An Aug. 25 blog post by Reese Richardson, a scientific integrity expert at Northwestern University, showed how he and others have compiled nearly 19,000 manipulated images “presented as validation data for 17,495 unique antibody products sold by 15 different vendors.”

In addition to Thermo Fisher, other companies selling antibodies with allegedly faked validation data include Abcam, Novus Biologicals/R&D Systems, Proteogenix, Origene, Millipore Sigma, LSBio, Bioss, Boster Bio, G-Biosciences, GeneTex, HUABIO, Antibodies.com, Abnova, and Santa Cruz Biotechnology.

Though Thermo Fisher had 5,580 suspect images across more than 4,800 products, it was not the biggest source of suspect images. That distinction went to St. Louis-based G-Biosciences, with 6,388 images across 6,373 products.

There’s a potential explanation for why the problem is occurring everywhere one looks. “It is clear that many of these vendors are using the same images as one another for their own versions of the same product,” Richardson wrote.

Ion Genomics News

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Other Genomics News

10x Genomics and Parse Biosciences: The Last Dance-Off?

10x Genomics and Parse Biosciences met again this week in a Delaware federal courthouse for a patent infringement trial, a potentially pivotal moment for the single-cell sequencing technology market.

This case, inherited (acquired?) by 10x from Scale Biosciences, is one of its last and best chances to squeeze out Parse. So far, 10x has failed to use its core IP to trip up Parse and if it is unsuccessful here, it’s unclear where 10x turns next to continue applying legal pressure.

However, I have heard rumblings that Scale’s IP position is strong. Both companies commercialized single-cell tech based on combinatorial barcoding strategies. One probably only has to look at their dealings with NanoString and Bruker to see what 10x management will try to extract if they win. A 2025 settlement led to $68 million in licensing fees and an ongoing royalty on spatial biology products, paid by Bruker.

Parse had earlier convinced the judge to invalidate one of the patents, but was unable to convince him to invalidate all-three in a pre-trial motion.

By now, the jury is set, opening arguments have been made, and evidence is being presented. Key witnesses so far include Scale Cofounder and Stanford University researcher Garry Nolan, former Scale CEO Giovanna Prout, 10x Cofounder and CTO Michael Schnall-Levin, and Parse Cofounder and CTO Charlie Roco. The judge said both sides are on a timer and will have until the end of the week to present evidence. Perhaps next week’s newsletter will feature a jury verdict.

BGI Genomics also reported first half financials with total revenue up 10 percent, driven by 31 percent growth in precision medicine testing revenue to 917.2 million yuan.

BGI closed offices in Colombia and South Africa while setting up a new German subsidiary called DNB Tech, as reported by Huanjia Zhang at GenomeWeb (paywall.)

OmicsBank $2.3M Seed funding

OmicsBank, a clinical data company, announced $2.3 million in seed funding from Redesign Health. The company’s technology has captured longitudinal EHR data from 12.5 million patients, 6 million pathology slides, and 500,000 genome sequences and is in use at 90 hospitals and diagnostic labs in Asia.

“Drug development and healthcare AI are becoming increasingly sophisticated, but the data powering them still represents a relatively narrow slice of the world,” CEO and Cofounder Sumit Sinha said in a statement. “We’ve built the infrastructure to make rich clinical and biological data from Asia and other underrepresented populations available for research, ethically and at scale, while remaining compliant with local and international laws.”

Weill Cornell Medicine has created a new Department of Systems and Computational Biomedicine, naming Dan Landau, an oncologist and researcher known for single-cell profiling and whole-genome sequencing approaches to cancer biology, as its inaugural chair, effective Sept. 1. The department carries a mandate to build large patient-derived datasets combining genomics, wearable data, health records, and imaging for AI-driven disease research. The role is backed by a $20 million gift from Andrew and Ann Tisch.

My Omics Reading List

Leon-Perinan, et al. “Ultrafast and reference-free sequence discovery in single-cell data.” Nature. Aug. 26, 2026.

Researchers from the Max Delbrück Center for Molecular Medicine introduce Malva, a computational platform that enables “ultrafast, species-agnostic and reference-free interrogation of the raw sequence space.”

“Malva transforms single-cell atlases from static gene count tables into dynamic, sequence-resolved resources that may help to bridge human–machine reasoning about biology.”

It allows researchers to query single-cell data using natural language — – asking, for instance, about cells expressing mitochondrial genes in tumor samples — – and to retrieve sequence-level results without a reference genome.

Abolhasani. “The Lab that Learns.” Science. Aug. 20, 2026.

Abolhasani notes: “AI systems generate hypotheses and suggest experiments faster than most laboratory hardware can perform and validate them.”

Elsewhere on the Internet

American cultural icon Dolly Parton died this week at 80, a loss of one of the few nearly universally-liked public figures left in this country. One of my favorite internet “facts” that I’ve seen go around a few times now is that Parton wrote “Jolene” and “I Will Always Love You” (made even more famous by Whitney Houston) on the same night.

That may or may not be true, as Dolly Parton shared in this 2020 video; however, it’s still remarkable that they emerged from the same burst of songwriting that led to the album featuring both songs, also titled Jolene.

According to the company’s semiannual report filed with the Shanghai Stock Exchange on Aug. 22, the Chinese sequencing and laboratory automation company’s fastest-growing segment was multiomics, where revenue rose 45 percent year over year to 162.2 million yuan.

Sequencing, including both short-read and long-read platforms, grew 18 percent year over year to 1.06 billion yuan. Laboratory automation revenue rose 4 percent year over year to 116.2 million yuan.

Within the sequencing segment, consumables revenue grew 16 percent year over year while instrument revenue fell 6 percent.

R&D expenses fell 29 percent to 277.6 million yuan from 392.7 million yuan a year earlier. The company attributed the decline to core R&D projects completed in 2025 moving into a maintenance phase.

In a judgment issued Aug. 21 in the US District Court for the District of Delaware, Judge Gregory Williams said Guardant must pay $119.4 million in royalties for sales of infringing Guardant products, including the Reveal, Shield, and Guardant360 LDT/CDx/Response/Tissue Next tests, over the period of Feb.5, 2024 and May 31, 2026 as well as $19.5 million in supplemental damages and $22.9 million in pre- and post-judgment interest.

Combined with a prior $83.4 million jury verdict, Guardant faces a total bill of $245.2 million, though the company announced Aug. 24 that it will appeal the judgment.

“We strongly disagree with this decision and will promptly be appealing for its overturn,” John Saia, Guardant’s chief legal officer, said in a statement. “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.”

