Biotherapeutics startup Hummingbird Bioscience brings its total Series B funding to $25 million

Hummingbird Bioscience, a startup focused on developing new treatments for cancer and other diseases, announced today it has added $6 million to its previously announced Series B, bringing the round’s total to $25 million.

The extension was led by SK Holdings, and included participation from returning investors including Heritas Capital and SEEDS Capital, the investment arm of Enterprise Singapore, a government agency that supports small- to medium-sized businesses.

This brings Hummingbird Bioscience’s total raised so far to $65 million. The company says it extended its Series B because the round was oversubscribed. The new funding will be used to take treatments Hummingbird Bioscience is developing to clinical trials more quickly, and expand research and development for its early stage pipeline.

Heritas Capital Management executive director and CEO Chik Wai Chiew said in a press statement that “Heritas Capital is pleased to continue our backing of the Hummingbird team since leading its Series A extended round. Even as the COVID-19 pandemic has resulted in a slow-down in investing, we are mindful that backing innovative biotech companies, especially players such as Hummingbird, to develop cures for addressing patients’ needs remains our priority.”

The company published data earlier this year on two antibodies, both oncology treatments, and expects to make regulatory submissions to start Phase 1 studies in the second half of this year.

Hummingbird Bioscience has offices in Singapore, Houston and South San Francisco and strategic collaborations with Cancer Research United Kingdom and Amgen. It was previously awarded a product development grant from the Cancer Prevention and Research Institute of Texas.

Health APIs usher in the patient revolution we have been waiting for

If you’ve ever been stuck using a health provider’s clunky online patient portal or had to make multiple calls to transfer medical records, you know how difficult it is to access your health data.

In an era when control over personal data is more important than ever before, the healthcare industry has notably lagged behind — but that’s about to change. This past month, the U.S. Department of Health and Human Services (HHS) published two final rules around patient data access and interoperability that will require providers and payers to create APIs that can be used by third-party applications to let patients access their health data.

This means you will soon have consumer apps that will plug into your clinic’s health records and make them viewable to you on your smartphone.

Critics of the new rulings have voiced privacy concerns over patient health data leaving internal electronic health record (EHR) systems and being surfaced to the front lines of smartphone apps. Vendors such as Epic and many health providers have publicly opposed the HHS rulings, while others, such as Cerner, have been supportive.

While that debate has been heated, the new HHS rulings represent a final decision that follows initial rules proposed a year ago. It’s a multi-year win for advocates of greater data access and control by patients.

The scope of what this could lead to — more control over your health records, and apps on top of it — is immense. Apple has been making progress with its Health Records app for some time now, and other technology companies, including Microsoft and Amazon, have undertaken healthcare initiatives with both new apps and cloud services.

It’s not just big tech that is getting in on the action: startups are emerging as well, such as Commure and Particle Health, which help developers work with patient health data. The unlocking of patient health data could be as influential as the unlocking of banking data by Plaid, which powered the growth of multiple fintech startups, including Robinhood, Venmo and Betterment.

What’s clear is that the HHS rulings are here to stay. In fact, many of the provisions require providers and payers to provide partial data access within the next 6-12 months. With this new market opening up, though, it’s time for more health entrepreneurs to take a deeper look at what patient data may offer in terms of clinical and consumer innovation.

The incredible complexity of today’s patient data systems

Apple awards $10 million to rapidly scale COVID-19 sample collection kit production

Apple has awarded $10 million from its Advanced Manufacturing Fund to COPAN Diagnostics, a company focused on producing sample collection kits for testing COVID-19 to hospitals in the U.S. The money comes from the fund that Apple established to support the development and growth of U.S.-based manufacturing, but is particularly notable because to date, the fund has been used to support companies tied more directly to its own supply chain.

The $10 million award also includes Apple employing its sourcing resources to find equipment and materials for COPAN Diagnostics, including new advanced equipment the iPhone-maker is helping design itself. Funds will also be used by COPAN to expand to a larger production facility in Southern California that can output more supply, growing its run rate from around several thousand currently, to over one million kits weekly by July, according to Apple. Apple notes that it will also result in the creation of around 50 new U.S. jobs.

COPAN is a pioneer in the diagnostics world, having previously invented flocked swabs in 2003, and it currently offers the world’s leading transport medium for virus-containing clinical specimens. The investment here from Apple is focused primarily on scale, taking the existing expertise of COPAN and making it into something that can operate somewhere closer to the amazing production volumes that Apple can accomplish, in order to help address the urgent need for more testing supplies to prevent that being the bottleneck to widespread COVID-19 diagnostics in the U.S.

Apple has redirected many of its resources, including monetary donations, protective equipment sourcing, and software development resources for both symptom-checking apps and the forthcoming partnership with Google on exposure notification software, to combatting the global coronavirus crisis. This deployment of the Advanced Manufacturing Fund is yet another example of how the company can address the pandemic in a variety of ways that are unique to its global position, expertise and relationships.

