just be about video calling a doctor. Pre-screening your vitals via remote cameras will deliver extensive efficiencies and hopefully health benefits.

“The biggest opportunity in visual technology in telemedicine is in solving specific use cases. Whether it be detecting your pulse, blood pressure or eye problems, visual technology will be key to collecting data,” says Jeff Nadler, Teldoc health.

Remote patient monitoring (RPM) will be a major factor in the growth of telemedicine and the overall personalization of care. RPM devices, like we are seeing with the Apple Watch, will be a primary source of real-time patient data used to make medical decisions that take into account everyday health and lifestyle factors. This personal data will be collected and owned by patients themselves and provided to doctors.

Visual Tech Will Power the Transformation of Healthcare Over the Next Decade

Visual technologies have deep implications for the future of personalized healthcare and will hopefully improve the health of people worldwide. It represents unique investment opportunities and we at LDV Capital have reviewed over 100 research papers from BCC Research, CBInsights, Frost & Sullivan, McKinsey, Wired, IEEE Spectrum and many more to compile our 2018 LDV Capital Insights report. This report highlights the sectors that power to improve healthcare based on the transformative nature of the technology in the sector, projected growth and business opportunity.

There are tremendous investment opportunities in visual technologies across diagnosis, treatment and continuing care & prevention that will help make people healthier across the globe.

US startups off to a strong M&A run in 2018

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With Microsoft’s $7.5 billion acquisition of GitHub this week, we can now decisively declare a trend: 2018 is shaping up as a darn good year for U.S. venture-backed M&A.

So far this year, acquirers have spent just over $20 billion in disclosed-price purchases of U.S. VC-funded companies, according to Crunchbase data. That’s about 80 percent of the 2017 full-year total, which is pretty impressive, considering we’re barely five months into 2018.

If one included unreported purchase prices, the totals would be quite a bit higher. Fewer than 20 percent of acquisitions in our data set came with reported prices.1 Undisclosed prices are mostly for smaller deals, but not always. We put together a list of a dozen undisclosed price M&A transactions this year involving companies snapped up by large-cap acquirers after raising more than $20 million in venture funding.

The big deals

The deals that everyone talks about, however, are the ones with the big and disclosed price tags. And we’ve seen quite a few of those lately.

As we approach the half-year mark, nothing comes close to topping the GitHub deal, which ranks as one of the biggest acquisitions of a private, U.S. venture-backed company ever. The last deal to top it was Facebook’s $19 billion purchase of WhatsApp in 2014, according to Crunchbase.

Of course, GitHub is a unique story with an astounding growth trajectory. Its platform for code development, most popular among programmers, has drawn 28 million users. For context, that’s more than the entire population of Australia.

Still, let’s not forget about the other big deals announced in 2018. We list the top six below:

Flatiron Health, a provider of software used by cancer care providers and researchers, ranks as the second-biggest VC-backed acquisition of 2018. Its purchaser, Roche, was an existing stakeholder who apparently liked what it saw enough to buy up all remaining shares.

Next up is job and employer review site Glassdoor, a company familiar to many of those who’ve looked for a new post or handled hiring in the past decade. The 11-year-old company found a fan in Tokyo-based Recruit Holdings, a provider of recruitment and human resources services that also owns leading job site Indeed.com.

Meanwhile, Impact Biomedicines, a cancer therapy developer that sold to Celgene for $1.1 billion, could end up delivering an even larger exit. The acquisition deal includes potential milestone payments approaching nearly $6 billion.

Deal counts look flat

Not all metrics are trending up, however. While acquirers are doing bigger deals, they don’t appear to be buying a larger number of startups.

Crunchbase shows 216 startups in our data set that sold this year. That’s roughly on par with the pace of dealmaking in the year-ago period, which had 222 M&A exits using similar parameters. (For all of 2017, there were 508 startup acquisitions that met our parameters.2)

Below, we look at M&A counts for the past five calendar years:

Looking at prior years for comparison, the takeaway seems to be that M&A deal counts for 2018 look just fine, but we’re not seeing a big spike.

What’s changed?

The more notable shift from 2017 seems to be buyers’ bigger appetite for unicorn-scale deals. Last year, we saw just one acquisition of a software company for more than a billion dollars — Cisco’s $3.7 billion purchase of AppDynamics — and that was only after the performance management software provider filed to go public. The only other billion-plus deal was PetSmart’s $3.4 billion acquisition of pet food delivery service Chewy, which previously raised early venture funding and later private equity backing.

There are plenty of reasons why acquirers could be spending more freely this year. Some that come to mind: Stock indexes are chugging along, and U.S. legislators have slashed corporate tax rates. U.S. companies with large cash hordes held overseas, like Apple and Microsoft, also received new financial incentives to repatriate that money.

That’s not to say companies are doing acquisitions for these reasons. There’s no obligation to spend repatriated cash in any particular way. Many prefer share buybacks or sitting on piles of money. Nonetheless, the combination of these two things — more money and less uncertainty around tax reform — are certainly not a bad thing for M&A.

High public valuations, particularly for tech, also help. Microsoft shares, for instance, have risen by more than 44 percent in the past year. That means that it took about a third fewer shares to buy GitHub this month than it would have a year ago. (Of course, GitHub’s valuation probably rose as well, but we’ll ignore that for now.)

Paying retail

Overall, this is not looking like an M&A market for bargain hunters.

Large-cap acquirers seem willing to pay retail price for startups they like, given the competitive environment. After all, the IPO window is wide open. Plus, fast-growing unicorns have the option of staying private and raising money from SoftBank or a panoply of other highly capitalized investors.

Meanwhile, acquirers themselves are competing for desirable startups. Microsoft’s winning bid for GitHub reportedly followed overtures by Google, Atlassian and a host of other would-be buyers.

But even in the most buoyant climate, one rule of acquiring remains true: It’s hard to turn down $7.5 billion.

  1. The data set included companies that have raised $1 million or more in venture or seed funding, with their most recent round closing within the past five years.
  2. For the prior year comparisons, including the chart, the data set consisted of companies acquired in a specified year that raised $1 million or more in venture or seed funding, with their most recent round closing no more than five years before the middle of that year.

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