Seattle biotech startup BrainChild Bio has raised $116 million to advance an experimental CAR T cell therapy for one of the deadliest forms of childhood brain cancer.

The Series A financing will primarily fund a pivotal Phase 2 clinical trial of an investigational therapy being developed for diffuse intrinsic pontine glioma, or DIPG. The rare brainstem tumor primarily affects children ages 5 to 10 and has few treatment options.

The financing was led by an undisclosed private family fund and foundation, with participation from BrainChild Bio’s initial investor, Seattle Children’s, and new investor WRF Capital.

BrainChild Bio is building on CAR T cell technology developed at Seattle Children’s and licensed exclusively to the company in 2023. The approach involves genetically engineering a patient’s own T cells to recognize and attack cancer cells.

The company says its new therapy has now entered its ILLUMINATE Phase 2 study, designed as a registration-stage trial that could eventually support an application to the U.S. Food and Drug Administration.

DIPG presents a particularly difficult challenge for cancer researchers because the tumors grow in the brainstem, an area critical to basic functions, and the blood-brain barrier can limit the ability of treatments to reach the tumor.

BrainChild Bio’s approach delivers the CAR T cells directly into cerebrospinal fluid through an implanted catheter, allowing the cells to reach the tumor locally and potentially be administered repeatedly.

About 300 children in the U.S. are diagnosed with DIPG each year, a devastating brain tumor with no cure and few treatment options. Radiation is the current standard of care, but children diagnosed with DIPG have a median overall survival of only about 11 months.

BrainChild Bio also plans to use proceeds from the new financing to advance a CAR T therapy designed to target three different cancer markers, toward initial clinical testing in glioblastoma.

The company was founded by Michael Jensen, who previously helped develop the underlying work at Seattle Children’s and was a co-founder of Umoja Biopharma and Juno Therapeutics. The CEO is Steven Brugger, who most recently served as founder and CEO of Affinivax, a biotech company which was acquired by GSK for $3.3 billion in 2022. 

“This financing enables us to chart our path forward to serve the children and families afflicted with devastating brain tumors and represents a new paradigm for treating CNS brain tumors in children and adults,” Jensen said in a statement. “Our team at BrainChild Bio is steadfast in its commitment to harness CAR T cell technology in CNS tumors and we are uniquely positioned to do so.”

Three of Seattle’s top scientific institutions are launching a nearly $95 million research initiative that will generate data and train AI models to design proteins and genes that don’t exist in nature — sharing the results freely to help others develop new medicines and materials.

The initiative, called AI BioDesign, brings together the Allen Institute, the University of Washington and Fred Hutch Cancer Center, with funding from the Fund for Science and Technology (FFST), created by the estate of Microsoft co-founder Paul Allen.

AI BioDesign is led by David Baker, the UW biochemist who won the 2024 Nobel Prize in Chemistry for using computers to design new proteins, and Jay Shendure, a leading genome scientist at the UW and the Allen Institute.

The plan is to “hijack a lot of the machinery that evolution provided us” — the cellular assembly line that turns DNA into proteins — to design and measure millions of novel biological molecules, Shendure said in an interview in advance of the announcement.

That will help AI models learn the rules of biological design from a huge set of examples, instead of inferring them from the relatively limited number that nature has produced.

The field, Shendure said, is “putting too much emphasis on taking the cranks that we have and just running with them, as opposed to building the right cranks.”

The goal is to make designing biology more like ordering a part: a molecule that latches onto a cancer cell, for example, or a genetic switch that fires only inside brain cells and nowhere else.

Potential outcomes could include everything from new therapies for disease, to proteins that dissolve plastic in the environment, to cells that travel through the body in a programmed way, said Sanjay Srivatsan, a Fred Hutch assistant professor who leads the cancer center’s work on the initiative, in a video released with the announcement.

“For the first time, the speed of AI is beginning to match the experimental power of synthetic biology,” Baker said in a statement. “That changes the question from ‘what has nature already made?’ to ‘what else is possible, and how can we test it?'”

Where the money goes

The Fund for Science and Technology is providing $94.6 million for AI BioDesign over five years. The foundation launched publicly last year with a mandate to direct a large share of Allen’s fortune into bioscience, environmental and AI research.

The funding from FFST is allocated as $46.1 million to the Allen Institute, $43.8 million to the UW and $4.7 million to Fred Hutch, according to an Allen Institute spokesperson.