Moreover, in a statement Guardant said that both TwinStrand patents have been “preliminarily invalidated” in challenges before the US Patent and Trademark Office.

Guardant did not immediately respond to a list of questions, including what the focus of its appeal will be.

The judgment excludes reworked versions of certain products, including Guardant Reveal (upgraded since December 2024) and Shield (since July 22, 2026), suggesting the company has already made design changes to avoid infringing the patents going forward.

TwinStrand sued Guardant in 2021, alleging infringement of patents covering duplex sequencing, a method that sequences both strands of DNA to reduce errors in liquid biopsy testing. The jury found Guardant liable for infringement and awarded it the $83.4 million verdict in 2023.

In June, Judge Williams denied Guardant’s request to overturn the jury decision.

The so-called “royalty bearing instrumentalities” also include GuardantOMNI, HEME, GuardantINFINITY/Sirius, and Guardant Companion and Explore services.

Guardant added that it has “validated design improvements to Guardant360 and related services that would exclude impact of the potential ongoing royalties in the decision.”

In a blog post, Anthropic said it had used its recently-launched Claude Science to design so-called minibinders, or small proteins designed to bind a larger target. Wet lab work from Twist and Adaptyv Bio, a Swiss lab that touts itself as being “built for AI-first protein engineering,” showed that Claude went 14 for 15 on designing binders for targets including PD-L1, VEGF-A, IL-7R⍺, EGFR, and SpCas9.

Overall, 354 out of 1,320 designed proteins bound their target, an overall hit rate of 27 percent, though per-target hit rates varied widely.

“This case study shows that Claude is at least expert-level at orchestrating protein design tools,” Adaptyv wrote in a separate blog post. “That’s great news, since protein design tools are hard to use. Before AI, even setting up a protein structure prediction tool could take hours of debugging.”

The collaboration with Anthropic seemed to ease some investor doubts that Twist stood to benefit materially from AI-driven drug discovery. The company has been touting its growth there for nearly a year and on Twist’s most recent earnings call, CEO and Cofounder Emily Leproust said she expects AI-enabled drug discovery orders to double by the end of its fiscal year 2027 to approximately $100 million.

“After important partnerships (e.g., Amazon Bio Discovery) and publicly proven results (e.g., Anthropic’s Claude Science) we are increasingly confident that Twist is poised to play an important role in AI model building through the critical validation of key AI outputs,” Canaccord Genuity Analyst Kyle Mikson wrote in an Aug. 19 note to investors.

The protein binding experiment was accompanied by an experiment into whether Claude models could accelerate chemical analysis. Anthropic’s conclusion was that it could: using only raw files from a contract lab and a two-sentence prompt, Claude returned finished nuclear magnetic resonance spectroscopy and mass spectrometry results in under 25 minutes, matching the lab’s own purity analysis.

Anthropic noted that both the protein design and data analysis tasks are “representative of the work that makes up some parts of the early stages of the drug development process. Accelerating these phases is one component of our much larger effort to speed up drug development end-to-end, many aspects of which have more to do with policy and operational bottlenecks than with improvements in core scientific capabilities.”

The protein design work was “carried out with minimal human involvement beyond the information we provided Claude in our initial prompt,” Anthropic wrote, suggesting that guidance from experts in the field could yield even stronger results.

The experiments underscore how Anthropic is courting the scientific community, especially in life sciences, a strategy that sets it apart from many of its competitors. Last month, Anthropic announced that it was launching Claude Science, which can do various tasks besides protein design, including assisting in literature reviews as well as analyses of data such as germline variants in disease and single-cell gene expression data.

Anthropic has garnered headlines for how its newest models, including Mythos and Fable, have vastly improved their core capabilities, including writing code. The company noted that “life science research tasks are currently blocked in our most capable model,” (likely Fable) but said “one of our highest priorities” is to launch an access program for scientists, with more details to come “soon.”

Under the collaboration, Deepcell will image Gilead’s CHO cell lines on its REM-I imaging platform and train the model to learn morphological structure without manual labeling. The companies plan to publish an open-weight version of the model for the broader research and bioprocessing community.

The model could provide an earlier read on cell line quality by learning directly from single-cell morphology. Financial and other details were not disclosed.

“Beyond scoring cell line quality, the REM-I platform gives teams a window into transfection efficiency, timing, and culture and media conditions, and those same insights may extend to monitoring cells in a bioreactor,” Deepcell CTO Mahyar Salek said in a statement. “We built REM-I to read biology that humans can’t, and a CHO foundation model puts that capability directly into the hands of process development scientists.”

The deal is the second AI and imaging partnership in as many weeks for Gilead, which announced a deal Aug. 14 with Israel’s Nucleai to support antibody-drug conjugate development in cancer therapy.

New investor Flat Capital led the round, joined existing investors Industrifonden and Navigare Ventures. Stockholm-based Pixelgen said it would use the funding to accelerate commercialization of its Proxiome Kit and expand into new markets around the world.

Pixelgen’s Proxiome Kit uses its proximity network assay to show researchers how proteins are grouped and organized on the surface of individual cells.

Alongside the financing, Pixelgen is adding Flat Capital CEO Rickard El Tarzi and life sciences entrepreneur Ramon Felciano to its board of directors. El Tarzi previously served as chief strategy and product officer at Olink, now part of Thermo Fisher Scientific. Felciano founded Ingenuity Systems, an AI-driven genome interpretation company acquired by Qiagen in 2013 for $105 million and later served as that company’s CTO.

Under the terms of the deal, Bioptimus will use Stratification in COloRectal cancer Trial (S:CORT) data to train and evaluate its Spatial Tissue Embedding Learning Atlas (STELA) AI foundation model. The dataset, assembled from multiple UK patient cohorts, integrates as many as six data modalities per patient, pairing molecular and cellular profiling with longitudinal clinical outcomes.

“Building AI models that genuinely move the needle for cancer patients requires data of exceptional depth and quality,” said Jean-Philippe Vert, chief executive officer of Bioptimus. “The S:CORT dataset, with its rich combination of imaging, genomic, transcriptomic, and clinical data, is exactly the kind of resource that allows us to rigorously evaluate and continue the development of M-Optimus to deliver real-world clinical advancements.”

Bioptimus added that S:CORT data will serve as a key evaluation benchmark. Financial and other details were not disclosed.

Cancer Research Horizons is part of Cancer Research UK. The agreement is Bioptimus’ third partnership under the STELA initiative since its launch five months ago.

In June, Bioptimus signed a similar agreement for access to gastrointestinal cancer data with France’s Fédération Francophone de Cancérologie Digestive (FFCD).

