The team found that in mice genetically engineered to develop biological symptoms of dementia (PS19 mice), those animals that received the BCG vaccine were less likely to show hallmark signs of the disease, such as neurofibrillary (tau) tangles (NFTs) in the brain, sustained immune cell activation, and memory loss compared to mice that received no vaccine. BCG-treated mice performed better in a novel object recognition test, and showed improved maintenance of body-weight and survival.

Research lead William Bishai, MD, PhD, co-director of the Johns Hopkins Center for Tuberculosis Research, believes that myeloid cells in the central nervous system and brain are using information from BCG to recognize and help the body respond to the formation of plaques and tangles characteristic of Alzheimer’s disease and related dementias. Bishai said, “We’re hard at work trying to understand the detailed mechanism for how it works, but this research points to early clues that aspects of trained immunity are likely driving this response.”

Trained immunity refers to the ability, in mammals, of innate immune system cells to take on an expanded role. Following an initial stimulus, innate immune cells, including monocytes and macrophages, may learn how to identify and respond to future threats that are different from the first. Typically, other immune system cells, such as T cells, take on this type of adaptive and learned response.

Bishai is senior and corresponding author of the team’s published paper in Science Advances, titled “BCG vaccination mitigates tau pathology and restores cognitive functions in PS19 mice,” in which the authors concluded “Our study strongly suggests that dementia protection by BCG is a credible observation that merits future basic research and large-scale prospective clinical trials to provide definitive answers.”

Observational studies in humans—those not designed to show cause and effect—have linked off-target effects of vaccines to a reduced incidence of dementia. “There is a growing appreciation that vaccines may have beneficial off-target effects such as reducing the risk of dementia,” the authors wrote. The shingles vaccine has been linked to a 20% reduced incidence of dementia, while several previous studies cited by the researchers found that BCG used as an immunotherapy for non-muscle invasive bladder cancer was linked to a 12% to 78% reduced risk of dementia throughout a three- to 15-year period.

“While less publicized, there is also considerable evidence that Bacille Calmette-Guérin or BCG, the live attenuated vaccine to prevent tuberculosis (TB) and treat bladder cancer, may also have dementia-preventive properties,” the team continued.

It’s been postulated that trained immunity is a mechanism by which BCG could protect against dementia, they noted. “Upon exposure to a first antigen such as BCG, innate immune cells, typically myeloid cells, have been shown to undergo epigenetic and metabolomic reprogramming such that upon exposure to a second, unrelated antigen, their immune response is greater than it was to the first,” they explained.

To test directly whether BCG could represent a preventive therapy for Alzheimer’s disease, the team turned to the PS19 (P301S) mouse model, which develops symptoms of dementia, specifically marked by tau pathology or a clumping of tau proteins in the brain representing late stages of the disease. ‘The overexpression of P301S tau is associated with AD-relevant pathological and functional features, including neuronal loss, microgliosis, neurofibrillary tangles (NFT) deposition, and cognitive impairment,” they wrote.

The team divided mice into cohorts that received the BCG vaccine and those that received a saline injection. An additional comparison group included age-matched mice that did not have dementia and that also received the saline injection. Mice in the BCG treatment group received the vaccine at three months of age. Multiple assessments, based on brain imaging, memory recall (through an object recognition test) and indicators of disease, including neuroinflammation and the expression of genes linked to Alzheimer’s disease, were conducted eight to nine months later.

The researchers found that those mice that received BCG were about five times more likely to have signs of reduced tau deposits in their brain. They were also four times less likely to have markers of sustained inflammation, signaling that their immune cells had already likely responded to tau by clearing out some of the tangles, and had created a stable or protective immune response.

The untreated mice showed activation of 716 genes connected to Alzheimer’s disease, cell death, and neuroinflammation. BCG administration normalized all but nine of these. Compared to untreated mice, the mice who received BCG were less likely to have signs of brain atrophy and also more likely to live longer and perform better on tasks related to remembering and identifying objects.

“BCG seems to be reducing the degree of hyperinflammation in the brain—which is a good thing—and it may be doing it through a trained immune cell mechanism,” said Bishai. “There are a number of other characteristics of trained immunity that we are studying in the lab now.”

In their paper the team wrote in summary, “We found that early BCG administration starting at three months of age reduced brain atrophy, p-tau levels, and neuronal loss measured at the later time point of eight to nine months. Simultaneously, BCG therapy restored glutamate levels in vivo and improved recognition-memory performance, body weight, and survival of PS19 mice, suggesting key disease modifying effects.”

