5 digital health startups you need to watch in 2019

(Image from Unsplash)

Funding for digital health companies continues to rise, with 2018 the biggest year so far this decade, according to healthcare investment firm StartUp Health. Investors took a greater interest in machine learning, blockchain and artificial intelligence (AI).

Digital health funding was 14 times greater than it was eight years ago, when New York-based StartUp Health began tracking these investments. From 2017 to 2018, the average deal size grew by $6 million. Machine learning companies cut 66 deals to raise $940 million, an 80% increase in funding compared to 2017. Patient empowerment received the most funding of any function in 2018, $3 billion across 193 deals.

Here are five of the up-and-coming digital health companies to watch in 2019:

Get the full story on our sister site, Medical Design & Outsourcing.

FDA wants public input on AI-enabled device regulation

(Image from FDA)

The FDA today floated some ideas on how it might regulate medical devices armed with artificial intelligence — also known as software-as-a-medical-device (SaMD) — whose algorithms can change based on machine learning (ML) and possibly affect people in ways for which they were not approved or cleared. It is also asking for the public’s feedback.

To date, the agency has cleared or approved AI/ML-assisted devices whose algorithms have typically been locked before hitting the market. The FDA’s 20-page discussion paper includes a proposed regulatory framework for devices that have algorithms that can learn and change after the devices have been sold.

Get the full story on our sister site, Medical Design & Outsourcing.

Senseonics inks CGM data deal with Glooko

SenseonicsSenseonics (NYSE:SENS) said today that data from its Eversense continuous glucose monitoring system can be integrated into Glooko‘s diabetes data management tech.

Thanks to the new partnership, Eversense users will be able to view historical glucose trends in Glooko’s mobile and web apps as well as real-time data from the Eversense mobile app, according to Senseonics.

Get the full story at our sister site, Drug Delivery Business News.

The post Senseonics inks CGM data deal with Glooko appeared first on MassDevice.

How NeuroMetrix seeks to better relieve pain with AI

NeuroMetrix Quell 2.0 AI artificial intelligence pain relief

NeuroMetrix’s Quell 2.0 [Image courtesy of NeuroMetrix]

NeuroMetrix plans to add artificial intelligence to the latest iteration of its Quell transcutaneous electrical nerve stimulation (TENS) device.

AI will allow Quell 2.0 to tailor treatment to each individual user, according to the Waltham, Mass.–based based company.

Launched in September 2018 Quell 2.0 is 50% smaller and 20% more powerful than the original Quell, which debuted in 2015. Quell is worn on the leg regardless of the site of pain and is designed to send neural pulses to the brain that trigger a natural pain relief response in the central nervous system. Patients control the device and track their pain using a smartphone app. Quell 2.0 is available over-the-counter for about $300.

So how could AI help patients who use the device? NeuroMetrix chief commercial officer Frank McGillin recently discussed the decision to use AI and the future of Quell with our sister site Medical Design & Outsourcing.

The post How NeuroMetrix seeks to better relieve pain with AI appeared first on MassDevice.

Here’s how precision medicine could change medical imaging

Siemens Healthineers recently won FDA approval for the Cios Spin, a mobile C-arm that delivers precise 3D images for intraoperative quality assurance. (Photo from Siemens Healthineers)

The business of precision medical imaging is poised to take off in the next few years, according to a new analysis by Frost & Sullivan.

The market research firm’s report, “Growth Opportunities in Precision Medical Imaging, Forecast to 2022,” said new technologies and processes in diagnostic and therapeutic imaging could spur the market to grow from $120 million in 2017 to more than $8 billion by 2027. Technology advances such as clinical decision support software, sensors, 3D printing, and precision analytics capabilities like deep learning and artificial intelligence (AI) will be applied to medical imaging.

A few firms have pulled ahead, and the rest won’t be far behind, the firm predicted.

Get the full story on our sister site, Medical Design & Outsourcing.

The post Here’s how precision medicine could change medical imaging appeared first on MassDevice.

UnitedHealth Group’s Optum sues VP who left for Amazon venture

judge gavel lawsuit medtech medical device Optum Amazon

[Image from Unsplash]

UnitedHealth Group’s Optum IT-based health services unit has sued former VP David Smith, claiming that he misappropriated trade secrets before leaving to join a new healthcare venture supported by Amazon.