The latter decision means the two companies are headed to trial next week in a key case for the future of the single-cell sequencing technology market.

In an opinion issued Aug. 19, a three-judge panel from the US Court of Appeals for the Federal Circuit upheld the invalidation of three patents for single-cell sequencing technology held by 10x Genomics by the USPTO’s Patent Trial and Appeals Board (PTAB.)

PTAB invalidated US Patent Nos. 10,155,981; 10,240,197; and 10,697,013 after an inter partes review filed by Parse Biosciences, now part of Qiagen. Parse challenged the patents, all titled “Methods for analyzing nucleic acids from single cells,” following 10x’s allegations of infringement in 2022.

A Parse spokesperson said the company welcomed the decision while a 10x Genomics spokesperson declined to comment.

The Aug. 19 appellate decision closes one of the remaining avenues available to 10x as it seeks to apply pressure to Parse via the legal system. 10x could petition to have its case heard by the US Supreme Court, though it seems unlikely to be taken up.

Yet, the IP war between the single-cell sequencing companies rages on, as Parse was unsuccessful in its bid to knock down key claims of three other patents held by 10x in a different patent infringement suit between the parties.

Judge Christopher Burke of the US District Court for the District of Delaware on Aug. 18 denied a request from Parse for summary judgment to invalidate three single-cell patents acquired by 10x when it bought Scale Biosciences in 2025. Prior to the acquisition, Scale had sued Parse, alleging infringement of four patents.

Parse had already successfully argued for the complete invalidation of one of the patents at suit, in October 2025. More recently, Parse had asked Burke to invalidate certain claims in the other three. However, Burke suggested there was a dispute of material fact that a jury should decide.

The Parse spokesperson declined to comment on this case. A 10x spokesperson said the sides are preparing for a trial next week.

Following approval of a revision to the LC-SCRUM-Asia project protocol, testing should begin this month. Over two years, LSI Medience will perform testing for approximately 2,000 patients, using oncoReveal Essential+ to screen circulating cell-free DNA (cfDNA) and cell-free RNA (cfRNA) for genomic alterations.

“Rapid and reliable genomic testing is essential for identifying patients who may benefit from biomarker-driven clinical studies and emerging precision therapies,” Koichi Goto, a researcher on LC-SCRUM-Asia and an oncologist at Japan’s National Cancer Center Hospital East (NCCHE,) said in a statement. The test will provide the LC-SCRUM-Asia network “with a highly accurate and accessible liquid biopsy solution for analyzing cfDNA and cfRNA from patients with non-small cell lung cancer, while supporting the rapid turnaround needed for clinical research,” he added.

LC-SCRUM-Asia is a large-scale lung cancer genomic screening and clinical research network led by NCCHE.

Investors include Section 32, Thiel Bio, Founders Fund, Breyer Capital, Blue Venture Fund, and JSL Health Capital, among others.

In a statement, Network Bio said it plans to use data from academic medical center biobanks to develop disease-specific AI models. The company has collaborations with Mass General Brigham, the University of Pennsylvania, and the University of Colorado Anschutz.

“No single academic medical center can capture the full complexity of human disease,” Kimberly Muller, chief innovation officer at CU Anschutz Innovations, said in a statement. “By bringing together biobanks from leading institutions with industry partners, Network Bio is creating a research resource that reflects diverse patient populations and supports discoveries that can translate into real-world clinical practice.”

Network Bio is based in Palo Alto, California and cofounded by Hani Goodarzi, a researcher at the Arc Institute, and CEO Asad Ali Ahmad and Chief Business Officer Raphael Potter, both formerly of nference, an AI-based clinical data software company.

Network’s Nvidia collaboration aims to build the first foundation model trained on cfRNA.

Network will combine its datasets from patient-derived tissues and paired blood samples linked to longitudinal clinical outcomes with Nvidia’s accelerated computing, Parabricks genomic software suite, and BioNeMo Recipes for model training.

Specifically the company plans to “scale training of Nexus, a self-supervised transformer trained on cfRNA expression profiles.” It’ll also try to speed up cfRNA bioinformatics, including secondary analysis, alignment, quantification, and quality control.

Oxford Nanopore Technologies officially announced first-half financial results, largely matching preliminary figures released a month ago, but the real news was two deals reached since June 30 and disclosed yesterday.

The one with the biggest material impact is a new global intellectual property cross-licensing agreement with an unnamed diagnostics company. Oxford Nanopore will recognize approximately $20 million in licensing fees in the second half of this year, along with $15 million in committed product purchases over fiscal years 2027 and 2028, and an ongoing royalty on revenues from certain products incorporating the licensed IP in the low-to-mid single digits.

The company did not immediately respond to a request for additional information, understandable, given the time difference. If I were forced to guess the identity of this partner, it’d be Danaher’s Cepheid. The companies expanded a collaboration for rapid bacterial and fungal pathogen identification earlier this year and plan to launch an early access program soon. But that’s just a guess.

The unnamed partner “did not have a prior relationship with Oxford Nanopore,” Canaccord Genuity Analyst Kyle Mikson wrote in a late-night Aug. 19 note to investors.

In addition, Oxford Nanopore cemented its place with MyOme’s Zenith rare disease platform. Researchers from MyOme and Natera led publication of a study on implementation of nanopore sequencing for confirming copy number variants in a clinical setting, published in the Journal of Translational Medicine in 2023. Zenith has been launched in collaboration with Natera.

Oxford Nanopore also announced the appointments of Davide Manissero as chief medical officer this month and Conor McKechnie as chief marketing and communications officer come October.

Manissero was previously CMO at Denmark’s Radiometer and CMO at Qiagen from 2019 to 2024. McKechnie was previously VP of Marketing at Danaher’s Cytiva and spent more than a decade in communications and marketing at GE Healthcare.

Ion Genomics News

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If you haven’t yet listened to last week’s podcast with my friend and fellow reporter Will Herkewitz, check out our discussion about technology and its place in fighting ongoing epidemics of ebola and tuberculosis.

Other genomics news

As reported by GenomeWeb’s Huanjia Zhang, researchers at the State University of New York at Albany have developed a way to directly sequence RNA using mass spectrometry. They published their study in Nucleic Acids Research in July.

UK-based Tagomics has launched LiquiPath, a cell-free DNA blood test for drug safety monitoring. LiquiPath combines Tagomics’ epigenetic technology, Activace, with methylation data to trace circulating cell-free DNA back to its tissue of origin. Tagomics has also launched an early-access program with AstraZeneca already among its pharma partners.