This research, Bishai says, is believed to be the first to study BCG and dementia in mouse models with tau pathology (specifically showing how immune cells may play a role in clearing neurofibrillary tangles). “Mechanistically, our study identified BCG-induced trained immunity properties as playing key roles in the clearance of tau NFTs,” they stated. Others have found similar findings with BCG and improved cognition in amyloid mouse models—which represent earlier stages of the disease marked by plaque formation.

“This is a great example of translational science working in reverse—starting with an intriguing observation in people and then going back to the laboratory to understand why it might be happening,” commented co-author Barbara Slusher, PhD, professor of neurology at the Johns Hopkins University School of Medicine and director of the Johns Hopkins Drug Discovery program.

Slusher cautions that researchers still need to understand more of the underlying biology before they can say who might benefit, when treatment would need to be given and whether the effect can be safely reproduced in people at risk for dementia. “If we can identify the specific immune changes that are protective, we may be able to develop even more targeted approaches for the prevention of Alzheimer’s disease.”

The post BCG Vaccine-Induced Trained Immunity May Help Protect Against Dementia appeared first on GEN - Genetic Engineering and Biotechnology News.

The researchers—nine from Johns Hopkins University, one from The Ohio State University—analyzed 151,642 people with clinical obesity and 128,874 controls without obesity spanning five ancestry groups, using data from the UK Biobank and All of Us Research Program. The biobank says it possesses the world’s most comprehensive dataset of biological health and lifestyle data gathered from a half million participants, while All of Us is the NIH initiative designed to advance precision medicine by collecting and study data from 1 million or more people living in the United States.

Researchers identified 127 independent genetic loci associated with clinical obesity. Of these, 63 had no significant association with BMI. The most discordant variant, researchers reported, was rs15285, a single-nucleotide polymorphism (SNP) located within the 3′-untranslated region (3′UTR) of the LPL gene that encodes lipoprotein lipase. That variant was colocalized to expression quantitative trait loci (eQTLs) for lipoprotein lipase, and associated with elevated triglyceride levels.

The team also developed a clinical obesity polygenic score that combined information from numerous genetic variants, a score that was shown to be significantly associated with BMI, body fat percentage, and waist circumference. Compared to a BMI polygenic score, the clinical obesity polygenic score developed by the researchers showed improved association with cardiovascular risk factors and proteomic markers of inflammation—such as interleukin-6, fibroblast growth factor 21, and hepatic growth factor—as well as markers of insulin resistance, including adiponectin, resistin, leptin, and leptin receptor.

The clinical obesity polygenic score improved risk discrimination over a BMI polygenic score for myocardial infarction (heart attack), heart failure, and stroke, the research team added.

Researchers then validated the improvement across four additional long-running U.S. public health studies:

• Atherosclerosis Risk in Communities (ARIC), a study of the NIH’s National Heart, Lung, and Blood Institute whose focus has widened from identifying risk factors for subclinical atherosclerosis to risk factors for heart diseases including heart attack, coronary heart disease, stroke, and heart failure. About 16,000 U.S. adults have been enrolled.
• Multi-Ethnic Study of Atherosclerosis (MESA), an NHLBI-sponsored study of the characteristics of subclinical cardiovascular disease and the risk factors that predict progression to clinically overt cardiovascular disease or progression of the subclinical disease. MESA enrolled 6,814 adults during its baseline period between 2000-2002.
• Framingham Heart Study, under NHLBI direction, was launched in 1948 to identify common factors or characteristics that contribute to cardiovascular disease. Since 1971, the Boston University School of Medicine has served as NHLBI’s contractor and academic partner for the study. More than 15,400 across multiple cohorts have been enrolled.
• Women’s Health Initiative, which first won funding in 1992 and is also NHLBI-sponsored, focuses on strategies for preventing heart disease, breast and colorectal cancer, and osteoporosis in postmenopausal women. 161,808 women have been enrolled.

‘Biologically and clinically relevant’

“These findings demonstrate that clinical obesity captures genetic loci distinct from BMI that are biologically and clinically relevant to cardiovascular health,” the researchers concluded.