Smith’s lawyers are seeking to move the case to arbitration.

The complaint, filed Jan. 16 in U.S. District Court in Massachusetts, accuses Smith of printing out a confidential Optum in-depth healthcare market analysis just a minute before printing out his resume. It was the same day that he spoke with the healthcare innovation venture nicknamed ABC, now led by Dr. Atul Gawande and supported by Amazon, Berkshire Hathaway and J.P. Morgan Chase.

Smith, who went from being VP of corporate strategy to being VP of product during 18 months at Optum, also sought confidential information from colleagues that was not related to his job duties, according to the lawsuit complaint.

Smith resigned Optum last month to join ABC as director of product strategy and research. Just a day before he told Optum that he planned to resign, he printed out a highly confidential document including product portfolio performance, new product development and a product job family and assessment plan, the complaint said.

“If Smith is permitted to work for ABC, he will inevitably use Optum’s trade secrets to expedite ABC’s development of competitive capabilities and products. Even if those products take more than a year to commercialize, Smith’s assistance in the process of beginning to develop them now is a direct competitive harm to Optum,” Optum’s lawyers said in the complaint.

Optum is seeking an injunction to prevent Smith from working for ABC or divulging trade secrets, as well as damages.

Smith’s lawyers in their own filing argue that the dispute falls under Optum’s employment arbitration policy, so the case should be handled through arbitration, not a lawsuit trial.

Said Smith’s lawyers: “There is no reason for this case to be in court.”

The post UnitedHealth Group’s Optum sues VP who left for Amazon venture appeared first on MassDevice.

How AI can detect cervical cancer

Cervical cancer cells (Image from National Cancer InstituteWinship Cancer Institute of Emory University)

Researchers have developed a computer algorithm that they say can analyze digital images of a woman’s cervix and accurately identify precancerous changes that require medical attention. This artificial intelligence approach, called automated visual evaluation, has the potential to revolutionize cervical cancer screening, particularly in low-resource settings.

Led by investigators from the National Institutes of Health and humanitarian tech investment fund Global Good, the researchers used comprehensive datasets to “train” a machine-learning algorithm to recognize patterns in complex visual inputs, such as medical images. The findings were confirmed independently by experts at the National Library of Medicine. The results appeared in the Journal of the National Cancer Institute (NCI).

Get the full story on our sister site, Medical Design & Outsourcing.

The post How AI can detect cervical cancer appeared first on MassDevice.

Novo Nordisk partners with Flex for digital diabetes management tools

Novo Nordisk - updated logoFlex (NSDQ:FLEX) today announced a partnership with Novo Nordisk (NYSE:NVO) to develop digital diabetes management tools using Flex’s BrightInsight IoT platform.

Novo Nordisk plans to use Flex’s BrightInsight system to build and manage connected medical devices and the corresponding data. The company’s IoT platform is designed to enable organizations to develop digital health devices while remaining compliant with global privacy and security regulations.

Get the full story at our sister site, Drug Delivery Business News.

The post Novo Nordisk partners with Flex for digital diabetes management tools appeared first on MassDevice.

Nvidia, Scripps look to tackle atrial fibrillation with deep learning

Nvidia, Scripps logoNvidia (NSDQ:NVDA) and Scripps Research Translational Institute announced today that the groups are teaming up to develop deep learning tools to process genomic and medical sensor data.

The tech giant and the non-profit research org hope to leverage artificial intelligence to prevent disease and accelerate biomedical research efforts.

The use of AI in healthcare is currently limited to medical imaging, Scripps’ founder & director Dr. Eric Topol noted in a call with reporters last week. Topol said he expects that deep learning techniques could be used to analyze entire genomic sequences and data from continuous medical sensors, generating insights into disease prevention.

The Nvidia-Scripps team will first focus on creating tools to help predict atrial fibrillation, with an eye on exploring other diseases and datasets down the road – including blood pressure monitoring and blood glucose.

“AI has tremendous promise to transform the future of medicine,” Topol said in prepared remarks. “With Nvidia, we aim to establish a center of excellence for artificial intelligence in genomics and digital sensors, with the ultimate goal of developing best practices, tools and AI infrastructure for broader adoption and application by the biomedical research community.”