Elsewhere on SubStack

More from Nava Whiteford at ASeq: DNA Electronics, a UK-based startup that has raised millions to build a DNA sequencer, may be shutting down, according to a LinkedIn post from a former employee.

ASeq Newsletter

DNAe Dead

I’ve been hearing rumors that DNA electronics is dead for a while, but this is the first public post I’ve seen…

Read more

12 days ago · 1 like · 5 comments · Nava Whiteford

DNAe did not respond to Ion Genomics’ request for comment.

My Omics Reading List

Holley, G., Eggertsson, H.P., Kristmundsdottir, S. et al. “An Icelandic pangenome reference.” Nature. Aug. 19, 2026.

—

Qiu et al. “A cross-organ single-cell analysis of hypertension.” Science. Aug. 13, 2026.

Working in mice and rats, the authors

—

Kinney, et al. “UNCOVERseq enables sensitive and controlled gene editing off-target nomination across CRISPR-Cas modalities and systems.” Nature Communications. Aug. 11, 2026.

Elsewhere on the internet

President Donald Trump has nominated Heidi Overton, a White House aide and physician, as FDA Commissioner.

From the Reuters article on her nomination:

Chris Meekins, a former Trump health official who ​is now an analyst at Raymond James, [...] wrote in an analyst note on Wednesday that Overton has “seemingly no real ​experience running anything of consequence.

“Industry will view this ​pick as extremely troublesome and FDA ⁠career staff will continue to flee the agency in my view,” Meekins wrote. “Any progress made since Makary’s departure is likely to be quickly reversed if she is confirmed.”

For those of us who missed it, the previous commish, Marty Makary, “resigned ‌in May after 13 months in the job, following clashes with White House officials over flavored vapes,” among other issues.

Alongside the interim results, the company announced a new global cross-licensing agreement with an unnamed diagnostics company and a deal with MyOme to incorporate nanopore sequencing into MyOme’s Zenith rare disease platform.

Under the diagnostics deal, Oxford Nanopore will recognize approximately $20 million in licensing fees in the second half of the year, along with $15 million in committed product purchases over fiscal years 2027 and 2028, and an ongoing net royalty calculated as a low-to-mid-single-digit percentage of revenues from certain products incorporating the licensed intellectual property.

The company did not immediately respond to a request for more information. Additional details of the MyOme deal were not disclosed.

The Oxford, UK-based nanopore sequencing company reported H1 2026 revenue of £116.7 million, up from £105.6 million in H1 2025, and up 12 percent year over year on a constant currency basis. The results came in below management expectations, as previously disclosed, due to weakness in China and the Middle East.

PromethIon products led growth, with revenue up 16 percent year over year to £59.1 million from £51.1 million a year ago, driven by strong demand for the P2i instrument. MinIon revenue grew 4 percent to £28.8 million from £27.6 million a year ago. Other revenue, comprising kits, services, and other devices, grew 7 percent to £28.9 million. By product type, devices and services revenue grew 33 percent to £37.0 million, while consumables revenue grew 3 percent to £79.7 million, with growth muted by the completion of large research contracts and the decline in China.

By end market, research revenue grew 5 percent to £76.0 million from £72.1 million a year ago, reflecting large-scale cohort programs in Europe, the Middle East, Africa, and India (EMEAI) offset by the roll-off of Genomics England and UK National Institute for Health and Care Research (NIHR) contracts. Clinical was the fastest-growing segment, rising 35 percent to £17.6 million from £13.0 million a year ago, driven by growth across all geographic regions. Industrial revenue grew 6 percent to £13.7 million, and biopharma grew 25.0 percent to £9.5 million from £7.6 million, driven by mRNA, direct RNA sequencing, and biomanufacturing quality control applications.

The EMEAI region delivered the strongest growth, with revenue up 25 percent to £55.6 million from £44.6 million a year ago, driven by clinical and biopharma momentum and large-scale cohort sequencing programs. Americas revenue grew 9 percent to £39.1 million from £36.0 million, though growth was slower than anticipated due to the timing of customer orders and contract wins; approximately £900,000 of revenue slipped into Q3 due to shipment timing. Asia-Pacific revenue declined 12 percent to £22.0 million from £24.9 million, driven by a 16 percent decline in China due to enhanced export control restrictions and the completion of the PRECISE II contract in Singapore.

Comprehensive loss for the period was £48.0 million, compared to a loss of £71.8 million in H1 2025.

R&D expenses fell 16 percent to £36.9 million from £44.1 million a year ago, reflecting a reduction in headcount from 2025. SG&A expenses fell 9 percent to £86.4 million from £95.1 million a year ago.

As of June 30, Oxford Nanopore had £234.5 million in cash, cash equivalents, and liquid investments.

Oxford Nanopore maintained its full-year 2026 constant currency revenue growth guidance of 16 to 20 percent, excluding the $20 million non-recurring cross-licensing fee. Including that fee, it expects full-year constant currency growth of approximately 23 to 27 percent.

Oxford nanopore also announced a long-range yearly revenue target of more than $700 million in 2030.

“Our next chapter is about harnessing the collective strength of Oxford Nanopore to deploy our differentiated technology seamlessly and at scale across an ever-expanding customer base,” CEO Francis Van Parys said in a statement. “Our focus is clear: to accelerate adoption in our fastest-growing end markets and realise our longer-term ambition to build Oxford Nanopore into a $1 billion-and-growing annual revenue business.”

As part of the expanded collaboration, announced Aug. 11, Nucleai has analyzed a large dataset of H&E and immunohistochemistry whole-slide images from several clinical studies spanning multiple oncology indications, integrating the tissue analysis with clinical outcomes data.

“Precision oncology is entering a new phase, where understanding tissue architecture is becoming just as important as understanding molecular alterations,” Nuclei CEO Avi Veidman, said in a statement. “Tissue Intelligence is becoming a foundational capability for precision medicine, helping identify the patients most likely to benefit while enabling pharmaceutical companies to translate tissue biology into reproducible biomarkers that improve the speed and success of oncology drug development.”

Israel-based Nucleai’s platform combines pathology, spatial biology, and clinical outcomes data. In a statement, Nucleai said it has generated candidate spatial biomarkers and biological insights.

The Gilead collaboration is the latest partnership Nucleai has announced in the last year, including a project with the UK’s University of Glasgow on colorectal cancer biomarkers and a partnership with Sirona Dx on spatial proteomics.

