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 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.”