Health care innovators joined Houston Methodist and Texas A&M University's ENMED program to discuss women in health care innovation and venture capital investment. Photo courtesy of Houston Methodist

Houston's health innovation community is making strides every day toward greater quality of care and technology adoption — but what challenges is the industry facing these days?

Through a partnership between Houston Methodist and Texas A&M University's ENMED program at Houston Tech Rodeo, health innovators weighed in on topics surrounding the industry, including biases and investment opportunities.

Missed the conversation? Here are seven key moments from the panels that took place at A&M's new ENMED building in the Texas Medical Center on Thursday, March 3.

“When I look at learning and understanding the priorities — how to take care of patients and also enable those who are doing that work, that’s part of understanding the culture and learning because in the 40 years that I’ve been in the industry, it’s never been the same. There are always things that continue to present challenges from unexpected places.”

​— Ayse McCracken, founder of Ignite Healthcare Network, says on the "Four Fierce Females" panel, referencing the rate of tech disruption and how new technologies, medicine, etc. can change the health care industry and practitioners need to find ways to keep up and stay ahead of the curve.

“Whenever you experience biases, what can you do? You can lean into the fact that we are in a position to help educate and make a change. And that’s going to look different for every one of us, but lean into that instead of feeling down by it.”

— Samantha Lewis, principal at Mercury Fund, says on the "Four Fierce Females" panel, explaining that women across industries should lean into being a change agent when met with bias in the workplace.

“The reason I feel so passionate is (I’m always thinking,) ‘What more can we be doing for our community? What’s working well and what’s not working well,' so I can take that back and make positive changes in our organization.”

— Michelle Stansbury, vice president of innovation and IT applications at Houston Methodist, says on the "Four Fierce Females" panel, explaining that when she's on the other side of the equation as a patient, she really considers her experience and how it could be better.

“Every time you raise money you’re telling a story. You have to figure out what adds value to that story. … I think health care is tricky too because people getting into it aren’t necessarily aware of how complex it is.”

— Dan Watkins, venture partner and co-founder at Mercury Fund, says on the "Where’s My Money At?" investor panel, adding how important it is to investors that founders have specific information — market potential, road map, etc. — when pitching to VCs.

“As a health care startup founder and CEO, you have to wear so many different hats — especially if you’re talking about diagnostics and medical devices. It starts in the science, moves to engineering, and then winds up being commercial. To expect someone to be an expert at all those fields is very difficult.”

— Tim Marx, venture partner at Baird Capital, says on the "Where’s My Money At?" investor panel, adding that, “That’s why we look for the CEOs who really understand where they are, where they’re going, and what they need.”

“One of the things we really appreciate when we engage with founders, it’s not about ‘here’s why my company is great.’ It’s more about understanding the questions your business needs to answer. … If you think about that, that’s what we want to fund. We want to invest in the vision, opportunity, and the people, but we want to fund the — the roadmap — that usually comes with being thoughtful about the questions you’re trying to answer.”

— John Reale, venture lead at TMC Venture Fund, says on the "Where’s My Money At?" investor panel, adding "That's where we get energized."

“The idea to attract talent that’s already built great companies across the US and the world to come here, hire here, and grow here — that’s starting to actually pay off. One of the things that’s big about Houston is it’s really gritty — it’s very ‘show me the data and prove it to me first.’ … We’re having those proven points.”

— Emily Reiser, associate director of innovation at the Texas Medical Center , says on the "Where’s My Money At?" investor panel about the work TMC is doing with its accelerator program.

It's all a numbers game, and Mercury Data Science is about setting up startups for success. Getty Images

Data-focused Houston company arms startups with the AI tools they need to grow

numbers game

While some say a picture is worth a thousand words, having the right data can be make or break. Houston-based Mercury Data Science is using data and artificial intelligence to paint some really specific pictures for its clients.

MDS was born out of a need for Houston-based Mercury Fund's portfolio companies that wanted a firmer handle on artificial intelligence and data science.

"Three years ago, a number of Mercury Fund portfolio companies and potential investments began to have increasingly important data science and AI components," says Dan Watkins, co-founder and managing director of Mercury Fund. "Mercury's partners wanted a deeper understanding of AI, to understand how the cutting edge meets industry use cases."