A full-time VC & part-time ER doctor shares his thoughts on COVID-19

An emergency room physician for the past 12 years, Dr. Robert Mittendorff joined Norwest Venture Partners eight years ago as a healthcare investor; the firm invests in a number of healthcare startups, including Talkspace, which raised a $50 million Series D last year, and TigerConnect.

As the COVID-19 pandemic spreads, Mittendorff is spending his weekdays with portfolio companies and weekends working with Kaiser Permanente in San Francisco. While he notes that his medical colleagues are “bearing the brunt” of the pandemic by working full time, we wanted to hear from someone who has a foot in both the investing and the healthcare world right now.

In this interview, he discusses what he’s learned from both roles, how it has influenced his healthcare investments, and offers his predictions regarding which companies will fare the best in the future.

This interview has been edited for length and clarity.

TechCrunch: How did you get to where you are today?

Dr. Robert Mittendorff: So, my journey to being a venture capitalist at Norwest and investing in healthcare companies as well as an emergency physician was really a parallel set of paths that overlapped and that cross every once in a while and now usually on a daily basis.

I started off life as a biomedical engineer really focused on wanting to be on the side of innovation and on the development of technologies to help human health. I knew early on that I wanted to be on the business side [of that], but it was important for me to understand and really be deeply in touch with what it was like to be a provider.

The journey started out going to engineering school, medical school, and then business school in the middle of medical school. I trained at Stanford, which really exposed me to county hospitals, which are probably going to be the more challenging situations as the weeks go on here, and then to Kaiser Permanente. And then, of course, Stanford, I was exposed to San Francisco General and then the Santa Clara Valley Hospital. I always practice part-time following up so it’s been 12 years as an attending, practicing part-time as an emergency physician.

In the venture space I saw an opportunity to really help select entrepreneurs and markets to grow them to a higher impact state.

Bill Gates details how his foundation shifted focus “almost entirely” to addressing COVID-19

Microsoft founder Bill Gates spoke to the Financial Times (via Fast Company) about how the work of the Bill & Melinda Gates Foundation has shifted “almost entirely” to working on addressing COVID-19, in the interest of making the post impact possible in the ongoing effort to contain and combat the global coronavirus pandemic. Gates told the FT that the spread of COVID-19 could have dire economic consequences which will result in more suffering globally than anyone could’ve anticipated, hence the need to address it with the full weight of the resources of one of the world’s most well-capitalized charitable organizations.

The Bill & Melinda Gates foundation has been funding vaccine trials, clinical studies and basic research related to drug and therapy development for COVID-19 since basically the disease debuted on the world scene. It means that the exiting mandate of the foundation, which includes seeking to eradicate polio and AIDS worldwide, will be temporarily slowed or paused while the organization focuses its resources on the pandemic, but Gates’ decision to focus the group’s significant resources here should only emphasize the seriousness of the situation.

The foundation’s temporary shift is actually, long-term, the best way it can serve its core goals, since the global impact of the coronavirus crisis is likely to have repercussions for every aspect of human life, including access to medical care, testing and therapies, not to mention food and basic necessities. Curbing the disease’s spread early could have the most significant impact in economies ill-prepared to deal with the fallout, and any impact there will eventually result in better ability to work on eradicating those other diseases in a reasonable timeline, instead of undermining local infrastructure and allowing them a longer foothold.

In a 2015 TED talk, Gates predicted the coming of a global outbreak and urged global health organizations and governments to come together to prepare for what to do in case of a large, widespread contagion. Gates was working mostly from the perspective of the 2014 Ebola outbreak, which exposed many of the existing gaps and flaws in the system, but his advice seems prescient in retrospect.

Unfortunately, Gates has been subject to a lot of spreading misinformation and bogus conspiracy theory nonsense owing to heightened paranoia and activity among groups that normally peddle in this kind of falsehood. Based on this interview, Gates seems to essentially expect that as something of a matter of course for high-profile individuals, however, and it doesn’t appear to be impacting the foundation’s ability to focus on potential fixes.

Microsoft built a ‘Plasma Bot’ to tell you if you can donate plasma to help fight COVID-19

Plasma taken from the blood of recovered COVID-19 patients stands a real change of being one of the more effective short-term measures feasible in the ongoing effort to control the global coronavirus pandemic. The FDA has issued a broad call for donation from eligible individuals, and now Microsoft has built an online screening tool on behalf of the CoVIg-19 Plasma Alliance (which is funded in part by the Bill and Melinda Gates Foundation).

