Hydrogel-Based Axon Model Improves Early Testing for MS Remyelination Therapies

Axons—the long, cable‑like projections that relay electrical signals across the nervous system—depend on tightly wrapped layers of myelin to keep those messages fast and reliable. When this insulation is damaged, as in multiple sclerosis (MS) and other neurodegenerative diseases, signal transmission slows and neurons eventually degenerate. Although oligodendrocytes can repair myelin early on in the process, this capacity declines with age and repeated inflammatory attacks, leaving researchers searching for therapies that can restore myelin more effectively.

A team at University College London (UCL) has now developed a more physiologically realistic way to study how myelin forms—and how potential drugs might influence that process. Their new hydrogel‑based axon model, described in Nature Methods in a paper titled “Tunable hydrogel‑based micropillar arrays for myelination studies,” recreates both the geometry and softness of real axons. The platform is designed to address a longstanding problem in the field: many drug candidates that appear promising in rigid, plastic‑based lab models ultimately fail in human trials.

“To stop MS, we need therapies that repair myelin,” said senior author Emad Moeendarbary, PhD, professor of cell mechanics and mechanobiology at UCL and CEO of BioRecode. “Promising drug candidates in the past have failed when tested in human patients. One factor might be that laboratory models do not replicate the basic physical properties of the human brain.”

The UCL team engineered vertical micropillars—each tens of times thinner than a human hair—using a microfabrication process called photolithography that allowed them to precisely tune diameter, spacing, and stiffness. Unlike earlier artificial axons made from hard polymers, these pillars are composed of polyacrylamide hydrogel, a material whose elasticity can be adjusted to match the ~5 kPa softness of native axons. As the authors noted in the paper, the system “mimics the three‑dimensional architecture and softness of axons,” enabling oligodendrocytes to form “multilayered compact myelin” around the pillars.

The researchers seeded the hydrogel pillars with human and rodent oligodendrocytes and tested several candidate remyelination drugs. When the pillars were tuned to realistic softness, drug performance dropped—suggesting that overly rigid models may have produced misleading hits in the past. “Our work suggests that commonly used rigid models, hundreds of times stiffer than real axons, can generate misleading drug hits,” Moeendarbary said. “We believe that our more life-like model can be used as a more robust early test of drug candidates and as a platform to discover new drugs.”

The study also marks the first demonstration of compact, multilayered myelin grown from human oligodendrocytes in a fully hydrogel‑based system. The platform’s design allows high‑content imaging, transcriptomic profiling, and systematic variation of mechanical cues—capabilities that could help researchers dissect how myelin forms and why it fails in disease.

Building such a soft, microscale structure was not trivial. “Hydrogel is a close mimic of living cells… but to fabricate a soft hydrogel at such a small scale is not an easy task,” Moeendarbary noted, crediting the five years of work led by PhD student Soufian Lasli and Claire Vinel, PhD.

By more faithfully recreating the physical environment of the brain, the UCL team hopes their model will provide a more reliable proving ground for remyelination therapies before they reach clinical trials.

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STAT+: Medicare Advantage plans win extra $18.6 billion as feds cut star ratings measures

The Trump administration is slashing the number of quality and care measures that Medicare Advantage plans will be graded on, a move that will funnel an extra $18.6 billion toward health insurers over the next decade.

The final regulation, released Thursday by President Trump’s Centers for Medicare and Medicaid Services, is significantly more beneficial for the insurance industry than originally expected. CMS previously estimated these changes to star ratings would cost $13.2 billion between 2028 and 2036 when the rule was proposed in November.

The extra funding from star ratings provides a sizable buffer for Medicare Advantage insurers, which are awaiting final payment rates for 2027 and experiencing higher medical claims. Insurers have lobbied Trump officials for more money in their baseline payments, and to scale back changes in how they record the sicknesses of their members. The government is supposed to release that regulation no later than April 6.

Continue to STAT+ to read the full story…

Health Beliefs and Perspectives of Parents Regarding Human Papillomavirus Vaccination in Kuwait: Qualitative Study

