A Houston-based software startup received a multimillion-dollar grant from the National Institutes of Health for its work within neurophysiology. Getty Images

Armed with a nearly $3.8 million federal grant, a Houston startup aims to boost neuroscience research around the world.

Vathes LLC, a developer of data management software that collaborates with neuroscience research labs in North America and Europe, recently received the $3.78 million grant from the Brain Research through Advancing Innovative Neurotechnologies (BRAIN) Initiative at the National Institutes of Health (NIH). That initiative is part of the National Institute of Neurological Disorders and Stroke.

Vathes says the NIH funding will enable the startup to ramp up its DataJoint Pipelines for Neurophysiology project. The project aims to make open-source software for data science and engineering available to researchers who specialize in neurophysiology, a branch of neuroscience that looks at how the nervous system functions. The pipeline project holds the promise of benefiting research in areas like autism, Alzheimer's disease, and amyotrophic lateral sclerosis (ALS, or Lou Gehrig's disease).

The project's principal investigator is Dimitri Yatsenko, vice president of research and development at Vathes. Technologically speaking, neuroscientists are playing catch-up with their counterparts in fields like astrophysics, genomics, and bioinformatics, according to Yatsenko.

Neuroscience "is undergoing a fast transformation in terms of moving toward much more data-centric, data-intensive, computation-intensive, and collaborative projects," Yatsenko says. This means that neuroscientists are "now finding themselves having to quickly adapt to an environment," he adds, "where they have to share big data and computations with their collaborators in very dynamic settings and perform them in a very fluid way."

Yatsenko says the NIH-funded project will help smaller research groups tap into the technical expertise of larger research labs.

Vathes' DataJoint Neuro platform and services, which help create so-called DataJoint pipelines, enable neuroscientists to streamline, analyze, and visualize complex data. Among its customers are Princeton University's Neuroscience Institute and Columbia University's Zuckerman Institute. The federally funded project will empower smaller labs to capitalize on existing DataJoint pipelines as ready-to-go turnkey packages, Yatsenko says.

In essence, Vathes' technology acts as a translator. Big research labs collect data in databases that can vary by computer language and platform. Through the Vathes setup, that data can be incorporated by a lab of any size into algorithmic, machine learning, and artificial intelligence mechanisms, regardless of the computer language or platform.

Edgar Walker, CEO of Vathes, says this simplifies the construction and use of databases, giving scientists "more room to focus on the logic of their data pipeline rather than on the physical implementation of it."

Founded in 2016, Vathes is housed at the Texas Medical Center's Innovation Institute. It employs 10 people. The startup previously received a $100,000 grant from the U.S. Defense Advanced Research Projects Agency (DARPA).

Yatsenko says the project backed by the $3.78 million NIH grant will propel the startup's growth, as it "gives us a big window of opportunity" to provide tools and services that support the startup's open-source software.

"As the NIH and other funding agencies are shifting a lot of their focus to collaborative projects that are distributed among multiple institutions," Walker says, "we've established a reputation as the company that can facilitate such research, be efficient, and actually be cost-effective as well, and make the projects very smooth."

"We expect to continue to grow this business at the same exponential rate," he adds. "We'll keep our fingers crossed and see how things go."


CEO Edgar Walker (left) and Dimitri Yatsenko, vice president of research and development, lead Houston-based Vathes. Photos courtesy of Vathes

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Austin company to bring AI-powered school to The Woodlands

AI education

Austin-based Alpha School, which operates AI-powered private schools, is opening its first Houston-area location in The Woodlands.

The 8,000-square-foot school, scheduled to be ready for the 2026-27 academic year, initially will serve students in kindergarten through eighth grade. Alpha says the school will offer “open workshop spaces and innovative classrooms that support personalized instruction, core academics, leadership development, and real-world life skills.”

Alpha sets aside two hours each school day for the AI-driven, self-paced study of core subjects like math, reading and science. The rest of each school day consists of life-skills workshops focusing on topics such as leadership and financial literacy.

Alpha’s school in The Woodlands has begun accepting applications for the 2026-27 school year. Annual tuition costs $40,000.

“The Woodlands is one of the most dynamic, forward-thinking communities in Texas, and Alpha is proud to bring

an innovative educational model that complements its strong academic foundation,” says Rachel Goodlad, head

of expansion for Alpha.

Founded in 2014, Alpha School combines adaptive technology-driven instruction with immersive life-skills workshops. Its model emphasizes mastery-based learning in core subjects alongside development of communication, critical thinking, financial literacy and leadership skills. It operates more than 15 schools across the country.

Elsewhere in Texas, Alpha operates schools in Austin, Brownsville, Fort Worth and Plano. Alpha also operates 12 Texas Sports Academy campuses in Texas, including locations in Houston, Pearland and Richmond, along with a NextGen Academy esports school in Austin, a school for gifted students in Georgetown, and lower-cost Nova Academy campuses in Austin and Bastrop.

Alpha has fans and critics. While supporters tout students’ high achievement rates, detractors complain about the high tuition and the AI-influenced depersonalization of education.

“Students and our country need to be in relationship with other human beings,” Randi Weingarten, president of the American Federation of Teachers, a teachers union, tells The New York Times. “When you have a school that is strictly AI, it is violating that core precept of the human endeavor and of education.”

Alpha co-founder MacKenzie Price, a podcaster and social media influencer, doesn’t share Weingarten’s views.

“Parents and teachers: We need to embrace this change,” Price wrote after President Trump signed an executive order promoting AI in schools.

The Times notes that Alpha doesn’t employ AI as a tutor or a supplement. Rather, the newspaper says, AI is “the school’s primary educational driver to move students through academic content.”

Houston researcher secures $1.7M to develop drug for aggressive form of breast cancer

cancer research

A University of Houston researcher has joined a $3.2 million effort to develop a new drug designed to attack a cancer-driving protein commonly found in triple-negative breast cancer.

Triple-negative breast cancer (TNBC) is one of the most difficult-to-treat forms of cancer and accounts for 10 percent to 15 percent of all breast cancer cases. The disease gets its name because tumors associated with it test negative for estrogen receptors, progesterone receptors and excess HER2 protein, making it difficult to target. Due to this, TNBC is often treated with general chemotherapy, which can come with negative side effects and drug resistance, according to UH.

UH College of Pharmacy research associate professor Wei Wang is developing a drug that can target the disease more specifically. The drug will target MDM2, a protein often overproduced in TNBC that also contributes to faster tumor growth.

Wang is working on a team led by Wei Li, director of the University of Tennessee Health Science Center College of Pharmacy’s Drug Discovery Center. She has received $1.7 million to support the research.

Wang and UH professor of pharmacology and toxicology Ruiwen Zhang have discovered a compound that can break down MDM2. In early laboratory models, the compound has shown the ability to shrink tumors.

Wang and Zhang will focus on understanding how the treatment works and monitoring its effectiveness in models that closely mirror human disease.

“We will study how the drug targets MDM2 and evaluate the most promising drug candidates to determine effective dosing, understand how the drug behaves in the body, compare it with existing treatments and assess early safety,” Wang said in a news release.

Li’s team at the University of Tennessee will be working on the chemistry and drug design end of the project.

“This work could lead to an entirely new class of therapies for triple-negative breast cancer,” Li added in the release. “We’re hopeful that by directly removing the MDM2 protein from cancer cells, we can help more patients respond to treatment regardless of their tumor type.”