The ‘CoVIg-19 Plasma Bot’ that Microsoft created for the foundation is just the latest COVID-19-related bot built by Microsoft using its technology, and its symptom self-checker for the CDC was one of the earliest large-scale efforts of its kind in the U.S. The Plasma Bot takes you through a series of simple questions to determine your eligibility, from the perspective of both your ability to meet the actual biological and health requirements, to your willingness and a ability to participate in the plasma collection process itself at a donation center.

Use of convalescent plasma, or the liquid part of blood taken from people who have had, and subsequently fully recovered from, COVID-19, is a key treatment avenue being explored by a number of different scientists and researchers. The investigations into its use take two main paths: First, direct use of the plasma injected into coronavirus patients and high-risk individuals in order to boost their own immune system for either prevention or faster recovery; and development of what are known as hyperimmune therapies, which concentrate the antibodies from donated plasma to develop treatments that are potentially easier and more effective to administer at scale.

The biggest bottleneck to overcome for the trials and therapeutics in development related to convalescent plasma is definitely the plasma itself, which can only come from patients who’ve had COVID-19 and are now fully recovered and healthy, and who also meet other standard, existing requirements for donating blood and plasma.

Unlike a lot of other treatments under investigation and development to address COVID-19, convalescent plasma has been shown to have been effective in treating other respiratory infections, and it has a long history of use for such applications.

Unlearn.AI nabs $12M to build “digital twins” to speed up and improve clinical trials

Twins have long played a role in the world of medical research, specifically in the area of clinical trials, where they can help measure the effectiveness of a therapy by applying a control to one of a genetically-similar pair. Today, a startup founded by a former principal scientist at Pfizer, which has developed a way of digitising this concept through the use of AI, is announcing some funding to further its efforts. Unlearn.AI, which has built a machine learning platform that builds “digital twin” profiles of patients that become the controls in clinical trials — is announcing that it has raised $12 million in a Series A round.

The round is being led by 8VC with previous investors DCVC, DCVC Bio and Mubadala Capital Ventures also participating.

The startup’s DiGenesis platform is first being applied to neurological diseases, specifically Alzheimer’s Disease and Multiple Sclerosis, where effective treatment options remain an elusive goal and it has been hard to build clinical trials around patients with already-impacted health.

Although Unlearn.AI is not working on anything close to medicines related to the COVID-19 pandemic, it’s a timely reminder of why improving clinical trials is important. We’re now in an urgent race to find vaccines and treatments for this new virus, and that highlights the need for more efficient approaches to trials, and that is an area where AI could prove to be a boost.

Unlearn does not disclose who its commercial partners are today, nor how far they’ve come with rolling out active, live trials. The funding will be used to inch closer to that point, it seems.

“This new financing marks an important milestone in our growth and will contribute to the significant progress we are making with regulators and with our commercial partners, who are already running studies with Digital Twins and demonstrating their value in generating robust evidence and increasing the potential for trial success,” said Charles K. Fisher, Ph.D., founder and CEO of Unlearn.AI, in a statement.

“Clinical trials are facing a number of persistent challenges that have only been exacerbated in recent weeks. With support from our forward-thinking investors and industry partners, we are excited to continue growing our exceptional team and advancing the science behind our first-of-its-kind Digital Twin approach.”

Fisher’s background is one that falls squarely at the nexus of technology and medical research. In addition to time spent as a principal scientist at pharma giant Pfizer, he has also worked at Leap Motion, and those roles followed years of studying and researching biophysics in academia.

Unlearn approaches the idea of building these so-called digital twins as a classic machine learning problem, using “clinical trial datasets from thousands of patients to build the disease-specific machine learning models used to create Digital Twins and their corresponding virtual medical records.”

These are more than simple medical profiles: they match people according to demographics, lab tests and biomarkers. The idea is that by building AI-based twins, there is less of a need to find similar actual pairs of people — actual twins, even — to run tests and controls.

Unlearn has been working on its platform since 2017, but the use of twins (and the pair’s very close genetic makeups in medical research) to track pathology and treatments goes back decades, and interestingly one of the novel coronavirus tracking apps that has seen some strong traction was borne out of a long-term twins study run out of Kings College Hospital in London working with Stanford and Massachusetts General Hospital in the US.

The growth of using AI to build “people” to run the effects of drugs also follows a much bigger theme of using computers and algorithms to test and create chemical combinations and therapies that would have in the past taken much longer, and cost much more, to run out manually. (Another example of where this is being applied is in the world of product development, where consumer goods companies are using AI platforms to formulate new soaps and other goods.)

“Unlearn’s pioneering use of Digital Twins will limit the number of patients that need to go on placebo while also reducing overall trial enrollment time,” said 8VC Principal, Dr Francisco Gimenez, in a statement. “As investors at the intersection of healthcare and technology, we’re passionate about companies that pair cutting-edge computational techniques and innovative business models to meaningfully improve patient care. 8VC is excited to partner with Unlearn to bring about the biggest change in the drug approval process since the RCT.” Gimenez is joining the board of the startup with this round.