Background: After breast cancer, cervical cancer (CC) is one of the leading causes of female mortality. CC accounts for more than 7.5% of female cancer deaths worldwide. Human papillomavirus (HPV) is the most common sexually transmitted disease in women and the leading cause of CC in almost 99% of all CC cases. HPV vaccination could prevent up to 70% of HPV-related CC and 90% of genital warts. HPV vaccination is the bedrock of primary prevention and helps reduce the incidence and death rates of HPV-associated CC. Objective: The study aimed to understand the knowledge, health beliefs, and perspectives of Kuwaiti parents regarding HPV vaccination, with the goal of developing a health promotion policy and introducing a national immunization program in Kuwait. Methods: A total of 37 participants were evaluated using purposive sampling to select 20 (54%) participants for one-on-one semistructured interviews. We wanted to include both participants (male and female parents) with primary education (diploma or below) or secondary and higher education (bachelor’s degree and above). We had four categories (male parents/guardians with a diploma or below, male parents/guardians with a bachelor’s degree or above, female parents/guardians with a diploma or below, and female parents/guardians with a bachelor’s degree or above) with at least 5 participants in each category, which gave us 20 participants. Semistructured interviews were based on the Health Belief Model (HBM). The data were thematically analyzed using an inductive approach, generating themes through the theoretical framework of the HBM, and theme extraction analyses were managed on a semantic level. Results: We identified 7 main themes containing 20 subthemes. The seven themes were (1) knowledge and awareness about HPV infection and vaccination (3 subthemes); (2) perceived susceptibility, which is explained by the HPV infection effect based on sex (2 subthemes); (3) perceived barriers to HPV vaccination (8 subthemes); (4) perceived benefits (1 subtheme); (5) perceived severity (2 subthemes); (6) perceived efficacy (2 subthemes); and (7) cues to action (2 subthemes). Conclusions: The HBM framework is beneficial for Kuwait’s HPV vaccination campaign. The correlation between sexual intercourse and the HPV vaccine frequently adds complexity to the decision-making process about immunization. This study demonstrates that positive cues to action from health care practitioners and educational vaccination benefits can overcome perceived barriers among parents related to stigma and religion. It is essential to conduct more such research to guide the development of interventions aimed at promoting adoption of the HPV vaccine.
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EPA to put microplastics on study list of contaminants in drinking water

The Environmental Protection Agency on Thursday proposed including microplastics and pharmaceuticals on a list of contaminants in drinking water for the first time, a step that could eventually lead to new limits on those substances for water utilities.

EPA Administrator Lee Zeldin said the agency is responding to Americans who have worried about plastics and pharmaceuticals in their drinking water. The gesture also aims to hand a win to Health Secretary Robert F. Kennedy Jr.’s MAHA movement, which for months has pressured Zeldin to further crack down on environmental contaminants.

Read the rest…

AI In Silico Multi-Omics Technique Cuts Therapeutic Development Costs

Bringing a drug from discovery through clinical trials takes too long and is too expensive, with preclinical costs alone estimated at $15 to $100 million. Employing artificial intelligence (AI) early in the process can lower those costs dramatically.

AI itself isn’t a panacea, though, Jayson Uffens, CTO and chairman of GATC Health, tells GEN. Instead, “Smart computing makes smart people smarter. There’s still a lot of expertise from people on the ground who bring a lot of value—maybe the ultimate value—to the mix.”

GATC Health, an AI-driven therapeutic discovery company, uses AI to raise the floor on opportunities to get high-potential compounds into human studies faster and thereby drive success.

Its proprietary approach to hit and lead identification and program derisking can cut preclinical development costs, according to Uffens, who maintains that the earlier AI is used in a program, the more dramatic the results.

The success GATC Health touts is based on deploying Operon™, the company’s proprietary AI platform. Operon deploys in silico models to simulate human biology and takes a multi-omics approach to analysis. That approach has allowed GATC to deliver three to five optimized compounds within six months, claims Uffens, versus the up to 48 months associated with traditional high-throughput screening methods.

Such acceleration occurs by using advanced in silico models to circumvent the “hundreds of thousands of dollars’ worth of experiments performed to get a hit and, ultimately, a lead,” Uffens says.

Rather than relying upon one huge model, he elaborates, “We attack the problem from multiple facets, looking at individual problems with various models and different architectures…and coordinate hundreds of AI models to answer different questions. That’s the starting point. There’s a lot of value in how we curate and parameterize our data in those specific contexts.”

The company also launched the Derisq™ AI Report, an in-depth analysis of drug candidates that highlights safety concerns, efficacy, and non-obvious risks early, while decision-makers can still modulate those risks.

This predictive intelligence layer is, in fact, a key element of GATC’s clinical trial insurance product. Underwritten by Medical and Commercial International (MCI) under the Lloyd’s of London framework, this insurance product leverages GATC’s predictive capabilities to identify risk. It reimburses the full cost of the trial if safety or efficacy endpoints aren’t met.

Typically, MCI’s preclinical trial insurance clients would provide that company with the relevant trial information, which would be run through the Derisq tool as part of their risk analysis.

