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

biotech breakthrough

Rice University scientists Kshitij Rai, Caleb Bashor and Ronan O’Connell have developed CLASSIC, a new AI-driven process that can generate and test millions of DNA designs at the same. Photo by Jeff Fitlow. Courtesy Rice University.

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.”

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New findings from a team of Rice University researchers could enhance MRI clarity. Photo via Unsplash.

Rice University researchers unveil new model that could sharpen MRI scans

MRI innovation

Researchers at Rice University, in collaboration with Oak Ridge National Laboratory, have developed a new model that could lead to sharper imaging and safer diagnostics using magnetic resonance imaging, or MRI.

In a study recently published in The Journal of Chemical Physics, the team of researchers showed how they used the Fokker-Planck equation to better understand how water molecules respond to contrast agents in a process known as “relaxation.” Previous models only approximated how water molecules relaxed around contrasting agents. However, through this new model, known as the NMR eigenmodes framework, the research team has uncovered the “full physical equations” to explain the process.

“The concept is similar to how a musical chord consists of many notes,” Thiago Pinheiro, the study’s first author, a Rice doctoral graduate in chemical and biomolecular engineering and postdoctoral researcher in the chemical sciences division at Oak Ridge National Laboratory, said in a news release. “Previous models only captured one or two notes, while ours picks up the full harmony.”

According to Rice, the findings could lead to the development and application of new contrast agents for clearer MRIs in medicine and materials science. Beyond MRIs, the NMR relaxation method could also be applied to other areas like battery design and subsurface fluid flow.

“In the present paper, we developed a comprehensive theory to interpret those previous molecular dynamics simulations and experimental findings,” Dilipkumar Asthagiri, a senior computational biomedical scientist in the National Center for Computational Sciences at Oak Ridge National Laboratory, said in the release. ”The theory, however, is general and can be used to understand NMR relaxation in liquids broadly.”

The team has also made its code available as open source to encourage its adoption and further development by the broader scientific community.

“By better modeling the physics of nuclear magnetic resonance relaxation in liquids, we gain a tool that doesn’t just predict but also explains the phenomenon,” Walter Chapman, a professor of chemical and biomolecular engineering at Rice, added in the release. “That is crucial when lives and technologies depend on accurate scientific understanding.”

The study was backed by The Ken Kennedy Institute, Rice Creative Ventures Fund, Robert A. Welch Foundation and Oak Ridge Leadership Computing Facility at Oak Ridge National Laboratory.

Vicky Yao and Qiliang Lai. Photo courtesy of Rice University

Rice University scientists invent new algorithm to fight Alzheimer's

A Seismic Breakthrough

A new breakthrough from researchers at Rice University could unlock the genetic components that determine several human diseases such as Parkinson's and Alzheimer's.

Alzheimer's disease affected 57 million people worldwide in 2021, and cases in the United States are expected to double in the next couple of decades. Despite its prevalence and widespread attention of the condition, the full mechanisms are still poorly understood. One hurdle has been identifying which brain cells are linked to the disease.

For years, it was thought that the cells most linked with Alzheimer's pathology via DNA evidence were microglia, infection-fighting cells in the brain. However, this did not match with actual studies of Alzheimer's patients' brains. It's the memory-making cells in the human brain that are implicated in the pathology.

To prove this link, researchers at Rice, alongside Boston University, developed a computational algorithm called “Single-cell Expression Integration System for Mapping Genetically Implicated Cell Types," or SEISMIC. It allows researchers to zero in on specific neurons linked to Alzheimer's, the first of its kind. Qiliang Lai, a Rice doctoral student and the lead author of a paper on the discovery published in Nature Communications, believes that this is an important step in the fight against Alzheimer's.

“As we age, some brain cells naturally slow down, but in dementia — a memory-loss disease — specific brain cells actually die and can’t be replaced,” said Lai. “The fact that it is memory-making brain cells dying and not infection-fighting brain cells raises this confusing puzzle where DNA evidence and brain evidence don’t match up.”

Studying Alzheimer's has been hampered by the limitations of computational analysis. Genome-wide association studies (GWAS) and single-cell RNA sequencing (scRNA-seq) map small differences in the DNA of Alzheimer's patients. The genetic signal in these studies would often over-emphasize the presence of infection fighting cells, essentially making the activity of those cells too "loud" statistically to identify other factors. Combined with greater specificity in brain regional activity, SEISMIC reduces the data chatter to grant a clearer picture of the genetic component of Alzheimer's.