My guest this week, my dear friend and fellow journalist William Herkewitz, is reporting on the recent Ebola outbreak in the Democratic Republic of Congo as well as tuberculosis around the world. A former communications director for now defunct USAID in multiple African countries, he has seen firsthand how funding from the US helped keep people healthy and infectious disease at bay.

In the old funding regime, a USAID partner organization might have been in place to raise the alarm about a hemorrhagic fever that looks a lot like Ebola and that could have led to a faster response, Herkewitz told me.

“And a much faster response for this outbreak absolutely could have been the difference [in avoiding] the trajectory we’re on now, which is maybe the largest Ebola outbreak in history, one that for sure is going to be going on for years.”

We discuss what happens when dollars disappear, and with them, networks of people and trust. We also evaluate PCR, next-generation sequencing, and paper-based diagnostic tests in these remote and resource-limited settings.

For more of Will’s reporting, check out The Rift Valley Dispatch, also on Substack.

The Rift Valley Dispatch

A Newsletter About Global Disease, Medicine, and Money. Written by Kenya-based journalist, William Herkewitz.

The podcast is also available on Apple and Spotify.

Show Notes

Will’s New York Times op-ed. “Why We Couldn’t Sell America on U.S.A.I.D.”

His appearance on MS NOW (formerly MSNBC) to discuss his op-ed:

“Rollout of 5,000 Near Point-of-Care TB Test Systems in 13 Countries Begins With $50M in Funding,” by Madeleine Johnson

The beer I referenced in the opening anecdote about the bar that was closed on weekends, Zlaty Bažant a.k.a. the Golden Pheasant.

https://www.beeradvocate.com/beer/profile/1195/3349/

Cover art: Colorized microscope image of Ebola virus. Image credit: CDC Global via Wikimedia Commons.

The designation applies to the proposed use of SimpleScreen Lung in adults ages 50 to 80 with at least a 20 pack-year smoking history who are not currently participating in guideline-recommended lung cancer screening. The test would be ordered by a healthcare provider and is designed to detect early signals of lung cancer from a standard blood draw.

“The Breakthrough Device Designation from the FDA recognizes the substantial unmet need for lung cancer screening and accelerates our path to bring SimpleScreen Lung to patients,” Freenome CEO Aaron Elliott said in a statement. “By identifying high-risk individuals who would benefit from low-dose computed tomography (LDCT), we believe our test will complement the current standard of care and improve detection rates. We continue to advance the clinical work necessary to submit SimpleScreen Lung for FDA review.”

SimpleScreen Lung builds on the methylation and next-generation sequencing platform underlying SimpleScreen CRC, Freenome’s colorectal cancer screening test that received FDA approval last month.

The lung test incorporates methylation and proteomics data; a positive result would be followed by LDCT imaging, while a negative result would not rule out cancer.

Freenome said it has presented initial development data at the 2026 AACR Annual Meeting and is continuing evaluation through its prospective PROACT LUNG study.

Under the collaboration, announced Aug. 12, Latitude testing will provide circulating tumor DNA (ctDAN) dynamics at multiple timepoints as patients are treated with KUP-101.

“By leveraging the power of innate immune stimulation and the induction of trained immunity, KUP-101 represents a fundamentally different way of approaching hard-to-treat cancers,” Johanna Holldack, Kupando CEO and founder, said in a statement. “Natera’s Latitude test can provide valuable insights into treatment response dynamics, helping us better understand the molecular activity of this novel therapeutic approach and advance our clinical development program for patients with advanced solid tumors.”

KUP-101 from Germany-based Kupando is designed to activate the innate immune system and induce trained immunity. In a statement, Kupando said it has potential as a tissue-agnostic treatment across multiple solid tumor types, either alone or in combination with other therapies.

Former Oxford Nanopore Technologies CTO Clive Brown wasted no time serving up food for thought:

The full post continues:

… (in the west). The combined IP portfolio would be formidable and the combined entity - a juicier acquisition target. ONT gets on NASDAQ and likely a valuation uplift with $450M+ revenues. ONT shareholders would need to be in the driving seat. New board for ONT.

Over on LinkedIn, genomics commentator Alex Dickinson picked up the idea and ran with it, adding the following points, among others:

1. PacBio and ONT have been duking it out over a small part of the total sequencing market for years.

2. The costs of operating as a single publicly-traded company would help the long-term economics.

3. A deal could give ONT shareholders a large stake in a company based and traded in the US, where there’s a lot more money sloshing around and more likely to invest in genomics.

4. Such a deal could circumvent PacBio’s debt issues (which are above my paygrade.)

I don’t know if this helps the case to make this happen or hurts it, but my own thoughts are that PacBio and ONT have developed subniches within the long-read market resulting in mostly non-overlapping customer bases (excluding core labs.) Oxford Nanopore has done well with researchers who need speed and flexibility, including in metagenomic sequencing, especially in the field. PacBio had leveraged its accuracy to get into more clinical and human health-related applications.

Nanopore sequencing is finding a place in the clinic, again using speed as its differentiator, for rapid newborn whole-genome sequencing and intra-operative classification of brain tumors. Both are useful in telomere-to-telomere genome assemblies.

I recently spoke to new PacBio CEO Mark Van Oene for feature on the leadership transition (more on that next), we discussed whether it was important for PacBio to operate as a standalone company. He thought that it should at least stand alone. But could it and ONT benefit from standing together?

I published that feature story earlier today. According to both Van Oene and the man he replaced, Christian Henry, the succession was “always part of the plan” from the moment Henry brought Van Oene on board as chief operating officer.

I also delved into the challenge facing Van Oene:

Ion Genomics News

Check out this Raw Reads entry, a collection of everything 10x Genomics CEO and Cofounder Serge Saxonov said about AI on his Q2 call with Wall Street analysts:

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Other genomics news

Speaking of 10x: Spatial Genomics, a company commercializing sequential fluorescence in situ hybridization (seqFISH) technology, and CalTech, where researcher Long Cai developed the tech, have sued 10x Genomics in US Federal court, alleging patent infringement.

Specifically, the plaintiffs allege that 10x’s Xenium spatial analysis instrument infringes several patents, including US Patent No. 10,457,980 titled “Multiplex Labeling of Molecules by Sequential Hybridization Barcoding.”

The plaintiffs have asked the court to file their complaint under seal. A redacted version of the complaint says Spatial Genomics sells an instrument called GenePS, based on seqFISH technology; however, it’s unclear how many boxes the company has placed.