“AI is already transforming healthcare by using electronic health records and medical imaging to better diagnose and treat disease,” Kimberly Powell, VP of healthcare at Nvidia, added. “Our collaboration with Scripps expands these opportunities by tapping into the rapid accessibility of genomic and digital wearable data, and furthers the quest to better predict and prevent disease.”

The post Nvidia, Scripps look to tackle atrial fibrillation with deep learning appeared first on MassDevice.

6 reasons you shouldn’t bet on blockchain disrupting healthcare

[Image from Daniel von Appen on Unsplash]

Blockchain is the big buzzword these days, bruited as a disruptive force for industries covering the spectrum. But there seems to be little understanding of what exactly “blockchain” means, let alone how it could affect so many different markets so profoundly.

Simply put, a blockchain is a decentralized database with tight rules about how data is entered, maintained and accessed. Instead of being stored at a single location, the data in a blockchain are stored in a series of discrete nodes. Think of it as a connected series of ledgers, each with identical data. Because each transaction must be exactly the same across all the ledgers, blockchains are “very difficult to work with, expensive to maintain, hard to upgrade and a pain to scale,” writes developer Jimmy Song at the Medium website.

“The main thing distinguishing a blockchain from a normal database is that there are specific rules about how to put data into the database. That is, it cannot conflict with some other data that’s already in the database (consistent), it’s append-only (immutable), and the data itself is locked to an owner (ownable), it’s replicable and available. Finally, everyone agrees on what the state of the things in the database are (canonical) without a central party (decentralized),” according to Song. “It is this last point that really is the holy grail of blockchain. Decentralization is very attractive because it implies there is no single point of failure. That is, no single authority will be able to take away your asset or change ‘history’ to suit their needs. This immutable audit trail where you don’t have to trust anyone is the benefit that everyone that’s playing with this technology is looking for. This benefit, however, comes at a great cost.”

Here are the six factors Song cites as reasons why blockchain is great for one specific task but terrible for most of the others its hyped for, including healthcare:

  1. Development is stricter and slower. Because the blockchain’s data must be consistent across all of its nodes, a tiny error in one place can corrupt the entire database. Perhaps worse, that bug could render some data different in one node than in the other nodes. “There is no ‘move fast and break things’ in a blockchain,” Song explains. “If you break things, you lose consistency and the blockchain becomes corrupted and worthless.” And its incredibly hard to fix a bug, he adds, because all users must agree to any changes. “The blockchain has to be a public resource that’s not under the control of a single entity,” he says.
  2. Incentive structures are difficult to design. Ensuring that bad-actor users can’t abuse or corrupt the blockchain means creating incentives that span the gap between a low barrier to data entry – resulting in frivolous, useless data – and a too-high barrier resulting in a blockchain with almost no data. “What gives the data finality? How can you ensure that the rewards are aligned with the network goals? Why do nodes keep or update the data and what makes them choose one piece of data over another when they are in conflict? These are all incentive questions that need good answers and they need to be aligned not just at the beginning but at all points in the future as technology and companies change, otherwise the blockchain is not useful,” Song writes.
  3. Maintenance is very costly. That’s because, compared with a centralized model in which tasks are performed only once, with blockchain those functions must run thousands of times.
  4. Users are sovereign. Bad actors can’t be booted from your blockchain for entering frivolous data or gaming the system for profit, because there’s no governing entity with the authority to do it. “The blockchain has to be impartial and enforce the rules defined by the software. If the rules are insufficient to deter bad behavior, you’re out of luck,” according to Song.
  5. A forced upgrade is not an option. “The point of a blockchain is that it’s not under the control of a single entity and this is violated with a forced upgrade,” he explains. That means all upgrades must be backwards-compatible, making the addition of new features and testing new versions extremely challenging.
  6. Scaling is really hard. “The same data has to live in hundreds or thousands of places [rather] than in a single place. The overhead of transmission, verification and storage is enormous as every single copy of the database must pay them instead of those costs being paid just once in a traditional, centralized database.

Most of the industries looking to blockchain for salvation really need upgrades to their IT infrastructure, especially the “notoriously terrible” software used by the healthcare industry, Song says.

“What’s clear is that a lot of companies looking to use the blockchain are not really wanting a blockchain at all, but rather IT upgrades to their particular industry,” he says.

The post 6 reasons you shouldn’t bet on blockchain disrupting healthcare appeared first on MassDevice.