Data diversifying

Houston data startup plans to expand its technology from oil and gas to include health care and defense industries

Houston-based Pandata Tech uses its machine learning technology to advance oil and gas operations. Thomas Miller/Breitling Energy

There are about 40,000 sensors on an offshore drilling rig, and each collects information about how the rig's many machines are operating. But sensors can fail or be miscalibrated and, in the relay between the rig and data scientists, data can pick up errors. The scientists will first have to clean and validate the information to ensure its credible.

That's where Pandata Tech comes in. The Houston-based company can run a data quality check for its oil and gas clients. But Gustavo Sanchez, co-founder and CEO of the company, is speeding up that process by automating it. Pandata Tech uses machine learning to review data generated by drilling rigs — and the algorithms determine how likely that data can be trusted. And for Houston's 175,000 residents employed in oil and gas, that data needs to be trustworthy.

"If the data's bad, then you're going to have a lot of bad decisions," Sanchez says.

The legacy of machine learning began in the 1950s, when computer scientist Arthur Samuel wrote a program for a computer to play checkers and improve at the game the more it played. Since then, the complex algorithms written for computers to learn and develop without human intervention have been implemented in industries like finance, sales, surveillance, and more.

Sanchez and his business partner, Jessica Reitmeier, met in China during graduate school. They founded the company after a stint for Sanchez in finance data science. He realized that small service companies had no control over their equipment operated and put data analytics in the hands of small, independent service contractors. So they developed Pandata Tech in January 2016, and today their core team has three people who manage data science, marketing and operations, and staff development.

Pandata Tech's software reduces the amount of time data scientists have to spend validating their data — from 80 percent of their time down to just 20 percent, Sanchez says. It works by using models to generate a data quality score.

For example, a sensor that monitors pressure levels is paired with a computer model of what those levels should be — and the software checks for missing or incorrect data, then uses statistics to determine how likely that the sensors are picking up correct data. It creates a quality score for that data between 0 and 100 in the short and long term; if it compiles the data for a 24-hour window, then the score should be close to 100, but the software can also analyze data for 90-day streaks. In this case, the ideal might be above 60. It's a lot like a credit check, Sanchez says.

And while Pandata Tech began in the energy industry, the team is now expanding to fields like defense and healthcare, which also generate hundreds of thousands of data points that need it be checked. The unique challenges of working with large drilling rigs have translated well to working with aircrafts. And the healthcare field is similar — with the Texas Medical Center, Houston's medical research centers can benefit from hastening the process of data validation.

"There's so much data, and it's so noisy, that it's hard to know whether the data can be trusted or not," Sanchez says.

Pandata Tech is focusing on its current revenue sources in these three fields. Recently, they closed on a deal with one of the largest offshore drilling companies in the world, and Sanchez hopes to double his team size within the year. But he's staying cautious — and the move to healthcare and defense industries is not just a move to expand the use of his company's technology. It's also a way of reducing risk, by not investing in just one industry.

"It's hard to sell scale to a startup," Sanchez says. "We've gotta reduce our risk so we can continue to grow."

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Building Houston

 
 

You can now hop online and invest in this promising cell therapy startup. Photo via Getty Images

A clinical-stage company headquartered in Houston has opened an online funding campaign.

FibroBiologics, which is developing fibroblast cell-based therapeutics for chronic diseases, launched a campaign with equity crowdfunding platform StartEngine. The platform lets anyone — regardless of their net worth or income level — to invest in securities issued by startups.

The funding, according to a press release, will be used to support ongoing operations of Fibrobiologics and advance its clinical programs in multiple sclerosis, degenerative disc disease, wound care, extension of life, and cancer.

"We're excited to partner with StartEngine on this campaign. StartEngine has over 600,000 investors as part of their community and has raised over half a billion dollars for its clients," says FibroBiologics' Founder and CEO Pete O'Heeron, in the release.

"This is an exciting time at FibroBiologics as we continue progressing our clinical pipeline and developing innovative therapies to treat chronic diseases," he continues. "This new funding will fuel our growth in the lab and bring us one step closer to commercialization."

The campaign, launched this week, already has over 100 investors, at the time of publication, and has raised nearly $2 million, according to the page. The minimum investment is set at around $500, and the company's indicated valuation is $252.57 million.

In 2021, FibroBiologics announced its intention of going public. Last year, O'Heeron told InnovationMap on the Houston Innovators Podcast of the company's growth plans as well as the specifics of the technology.

Only two types of cells — stem cells and fibroblasts — can be used in cell therapy for a regenerative treatment, which is when specialists take healthy cells from a patient and inject them into a part of the body that needs it the most. As O'Heeron explains in the podcast, fibroblasts can do it more effectively and cheaper than stem cells.

"(Fibroblasts) can essentially do everything a stem cell can do, only they can do it better," says O'Heeron. "We've done tests in the lab and we've seen them outperform stem cells by a low of 50 percent to a high of about 220 percent on different disease paths."


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