According to a paper published earlier this year in Chemical & Biomedical Imaging, seqFISH offers the ability to:

connect dynamic phenotypes exhibited by individual cells with their corresponding genotypes. However, widespread adoption of this strategy has been constrained by two technical challenges: (1) compromised in situ genotyping efficiency due to nonspecific fluorescent probe aggregation in confined microfluidic growth chambers, and (2) the reliance on high-copy-number plasmids to ensure genotyping sensitivity, which often distorts dynamic phenotypes and perturbs normal physiology during live-cell imaging.

Broken String Biosciences has launched an extension of its INDUCE-seq technology to support adenine base editing workflows. The company has also launched an early access program where it plans to work with researchers developing genome-editing therapies.

Elsewhere on SubStack

Nava Whiteford brings us a view of the electronic guts of a MinIon flow cell, based on a tear-down video from YouTube.

ASeq Newsletter

MinION Disassembly/Teardown

Mike has posted a teardown of the MinION and flowcell over on Youtube…

Read more

15 days ago · 3 likes · Nava Whiteford

“As previously estimated this is likely a [bill of materials] cost in the $200 range,” he wrote. That’s compared to the list price of $840 for a MinIon Flow Cell.

Over at BridgeCross Bio, Matt Marlowe reports that WuXi AppTec has scored an early win in its fight its inclusion on the so-called 1260H list recently issued by the US Department of Defense.

According to the opinion, the case has revealed that a DoD report mistakenly said that a Chinese government-linked investment fund owned 5.2 percent of WuXi AppTec, when in reality that figure was percentage of the total fund allocated to shares in the company.

The fund appears to only own approximately $200,000 worth of shares, not 5 percent of the company, which would have been worth hundreds of millions of dollars.

Also, another piece of evidence used by the DoD turned out to be documents listing WuXi AppTec as a “third-party laboratory” by pharma giant Novo Nordisk as it sought to do business with China’s Ministry of Science and Technology.

BridgeCross Bio

WuXi Won in Court. Can It Undo the Chill?

WuXi AppTec has won an important first round in its legal battle with the US Department of Defense…

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14 days ago · Matt Marlowe

However, damage has already been done. “In the weeks since publication, WuXi’s customers and suppliers have canceled contracts, terminated longstanding relationships, and moved their business to competitors,” the judge noted.

The incompetence on display certainly raises questions about other additions to the list.

My Omics Reading List

Eapen, et al. “An Integrated Spatial Multi-Omics Workflow for Sequential RNA and Protein Profiling in FFPE Tumor Tissue.” Cancer Research Communications. Aug. 7, 2026.

King, et al. “Generative design of bacteriophages with genome language models.” Science. Aug. 6, 2026.

Researchers at Stanford University and the Arc Institute used the Evo genomic language model to computationally design complete bacteriophage genomes from scratch, then tested them against Escherichia coli that had evolved resistance to a natural phage.

Elsewhere on the internet

“This was always the plan,” Van Oene told Ion Genomics, dating back to 2021 when ex-CEO Christian Henry recruited him to PacBio from Illumina. “The conversation from the beginning was, ‘Mark, come help me transform PacBio and round out your career and we’ll work through a succession plan when the timing’s right,’” he said.

According to Van Oene, that succession plan was officially put in place with the board last year. He took another step closer earlier this year when PacBio removed its VP of Global Sales, prompting Henry, who had been overseeing the company’s commercial operation, to swap responsibilities with Van Oene, who had been in charge of operations and R&D. This swap was documented in a filing with the US Securities and Exchange Commission.

When Van Oene and Henry cut PacBio’s payroll with yet another round of layoffs in recent weeks, they decided it was time to make the switch.

“The timing of the decision was more recent, but the plan was always there for this transition to happen here over the course of this year,” Van Oene said.

Given the layoffs —– the company’s third round in as many years —– and the fact that they’d have to soon report second quarter revenue below the prior-year period and Wall Street’s expectations, it’s worth considering whether other forces were in play. After a year of recovery against a bad 2024, progress on revenue growth has stalled the past two quarters. However, whether Henry’s seat was actually getting hot, and where that heat may have been coming from, is unclear. Henry isn’t leaving the board yet and will continue to advise Van Oene in an official capacity until the end of the year.

Regardless of how he got here, Van Oene is now strapped into a two-stage rocket of Henry’s making. Over the next year or two, Van Oene will need to pull off a transition to new reusable consumables that allow PacBio a price per genome that is at least competitive with short-read sequencing. Following that, he’ll need to correctly time and execute the launch of PacBio’s next instrument, a production-scale long-read sequencer that can make use of the lower sequencing costs while meeting the demands of larger human sequencing endeavors, such as clinical and population sequencing.

How he pilots this stretch will determine whether PacBio finally takes off or if it crashes back down.

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For his part, Henry said he has “no regrets.” That includes the 2021 acquisition of Omniome —– which cost $316 million in cash and approximately $250 million in stock upfront, plus at least $96.2 million in cash milestones —– and the 2023 acquisition of Apton Biosciences for $110 million. These deals fed the launch of Onso, a benchtop, mid-throughput, short-read sequencing platform that performed poorly amidst strong competition. Earlier this year, PacBio sold the scraps of its short-read technology portfolio, mostly from Apton, to Illumina for just $48.1 million.

“The decision about believing in the short-read side didn’t play out the way we had hoped,” Henry told Ion Genomics. However, he defended the strategy behind those decisions. “If interest rates and the academic market hadn’t blown up, it likely would have worked.”

Kyle Mikson, a stock analyst at Canaccord Genuity who covers PacBio, agreed. “In the moment it was the time to make these aggressive decisions and high growth potential. Money was flying [around],” he said. “But looking back, stuff didn’t work out. You only get so many chances.”

While a steep price to pay, the ability to launch Onso along with Revio appears to have placed PacBio salespeople into more conversations and deal rooms. Those likely helped set the stage for new conversations Van Oene will have as he tries to capitalize on the move to cheaper pricing and higher-throughput, albeit only for long reads.

On their Q2 call with analysts, PacBio officials noted that the transition to the SPRQ-Nx reusable consumables is providing a drag on revenue, as customers work through stockpiles of older products.

At the same time, “customer enthusiasm for SPRQ-Nx has remained strong since full launch,” Van Oene said on the call. Customers are installing the software needed to facilitate usage of SPRQ-Nx and “many of our high-throughput customers are currently in the process of validating the new multi-use workflows in their own laboratories,” he added.

The high-throughput long-read instrument is coming soon. PacBio officials said that they’ll soon be “[moving] past development spending” on it. Van Oene added that he knows he needs to “keep it on track.”

“The challenge has always been the throughput of the technology and the economics,” Van Oene said. “We’re finally at that point with SPRQ-Nx, where it’s getting close enough that it’s getting people to pay attention to using our data for much larger scale projects.”