Buyers for this insurance tend to be biopharma companies that aren’t large enough to self-insure their own trials. “Capital is expensive for them,” Uffens points out. “The insurance product is there to help them lower the cost of capital and open capital doors that may not be open otherwise.”

Multiomics to Discovery

What’s different about GATC’s approach to AI, Uffens says, is that “We come in, generally, as outsiders.” The founding team includes computer scientists as well as those with strong biology and genetics backgrounds, but not necessarily industry experience.

“We built our technology originally as a genetics interpretation platform,” he recalls, “and expanded it to find additional value.” The company was formed officially in 2020.

The turning point came when GATC became involved in a failed, big pharma program for addiction research.

“(The big pharma company) hadn’t found a solution, but had really valuable data and samples. A partner of ours was working with it to identify biomarkers and thought we could validate them. We discovered that not only could we validate the biomarkers, but we could also identify the therapeutic targets. That’s how we moved from multi-omics analysis into discovery,” Uffens recalls.

Moving forward, “We want to empower researchers,” he says. This means not only helping clients advance existing programs but also by identifying potentially more valuable targets.

Working with GATC

GATC’s key partners most likely will be biotech rather than big pharma, Uffens predicts. And, he notes, “We’re fairly agnostic to therapeutic area.”

“Most of our customers have called us because they want to realize the benefits of AI sooner rather than later,” Uffens says. “There is a lot of risk in the space. Folks who are willing to adopt AI at this stage…are looking for additional help before they risk more capital…” to solve particular challenges.

For a company to begin working with GATC, he explains, “The data we’re looking for is very similar to what they would include in an Investigational New Drug (IND) package. The earlier they are in the process, the less data they will have, but, at a minimum, we need some particulars on their therapeutic’s chemistry and the intended mechanism of action.”

Challenges

Drug development is a difficult space with plentiful challenges, he admits. Therefore, “We approach things as a tech company. We iterate through a problem and find where we can succeed or fail as quickly as we can to develop a solution. We’ve gone through multiple generations of architectures, finding ways that work best.”

The next milestone is to accumulate multiple successes with Operon and Derisq in human trials. “‘Wins in humans’ is our [next] frontier,” he says. That includes wins for its insurance underwriting partners as well as for companies working directly with GATC to advance therapeutics to human trials.

As part of that goal, GATC and BioAtla are closing a deal for a Phase III trial of ozuriftamab vedotin for oropharyngeal squamous cell carcinoma and to further develop conditionally active biologic senolytic therapies. Termed a special purpose vehicle transaction—a financial entity designed to hold specific assets that last for the life of the project—the $40 million deal formed Inversagen AI, LLC, to leverage the strengths of the founding companies.

“GATC and BioAtla are equal partners in Inversagen,” Uffens says. “GATC will own a percentage of ozuriftamab vedotin and a larger stake in future joint discoveries,” thus potentially discovering new therapeutic combinations that may be effective as conditionally active biologics.

Currently, the GATC is fine-tuning its own project prioritization. “The AI landscape is both beneficial and challenging,” Uffens acknowledges. “People have certain expectations about what AI can and should do, how it works, and how they might adopt it. Getting them to hear our unique perspective comes back to our focus on wins in humans.”

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Top 10 Organoid Companies

The past year marked a proverbial inflection point for organoid models designed to uncover biological insights previously unattainable through traditional cell culture experiments or animal models.

The FDA in October approved the first-ever investigational new drug (IND) submission supported solely through human vascularized organoid-based combination studies, without relying on traditional animal efficacy proof-of-concept (POC) testing. The IND application by SillaJen enabled the South Korea-based developer of oncolytic virus immunotherapeutics to begin clinical trials for a combination therapy consisting of tislelizumab or paclitaxel and BAL0891, a dual inhibitor of threonine tyrosine kinase (TTK) and polo-like kinase 1 (PLK).

SillaJen’s combo therapy incorporating BAL0891 is being evaluated in a Phase I trial (NCT05768932) whose primary completion date is estimated at December 24. SillaJen’s IND included preclinical efficacy data generated through the vascularized tumor immune microenvironment model (vTIME) developed by Qureator.

The vTIME platform and SillaJen’s trial are early examples of the shift away from animal testing toward new approach methodologies (NAMs), which the FDA sought to advance through the FDA Modernization Act 2.0, enacted in 2022. The measure removed the animal testing requirement for new FDA-regulated products that was imposed through the Federal Food, Drug, and Cosmetics Act of 1938.

