Houston data science company expands pandemic-inspired research tool

by the numbers

Mercury Data Science has taken a tool it originally developed for COVID-19 research and applied it into new areas of research and innovation. Photo via Getty Images

Last fall, Houston-based Mercury Data Science released an AI-driven app designed to help researchers unlock COVID-19-related information tucked into biomedical literature. The app simplified access to data about subjects like genes, proteins, drugs, and diseases.

Now, a year into the coronavirus pandemic, Mercury Data Science is applying this technology to areas like agricultural biotech, cancer therapeutics, and neuroscience. It's an innovation that arose from the pandemic but that promises broader, long-lasting benefits.

Angela Holmes, chief operating officer of Mercury Data Science, says the platform relies on an AI concept known as natural language processing (NLP) to mine scientific literature and deliver real-time results to researchers.

"We developed this NLP platform as a publicly available app to enable scientists to efficiently discover biological relationships contained in COVID research publications," Holmes says.

The platform:

  • Contains dictionaries with synonyms to identify things like genes and proteins that may go by various names in scientific literature.
  • Produces data visualizations of relationships among various biological functions.
  • Summarizes the most important data points on a given topic from an array of publications.
  • Depends on data architecture to automate how data is retrieved and processed.

In agricultural biotech, the platform enables researchers to sift through literature to dig up data about plant genetics, Holmes says. The lack of gene-naming standards in the world of plants complicates efforts to search data about plant genetics, she says.


Angela Holmes is the COO of MDS. Photo via mercuryds.com


The platform's ability to easily ferret out information about plant genetics "allows companies seeking gene-editing targets to make crops more nutritious and more sustainable as the climate changes to have a rapid way to de-risk their genomic analyses by quickly assessing what is already known versus what is unknown," Holmes says.

The platform allowed one of Mercury Data Science's agricultural biotech customers to comb through scientific literature about plant genetics to support targeted gene editing in a bid to improve crop yields.

In the field of cancer therapeutics and other areas of pharmaceuticals, the platform helps prioritize drug candidates, Holmes says. One of Mercury Data Science's customers used the platform to extract data from about 2 terabytes (or 2 trillion bytes) of information to evaluate drug candidates. The information included drug studies, clinical trials, and patents. Armed with that data, Mercury Data Science's cancer therapy client signed agreements with new pharmaceutical partners.

The platform also applies to the hunt for biomarkers in neuroscience, including disorders such as depression, anxiety, autism and multiple sclerosis. Data delivered through the platform helps bring new neurobehavioral therapeutics to market, Holmes says.

"An NLP platform to automatically process newly published literature for more insight on the search for digital biomarkers represents a great opportunity to accelerate research in this area," she says.

Mercury Data Science has experience in the field of digital biomarkers, including work for one customer to develop a voice and video platform to improve insights into patients with depression and anxiety in order to improve treatment of those conditions.

The new platform — initially developed as a tool to combat COVID-19 — falls under the startup's vast umbrella of artificial intelligence and data science. Founded in 2017, Mercury Data Science emerged because portfolio companies of the Houston-based Mercury Fund were seeking to get a better handle on AI and data science.

Last April, Angela Wilkins, founder, co-CEO and chief technology officer of Mercury Data Science, left the company to lead Rice University's Ken Kennedy Institute. Dan Watkins, co-founder and managing director of the Mercury Fund, remains at Mercury Data Science as CEO.

The Ken Kennedy Institute fosters collaborations in computing and data. Wilkins replaced Jan Odegard as executive director of the institute. Odegard now is senior director of industry and academic partnerships at The Ion, the Rice-led innovation hub.

Wilkins "is an academic at heart with considerable experience working with faculty and students, and an entrepreneur who has helped build a successful technology company," Lydia Kavraki, director of the Ken Kennedy Institute, said in a news release announcing Wilkins' new role. "Over her career, Angela has worked on data and computing problems in a number of disciplines, including engineering, life sciences, health care, agriculture, policy, technology, and energy."

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Houston investor on SaaS investing and cracking product-market fit

Houston innovators podcast episode 230

Aziz Gilani's career in tech dates back to when he'd ride his bike from Clear Lake High School to a local tech organization that was digitizing manuals from mission control. After years working on every side of the equation of software technology, he's in the driver's seat at a local venture capital firm deploying funding into innovative software businesses.

As managing director at Mercury, the firm he's been at since 2008, Gilani looks for promising startups within the software-as-a-service space — everything from cloud computing and data science and beyond.

"Once a year at Mercury, we sit down with our partners and talk about the next investment cycle and the focuses we have for what makes companies stand out," Gilani says on the Houston Innovators Podcast. "The current software investment cycle is very focused on companies that have truly achieved product-market fit and are showing large customer adoption."

An example of this type of company is Houston-based RepeatMD, which raised a $50 million series A round last November. Mercury's Fund V, which closed at an oversubscribed $160 million, contributed to RepeatMD's round.

"While looking at that investment, it really made me re-calibrate a lot of my thoughts in terms what product-market fit meant," Gilani says. "At RepeatMD, we had customers that were so eager for the service that they were literally buying into products while we were still making them."