Findings were reported in “Genome-wide analysis and polygenic prediction of clinical obesity,” a poster study presented during the American Society of Human Genetics (ASHG) 2026 Annual Meeting, held October 20-24 in Montreal. Co-corresponding authors were Sohail Zahid, MD, PhD, an investigator at the Johns Hopkins Ciccarone Center for the Prevention of Cardiovascular Disease; and Alexis Battle, PhD, director of the Malone Center for Engineering in Healthcare and director of the Research, Strategy, and Partnerships, Data Science and Artificial Intelligence Institute at Johns Hopkins.

The research team posted a preprint version of their study on medRxiv on May 22.

“Stratifying individuals into low, intermediate, and high inherited obesity risk groups, we found that clinical obesity polygenic risk reclassified 35% of individuals compared to BMI polygenic risk,” researchers reported in the preprint. “Unlike rare variant panel testing which already guides targeted therapy in monogenic obesity, further work is needed to determine the incremental benefit of clinical obesity polygenic scores for diagnosis, risk stratification, or management beyond BMI-based assessment.”

The new clinical obesity definition used by researchers was introduced last year by The Lancet Diabetes & Endocrinology Commission.  The 58-member Commission set out to establish objective criteria for disease diagnosis, aid clinical decision making, and prioritize therapeutic interventions and public health strategies, by characterizing excess body fat and dysfunctional adiposity beyond BMI.

“We recommend that BMI should be used only as a surrogate measure of health risk at a population level, for epidemiological studies, or for screening purposes, rather than as an individual measure of health,” the Commission stated last year. “Excess adiposity should be confirmed by either direct measurement of body fat, where available, or at least one anthropometric criterion (e.g., waist circumference, waist-to-hip ratio, or waist-to-height ratio) in addition to BMI, using validated methods and cutoff points appropriate to age, gender, and ethnicity.”

In people with very high BMI (i.e., >40 kg/m²), the Commission continued, excess adiposity can pragmatically be assumed without further confirmation: “We also recommend that people with confirmed obesity status (i.e., excess adiposity with or without abnormal organ or tissue function) should be assessed for clinical obesity.”

The post ASHG: Signals Based on Clinical Obesity Show Stronger Links to Cardiovascular Health than Those Linked to BMI appeared first on GEN - Genetic Engineering and Biotechnology News.

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Panelists:

Jamie Freeman, PhD

VP of Business Development and Commercial Strategy
Asimov

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Panelist

Jamie Freeman, PhD

Jamie Freeman, PhD, is VP of Business Development and Commercial Strategy at Asimov, where he works with partners to improve the design and manufacturing of novel biological therapeutics. Prior to joining Asimov, Jamie was responsible for the development and initial commercialization of Horizon Discovery’s CHO Source platform. Jamie earned a PhD in cell and molecular biology from Cardiff University, followed by a postdoc at the MRC Laboratory of Molecular Cell Biology.

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Protein foundation models have transformed binder design, but turning those binders into drugs remains an empirical, trial-and-error process. Lead optimization, cell line development, and process development each still rely on screening large numbers of candidates, clones, or conditions, with little ability to predict which will succeed.  As pipelines shift toward bispecifics and other complex formats, that approach is getting harder to sustain.

In this GEN webinar, Asimov’s VP of Business Development and Commercial Strategy Jamie Freeman, PhD, will show how Asimov combines bio-foundation models, AI agents, and synthetic biology to tailor expression vector design for each molecule. He will highlight how scientists use Kernel, Asimov’s computer-aided genetic design software, to automate the design of optimized expression vectors, and how AI agents can take on custom genetic designs for uncommon requirements. 

Through a series of case studies, he will also share how AI-designed vectors outperformed Asimov’s own previous best designs, how rapid stable pool data changed which multispecific lead a partner advanced, and how a model predicted chain ratios to improve correct pairing without reducing titer. Key takeaways from the webinar include:

• How exploring genetic design space, rather than relying on off-the-shelf vectors, can improve titer and product quality for both standard and complex formats
• How AI models trained on measurements from inside the cell can learn the mechanisms of expression and apply them to design better expression vectors
• How model-guided workflows and stable pools bring better-informed decisions to vector design and lead selection

A live Q&A session will follow the presentation offering you a chance to pose questions to our expert panelist.

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The post Using AI Agents and Bio-Foundation Models to Automate Vector Design for Cell Line Development appeared first on GEN - Genetic Engineering and Biotechnology News.