The initiative had 62 people as of mid-August, including some new hires and others redirected from existing projects at the three institutions. The UW accounts for 41 of them, the Allen Institute 13, and Fred Hutch eight. AI BioDesign is expected to continue growing over time.

“AI BioDesign is exactly the kind of ambitious, collaborative science FFST was created to support,” said Marc Malandro, the foundation’s chief programs officer and co-lead, in a statement. He joined FFST in May after nearly a decade at the Chan Zuckerberg Initiative, most recently as chief operating officer of CZI and the Chan Zuckerberg Biohub Network.

Malandro and Chief Financial and Operations Officer Liz Carey have been leading FFST on an interim basis since founding CEO Lynda Stuart stepped down in May.

Inside the lab

On a recent tour of the AI BioDesign lab, research associate Jack Boylan pulled up results from a run he’d done on their new DNA sequencer that morning — on free kits donated by a neighboring biotech company, a year past their expiration date.

“We decided, let’s give it a roll,” he said. It worked fine.

The sequencer is what makes the whole approach possible. It reads all of the millions of DNA sequences in a single tube at once and reports which ones performed. One recent experiment ran 6 million distinct sequences through it at once.

“The scale comes not from robotics, but from parallelizing inside the test tube,” said Jesse Gray, executive director of strategy and platform for AI BioDesign and the Seattle Hub for Synthetic Biology, and a former Harvard Medical School geneticist.

The lab, at Dexter Yard in Seattle’s South Lake Union neighborhood, a short walk from the Allen Institute’s headquarters, is organized into teams of five or six people, each working on a different design problem.

A separate four-person team of machine-learning specialists takes the incoming results and works with the bench teams to decide which experiments come next — the ones that will teach the models the most. Each round is judged on how much the models improved.

The Allen Institute calls projects like this “accelerators,” a term Rui Costa, the institute’s president and CEO, traced back to Paul Allen himself. The word came up in early planning sessions, Costa said. Allen wanted to “exponentially accelerate the field.”

Other accelerators at Dexter Yard include the Seattle Hub for Synthetic Biology, the Allen Institute’s collaboration with the Chan Zuckerberg Initiative and the UW, which Shendure also leads; and Cell Science, which works on engineering cells to assemble themselves into tissues.

The Allen Institute for AI (Ai2), the separate Seattle research organization also founded by Paul Allen, is involved informally rather than as a funded partner, Costa said.

Its robotics team has been talking with AI BioDesign about scaling up the protein work, and the two expect to collaborate on models and on tools that generate research hypotheses.

Why give it away

The decision to focus on open science also came from Allen, Costa said in an interview this week. “He was so visionary in the early 2000s: radically open science to exponentially impact and change fields, not to compete.”

That raises a question the initiative will face as soon as it produces anything valuable: what happens if a company builds a lucrative drug on data given away free? In traditional science, Costa said, being beaten to a discovery counts as a loss. Here it’s the goal.

“We would be so lucky if many companies would be taking this data and changing the world for good,” he said.

At the same time, Costa left open the possibility of the three principal institutions spinning out their own startups, nonprofits, or other initiatives from the work done by AI BioDesign.

Betting against the field

AI BioDesign’s approach runs against much of the current thinking in the field. Costa said most efforts to apply AI to biology are chasing a single general model that could answer questions about how any cell works. AI BioDesign is betting on the opposite: narrow models built for specific design problems, trained on data generated for that purpose.

“This project is a clear bet on a different way of doing things,” Costa said.

The people running the initiative are careful not to oversell. Gray said it remains an open question as to whether their approach beats the alternatives. “The jury’s still out,” he said.

Shendure put it plainly: “It’s never as easy as you think it’s going to be,” he said.

Costa said AI BioDesign needs to show real progress within 18 to 24 months — ideally even sooner — and expand to researchers around the world within five years.

Arzeda designs enzymes for products ranging from laundry detergent to stevia. But when it comes time to manufacture at commercial scale, the Seattle-based startup often has to look overseas.

That’s why, when a federal biotechnology commission visited Seattle on Tuesday, the industry came forward with a problem: They have the science, but lack the infrastructure and workforce pipeline to keep innovation on U.S. soil.

Arzeda’s designs reach an estimated 1.8 billion consumers worldwide, and the company has spent the better part of two decades building its technology. The company’s enzymes, sometimes designed in days rather than weeks thanks to AI, are largely manufactured in Western Europe and India — with one U.S. contract manufacturing partner in Wisconsin. 