“By leveraging AI-based computational modeling, human organ model-based lab testing, and real-world human data, we can get safer treatments to patients faster and more reliably, while also reducing R&D costs and drug prices,” FDA Commissioner Martin A. Makary, MD, stated last year. “It is a win-win for public health and ethics.”

The changing regulatory climate is expected to nearly triple the size of the global organoids market over the next five years, from $1.20 billion last year and a projected $1.42 billion this year to $3.29 billion in 2031—a compound annual growth rate (CAGR) of 18.31%, according to a Mordor Intelligence report released in February. The report listed market share leaders in several categories, including:

  • Source: Stem-cell-derived models (58.43%)
  • Organ type: Intestinal cultures (28.65%)
  • Application: Drug discovery and screening (46.54%)
  • End users: Biopharma companies (55.63%)
  • Technology: Scaffold-based 3D culture (32.65%)

Given their growing role in drug discovery and prospects for future growth, GEN has compiled its first-ever A-List of organoid companies.

Public companies are ranked by their combined revenues for 2025—or if not available, by their combined revenues for the first nine months of 2025 and fourth quarter of 2024—as disclosed in regulatory filings, including sales of products or services, as well as revenue from collaborations and R&D activity.

The top five public companies are ranked below. Just outside the top five at #6 was Takara Bio, whose reagents business includes organoids. Reagents generated a combined ¥31.211 billion ($197.19 million) in net sales between January and March 2025, the final quarter of its 2025 fiscal year, and April-December 2025, the first three quarters of its FY 2026. Also outside the top five was Tecan Group, whose Life Sciences Business racked up CHF 377.1 million (about $483 million) in 2025 revenue. Two Chinese companies, ACRObiosystems and Sino Biological, reported smaller revenue figures.

Private companies are ranked by the total capital they have raised, as disclosed by the companies themselves, either in press statements or in responses to GEN queries verifying figures compiled by other sources. Companies that failed to respond at deadline have been ranked according to their most recently published figures for total capital raised.

The top five private organoid companies are ranked below. Private companies placing between #6 and #10 in GEN’s rankings include Pandorum Technologies (a reported $43.7 million in total capital raised), Parallel Bio ($30 million), Mimetas (a reported $29.4 million), 28bio ($24 million), and Curi Bio (a reported $20.1 million).

28bio and publicly traded Corning co-sponsored GEN’s recent Spotlight on Organoids, a virtual summit exploring how, from drug developers to universities to research institutions, investigators are increasingly using organoid models. This inaugural GEN Spotlight is available to watch on demand; registration is free.

Not included among the ranked private companies is Crown Bioscience. While the San Diego provider of translational oncology services—including the organoid panel screening platform OrganoidXplore—has raised a reported $108 million in total capital, Crown announced plans last November to be sold by Sunnyvale, CA-based JSR Life Sciences for $204 million to Hangzhou, China-based Adicon Holdings, a portfolio company of The Carlyle Group.

 

Top 5 Public Companies

 

1. Thermo Fisher Scientific  (Life Sciences Solutions segment)

Revenue: $10.374 billion in 2025

Thermo Fisher Scientific’s Life Sciences Solutions segment includes sales from products used in developing organoids, such as OncoPro Tumoroid Cell Lines to support tumoroid development, StemFlex Medium for robust expansion of pluripotent stem cells, and Geltrex Flex matrix for the growth of a variety of cells in 3D cell cultures. In December, Thermo Fisher and AIM Biotech announced a partnership to develop standardized, reliable microphysiological systems (MPSs), focused initially on creating vascularized tumoroid models that the companies said could revolutionize cancer research and immunotherapy development. AIM Biotech contributed its organiX MPS for organoids and biopsies, as well as its VasQ Kit, all-in-one vascularization solution, and technical expertise, while Thermo Fisher provided well-characterized patient-derived tumoroid models, fit-for-purpose OncoPro Tumoroid Culture Medium, and supporting reagents.

 

2. Merck KGaA, Darmstadt, Germany (Life Science business)

Revenue: €8.98 billion ($10.348 billion) in 2025

Merck KGaA, Darmstadt, Germany, aims to build a leading presence in organoids through foundational technology, a growing portfolio of patient-derived models, and scalable commercial capabilities. In January 2025, the company announced its acquisition of organoid development pioneer HUB Organoids Holding, based in Utrecht, The Netherlands. By integrating HUB’s patient-derived organoid technology with its existing cell culture expertise, Merck KGaA envisioned enhancing its value to researchers seeking to apply 3D cell culture and next-generation biology to understand drug response earlier in development. In October, Merck KGaA launched a partnership with Promega to develop assays capable of tracking cellular activity in real time using a reporter system within organoids, allowing for testing in models that are physiologically more relevant than traditional two-dimensional models.