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Panelists:

Josh Wheeler, MD, PhD

Vice President, Research and Development
Genialis

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Panelist

Josh Wheeler, MD, PhD

Josh Wheeler, MD, PhD, is the vice president of Research and Development at Genialis with more than 15 years of experience spanning academic research, computational biology, and biotechnology. His work sits at the intersection of clinical development, translational medicine, AI and machine learning, diagnostics, and precision oncology. At Genialis, he leads clinical and research innovation strategy, biomarker and diagnostic development, clinical trial assay and regulatory strategy, and biopharma partnerships. Josh previously trained and practiced at Stanford across anatomic pathology, neuropathology, molecular diagnostics, and computational biology. He earned his MD from the University of Colorado Anschutz Medical Campus through the NIH-funded Medical Scientist Training Program and his PhD in biochemistry from the University of Colorado Boulder.

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Matthieu Spriet, PhD

Technical Specialist
Inventia Life Science

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Matthieu Spriet, PhD

Matthieu Spriet, PhD, is a technical sales specialist at Inventia Life Science with expertise in 3D biology, biochemistry, cell signaling, oncology, and assay development. He earned his PhD in biochemistry and molecular biology from the University of Nebraska Medical Center. His thesis focused on profiling and understanding RNA expression in cholangiocarcinoma.

After graduating, Matthieu spent many years working in early-stage drug discovery, developing cell-based assays across multiple disease models, including oncology, immunology, cardiology, hepatology, and regenerative medicine. Matthieu is passionate about scientific communication and collaboration, with a focus on advancing biomedical research through advanced 3D cell models and drug discovery innovation.

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Pancreatic cancer is experiencing a renaissance in therapeutic options and improvements in patient outcomes. Accelerating therapeutic advances demands a more robust translational pipeline linking patient biology to preclinical model systems. The tumor microenvironment shapes both prognosis and therapeutic vulnerabilities, making its representation in preclinical models critical for translation.

In this GEN webinar, our expert speaker Josh Wheeler, MD, PhD, will discuss a biology-first, interpretable AI approach to understand patient tumor states and next-generation preclinical models that reproduce their biological complexity. During the webinar, he will present Genialis Supermodel, an interpretable AI foundation model that translates tumor RNA-seq into biological states that can be compared across patients, experimental models, and Inventia’s RASTRUM platform, which enables bioprinted PDAC models with increasing microenvironmental complexity through the addition of cancer-associated fibroblasts (CAFs) and T cells.

Using pancreatic cancer as a case study, he will demonstrate how increasing microenvironmental complexity moved the bioprinted models toward distinct biological states observed in patients. You will learn how CAFs drove EMT and TGF-beta/SMAD activity with loss of classical epithelial identity, while adding immune cells produced inflammatory and interferon programs. These changes also exposed therapeutic biology not apparent in monoculture, including altered RAS/MAPK, EGFR, beta-catenin, and YAP/TEAD signaling. Key takeaways include:

• How technologies from Genialis and Inventia provide a framework to connect patient tumor biology with experimentally tractable model systems
• How patient-centered models generate therapeutic hypotheses that monoculture may miss

A live Q&A session will follow the presentation offering you a chance to pose questions to our expert panelists.

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The post Bridging the Translational Gap in Pancreatic Cancer Through Biology-First Modeling appeared first on GEN - Genetic Engineering and Biotechnology News.

The team from the Massachusetts Institute of Technology (MIT) showed that measuring the buoyant mass of T cells predicted patient response more accurately than a traditional tumor mutational burden (TMB) approach.

According to the researchers, the new technique could be used not only to predict cancer cell sensitivity to treatment, but also to address the productivity of cell cultures used in gene therapy manufacturing.

“We’ve wanted to show people this is a new physical marker that predicts the fate of the T cells,” explains Jiaquan Yu, PhD, a research scientist working in microfluidic engineering and cancer immunology at MIT.

“By fate, we mean we measure the naïve state of the T cells and get an indication of how they will behave after activation.”

The team used suspended microchannel resonator (SMR) technology, a specialized instrument that uses a vibrating sensor containing a microfluidic channel to measure buoyant mass, Yu says.

The buoyant mass of the T cells is measured relative to water and from the buoyant mass, they were able to calculate the immune fitness of the cells, Yu continues. And, thus, whether they were likely to activate to fight cancer as part of treatment with ICB immunotherapy.