“We built our SEISMIC algorithm to analyze genetic information and match it precisely to specific types of brain cells,” Lai said. “This enables us to create a more detailed picture of which cell types are affected by which genetic programs.”

Though the algorithm is not in and of itself likely to lead to a cure or treatment for Alzheimer's any time soon, the researchers say that SEISMIC is already performing significantly better than existing tools at identifying important disease-relevant cellular signals more clearly.

“We think this work could help reconcile some contradicting patterns in the data pertaining to Alzheimer’s research,” said Vicky Yao, assistant professor of computer science and a member of the Ken Kennedy Institute at Rice. “Beyond that, the method will likely be broadly valuable to help us better understand which cell types are relevant in different complex diseases.”

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This article originally appeared on CultureMap.com.

Rice University's new Bachelor of Science in AI will be one of only a few in the country. Photo via Getty Images.

Houston university to launch artificial intelligence major, one of first in nation

BS in AI

Rice University announced this month that it plans to introduce a Bachelor of Science in AI in the fall 2025 semester.

The new degree program will be part of the university's department of computer science in the George R. Brown School of Engineering and Computing and is one of only a few like it in the country. It aims to focus on "responsible and interdisciplinary approaches to AI," according to a news release from the university.

“We are in a moment of rapid transformation driven by AI, and Rice is committed to preparing students not just to participate in that future but to shape it responsibly,” Amy Dittmar, the Howard R. Hughes Provost and executive vice president for academic affairs, said in the release. “This new major builds on our strengths in computing and education and is a vital part of our broader vision to lead in ethical AI and deliver real-world solutions across health, sustainability and resilient communities.”

John Greiner, an assistant teaching professor of computer science in Rice's online Master of Computer Science program, will serve as the new program's director. Vicente Ordóñez-Román, an associate professor of computer science, was also instrumental in developing and approving the new major.

Until now, Rice students could study AI through elective courses and an advanced degree. The new bachelor's degree program opens up deeper learning opportunities to undergrads by blending traditional engineering and math requirements with other courses on ethics and philosophy as they relate to AI.

“With the major, we’re really setting out a curriculum that makes sense as a whole,” Greiner said in the release. “We are not simply taking a collection of courses that have been created already and putting a new wrapper around them. We’re actually creating a brand new curriculum. Most of the required courses are brand new courses designed for this major.”

Students in the program will also benefit from resources through Rice’s growing AI ecosystem, like the Ken Kennedy Institute, which focuses on AI solutions and ethical AI. The university also opened its new AI-focused "innovation factory," Rice Nexus, earlier this year.

“We have been building expertise in artificial intelligence,” Ordóñez-Román added in the release. “There are people working here on natural language processing, information retrieval systems for machine learning, more theoretical machine learning, quantum machine learning. We have a lot of expertise in these areas, and I think we’re trying to leverage that strength we’re building.”

The new Rice Nexus is partnering with Google Public Sector and Non Sibi Ventures to support high-potential AI-focused startups. Image via Rice University.

Google teams up with Rice University to launch AI-focused accelerator

eyes on AI

Google Public Sector is teaming up with Rice University to drive early-stage artificial intelligence innovation and commercialization via the new Rice AI Venture Accelerator, or RAVA.

RAVA will use Google Cloud technology and work with venture capital firm Non Sibi Ventures to connect high-potential AI-focused startups with public and private sector organizations. The incubator will be led by Rice Nexus, which launched earlier this year in the Ion District as an AI-focused "innovation factory.”

“Google Public Sector is proud to partner with a leading institution like Rice University to launch the Rice AI Venture Accelerator,” Reymund Dumlao, director of state and local government and education at Google Public Sector, said in a news release. “By providing access to Google Cloud’s cutting-edge AI, secure cloud infrastructure and expertise, we’re enabling the next generation of AI pioneers to develop solutions that address critical challenges across industries and within the public sector. This unique partnership between education and industry will give participants access to cutting-edge research, leading technologists, specialized resources and a collaborative academic ecosystem, fostering an environment for rapid innovation and growth.”

Participants will have access to Google Public Sector’s AI leadership as well as experts from Rice’s Ken Kennedy Institute, which focuses on AI and computing research. It will be led by Sanjoy Paul, Rice Nexus’ inaugural executive director. Paul previously worked at Accenture LLC as a managing director of technology and is a lecturer in Rice's Department of Computer Science.

Rice Nexus will serve as the physical hub for RAVA, but the program will support AI startups from across the U.S., as part of Rice’s Momentous strategic plan, according to the university.