Mercury Fund's first move was to tap data scientist Angela Wilkins to lead some training, which then turned into even more workshops and advising. The companies ranged from early seed stage startups to companies that had raised over $100 million — and they wanted Wilkins' help, either with the basics of data science or execution of analytics.

"In fact, many of the more established companies were sitting on data assets with plans to build AI-enabled products but didn't have the time or people to really start that process," Wilkins says. "After helping a few companies, we realized the need was pretty deep, and bigger than the Mercury Fund portfolio."

Wilkins, who serves the company as CTO and co-CEO with Watkins, has seen her efforts grow MDS client base. InnovationMap sat down with Wilkins to see how far MDS has come — and where it's going.

InnovationMap: What sort of problems and data solutions are you providing clients?

Angela Wilkins: We love projects that have a direct impact on human health. In health, we build machine learning driven products to create new forms of digital diagnostics to help improve diagnosis in areas like cognitive functioning and depression. We have helped several therapeutics companies accelerate drug discovery and development by extracting insights from biological and imaging data. We have internal tools that use natural language processing to extract knowledge from millions of scientific publications and patents.

We have also worked quite a bit in consumer behavior and some of our physics-oriented data scientists are now working on noise reduction in geophysics technologies.

IM: What feedback do you get from clients?

AW: Company leaders in every sector are feeling the pressure to gain the advantages of AI or risk falling behind. There are many expert level teams available to Fortune 500 organizations. We are one of the very few teams that is entrepreneurial and agile enough to work with earlier stage, high growth organizations.

IM: How does MDS work with Mercury Fund? Has that relationship evolved over the years?

AW: We continue to work with the Mercury Fund portfolio companies but that is a smaller part of what we do. We are venture backed ourselves, and have now become a Mercury Fund portfolio company, with the same growth ambitions as all venture backed companies.

IM: Recently, MDS has seen some growth. How many employees have you added and are you still hiring?

AW: We are up to 20 employees, mostly data scientists, many with 5 to 8 years of experience working in AI, bioinformatics, and data science to provide insights and build products. We are always looking for great data scientists and data engineers to join our team. We also started a fellowship position for recent graduates, and so we can identify and train the next generation of data scientists

IM: What's been the biggest surprise for you as MDS has grown?

AW: We have been able to create this unique culture that thrives on diversity of thought and background. Half of our team is women. We are solving hard problems that benefit from the creativity you get from a wide variety of views.

IM: Where are MDS clients based?

AW: We have clients from San Francisco to Basel. We have learned how to build an integrated, high communication team with the client, so location is not critical.

That being said, we are active in and committed contributors to the Houston innovation ecosystem. Many of us are from a computational biology and bioinformatics background with deep roots in the Texas Medical Center institutions. Houston has amazing talent and we want to show the data scientists that they don't have to leave Houston to work on interesting problems and continue to build skills at the cutting edge while working for companies all over the world.

IM: What sort of trends are you seeing in venture capital? Are these trends happening in Houston?

We are seeing increasing investments in health AI. Fierce Healthcare reports that health AI topped all other sectors last year with $4B invested into AI startups. Andreesen Horowitz has announced their third and largest biotech and health care fund with $750 million to invest: "Machine learning and artificial intelligence [will] have an outsize impact on how we discover drugs and diagnose disease."

We see similar trends in other areas from industrial software to financial services. The upshot is that the adoption of AI creates significant opportunities for startups and significant challenges for larger companies that are not entrepreneurial and able to build their own data science skill set.

As far as Houston goes, the same trends are there but we tend to lag the major technology hubs in adoption. Efforts like TMC Innovation, Station, Rice University/The Ion and Houston Exponential are having a big impact on both the number and pace of startups and, increasingly, those have AI as a key part of their technology stack.

IM: We've talked about how MDS flies under the radar — why do you think that is? Do you think that'll change as you grow?

AW: Our initial focus was on the work for our clients and on building our team. We are ready to be noticed. Thank you for helping us tell the story with this article.

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CultureMap Emails are Awesome

Houston doctor wins NIH grant to test virtual reality for ICU delirium

Virtual healing

Think of it like a reverse version of The Matrix. A person wakes up in a hospital bed and gets plugged into a virtual reality game world in order to heal.

While it may sound far-fetched, Dr. Hina Faisal, a Houston Methodist critical care specialist in the Department of Surgery, was recently awarded a $242,000 grant from the National Institute of Health to test the effects of VR games on patients coming out of major surgery in the intensive care unit (ICU).