Finding domestic manufacturers with the expertise and capacity to make these specialized proteins has been difficult, CEO Alexandre Zanghellini said. And for a company trying to commercialize new biotechnology, he added, manufacturing delays can be “catastrophic.” 

The federal group visiting Seattle — the National Security Commission on Emerging Biotechnology — was created by Congress to address these kinds of problems. Since 2022, the team of 11 bipartisan experts have examined how biotech intersects with national security, and what the U.S. needs to do to remain competitive with China. 

Last year, the commission drafted a report to Congress with 49 recommendations spanning at least $15 billion in federal investment over five years, with policies to get more private capital into biotechnology, build domestic manufacturing capacity, strengthen the workforce and reduce vulnerabilities in the supply chain. 

Now, with the commission sunsetting in December, its members are taking their case around the country. 

The science is here, the infrastructure isn’t

In Seattle, the urgent matter is finding a way to keep biotechnology breakthroughs in the United States. Alexander Titus, a commission member who has headed AI-focused biotech initiatives in Seattle and nationwide, said Washington stands out for its early innovation and research. 

“Companies like Arzeda are having pretty serious leadership roles in the AI and bio space,” he told GeekWire. “A lot of the work we have done in the commission has revolved around helping the U.S. meet the moment when it comes to this nexus.” 

Institutions like the University of Washington, Fred Hutchinson Cancer Center and the Allen Institute have helped build a deep life-sciences ecosystem in Washington. UW’s Institute for Protein Design, led by 2024 Nobel Prize winner David Baker, has spun out more than 20 companies.

One is Arzeda, which has an increasingly fast agentic workflow that can fine-tune a model, suggest the next experiment, and allow researchers to test thousands of sequences in a single round. The company’s first AI-designed commercial product was a stevia ingredient launched in 2024; it’s now negotiating a $44 million contract with the federal Defense Threat Reduction Agency related to biothreat response. 

While technology is moving quickly, the infrastructure needed to commercialize it is not — creating what Seattle biotech leaders called a “valley of death” between research and manufacturing.

The U.S. has federal funding for basic research, as well as a venture-capital system that can finance early-stage discoveries. But once a company needs to build or access physical infrastructure for commercial-scale manufacturing, the financing becomes much harder. Venture capital investors don’t see the returns attractive enough, Zanghellini said. Banks aren’t eager to finance them, either. 

The pull of overseas manufacturing

Meanwhile, China has spent two decades making biotechnology a strategic priority, and its 2026 Five-Year Plan doubles down on areas including biomedicine, biomanufacturing, pharmaceuticals and brain-computer interfaces. For U.S. companies in the race, that can create an uncomfortable incentive: If the infrastructure is cheaper and faster somewhere else, that’s where the work often goes. 

Last year, Seattle-based Sana Biotechnology canceled plans for a manufacturing plant that was supposed to employ hundreds of workers in Bothell, Wash., instead opting for a contract manufacturer elsewhere to cut costs. Snehal Patel, the company’s executive vice president and chief technical officer, said on Tuesday he’s optimistic the Seattle area could compete on speed and cost with China’s fully integrated supply chain — with the right resources.

Ideally, manufacturing facilities in the U.S. would offer flexibility and knowledge in different products and processes, while ensuring trade secret protection.

The commissioners recognize this need; among their recommendations for Congress is a nationwide manufacturing network for precommercial, bioindustrial product scale-up. That could address the problem Seattle companies face: a startup shouldn’t have to choose between sending manufacturing overseas or trying to build an entire facility itself.

The commission has also recommended requiring companies to disclose points of supply-chain vulnerability in foreign countries of concern. If a geopolitical conflict disrupts the supply of medicines or other biological products, Titus said, the consequences can reach Americans far from any battlefield.

“Being able to keep and maintain our leadership in certain industries allows us to have the edge in any given situation,” he said. “We want our industries to be able to produce here…it’s truly national security in the broadest sense at this point.”

Building the workforce pipeline

To accomplish this, companies need a stronger industrial biomanufacturing workforce.

Rebecca Bryant, Fred Hutch’s director of government relations and a former staffer for Rep. Adam Smith, said while Washington trains well for research, there’s no equivalent pipeline into entry-level biomanufacturing jobs. Titus sees the issue as part of a broader problem of “bioliteracy” — that biology should be a basic problem-solving tool in the same way that engineering, chemistry and computing are, rather than a specialized field understood by few. 

