AI’s biggest impact in science is Google DeepMind’s use of a deep learning model to predict the complex structures of proteins — the molecules that drive virtually every process in living cells.

But as AI models continue to spit out more candidates for potential treatments, there’s an emerging bottleneck: actually characterizing all those candidates in practice, for testing and mass production.

That’s the goal of 10x Science, a startup founded in December 2025 that announced a $4.8 million seed round today, led by Initialized Capital and with backing from Y Combinator, Civilization Ventures, and Founder Factor. Its three founders are David Roberts and Andrew Reiter, experienced biochemists, and Vishnu Tejas, a serial founder with expertise in computer science and AI models.

“When biopharma tries to create a drug candidate, they have all of these really nice prediction tools,” Roberts told TechCrunch. “You can add as many candidates as you want to the top of the funnel, but they all have to pass through this characterization process. Everything needs to be measured.”

Understanding the structure of proteins is key for researchers developing biologic drugs, which are produced in living cells and use sophisticated design to specifically target diseases and conditions. For example, they can be designed to target specific cells, like Keytruda, a popular drug sold by Merck that helps the immune system identify and attack cancers.

10x’s three founders worked together in the Stanford lab of Nobel laureate Dr. Carolyn Bertozzi, where they studied the interactions between cancer cells and the immune system, and were frustrated by their inability to understand precisely what was happening on a molecular level.

The most accurate way to assess molecules is through a complex technique called mass spectrometry, a way of determining their atomic structure by measuring them in an electric field. The relatively new technique generates complex data that requires significant expertise to interpret, and analyzing it takes up a lot of time.

10x’s platform combines deterministic algorithms rooted in chemistry and biology with AI agents that can interpret that data. The team had to do significant work to train the models on spectrometry data and make its analyses traceable, a key requirement for a tool that will be used to help companies achieve regulatory compliance.

Matthew Crawford is a scientist at Rilas Technologies, a firm that runs chemical analyses for other companies — saving clients like biotech startups from having to invest several million dollars in their own spectrometry equipment and the experts to operate it. Crawford has been using the 10x Science platform for several weeks and says it is speeding up his work.

Crawford said the model surprised him with its ability to explain its conclusions, find the right data for analyses on its own, and adapt to evaluating different kinds of molecules. While some AI tools he has experimented with in the past over-promised or suffered accuracy issues, he says this one makes reasonable assumptions, something he attributes to the deep domain expertise of its creators.

“I ran a particular protein through it, and it just kind of figured out, from what I named the file, what the protein probably was,” Crawford said. “It then searched databases online for the sequence for that protein, so I didn’t have to program in the sequence.”

10x executives say they’re also working with multiple major pharmaceutical companies, as well as academic researchers. The plan is to use this seed funding to hire more engineers and continue to refine the model and offer it to new customers. If they are able to gain traction characterizing proteins, Roberts hopes the company will expand to offer a new kind of understanding of biology, combining protein structure with other data about cells.

“The deeper thing behind what we’re building is actually a new way to define molecular intelligence,” Roberts said.

For its investors, 10x offers a useful way into the biotech space that isn’t dependent on a specific drug succeeding and winning regulatory approval. If the company works out the way its founders hope, it will become an important tool for drug development, whether or not the eventual products succeed in the marketplace.

“This is a SaaS platform that pharma has to pay for, every single month, to go through all of these potential candidates,” Zoe Perret, a partner at Initialized, said. She’s counting on the deep experience of the founders to protect the company from competitors; there simply aren’t that many people who understand these methods and the data they produce.

What the platform could do, Crawford says, is help unlock the techniques for researchers who could benefit from these methods but lack the time or resources to deploy them.

“Groups here are trying to make a new drug,” he told TechCrunch. “They just want to get a quick, simple answer out of mass spec, and then it opens up a whole can of worms. This software is going to help keep that can of worms closed and just get them the answer they actually need to then do the next thing in their research.”

Snapchat is rolling out a new “Place Loyalty” feature that will show users when they’re among the most frequent visitors to a place on Snap Map over the past year, the company announced on Wednesday.

If you’re in the top 25% of users who visit a certain place, you’ll see your ranking on the Snap Map and can choose to share it with others. You’ll receive a gold badge if you’re among the top 1% of visitors, silver if you’re top 10% and bronze if you’re top 25%. For brands and chains, Snapchat aggregates visits across all locations.

Of course, you will only see these badges if you choose to share your location with Snapchat. Additionally, Place Loyalty rankings are only visible to you, Snapchat says.

The new feature is one more way for users to engage with the app and encourage them to share their loyalty badges on other social platforms or with friends in their social circle.

Launched in 2017, Snap Map was originally seen as a way for users to see their friends’ locations and browse public snaps from around the world. Over time, the feature has evolved and now offers ways for users to discover local hotspots and find things to do. With this new feature, Snapchat is giving users another way to interact with the map.

Snapchat announced last year that Snap Map has surpassed 400 million monthly active users.

Snap Map originally gave the social network a competitive edge over rivals like TikTok and Instagram, but the latter took on Snapchat with its own “Instagram Map” last year. Instagram hasn’t shared any stats regarding how many people use the feature, so it’s unknown how exactly it stacks up against Snap Map.

Given that Snap Map is one of Snapchat’s core products, the social media giant often updates it with new features to attract and retain users. In 2025, the company launched a “Footsteps” feature that lets you see how much of the world you’ve explored and track where you’ve traveled.

Snapchat also rolled out “Promoted Places” on Snap Map last year as a way for users to discover new places. For brands, Promoted Places offers the ability to advertise and showcase all of their locations on Snap Map.

Social network X has made it more expensive to post links through its API. The change is designed to thwart spam and “vectors of misuse,” the company said. The new pricing increased costs from $0.01 per link to $0.20

Last week, the X developer account posted changes to its API rates. The two most notable hikes were an increase in link posting price and an increase in posting price, which went up from $0.01 to $0.15 per post.

This move might discourage many publications from posting links. For instance, tech news aggregator Techmeme stopped adding links to the original articles in its posts on X this week. Instead, the posts say “Visit Techmeme dot com for the link and full context!”

Earlier this week, Techmeme said that the price increase was one of the reasons to remove links, which it said may return later. The publication also cited a Nieman Lab study, which noted that including links with posts on X resulted in dropped engagement.

X’s head of product, Nikita Bier, refuted the study’s results and said that accounts covered in the study were “habitual headline+link posters” that posted no additional context. He also replied to the Techmeme founder Gabe Rivera, that there is “no there is no code that is deboosting links.”

He added that Techmeme should post a screenshot of reactions to the news along with the link.

Earlier in the week, Rivera reacted to API price changes and said that this would force news sites to pay hundreds of dollars or post manually.

“I think they’re saying if you have a news site that tweets links, and you don’t tweet them manually, you now have to pay X hundreds of dollars per month?” he argued.

The debate of X reducing the reach of posts with links is not new. A few years ago, the company cut headlines from the link previews on the platform but reverted the change after a few weeks.