The five-year study will focus on older patients using mental stimulation techniques to reduce incidences of delirium. The award comes courtesy of the National Institute on Aging K76 Paul B. Beeson Emerging Leaders Career Development Award in Aging.

“As the population of older adults continues to grow, the need for effective, scalable interventions to prevent postoperative complications like delirium is more important than ever,” Faisal said in a news release.

ICU delirium is a serious condition that can lead to major complications and even death. Roughly 87 percent of patients who undergo major surgery involving intubation will experience some form of delirium coming out of anesthesia. Causes can range from infection to drug reactions. While many cases are mild, prolonged ICU delirium may prevent a patient from following medical advice or even cause them to hurt themselves.

Using VR games to treat delirium is a rapidly emerging and exciting branch of medicine. Studies show that VR games can help promote mental activity, memory and cognitive function. However, the full benefits are currently unknown as studies have been hampered by small patient populations.

Faisal believes that half of all ICU delirium cases are preventable through VR treatment. Currently, a general lack of knowledge and resources has been holding back the advancement of the treatment.

Hopefully, the work of Faisal in one of the busiest medical cities in the world can alleviate that problem as she spends the next half-decade plugging patients into games to aid in their healing.

Houston scientists develop breakthrough AI-driven process to design, decode genetic circuits

biotech breakthrough

Researchers at Rice University have developed an innovative process that uses artificial intelligence to better understand complex genetic circuits.

A study, published in the journal Nature, shows how the new technique, known as “Combining Long- and Short-range Sequencing to Investigate Genetic Complexity,” or CLASSIC, can generate and test millions of DNA designs at the same time, which, according to Rice.

The work was led by Rice’s Caleb Bashor, deputy director for the Rice Synthetic Biology Institute and member of the Ken Kennedy Institute. Bashor has been working with Kshitij Rai and Ronan O’Connell, co-first authors on the study, on the CLASSIC for over four years, according to a news release.

“Our work is the first demonstration that you can use AI for designing these circuits,” Bashor said in the release.

Genetic circuits program cells to perform specific functions. Finding the circuit that matches a desired function or performance "can be like looking for a needle in a haystack," Bashor explained. This work looked to find a solution to this long-standing challenge in synthetic biology.

First, the team developed a library of proof-of-concept genetic circuits. It then pooled the circuits and inserted them into human cells. Next, they used long-read and short-read DNA sequencing to create "a master map" that linked each circuit to how it performed.

The data was then used to train AI and machine learning models to analyze circuits and make accurate predictions for how untested circuits might perform.

“We end up with measurements for a lot of the possible designs but not all of them, and that is where building the (machine learning) model comes in,” O’Connell explained in the release. “We use the data to train a model that can understand this landscape and predict things we were not able to generate data on.”

Ultimately, the researchers believe the circuit characterization and AI-driven understanding can speed up synthetic biology, lead to faster development of biotechnology and potentially support more cell-based therapy breakthroughs by shedding new light on how gene circuits behave, according to Rice.

“We think AI/ML-driven design is the future of synthetic biology,” Bashor added in the release. “As we collect more data using CLASSIC, we can train more complex models to make predictions for how to design even more sophisticated and useful cellular biotechnology.”

The team at Rice also worked with Pankaj Mehta’s group in the department of physics at Boston University and Todd Treangen’s group in Rice’s computer science department. Research was supported by the National Institutes of Health, Office of Naval Research, the Robert J. Kleberg Jr. and Helen C. Kleberg Foundation, the American Heart Association, National Library of Medicine, the National Science Foundation, Rice’s Ken Kennedy Institute and the Rice Institute of Synthetic Biology.

James Collins, a biomedical engineer at MIT who helped establish synthetic biology as a field, added that CLASSIC is a new, defining milestone.

“Twenty-five years ago, those early circuits showed that we could program living cells, but they were built one at a time, each requiring months of tuning,” said Collins, who was one of the inventors of the toggle switch. “Bashor and colleagues have now delivered a transformative leap: CLASSIC brings high-throughput engineering to gene circuit design, allowing exploration of combinatorial spaces that were previously out of reach. Their platform doesn’t just accelerate the design-build-test-learn cycle; it redefines its scale, marking a new era of data-driven synthetic biology.”