“For T cells, being in the heavier group suggests you’re better equipped to produce proteins,” Yu says. “And that capacity gives us an indication of the fitness of the cells and their ability to respond after activation.”

The team was able to test the performance of the technique in a clinical study of 28 patients with melanoma receiving ICB, Yu explains. And, in that study, they were able to prove that measuring buoyant mass was more effective than TMB at predicting treatment response.

“People are underestimating simple non-molecular signatures, such as mass, volume, and density, as we’re all focused on biomarkers focused on genes and RNA,” Yu says.

“What we’re showing here is that mass gives a result that integrates a lot of information.”

The post Researchers Validate Buoyant Mass for Cell Health Testing appeared first on GEN - Genetic Engineering and Biotechnology News.

“It is difficult to find the right cell line,” said Benjamin Fryer, PhD, CEO and cofounder of Pluristyx. Researchers often build promising processes around readily available lines, only to discover later that the material lacks the provenance, consent, or good manufacturing practice (GMP) pedigree needed for human use. By then, Fryer said, teams may have invested years in process development, animal studies, and publications—only to restart with a new line.

Clinical readiness also depends on whether donor consents support the intended use, said Priya Baraniak, PhD, chief commercial and development officer at Pluristyx. Beyond that, developers face the familiar manufacturing demands of robustness, reproducibility, and scale at a cost that is “clinically and commercially feasible,” she noted.

That makes the choice of starting material a bioprocessing decision, not merely a research decision. As developers move from milliliter-scale work toward liters or tens to hundreds of liters, Fryer said, “the manufacturing process has to be somewhat similar.” Passage number and population doublings should be controlled so cells at small and large scale are effectively the same biological age. Production format matters, too. “You need to make sure that the cells are available in the process format you’re going to use,” Fryer said. A therapy intended for suspension culture, for example, should move toward suspension early rather than undergo a disruptive conversion late in development.

Baraniak put the principle simply: “Standardizing your input is really important.” Even high-quality cells can introduce variability if their passage history, characterization, or biological state changes from run to run.

That issue is especially important for iPSCs because their expansion potential can create a false sense of security. “We often fall into a false narrative that these cells can be expanded forever and they’re an evergreen source,” Baraniak said. “They accumulate genetic mutations and aberrations as you expand them,” potentially leaving developers with a process built around cells that no longer behave as intended.

The challenge extends beyond raw material into process design. Baraniak said cell manufacturing still relies too heavily on “golden hands”—highly skilled operators whose tacit knowledge can be difficult to reproduce across people, sites, and scales. “You can’t rely on just golden hands,” she said. Processes must instead be engineered to minimize operator-dependent decisions and tolerate normal manufacturing variation.

That transition also changes the role of automation. Fryer cautioned that simply replacing a human hand with a robotic one does not solve a poorly understood process. Manufacturers first need to understand why cells respond to particular media, handling steps, environmental conditions, and culture parameters. That mechanistic knowledge can guide smarter automation, closed systems, and process analytics rather than locking fragile procedures into hardware.

The same manufacturing discipline could expand the usefulness of iPSCs in new approach methodologies (NAMs), including drug screening, toxicology, disease modeling, and engineered tissues. Unlike limited primary tissues, well-controlled iPSC banks can provide renewable human material representing different donors, disease states, and genetically engineered variants. But those models only become useful at industrial scale if they can be manufactured, distributed, and reproduced consistently.

For Baraniak, that need for reproducibility reflects how far the field has come. “We’ve moved past the point of proving that these therapies have viability, that iPSCs work,” she said. “So now it’s how do we make them work over and over and over.”

That shift—from demonstrating biological possibility to engineering repeatable manufacturing—might define the next phase of iPSC commercialization. Better starting materials, deeper process understanding, automation, and more open sharing of manufacturing experience will not eliminate biological complexity. But they could keep that complexity from becoming the bottleneck that prevents promising iPSC technologies from reaching patients.

The post iPSC Manufacturing Starts with the Source appeared first on GEN - Genetic Engineering and Biotechnology News.

Fusing Raman and near-infrared (NIR) spectroscopy into a multimodal soft-sensing framework appears, however, to remove that bottleneck. This new framework provides high-frequency, low-latency measurements that aren’t typically available with existing commercial, off-line sensors. Its developers say it provides “accurate, online-compatible glucose soft sensing,” and that it is also amenable for in-line applications.