“This hub enables AI startups to go beyond building minimum viable products that meet industry privacy standards by utilizing the latest AI technologies from Google Cloud,” Paul said in the news release. “Our goal is to maximize the return on investment for our corporate partners, driving meaningful innovation that will have lasting impact on their industries.”

The 10,000-square-foot Rice Nexus space currently serves as home base for several startups with ties to Rice, including Solidec, BeOne Sports and others. Read more about the new incubation space here.

OpenSafe.AI, a new platform that utilizes AI, data, and hazard and resilience models to support storm response decision makers, has secured an NSF grant. Photo by Eric Turnquist

Houston-area researchers score $1.5M grant to develop storm response tech platform

fresh funding

Researchers from Rice University have secured a $1.5 million grant from the National Science Foundation to continue their work on improving safety and resiliency of coastal communities plagued by flooding and hazardous weather.

The Rice team of engineers and collaborators includes Jamie Padgett, Ben Hu, and Avantika Gori along with David Retchless at Texas A&M University at Galveston. The researchers are working in collaboration with the Severe Storm Prediction, Education and Evacuation from Disasters (SSPEED) Center and the Ken Kennedy Institute at Rice and A&M-Galveston’s Institute for a Disaster Resilient Texas.

Together, the team is developing and hopes to deploy “Open-Source Situational Awareness Framework for Equitable Multi-Hazard Impact Sensing using Responsible AI,” or OpenSafe.AI, a new platform that utilizes AI, data, and hazard and resilience models "to provide timely, reliable and equitable insights to emergency response organizations and communities before, during and after tropical cyclones and coastal storm events," reads a news release from Rice.

“Our goal with this project is to enable communities to better prepare for and navigate severe weather by providing better estimates of what is actually happening or might happen within the next hours or days,” Padgett, Rice’s Stanley C. Moore Professor in Engineering and chair of the Department of Civil and Environmental Engineering, says in the release. “OpenSafe.AI will take into account multiple hazards such as high-speed winds, storm surge and compound flooding and forecast their potential impact on the built environment such as transportation infrastructure performance or hazardous material spills triggered by severe storms.”

OpenSafe.AI platform will be developed to support decision makers before, during, and after a storm.

“By combining cutting-edge AI with a deep understanding of the needs of emergency responders, we aim to provide accurate, real-time information that will enable better decision-making in the face of disasters,” adds Hu, associate professor of computer science at Rice.

In the long term, OpenSafe.AI hopes to explore how the system can be applied to and scaled in other regions in need of equitable resilience to climate-driven hazards.

“Our goal is not only to develop a powerful tool for emergency response agencies along the coast but to ensure that all communities ⎯ especially the ones most vulnerable to storm-induced damage ⎯ can rely on this technology to better respond to and recover from the devastating effects of coastal storms,” adds Gori, assistant professor of civil and environmental engineering at Rice.

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This article originally ran on EnergyCapital.

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New UH survey reveals concerns over AI data center growth in Houston

data findings

A new report out of the University of Houston shows that area residents remain wary of the long-term effects of operating data centers.

The recent survey from the University of Houston’s latest SPACE City Panel, conducted by the Center for Public Policy at the Hobby School of Public Affairs, shows that while 85 percent of Houston-area residents use AI, nearly 63 percent oppose the construction of AI data centers within 1 mile of their homes.

Respondents’ concerns centered around data centers’ high energy demand and the area’s power grid reliability. According to the survey, 32 percent of residents who oppose local data center projects would be more likely to support the centers if they relied on renewable energy over fossil fuels.

“Respondents understand that AI can bring economic and educational benefits, but they are also concerned about the physical infrastructure needed to fuel AI, especially data centers,” Soran Mohtadi, post-doctoral fellow at the Hobby School and a researcher on the report, said in a news release. “This physical infrastructure demands more electricity and water, leading to environmental impacts.”

Experts estimate that 6.5 gigawatts of data center capacity will be added to the Texas grid by 2030. And Houston’s data center capacity is predicted to more than double by 2028.

The Electric Reliability Council of Texas also projects electricity demand could reach 218 gigawatts by 2031, which would be more than double the record peak set in August 2023. Data centers are expected to account for 86 gigawatts of that new demand.

Survey respondents also said they are concerned about the state's future water supply, given the large amounts of water that data centers need to stay cool.

In terms of who’s responsible for that issue, 57.6 percent of respondents said they put the onus on Texas lawmakers, while 31.5 percent say tech companies should be responsible.