In Washington, the Hutch Advance partnership with Shoreline Community College trains and places lab technicians, while Sana Biotechnology has worked on a model for moving workers into biomanufacturing. Seattle industry leaders suggested a state or federally-supported workforce consortium to bolster the effort. Meanwhile, the commission has urged Congress for more biomanufacturing training support. 

According to the commission, the next three years will determine whether the U.S. remains the global leader in biotechnology or cedes the future to China. Of the commission’s 49 recommendations, Titus said, 26 have been written into law in some capacity. The next step is in the hands of Congress, federal agencies, states and the industry itself. 

A federal judge has entered a final judgment requiring Guardant Health to pay more than $245 million to Seattle biotech TwinStrand Biosciences and the University of Washington over DNA sequencing technology developed at the university.

The judgment, entered Friday in U.S. District Court in Delaware, follows a 2023 jury verdict that found Guardant willfully infringed two patents covering TwinStrand’s Duplex Sequencing technology.

The case also establishes a continuing revenue stream for the university and TwinStrand from some of Guardant’s products.

The court’s final judgment includes $83.4 million in damages awarded by the jury for infringement through June 2023, plus $19.5 million in supplemental damages, $119.4 million in accrued royalties and $22.9 million in interest.

Going forward, Guardant is required under the judgment to pay a 6% royalty on covered sales through March 2033, when the patents expire.

The technology at the center of the case traces back to research at the University of Washington, where scientists, including co-founder Jesse Salk, developed Duplex Sequencing as a way to make DNA sequencing more accurate. Salk — who stepped down as CEO of TwinStrand in 2022 — now is the co-founder of cancer diagnostics startup CytoTerra.

The molecular biologist and clinical oncologist is the grandson of the late Jonas Salk, the scientist who discovered and developed the polio vaccine.

TwinStrand says its Duplex Sequencing technology can improve the accuracy of next-generation sequencing by more than 10,000-fold, allowing researchers to detect extremely rare genetic mutations that can be obscured by sequencing errors.

“Duplex Sequencing solved an accuracy problem the sequencing field had worked on for years, and this judgment affirms the jury’s finding that Guardant Health built products on that invention without a license,” said Chad Waite, chair of the TwinStrand board of directors, in a press release. “We remained steadfast in our conviction that the facts would prevail, and they have. We intend to see this through and stand firmly behind the intellectual property at the core of our technology.”

Salk and his colleagues from the University of Washington launched TwinStrand in 2015 to commercialize the technology. Based in Seattle, the startup raised funding from Madrona Venture Group, Soleus Capital, Janus Henderson Investors, Ridgeback Capital, Alexandria Venture Investments. Section 32 led a $50 million series B round in the company in 2021.

A jury found in November 2023 that Guardant willfully infringed the patents through 11 products and services. The products identified in the judgment include Guardant360, Guardant Reveal, Guardant Shield and other cancer-testing products.

The Delaware court subsequently rejected Guardant’s effort to overturn the verdict or obtain a new trial. In June, the court also awarded TwinStrand and UW ongoing royalties and supplemental damages. The final judgment now formalizes those awards.

Guardant is not accepting the ruling.

The California-based precision oncology company said Monday that it plans to appeal the judgment, arguing that the court’s order covers products that existed at the time of the 2023 trial and that many have since been discontinued or substantially upgraded. Guardant also said current versions of its Reveal and Shield products are excluded from the final district court order.

Guardant — founded in 2012 — said the judgment and collection of potential royalties will be stayed pending the appeal.

“We strongly disagree with this decision and will promptly be appealing for its overturn,” said John Saia, Guardant Health Chief Legal Officer, in a press release. “We have full faith in the strengths and merits of Guardant’s intellectual property and R&D and are confident we will ultimately prevail on appeal.”

A bio-manufacturing facility in Everett, Wash., which was built by Seattle biotech giant Seagen but never opened under its Pfizer ownership, is getting a new lease on life.

Breakthrough Properties, a life sciences real estate company, said Friday that it has acquired the 270,000-square-foot facility at 215 Shuksan Way for $78 million and leased the entire campus for 21 years to an unnamed global biopharmaceutical company.