More specifically, Raman spectroscopy offers crisp, highly specific chemical fingerprints, while NIR offers broad, information-laden spectral coverage. Realizing this, a team including senior authors Xiwei Tian, DEng, of East China University of Science and Technology in Shanghai and Yinlan Ruan, PhD, of Guilin University of Electronic Technology, encoded each modality separately and then merged them using dual-stream, cross-attention transformer architecture (DS-CAT).

The team tested their system using 142 preprocessed, synchronized Raman-NIR records.

Writing in Bioprocess and Biosystems Engineering, they report that their model explained 99% of the variation in true glucose concentration. Anything above 95% is considered good. Likewise, the root mean square error of 1.09 g/L was well within the level needed to ensure effective feed control. Furthermore, the mean absolute error of 0.89 g/L achieved by this model suggests it is consistently accurate. Such consistency is particularly important for real-time processing controls, where outliers could negatively affect feeding strategies. Results remained similar throughout five-fold validation, the scientists report.

Additionally, “Prediction-based perturbation…revealed strong dependence on Raman information, while Raman-block sensitivity analysis identified 1122−1335 cm^-1 [which is associated with carbohydrate vibrational modes] as the interval showing the strongest prediction sensitivity,” Tien, Ruan, and colleagues point out. Those findings are comparable to other literature reports, while demonstrating the enhanced sensitivity, reduced noise, and reduced drift of this new framework.

Notably, the researchers note that the DS-CAT framework “outperform[ed] partial least squares regression, gradient boosting regression trees, convolutional neural networks, and temporal convolutional networks under the same evaluation protocol.” By performing better than these four industry-standard modeling approaches, DS-CAT has the potential to substantially improve soft-sensor capabilities for real-time glucose monitoring.

These findings suggest the DS-CAT approach to glucose sensing may enable reliable insights that lead to better control of a critical parameter in closed-loop mammalian and microbial fermentation. If so, the high-frequency and low-latency data measurements this method delivers may become a key element in a rational transition from fed-batch fermentation toward continuous manufacturing.

The post Raman+NIR Spectra Improves Glucose Soft Sensing appeared first on GEN - Genetic Engineering and Biotechnology News.

That is the view of researchers at Thermo Fisher Scientific, who examined the economics of gene therapy production in a study and concluded that choosing the right vector manufacturing platform is challenging.

“Optimal platform choice depends on indication prevalence, dose requirements, desired serotype flexibility, development timelines, and willingness to invest in process intensification,” study author Seyed Pouria Motevalian, PhD, writes.

Motevalian and co-authors compared three recombinant adeno-associated virus (rAAV) manufacturing methods—transient transfection, producer cell line approaches (PCLs), and baculovirus-based production—and found that the cost drivers for each differ markedly.

“On a per-batch basis, baculovirus infection is the most cost-efficient platform, followed by transient transfection and PCLs. However, when costs are normalized to vector titer, the ranking shifts, with transient transfection becoming the lowest-cost platform.

“Each platform has a distinct economic fingerprint: transient transfection is dominated by plasmids, transfection reagent, media, and endonuclease; PCL perfusion processes are driven by media and perfusion-related single-use hardware; and the baculovirus platform shifts a greater share of cost into downstream operations, particularly affinity capture,” Motevalian says.

Patient focus

With all this in mind, Motevalian and co-authors argue that, rather than focusing on material and reagent costs, developers must also factor in the needs of the target patient population when choosing how to produce viral vectors.

“Our analyses suggest there is no universally ‘best’ rAAV platform. Optimal platform choice depends on indication prevalence, dose requirements, desired serotype flexibility, development timelines, and willingness to invest in process intensification,” they say.

For example, for products intended for smaller populations, transient transfection, in which vector genes are introduced into producer cell lines, may be the best approach, despite the high cost of the DNA plasmids required.

In contrast, for mass market gene therapies, baculovirus infection or PCL-based vector manufacturing methods are a more cost-effective option, particularly in combination with optimized upstream and downstream processes.

Understanding these dynamics is critical for developers, according to the authors, who say gene therapy firms must factor them into process development as early as possible.

“Integrating quantitative cost modeling into platform selection and process development decisions early in program design will be essential for making rAAV therapies economically sustainable and expanding global patient access,” they say.

The post Patients Should Be Considered When Choosing a Vector Production Method appeared first on GEN - Genetic Engineering and Biotechnology News.