Additionally, more than 75 percent of respondents believed that data center developers and technology companies—not residents—should bear the cost of infrastructure upgrades to support data centers.

“Every decision legislators make has implications on residents’ everyday lives and local infrastructure now and in the future,” Maria P. Perez Arguelles, lead researcher on the report and research assistant professor at the Hobby School, added in the news release. “This issue is going to become more important in years to come, so this is just the beginning.”

Read the full report here.

Houston-born Cemvita makes breakthrough in sustainable fuel production

clean fuels

Houston-based biotech company Cemvita announced that it recently reached a critical milestone in the development of its FermOil product, which can be used to create Sustainable Aviation Fuel (SAF) and other renewable fuels at industrial scale.

The company shared in a news release that it completed a 75,000-liter industrial fermentation run at Belgium's Bio Base Europe Pilot Plant.

The campaign achieved target technical metrics for the production of FermOil, Cemvita’s renewable natural oil (RNO). FermOil is produced from industrial crude glycerin, an industrial byproduct, as opposed to traditional sugar-based feedstocks used in many bio-oil fermentation processes. It's designed to be a drop-in feedstock for creating SAFs.

Cemvita had previously advanced its FermOil production process through multiple scale-up stages before successfully reaching the 75,000-liter demonstration campaign, according to the company.

“This is not just a fermentation milestone,” Moji Karimi, CEO at Cemvita, said in the release. “It is a blueprint for how existing industrial infrastructure can evolve into circular bioeconomy infrastructure. Every biodiesel plant generating crude glycerin is a potential platform for renewable natural oil production.”

The milestone also supports the deployment of Cemvita’s industrial biomanufacturing platform, FermWorks, which integrates with existing energy and industrial infrastructure to turn waste carbon streams into SAFs and other materials. According to the release, Cemvita plans to move forward with commercial deployment discussions with partners in Brazil, Europe and in the UK. Cemvita already has a partnership with the Brazilian sustainable research institution REMA.

“We are proud to support innovative companies like Cemvita in scaling breakthrough industrial biotechnology solutions,” Hendrik Waegeman, head of business operations at Bio Base Europe Pilot Plant, added in the release. “Successfully operating at the 75,000-liter scale using a feedstock such as crude glycerin highlights both the maturity of the technology and the quality of the scale-up execution achieved by the Cemvita team.”

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This article originally appeared on our sister site, EnergyCapitalHTX.com.

Eli Lilly scoops up Houston biotech startup in $300 million deal

big pharma deal

Pharmaceutical giant Eli Lilly has acquired Houston biotech startup CrossBridge Bio, which develops antibody-drug conjugates for cancer, in a deal worth up to $300 million. The deal was celebrated by TMC Venture Fund and the University of Texas Health Science Center at Houston last week.

CrossBridge, founded in 2023, is developing ADCs based on research by Kyoji Tsuchikama and Zhiqiang An, both of UT Health Houston. Tsuchikama is an associate professor of medicinal chemistry and a globally recognized ADC pioneer, and An is a professor of molecular science and vice president of drug discovery.

Antibody-drug conjugates (ADCs) are a potent combination of targeted therapy and chemotherapy that kills cancer cells while saving healthy tissue.

Clinical trials for CrossBridge’s primary ADC candidate, CBB-120, are expected to start this year, pending approval from the U.S. Food and Drug Administration (FDA).

“I’m proud of how well our team has executed and advanced our platform in such a short time since the company’s founding,” Michael Torres, co-founder and CEO of CrossBridge, said in a news release. “By becoming a part of Lilly, a leader in patient-focused therapeutic development, we are well-positioned to further accelerate the clinical potential of this approach.”

Under the Lilly deal, CrossBridge shareholders were expected to receive an upfront payment along with a follow-up payment based on the achievement of certain milestones.

In 2024, CrossBridge closed a $10 million seed round. Among the investors in CrossBridge are the Texas Medical Center Venture Fund, CE-Ventures, Alexandria Venture Investments, Portal Innovations, Linden Lake Labs, and the Cancer Prevention and Research Institute of Texas (CPRIT). It was formed in TMC Innovation’s Accelerator for Cancer Therapeutics program."Built within the TMC ecosystem, CrossBridge Bio grew with the support, funding, and resources that helped shape its trajectory. TMC led the company's early financing and watched it evolve from its earliest days to its acquisition by Eli Lilly," William McKeon, president and CEO of the Texas Medical Center, shared in a LinkedIn post. "[This is a] strong reminder that breakthrough science and the right early backing can change what’s possible."
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