Gilani says he's focused on finding more of these high-growth companies to add to Mercury's portfolio amidst what, admittedly, has been a tough time for venture capital. But 2024 has been looking better for those fundraising.

"We've some potential for improvement," Gilani says. "But overall, the environment is constrained, interest rates haven't budged, and we've seen some potential for IPO activity."

Gilani shares more insight into his investment thesis, what areas of tech he's been focused on recently, and how Houston has developed as an ecosystem on the podcast.

Houston startup scores $12M grant to support clinical evaluation of cancer-fighting drug

fresh funding

Allterum Therapeutics, a Houston biopharmaceutical company, has been awarded a $12 million product development grant from the Cancer Prevention and Research Institute of Texas (CPRIT).

The funds will support the clinical evaluation of a therapeutic antibody that targets acute lymphoblastic leukemia (ALL), one of the most common childhood cancers.

However, CEO and President Atul Varadhachary, who's also the managing director of Fannin Innovation, tells InnovationMap, “Our mission has grown much beyond ALL.”

The antibody, called 4A10, was invented by Scott Durum PhD and his team at the National Cancer Institute (NCI). Licensed exclusively by Allterum, a company launched by Fannin, 4A10 is a novel immunotherapy that utilizes a patient’s own immune system to locate and kill cancer cells.

Varadhachary explained that while about 80 percent of patients afflicted with ALL have the B-cell version, the other 20 percent suffer from T-cell ALL.

“Because the TLL population is so small, there are really no approved, effective drugs for it. The last drug that was approved was 18 or 19 years ago,” the CEO-scientist said. 4A10 addresses this unmet need, but also goes beyond it.

Because 4A10 targets CD127, also known as the interleukin-7 receptor, it could be useful in the treatment of myriad cancers. In fact, the receptor is expressed not just in hematological cancers like ALL, but also solid tumors like breast, lung, and colorectal cancers. There’s also “robust data,” according to Varadhachary for the antibody’s success against B-cell ALL, as well as many other cancers.

“Now what we're doing in parallel with doing the development for ALL is that we're continuing to do additional preclinical work in these other indications, and then at some point, we will raise a series A financing that will allow us to expand markets into things which are much more commercially attractive,” Varadhachary explains.

Why did they go for the less commercially viable application first? As Varadhachary put it, “The Fannin model is to allow us to go after areas which are major unmet medical needs, even if they are not necessarily as attractive on a commercial basis.”

But betting on a less common malady could have a bigger payoff than the Allterum team originally expected.

Before the new CPRIT grant, Allterum’s funding included a previous seed grant from CPRIT of $3 million. Other funds included an SBIR grant from NCI, as well as another NCI program called NExT, which deals specifically with experimental therapies.

“To get an antibody from research into clinical testing takes about $10 million,” Varadhachary says. “It's an expensive proposition.”

With this, and other nontraditional financing, the company was able to take what Varadhachary called “a huge unmet medical need but a really tiny commercial market” and potentially help combat a raft of other childhood cancers.

“That's our vision. It's not economically hugely attractive, but we think it's important,” says Varadhachary.

Atul Varadhachary is the managing director of Fannin Innovation. Photo via LinkedIn

Houston researcher scores prestigious NSF award for machine learning, power grid tech

grant funding

An associate professor at the University of Houston received the highly competitive National Science Foundation CAREER Award earlier this month for a proposal focused on integrating renewable resources to improve power grids.

The award grants more than $500,000 to Xingpeng Li, assistant professor of electrical and computer engineering and leader of the Renewable Power Grid Lab at UH, to continue his work on developing ways to use machine learning to ensure that power systems can continue to run efficiently when pulling their energy from wind and solar sources, according to a statement from UH. This work has applications in the events of large disturbances to the grid.

Li explains that currently, power grids run off of converted, stored kinetic energy during grid disturbances.

"For example, when the grid experiences sudden large generation losses or increased electrical loads, the stored kinetic energy immediately converted to electrical energy and addressed the temporary shortfall in generation,” Li said in a statement. “However, as the proportion of wind and solar power increases in the grid, we want to maximize their use since their marginal costs are zero and they provide clean energy. Since we reduce the use of those traditional generators, we also reduce the power system inertia (or stored kinetic energy) substantially.”

Li plans to use machine learning to create more streamlined models that can be implemented into day-ahead scheduling applications that grid operators currently use.

“With the proposed new modeling and computational approaches, we can better manage grids and ensure it can supply continuous quality power to all the consumers," he said.

In addition to supporting Li's research and model creations, the funds will also go toward Li and his team's creation of a free, open-source tool for students from kindergarten up through their graduate studies. They are also developing an “Applied Machine Learning in Power Systems” course. Li says the course will help meet workforce needs.

The CAREER Award recognizes early-career faculty members who “have the potential to serve as academic role models in research and education and to lead advances in the mission of their department or organization,” according to the NSF. It's given to about 500 researchers each year.

Earlier this year, Rice assistant professor Amanda Marciel was also

granted an NSF CAREER Award to continue her research in designing branch elastomers that return to their original shape after being stretched. The research has applications in stretchable electronics and biomimetic tissues.

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This article originally ran on EnergyCapital.

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