 

3. Danaher (Life Sciences segment)

Revenue: $7.334 billion in2025

In a December 3 post on its blog, Danaher tallied eight companies within its family of operating companies as being involved in developing organoids: Abcam, Beckman Coulter (non-diagnostic business), Genedata, IDBS, Leica Microsystems, Molecular Devices, Phenomenex, and SCIEX. The eight offer a comprehensive suite of products and technologies designed to support every stage of organoid development, from sample preparation to advanced data analysis. In December, researchers at Cincinnati Children’s Hospital Medical Center’s Center for Stem Cell and Organoid Medicine (CuSTOM), Molecular Devices, and other partners published a study detailing a new human liver organoid microarray developed by the hospital and Roche—a study co-funded by Danaher, Roche, and the Farmer Family Foundation. CuSTOM and Danaher launched their organoid development partnership in 2024.

 

4. Charles River Laboratories (Discovery and Safety Assessment segment)

Revenue: $2.403 billion in 2025 1

“From models to living systems, next-generation organoids are on the rise,” Charles River Laboratories declared in a December 4 post on its Eureka blog. “As drug discovery and development accelerate the adoption of NAMs, organoids themselves are entering a transformative era,” added Tània Martiáñez Canales, PhD, senior scientist, and Ludovico Buti, PhD, senior research leader. Immune and vascular-competent tumor organoids now capture the full complexity of the tumor microenvironment, while recent liver organoid models now approach the quality of transplant-grade tissues by exhibiting complete metabolic zonation, recapitulating the three liver’s metabolic zones, and even organ-specific vasculature. In November, Charles River committed to “evaluating opportunities to enhance its scientific capabilities” in NAMs while refining its portfolio to maximize financial performance and divest underperforming or non-core assets.

 

5. Corning (Life Sciences segment)

Revenue: $972 million in 2025

Corning offerings for organoid development include a software extension enabling Corning Cell Counter® operators to capture rapid data of 3D cell cultures based on the structure’s morphology, to the company’s Corning® Matrigel® Matrix, a solubilized basement membrane preparation used as a scaffold option to support cell expansion in organoid cultures, and Matrigel Matrix 3D plates. Matrigel and a Corning 96-well round-bottom ultra-low adhesion plate were among supplies from numerous companies used by researchers at Bernhard Nocht Institute for Tropical Medicine in Hamburg, Germany, in creating a West Nile virus encephalitis model using human cerebral organoids generated with male induced pluripotent stem cells—an effort detailed in a paper published March 7 in Nature Communications.

 

1 2025 revenue consists of the 12 months ending December 27, 2025

 

 

Top 5 Private Companies

 

1. Emulate

Total Capital Raised: $250 million

Emulate partnered with FujiFilm Cellular Dynamics in November to launch the Emulate Brain-Chip R1, a first-in-class isogenic model of the neurovascular unit designed to offer researchers a new platform for studying drug transport across the blood-brain barrier, as well as investigating mechanisms of neuroinflammation. Brain-Chip R1 integrates FujiFilm’s iCell® products co-cultured with Emulate’s induced Brain Microvascular Endothelial Cells. In June, Emulate commercially introduced the AVA™ Emulation System, a self-contained instrument designed to culture, incubate, and image up to 96 individual organ-chip samples or “Emulations” in a single run—as well as to deliver in vivo-level insights faster than animal models while cutting consumable costs fourfold and in-lab labor by half compared to current generation technologies.

 

2. Prellis Biologics

Total Capital Raised: “More than” $88 million

Prellis Biologics has combined its EXIS™ organoid and AntiGen AI platforms into a platform called Biological AI that is being applied by Eli Lilly to develop next-generation antibodies, under a collaboration of undisclosed value announced in September. Lilly agreed to pay Prellis an upfront payment, payments tied to achieving development and sales milestones, plus royalties for the licensed antibodies. “With industry-leading speed (about 3-4 weeks), the EXIS™ platform generates diverse, high-affinity antibodies, derived from fully human artificial lymph node organoids against a wide array of targets and target classes, including GPCRs. These hits are then matured by artificial intelligence into drug candidates,” stated Prellis CEO Mike Nohaile, PhD.