Van Oene has given a lot of thought to where PacBio is headed. He even took responsibility for the recent layoffs in marketing, saying he “really wanted to refocus the commercial energy towards the clinical opportunity we’re seeing for rare disease and whole genome sequencing in Europe.”

What he hasn’t yet given thought to is who might succeed him, whenever that time comes. “I am a huge fan of succession planning and developing talent from within,” he said. “So it will be a priority for me, but not immediately.”

Under the agreement, the parties exchanged mutual releases with no payment by either side, and the case will be dismissed with prejudice, pending court approval.

According to the filing, the defendants continue to deny the allegations and any wrongdoing and agreed to the settlement to avoid the cost and uncertainty of continued litigation.

The lawsuit, filed in October 2023 in the Delaware Court of Chancery by Icahn Partners, challenged Illumina’s approximately $8 billion reacquisition of Grail, announced in September 2020. The plaintiffs alleged that Illumina’s board breached its fiduciary duties by closing the deal in August 2021 despite regulatory scrutiny in the US and Europe.

The European Commission (EC) later ordered Illumina to divest Grail and fined the company $476 million for closing the deal before EU merger review concluded, while the US Federal Trade Commission separately ordered a divestiture.

Illumina spun off Grail in June 2024 via a public offering of stock in the early-cancer detection company. Just a few months later, a European court ruled that the EC didn’t have jurisdiction to review the deal and the fine was rescinded.

The settlement resolves the Icahn-led suit but leaves three other derivative lawsuits brought by a variety of retirement systems and pension funds still pending. The settlement also releases any potential claims by Illumina against Andrew Teno, who won election to Illumina’s board backed by Icahn, related to the sharing of confidential or privileged information during the litigation.

The Delaware Court of Chancery is scheduled to hold a hearing on Nov. 2.

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Single-cell sequencing has for the last several years already formed the basis of AI foundation models of cells, so it’s no surprise that 10x Genomics CEO and Cofounder Serge Saxonov is tracking that field closely.

I’ve spoken to him about it personally, but wasn’t sure if he’d commented so much about it publicly, as he did during the company’s second quarter financial results call. AI and its impact on 10x came up in both Saxonov’s prepared remarks as well as in the Q&A session.

The following is everything Saxonov said about AI during the call:

Serge Saxonov (00:00) — CEO and Co-founder, 10x Genomics

… Over the past several quarters, products like Flex Apex have enabled a new generation of this work, particularly in biopharma and translational research. … A significant trend in single-cell has been an increase in large-scale perturbation experiments to map biological mechanisms and resolve causality. We’re finding that Flex Apex is becoming the standard assay for these experiments because of its scalability, robustness, and sensitivity. While we see significant flex Apex adoption across all customer segments, the uptake of Apex in biopharma has been particularly strong, driven by the application of perturbation screening to target identification.

The value of these studies is also increasing because of the progress in AI, which helps derive mechanistic insights from the large amounts of data generated by these experiments. As we have discussed before, we believe AI represents a significant and structural tailwind for our business. AI has enormous potential to transform biology and human health, but realizing that potential depends on generating vastly more of the right kinds of data. The key bottleneck for AI-driven progress in biology is the same bottleneck we identified when we started the company. Biology is incredibly complex; we understand only a tiny fraction of it, and solving that complexity requires measuring biological systems at massive scale and high resolution. We build single-cell and spatial technologies for precisely that purpose, which is why they are now being deployed by so many of our customers to train AI models.

On the academic side, there are multiple well-known pioneering efforts, such as those led by [BioHub] and the Arc Institute, dedicated to building virtual biology models, but we’re also seeing a wider shift, where more of basic scientific research entails training AI models. This shift is driven bottom up by decisions of individual scientists, as well as top down by philanthropic and government funding priorities, such as those outlined in recent proposals from the White House, a similar shift is also starting to happen by pharma with a rapid growth in AI-focused investments. Initially, much of the AI work in drug development has focused on the chemistry side of the process, on creating molecular interventions once a target is known.

Going forward, we expect increasing investments to be made in modeling biology at the cell and tissue level to unlock new targets and to predict drug response in patients.

This work is also precisely what our tools enable, and why we anticipate a very large opportunity for our technologies over time. Most pharma companies now have strategic mandates to leverage AI to speed up drug development and increase the probability of success. At the same time, there is a rapidly growing number of biotech companies that seek to transform drug development using AI. More and more of them are focused on building sophisticated virtual models of human biology.

Customers overwhelmingly choose our products because they deliver the highest data quality, the largest scale, the widest biological context, and the most powerful multiomics capabilities. It has become increasingly clear in the field that all of these considerations are critical for building high-quality, generalizable, and useful models.

It should be noted that building better models is only a part of the AI story. For years, one of the biggest barriers to broader adoption of single-cell and spatial biology has been the bioinformatics expertise required to analyze increasingly rich datasets. Advances in agentic AI are beginning to remove that bottleneck.

We believe that will make single-cell and spatial analysis accessible to a much broader community of scientists, while increasing the value of the underlying data.

Together, these trends reinforce our conviction that single-cell and spatial biology are foundational to the future of basic science and drug discovery research. AI is increasing both the demand for high quality biological data and the ability of researchers to extract insights from that data. We believe those two forces will reinforce one another over the coming years.

…

Q&A

Kyle Mikson (Canaccord Genuity) (17:31)

Hey guys, thanks for the questions. Congrats on the quarter. Multi-part question first on instruments. So, on Atera, great to hear all the demand and the interest and all that, but why remain conservative with that expectation for the second half… And secondly, just quickly, Serge, on AI, getting a lot of questions on your differentiation. You obviously have a lot of, you know, strong push there, but what really sets 10x apart, to directly benefit from that? And can you talk about any tangible revenue that you’ve recognized so far. Thanks.

Saxonov (18:28)

Thanks, Kyle. So just like for your first question on Atera, as we talked about in our prepared remarks, the demand has been extraordinary, and that’s not the constraint here. Right? The constraint is actually you know the manufacturing capacity to to ship the units this in the second half of the year, and we continue to expect to be able to ship 40, which is what we said in the last call, and still continues to be the case going forward.

[Editor’s note: Saxonov did not appear to address Mikson’s question about AI-related revenue.]