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Panelists:

Arati Naveen, PhD

CIRM Postdoctoral Scholar
Cedars-Sinai Medical Center

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Panelist

Arati Naveen, PhD

Arati Naveen, PhD, graduated with her bachelor’s in biomedical engineering from the University of Buffalo. She then moved to L.A. to pursue her master’s in stem cell biology and regenerative medicine at the University of Southern California (USC). She received her PhD in biomedical and translational sciences at Cedars-Sinai in the Jefferies Lab, where her dissertation project explored the interplay between heart disease and immunometabolism. In the Sharma Lab, her work focuses on using cardiac organoids to study autoimmune mediated heart disease and for predictive modeling of drug cardiotoxicity.

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Human induced pluripotent stem cell (iPSC)-derived organoids combine the ability to generate diverse cell types with the retention of parental genetic backgrounds, providing opportunities to investigate human development, disease mechanisms, and individual differences in therapeutic responses. These models capture aspects of complex tissue architecture and multicellular interactions within a more physiologically relevant spatial environment. Over the past two decades, advances in stem cell reprogramming, directed differentiation, and three-dimensional culturing techniques have enabled the development of organoid models for the brain, retina, heart, lung, intestine, liver, pancreas, kidney, and many more.

In this GEN webinar, our expert speaker, Arati Naveen, PhD, will trace the foundational discoveries that shaped organoid technology as a new approach methodology (NAM), while highlighting pioneering contributions and contemporary advances. This webinar will examine the ways in which the challenges of tissue maturation, vascularization, reproducibility, and scalability, are being addressed. One example explored is harnessing microgravity to strengthen organoid performance and support the broader adoption as NAMs.

A live Q&A session will follow the presentation offering you the chance to pose questions to our expert panelist.

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The post The Organoid Odyssey: A Glimpse Into the Past, Present, and Future of hPSC-Derived 3D Models appeared first on GEN - Genetic Engineering and Biotechnology News.

The study, led by Bruce Rittmann, PhD, director of ASU’s Biodesign Swette Center for Environmental Biotechnology, involved collaborators at Rice University, Tongji University, the National University of Singapore, and Nanjing University. Published in Proceedings of the National Academy of Sciences, the paper is titled “Catalytic Reactive-Hydrogen Membranes for Rapid Capture and Hydrodefluorination of Six PFAS of Regulatory Concern.”

“PFAS are hard to break down, and normal processes that we use don’t work,” Rittmann said.

That persistence stems from the compounds’ strong carbon–fluorine bonds. Activated carbon, ion exchange, and membrane filtration can remove PFAS from water, but do not themselves resolve the challenge of destroying the captured contaminants. The new system instead brings PFAS and reactive hydrogen together on palladium-coated membrane fibers under ambient conditions.

Hydrogen gas travels through the fibers to the palladium catalyst, where it generates two forms of active hydrogen with complementary functions. Surface hydrogen supports PFAS capture, while subsurface hydrogen stored as beta-phase palladium hydride supplies the driving force for hydrodefluorination.

“The palladium attracts the PFAS molecule, and the palladium attracts the hydrogen and puts them together,” Rittmann added.

Solid-state analyses identified formation of the palladium hydride and associated lattice expansion. In the paper, the researchers described their findings as “a mechanistic framework for how active hydrogen is generated, stored, and deployed in catalytic membranes.”

The team tested PFOA, PFOS, PFNA, PFHxS, PFBS, and GenX. During 58 days of continuous operation, the system achieved up to 96% removal and 83% defluorination.

Performance also varied by compound. Long-chain PFAS were removed and defluorinated faster than short-chain analogs. GenX was more resistant, which the authors attributed to its ether linkage, weaker adsorption, and higher average carbon–fluorine bond dissociation energy. Nevertheless, the membrane enabled GenX removal and defluorination, producing 2-propoxypropanoic acid.

Practical deployment will require further engineering, including reducing palladium use. “Palladium is expensive,” Rittmann said. One potential application is treating concentrated waste streams generated by existing PFAS-removal systems, rather than replacing those systems outright. The researchers are also developing related hybrid membranes combining palladium with pollutant-degrading bacteria, although the current study’s catalytic system uses palladium rather than microbes.

The post New Catalytic Reactive-Hydrogen Membranes Capture and Break Down PFAS appeared first on GEN - Genetic Engineering and Biotechnology News.