 

3. InSphero

Total Capital Raised: $63.5 million 1

Swiss-based InSphero, in February, joined PharmaNest to launch a translational fibrosis partnership of undisclosed value, through which the companies will apply machine learning tools in combination with human preclinical models to decipher complex pathological phenotypes toward the identification of effective therapies. The collaboration combines InSphero’s advanced 3D spheroid models with PharmaNest’s high-resolution, single-fiber digital pathology, with the aim of enabling AI-assisted, precise phenotyping of fibrosis severity and remodeling for liver fibrosis in metabolic dysfunction-associated steatohepatitis (MASH) and other fibrotic 3D in-vitro models. Also in February, InSphero completed its acquisition for an undisclosed price of Doppl and its Sun Bioscience Gri3D® organoid culture platform. “For our customers, this acquisition means access to an even broader, more integrated portfolio of scalable 3D cell culture plates and organoid technologies designed to work seamlessly together,” InSphero CEO and co-founder Jan Lichtenberg, PhD, stated on LinkedIn.

 

4. CN Bio

Total Capital Raised: $60 million

CN Bio isn’t an organoid company per se, but it told GEN its organ-on-a-chip (OOC) technology is positioned to improve the human accuracy and predictivity of organoid workflows. CN Bio recommends supplementing organoids with OOC cultures designed to represent 3D tissues with more human-relevant spatial organization: “Supplementing organoid use with OOC provides the means to further advance workflows by unlocking the ability to detect deeper mechanistic insights, more complex and latent effects that may otherwise be missed,” Emily Richardson, PhD, a lead scientist on CN Bio’s R&D team, wrote on the company’s blog. In October, CN Bio launched PhysioMimix® Core, an all-in-one OOC microphysiological system (MPS) designed to be the first OOC solution to deliver validated performance across single-organ, multi-organ, and higher-throughput configurations.

 

5. Inventia Life Science

Total Capital Raised: AU$65 million ($46.5 million)

Inventia Life Science’s RASTRUM™ platform is designed to help researchers generate reproducible organoids in minutes by enabling the automated, high-throughput 3D bioprinting of cell-laden hydrogels. Last year, Sydney-based Inventia launched its next-generation version of the platform, RASTRUM™ Allegro, whose specs include producing 3D cell models in six minutes for a 96-well plate and nine minutes for a 384-well plate, with a throughput of 35+ plates a day. Optimized for patient-derived samples and translational research, RASTRUM Allegro is intended to enable the creation of more models from limited cell numbers, up to 3.5x more cell models compared to previous generations—a milestone, says the company, toward democratizing 3D cell culture for all researchers.

 

1 Figure published by PitchBook. At deadline, InSphero had not responded to GEN queries seeking to confirm the total capital raised figure.

 

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Bacteria Defense Insights Could Revolutionize Genetic Editing

A computer program that can predict which genes help bacteria to defend themselves against viruses could lead to the next generation of precision genetic engineering tools.

The artificial intelligence model recognizes genetic sequences involved in defenses that act against bacteriophages—viral invaders that infect bacteria.

These anti-viral immune systems have already been repurposed into powerful gene-editing technology, such as CRISPR-Cas, that enable DNA sequences to be precisely cut, modified, or deleted within an organism.

The DefensePredictor tool, outlined in Science, is available as an open-source tool to enable the discovery of more prokaryotic immune systems.

“Identifying new antiphage defense systems may yield the next generation of precision molecular tools while also shedding important light on the ongoing arms race between bacteria and phages,” said MIT-based molecular biologist Michael Laub, PhD, and co-workers.

Intense selective pressure to evade or survive infection has driven the evolution of numerous antiphage defense mechanisms, including restriction enzymes and the CRISPR-Cas systems.

While antiphage immunity genes often cluster into “defense islands” in prokaryotic genomes, this does not always occur and many systems are dispersed or carried on mobile elements such as plasmids, prophages, and transposons.

In an attempt to create a model to identify antiphage proteins, Laub and team first looked at around 17,000 genomes of prokaryotic organisms.

They labelled homologs of known defense and nondefense genes and built representations of the proteins coded by these genes as well as their four nearest neighbors on the genome.

DefensePredictor was trained through this to distinguish whether a gene was involved in defense systems.

After performing well in silico, it was tested on 69 diverse Escherichia coli genes and identified 624 different proteins that it confidently predicted were involved in defense, including 154 that shared no detectable homology to known defense proteins.

Nearly half of the defense proteins identified were not encoded in plasmids, prophages, or defense islands, showing that the model was able to identify systems in a wide range of genomic contexts.

Of 94 predicted genes tested in the lab, 42 provided protection against at least one of 24 phages tested, giving a validation rate of around 45%.