Michael Ryskin (Bank of America) (31:21)

Hey, thanks, guys. I want to go back to chromium and the single-cell platform. You know, chromium consumables are kind of flat, effectively quarter over quarter, just sequentially throughout the year. And instruments were a little bit on the lighter side. You know, I understand a lot of focus on spatial and maybe Xenium, but just we’ll have to dig into more to what you’re seeing there. You know, you’ve got things like the Billion Cell Atlas ongoing. You’ve got things like Perturb-seq ongoing. You’ve been talking about AI-driven drug discovery, which I think should tap into single-cell a lot. Why aren’t you seeing a little bit stronger numbers in Chromium? Is it all really tied to Flex, or is there anything else going on? And maybe if you could just quantify what you’re seeing, give us any tangible metric that we could sort of latch onto for AI-driven demand, just so we could sort of figure out, you know, how big it is for you right now in Q2. Thanks.

Saxonov (32:18)

Yeah, Mike, thanks for the question. So yeah, I mean, on single-cell. I would say the first order dynamic by far is that sort of transition that I talked about earlier, the rise of Flex Apex and transition of some of the other products to that to that assay. Again, it’s had a really nice pickup, a really nice momentum. We expect that to continue, and as a result of that, yeah, the the volume growth has been quite consistent and very robust and very encouraging, and a lot of the growth is in fact driven being driven by kind of emergence of AI applications and also more large scale experiments that involve larger cohorts and kind of distributed sample collection that that Flex is particularly great for.

That also has a bit of an influence, in fact, on instruments in the sense that because of the capability enabled by Flex of having this distributed sample collection and then centralization of processing, that naturally leads to more centralization to our service providers, to core labs, to big labs, which which kind of reduces the necessity to be placing instruments at every single lab, and also you know at this point we do have a lot of chromium instruments out there, so accessibility is generally not an issue at all.

So, overall, the dynamics around single-cell are very similar to what we’ve been describing for the last couple of quarters, and we expect that to continue in the over the rest of the year, and I do expect, like I said earlier, yeah, all the people or like large majority of the people who intend to transition to Apex will have largely done so by the end of the year, and that should put us in a good position to you know keep driving that sort of robust reaction growth, but also having it be translated into more top-line impact as well.

As far as the AI question is concerned, there’s a lot of layers to that, and I think it’s really, really important to set context here, which is what I did earlier as well with my my prepared remarks,

Like I said earlier, and I think there’s like a wide sort of recognition of that that AI is now a major structural tailwind for us, and because you know what these big AI models need is precisely what we have built over the years, and AI at this point, one way in one shape or form, is becoming pervasive across just about all of our customer segments.

At this point, you know there isn’t really a large project out there where AI isn’t like either a big driver or at least like a you know an an important influencer. And even small scale projects, I think in many instances are performed with an eye toward feeding the data into AI models, and so you know in some cases AI is a driver of demand. In some cases it’s an influencer, and sometimes an accelerator.

One issue here is that AI can mean a lot of different things, and also the landscape is changing quite fast, and so that’s why I went specifically in in a bit more detail in explaining how AI, for example, is used potentially in drug in the context of drug development for the parts specifically to measure biology. You know, if you think about the three stages of drug development: target ID, to understand the biology of what targets to go after, the chemistry; the middle part actually making the drug, the molecule; and then figuring out which patients to give the drug to.

And so there are some parts of our revenue where unambiguously AI revenue is coming from those, like tech bio companies, some large academic projects, but there’s also others where there is a mix of big pharma companies that we know are developing these AI models of biology, but also using our products for other for other goals, and same thing in academia, and so there’s a mix.

So right now at this stage, I’d say it’s still very early, but the opportunity is massive, and our products and technologies are particularly well positioned for this opportunity. And you know, as we go forward, and as these categories grow, we’ll provide more granular color on them and and and how to think about sort of numbers around them.

Matt Larew (William Blair) (38:03)

Hi, good afternoon. You referenced a number of the larger projects you’re working on with respect to AI, and also on the translational side. And in some cases, you know, customers adopting or increasing use of multiple platforms. I’m curious as you’re having these these discussions about larger projects, multi-year projects, kind of how important the suite of products that you have, and you know, software and analysis tools where there’s perhaps some integration or at least familiarity, you know, how that kind of ecosystem might be having an effect as customers think about you know longer term projects versus you know the merits of the platforms on their own.

Saxonov (38:48)

Yeah, really interesting question. Well, you know the first order answer I would say is that the platforms by themselves, whether you look at single-cell and spatial, have really strong merits just to stand on their own. I would say, and certainly is really appealing in many ways to our customers. You know, if you think about, for example, Flex Apex, really, really high sensitivity, incredible scalability, huge robustness. This is actually really important for AI in particular, a subtle point where it works across many different tissue types, many different cell types, many different contexts, and increasingly is becoming critical. So, if you want to build AI models that are useful that generalize, you really need to be able to measure lots of different contexts. You can’t be measuring the same cell line over and over again, for example, and Flex is incredibly great for that.

Also, another sort of emerging trend is, and maybe it’s a little bit your question too. Here is multiomics, being able to measure other modalities, and again, we have unmatched strength on that on along that dimension, and and yeah, certainly there is a there is an attractiveness to be able to do yeah to to train your models from a spatial perspective as well as from single-cell, and we certainly provide kind of these kinds of solutions to our customers, and also yes on the software side something we haven’t talked that much about, but of course we have invested in software fairly materially from the beginning of really the beginning of the company, and in particular is becoming important here because the data sets with Apex and with Atera are getting to be very large, especially for training AI models, and we have made quite a number of advances specifically to enable people to to run large-scale experiments in a straightforward kind of ergonomic manner.

So all of these pieces together do tie out to provide really compelling solutions for our customers, certainly much much more compelling than any other potential alternative on the market.

Puneet Souda (Leerink) (45:51)

Yeah, hi Serge and team. Thanks for taking my questions here. … On the AI side, I mean it does appear that the biology foundation models or the virtual cell models will require fundings in the scale of 100 million dollars or something closer in order to build the data for those models. Can you maybe just elaborate on what are the line of sight to the major large grants or funding sources right now that you see and the timing for those to land into you know 10x’s revenue. Thank you.

Saxonov (47:11)

[...] You know, as far as AI and funding is concerned, I think there’s a lot of work at the highest levels happening where I kind of spoke to that, where there’s a general kind of reappraisal of funding flows.

As people put in their priorities, whether it’s sort of from governments or from various philanthropic organizations, we anticipate that that will ultimately translate into you know more deployment of single-cell on spatial and ultimately more revenue to us.

Operator (57:21)

There are no further questions at this time. We have reached the end of the Q&A session. This concludes today’s call. Thank you for attending. You may now disconnect.