Seagen invested approximately $350 million to build out the facility, which was designed for drug manufacturing, quality-control labs, warehousing and distribution. But the company never moved in after drug maker Pfizer acquired Seagen for $43 billion in 2023.

“Pfizer regularly evaluates our manufacturing network to ensure capacity is effectively utilized based on projected product demands,” the company said in a statement to GeekWire in 2024. “After careful evaluation, we have made the difficult decision to wind down construction of the site.”

The facility sits about 25 miles north of Seattle along the I-5 corridor and is Breakthrough Properties’ first investment in the Puget Sound region.

The deal comes as pharmaceutical companies increase investment in U.S. manufacturing capacity. Breakthrough said major drugmakers have announced more than $600 billion in recent commitments to expand domestic production and strengthen supply chains.

The Everett facility was part of Seagen’s broader manufacturing expansion before the company was acquired by Pfizer for $43 billion. GeekWire previously reported on Seagen’s plans for the 270,000-square-foot Everett facility.

Breakthrough Properties is a joint venture between global real estate company Tishman Speyer and biotech investment firm Bellco Capital. A spokesperson for the company, which owns and develops life sciences properties in the U.S. and Europe, declined to provide details on the new tenant or the move-in date.

Medical researchers need cutting-edge tools to create new treatments, and Vancouver, BC startup ScopeSys wants to provide them.

Founded in 2017 and tracing its roots to research from University of British Columbia biophysicist Sabrina Leslie, ScopeSys uses physics to make testing new medicines quicker and cheaper.

The 7-person company, which recently closed a $1.1 million seed funding round, is developing tools that let drugmakers observe individual RNA and DNA molecules, giving researchers a more precise way to design new forms of medicines.

We caught up with ScopeSys CEO Padma Kodukula — a longtime biotech leader who most recently served as chief business officer at A-Alpha Bio — for this installment of GeekWire’s Startup Spotlight.

In 50 words or less, give us your startup’s elevator pitch.

ScopeSys is developing next-generation analytical instruments that reveal the size, payload, structure, and dynamic behavior of individual nanoparticles and biomolecules. Our proprietary Convex Lens-induced Confinement (CLiC) technology helps pharmaceutical and biotechnology companies design better genomic medicines, accelerate formulation development, improve scale-up, and strengthen manufacturing control.

What problem are you obsessed with solving?

I am obsessed with improving how genomic medicines are characterized. These therapies are complex and highly heterogeneous, yet many existing analytical methods report only population averages. We want to give scientists particle-by-particle and molecule-by-molecule insight so they can better understand what they are making, why it works, and how to manufacture it consistently.

What surprised you after talking to customers?

I was surprised by how actively customers seek technologies that can give them a meaningful competitive advantage. Pharmaceutical and biotechnology teams are highly sophisticated, but they still face major analytical gaps. They are willing to explore cutting-edge tools when technology can answer important questions that existing methods cannot and provide actionable data.

How has AI changed the way you build your company?

AI has multiplied our efficiency across nearly every part of the company. We use it to accelerate scientific research, analyze market and competitive information, refine product positioning, develop customer materials, support sales outreach, and improve internal decision-making. It allows a small team to operate with the speed and breadth of a much larger organization.

What is one thing people misunderstand about your startup?

Some people assume we are still an academic research project because our technology originated at the University of British Columbia. In reality, ScopeSys is a commercial, revenue-generating company. We are translating years of scientific innovation into robust instruments, consumables, AI datasets, and analytical services designed for pharmaceutical, biotechnology, and research laboratories.

What is the toughest decision you have made in the past year?

The toughest decision has been balancing near-term service revenue with the long-term investment required to commercialize our instrument platform. Services generate important customer validation and cash flow, but building a scalable product company requires disciplined choices about hiring, capital allocation, product development, and which opportunities to prioritize.

What is the one piece of advice you give to other entrepreneurs?

There will be many hurdles throughout the entrepreneurial journey, and some will feel overwhelming in the moment. Keep moving forward. Most challenges eventually pass, especially when you remain focused, adaptable, and persistent. Perseverance does not mean ignoring problems; it means continuing to solve them one at a time.

We will know our company has made it when…

Our technology and instruments are routinely used across pharmaceutical, biotechnology, and academic laboratories as a standard tool for developing genomic medicines—helping scientists build better formulations, accelerate process scale-up, understand product heterogeneity, and support manufacturing and quality control.