Fifteen protein domains across these 42 systems had not previously been validated as defensive, suggesting new immune systems remain undiscovered.

Expanding the predictive capacity of DefensePredictor beyond E. coli to 1000 diverse prokaryotic genomes revealed more than 5000 predicted defense proteins that were not clear homologs of those already known.

Another Science research article in the same issue of the journal also showed how AI could uncover unexplored diversity in bacterial immunity.

Ernest Mordret, PhD, from the Pasteur Institute, and co-workers demonstrated how deep-learning frameworks could lead to the large-scale discovery of antiphage and a vast atlas of bacterial antiviral immunity.

The team developed three complementary deep-learning models to predict antiphage proteins by leveraging genomic context (ALBERTDF), amino acid sequence (ESMDF), or both (GeneCLRDF).

Twelve newly predicted antiphage systems were then experimentally validated in Escherichia coli and Streptomyces albus.

When applied to more than 30,000 bacterial genomes, the models predict 2.39 million antiphage proteins, 85% of which had no previously known link to immunity, corresponding to approximately at least 23,000 predicted antiphage operon families.

All predictions have been made freely available through an interactive antiphage atlas.

“We developed deep learning models to predict antiphage systems,” the authors summarized.

“These methods extract cues about the “defensiveness” of a protein from two seemingly orthogonal sources: its genomic context across thousands of genomes, and its own amino acid sequence.

“By combining these complementary signals, we move from a fragmented, incomplete view of bacterial immunity toward a more resolved and quantitative understanding of its repertoire.”

The post Bacteria Defense Insights Could Revolutionize Genetic Editing appeared first on Inside Precision Medicine.

Screening the Digital Skills of Patients in Geriatric Rehabilitation: Multicenter Cross-Sectional Study

<strong>Background:</strong> Digitalization in geriatric rehabilitation presents unique challenges, making it essential to align eHealth solutions with patients’ digital skills. The Quickscan Digital Skills (QDS) is a tool designed to help health care professionals match eHealth interventions to individual skill levels. <strong>Objective:</strong> This study aimed to explore the applicability of QDS by comparing it to self-reported digital skills and to gain insight into the digital skills of patients in geriatric rehabilitation. <strong>Methods:</strong> In this multicenter cross-sectional study, participants from 13 geriatric rehabilitation centers in the Netherlands completed a survey, including demographic questions, QDS, and a numeric rating scale (NRS) for self-reported digital skills. Participants were categorized into 3 skill levels (beginner, intermediate, and experienced) based on the cutoff points in QDS scores. Cutoff points were predetermined, guided by the information provided on QDS. Descriptive statistics for median age and frequencies for skill levels were calculated. Comparative analysis using a Kruskal-Wallis test assessed differences between QDS and NRS within these groups, and Spearman rank-order correlation examined the relationship between the two measures. To gain more insight into the different skill levels between groups, data were visualized and associations among age, gender, and digital skill levels were examined using ordinal logistic regression analysis. <strong>Results:</strong> A total of 463 patients (median age 78, IQR 12 years; 282/463, 60.9% female) participated in this study. Based on QDS scores, 42.1% (195/463) were classified as beginners, 19.4% (90/463) as intermediates, and 38.4% (178/463) as experienced users. A moderate positive correlation was found between QDS and NRS scores. Digital skills generally declined with age: 69.8% (37/53) of participants younger than 65 years were experienced users compared to only 13.2% (5/38) of those older than 91 years. A logistic regression analysis showed that increasing age was significantly associated with lower digital skill levels (odds ratio 0.93, 95% CI 0.92-0.95; <i>P</i>&lt;.001). The association between age and digital skills does not differ between males and females. <strong>Conclusions:</strong> This study suggests that QDS is a promising and practical screening tool for assessing digital skills in patients in geriatric rehabilitation. Self-reported digital skills with an NRS do not capture the differentiation in the assessed abilities by QDS. QDS could be a practical tool for identifying digital skill levels in patients in geriatric rehabilitation and can support more personalized eHealth implementation. Further research should explore the parametric properties of QDS and how the scores relate to actual eHealth use.