Bradley Tusk on starting a company and seed investing in the coronavirus era

Bradley Tusk has carved a unique path in the VC investment landscape: A longtime political and communications operative, he has built a track record for Tusk Ventures by going after highly regulated industries, rather than shying away from them.

Whether it is ride-hailing, sports betting, cannabis or myriad other regulated sectors, Tusk takes the approach that laws are ultimately malleable, and if a service is popular, its users can mobilize to effect change.

Given his unique perspective, it was great to have him join us this week in an Extra Crunch Live call — our new initiative here at TechCrunch to bring tech-world thought leaders right to your screens.

In our conversation, Tusk talked about edtech, telemedicine, cannabis, mobile voting, biotech, pandemics and the future of regulated industries in this dastardly economic environment. We’ve transcribed a handful of his answers to our and our readers’ questions and have embedded the entire video below the fold.

We’ve edited his written answers for clarity and brevity.

University of Oxford coronavirus vaccine trial aims to have 500 people in testing by mid-May

One of the largest COVID-19 vaccine trials currently underway will have over 500 volunteers actively testing its solution by the middle of next month. Researchers at the University of Oxford have already secured that number of participants, including a representative sample of people between the ages of 18 to 55, for a large-scale randomized clinical early and mid-stage trial of its potential vaccine, which uses a harmless, modified virus to trigger an immune response that is also effective against the novel coronavirus.

The trial will divide a total of 510 participant sent five groups, with one group receiving a follow-up, booster shot of the vaccine after the original does. The technology behind the vaccine has already been used in developing about 10 different other treatments, but will require an approach that includes setting up different test groups in different countries to ensure representative results, since infection rates are varying greatly place to place with prevention measures in place, study lead Sarah Gilbert told Bloomberg.

The team behind the vaccine is also still seeking additional funding to help scale manufacturing, since it aims to begin producing it in volume following the six month period this human trial phase will span. The goal is to have mass production up and running by this fall, under the assumption that the trial proves the potential vaccine effective, with a final stage trial of 5,000 people and the potential to begin providing some doses for use by frontline healthcare workers by as early as September.

The Oxford trial is one of just a handful that have progressed to the human testing phase, but more are coming online all the time. Existing clinical human trials from Moderna and Inovio are underway in the U.S., and those have also expressed the potential for earlier access for emergency use prior to broad rollout following the initial clinical results.

Even if there is some availability by fall of some of these vaccine candidates (and that assumes they even prove effective), that doesn’t mean they’ll be broadly available: That will still require further testing, and scaling manufacturing, as well as working out distribution and administration – all processes that will add months of work. Already, however, the unprecedented nature of the COVID-19 pandemic has resulted in new efficiencies in the development process, and more could follow in these extraordinary times.

Mammoth Biosciences receives first peer-reviewed validation of CRISPR-based COVID-19 test

SF-based CRISPR diagnostics startup Mammoth Biosciences has published the first peer-reviewed study that shows validation of using its testing method to detect the presence of COVID-19 in patients. The study, published in Nature, shows performance on par with existing PCR-based molecular tests, the one ones currently authorized for use by the FDA to test for the novel coronavirus.

Mammoth’s DETECTR platform is designed to have advantages over traditional testing methods in a few different ways, including in its reconfigurability to address new viruses, since it uses CRISPR to target specific genetic sequences, and activate a “cleavage” that effectively acts as a signal for the diagnostic equipment to pick up. Basically, in the same way CRISPR allows scientists to target a specific string of DNA for removal or alteration, with scalpel-like precision, Mammoth’s diagnostic allows for programmable, targeted matching with a reference string, leading to confirmation that viral RNA is present in the patient.

The test that Mammoth is developing showed validated use in under two weeks, the researchers claim, since their platform is designed from the ground up for rapid reconfigurability to address new viral threats. The test can deliver results in under 45 minutes, and the results delivery is via what’s called a ‘lateral flow strip,’ which is essentially the same kind of read-out you see with at-home pregnancy tests, making them relatively easy to interpret. DETECTR also doesn’t require a lab setting to delver results, and instead can be conducted with portable heat blocks, combined with commonly available standard reagents.

In the study, which included samples from 36 patients with confirmed COVID-19 infections, and 42 patients who had other types of viral respiratory infections, the tests showed 95% positive diagnostic accuracy, and 100% negative efficacy. Samples used were taken from respiratory swabs.

This doesn’t mean this test can roll out to actual sites for use, but it’s a good validation of Mammoth’s model and test design, and could eventually lead to actual deployment of its test in a clinical setting, providing other, larger-scale studies back up the data.