Orchestrating the Development of a Sustainable Network IT Solution for a Research Network: Qualitative Participatory Multimethod Design

Background: Practice-based research networks (PBRNs) rely on sustainable and interoperable IT infrastructures to support coordination, data management, and long-term collaboration across geographically distributed primary care practices. Large federated initiatives, such as the German DESAM-ForNet (Initiative of German Practice-Based Research Networks) program, face substantial sociotechnical challenges, as diverse user groups, heterogeneous local systems, and multiple governance levels must align around shared digital solutions. Objective: The aim of this study was to design and evaluate a participatory, consensus-driven process for developing a sustainable and interoperable IT solution that supports the coordination of multiple regional PBRNs, and to identify the sociotechnical factors that influence how such a process unfolds. Methods: A qualitative participatory multimethod design combined an iterative consensus-based IT development process in a central working group, interdisciplinary domain-driven design workshops (N=40 stakeholders from 6 PBRNs), and qualitative content analysis of internal documents (2020‐2025). Members of the IT working group were nominated by networks based on IT responsibility and strategic involvement; workshop participants represented general practitioners, study nurses, researchers, and coordinators. Documents (meeting minutes, workshop artifacts, and decision logs) were coded inductively by 2 authors to trace sociotechnical dynamics and decision trajectories. Results: The analysis revealed pronounced differences in IT ambitions, resources, and established practices across the 6 PBRNs (ranging from 2 to 90 person-months), which resulted in divergent expectations and uneven readiness for joint development. This heterogeneity—spanning objectives from simple REDCap (Research Electronic Data Capture; Vanderbilt University) databases to comprehensive digitization strategies—necessitated network-specific bounded contexts within a federated architecture. Through iterative development, stakeholders reached consensus on 6 core use cases (base data management, screening or recruitment processes, study or event participation tracking, management of event participation, accreditation procedures, and standardized communication or data exchange) and 2 national proofs-of-concept: quarterly key performance indicator reporting and pseudonymized practice queries based on a shared core dataset. This collaborative process culminated in a 3-tier practice relationship management infrastructure that integrates local autonomy with central metadata management and connectors to the Medical Informatics Initiative and REDCap, and was endorsed by the steering committee as a scalable compromise balancing interoperability and data sovereignty. Conclusions: The study shows that developing a national, interoperable IT infrastructure for PBRNs depends as much on social and organizational alignment as it does on technical solutions. Iterative participatory collaboration, transparent governance, and early stakeholder engagement were essential for building shared understanding and trust. Strengthening these relational and organizational elements will be crucial for sustaining future implementation efforts and fully realizing the potential of federated data infrastructures in primary care research.
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Additive and Multiplicative Effects of Socially Stigmatized Identities Using Linear Regression to Model Effects on Self-Reported Overall Health as Reported in the All of Us Research Program: Quantitative Analysis

Background: Individuals with one or more socially stigmatized identities experience extensive health disparities, resulting in poorer health outcomes. However, most studies consider the effects of only individual stigmatized identities. Objective: We aimed to quantitatively estimate the additive and multiplicative effects of stigmatized identities on self-reported overall health. Methods: We used survey data from 387,411 participants in the All of Us Research Program, which has assembled a disease-agnostic cohort intended to reflect the US population, to statistically estimate the first- and second-order effects of 47 stigmatized identities on self-reported overall health. We used a linear model to estimate the effects of individual and pairwise stigmas on self-ratings of overall health. Results: We began by aiming to create cohorts for all 93 stigmatized identities previously found to affect health, of which 47 (51%) could be practicably examined. We first modeled individual stigmas alone to contrast the results with those that included both individual and pairwise stigmas. After using the false discovery rate to adjust for testing multiple hypotheses in the collective model, 29 individual and 116 pairs of stigmas had statistically significant effects on self-reported overall health. All significant individual effects were negative or neutral except for skin cancer. Those with the largest negative effect on self-rated overall health were difficulty walking or climbing stairs, unemployed or unable to work, difficulty with errands, and low educational attainment. Pairs of intersecting stigmas had a mix of negative and positive incremental effects, indicating that some stigmatized identities are negative modifiers, such as depression, and other combinations are less negative than the sum of their individual negative effects, such as having difficulty with multiple types of activities of daily living. The individual stigmas with the largest number of statistically significant stigma pairs were unemployed or unable to work (14/47, 30%); depression and low income (11/47 each, 24%); and difficulty walking or climbing stairs, cognitive difficulties, obesity, and skin cancer (8/47 each, 17%). Conclusions: Taken together, numerous pairs of stigmatized identities significantly affect self-reported overall health. While each stigmatization has both direct and indirect effects on health, the relative importance of direct and indirect effects will vary. Many of these are aligned with prior literature, and others warrant further exploration. While the large sample size of this study is a strength, we were unable to model higher-order intersectionality and encourage future research exploring this. The individual and pairwise identities with significant negative effects should be incorporated into research and clinical care by considering the multidimensionality of individuals and how that affects their overall health.
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