Germany – Page 5 – Relatix Bio

May 6, 2026

Next Generation CRISPR Gene Editing Could Help Target Cancer Cells

A CRISPR gene editing protein called Cas12a2 can be turned into a kind of programmable self‑destruct switch for cells, which researchers think could be a new way to treat conditions like cancer if the technique is validated.

Cas12a2 eliminates eukaryotic cells based purely on which RNA transcripts they express, and the investigators showed this can be used to selectively destroy virus‑infected cells, unedited cells, and cancer cells bearing a single‑nucleotide mutation.

“Common molecular and cell-based interventions, such as small-molecule inhibitors, toxins, antibodies, lytic viruses or programmed immune cells, eliminate cells through specific proteins or survival pathways; however, these methods cannot be tailored to arbitrary genetic or transcriptional states as well as difficult-to-drug scenarios such as mutations in non-coding sequences or complex etiologies,” write co-lead author Yang Liu, PhD, assistant professor in biochemistry at University of Utah Health, and colleagues in Nature.

“A cell-killing approach triggered directly by the specific recognition of prescribed DNA or RNA sequences could greatly broaden the range of targetable conditions, creating new means to counter select against specific cells in a variety of situations and applications.”

In this study, the researchers first tested the technology in yeast and human cell lines against a harmless target. They found that the guided Cas12a2 destroyed the cells carrying the marker by effectively shredding their DNA. When they checked for off-target effects they were rare and weak.

They then tested the technology on cancer cells carrying the HPV virus by targeting viral RNA. The method killed cells containing the virus, but not cells negative for HPV. The team also used the Cas12a2 method to “clean up” after gene editing by killing unedited cells and enriching edited ones. Finally, they tested if Cas12a2 could recognize a single mutation in the cancer gene KRAS and showed it could destroy cells with this mutation while leaving cells with a non-mutant version of KRAS alone. This worked even when those cells were resistant to an approved KRAS drug.

“The enzyme that we’re working with is extremely specific,” Liu says. “It does not touch the healthy cells. So if we’re thinking about a cancer therapy, you’re treating cancer with no side effects. That was striking to us. We did not know that was possible.”

This research is early stage, and it will take some time to enter the clinic, as testing in animal models is needed first, but the research team say the results are promising. The technology is being developed commercially by German biotech Akribion Therapeutics, a biotech spin-off from BRAIN Biotech launched in 2024.

The post Next Generation CRISPR Gene Editing Could Help Target Cancer Cells appeared first on Inside Precision Medicine.

May 5, 2026

Muscle Quality and Fat Distribution Predict Mortality Risk Better than BMI

Researchers at the University Medical Center Freiburg in Germany, say that detailed measures of body composition derived from whole-body MRI scans can predict diabetes, cardiovascular events, and mortality risk better than current methods that rely on body mass index (BMI). Using MRI imaging data from more than 66,000 people, the team has developed age-, sex-, and height-adjusted reference standards that show how fat and muscle are distributed across the body and how these patterns relate to health outcomes. Their findings, published in the journal Radiology, show analysis of both the quantity and quality of skeletal muscle, along with where fat is distributed in the body, can provide a more accurate way to determine risk as opposed to weight-based methods alone.

“Many risk scores and treatment decisions still rely on BMI or waist circumference because they are simple to obtain,” said senior author Jakob Weiss, MD, PhD, an interventional radiologist at University Medical Center Freiburg. “But BMI does not reliably reflect a person’s actual body composition.” This is one of the central findings of the study: that individuals with similar BMI values can have markedly different distributions of fat and muscle, which carry different levels of risk for cardiometabolic disease and mortality.

The team’s retrospective study analyzed whole-body MRI scans from 66,608 people using data from the UK Biobank and the German National Cohort collected between April 2014 and May 2022. The cohort had a mean age of 57.7 years and an average BMI of 26.2. Using a fully automated deep learning framework, the researchers quantified multiple body composition measures, including subcutaneous adipose tissue, visceral adipose tissue, skeletal muscle, skeletal muscle fat fraction, and intramuscular adipose tissue. These measures were normalized for age, sex, and height. A score is developed from these data to show how far individuals deviated from a population-adjusted reference.

“Whole-body MRI–derived BC (body composition) z-scores were used to identify at-risk individuals and predict cardiometabolic outcomes and mortality beyond traditional risk factors.” They then used the z-score categories to assess associations and clinical outcomes.

Their data showed that individuals with high visceral fat had a 2.26-fold increased risk of developing diabetes. High intramuscular fat was associated with a 1.54-fold increased risk of major adverse cardiovascular events, while low skeletal muscle was linked to a 1.44-fold increase in all-cause mortality.

The deep learning system used to develop the risk profiles was trained and evaluated against radiologist-defined reference standards, allowing it to extract volumetric measurements across the entire body rather than relying on single cross-sectional slices. This method allowed the researchers to capture meaningful variations in muscle quality and fat distribution that are not visible through other techniques.

“Manual BC measurement in large-scale imaging datasets is prohibitively time-consuming,” the researchers wrote. “However, recent advances in deep learning have enabled fully automated, accurate, and efficient quantification from cross-sectional imaging.” This capability allowed the team to construct reference curves reflective of how body composition changes with age and differs between men and women.

Importantly, the research shines a light on the limitations of using BMI to determine future risk. Because BMI is calculated using only two metrics, height and weight, it does not distinguish between fat and muscle or account for where fat is stored. Because of this, two people with the same BMI may have very different levels of visceral fat or muscle mass, factors that can lead to different to different health risks. The researchers showed that deviations in these specific components, captured via their MRI-based z-scores, were predictive of outcomes even after accounting for traditional risk factors.

“It’s not only how much muscle you have, but also it’s the quality of that muscle,” said first author Matthias Jung, MD, a radiologist at University Medical Center Freiburg. “Knowing the volume of intramuscular fat gives us a window into muscle quality that other methods like BMI, bioelectrical impedance analysis, or DEXA can’t easily provide.” This distinction is relevant because intramuscular fat is linked to metabolic dysfunction and cardiovascular risk.

The study also produced a web-based calculator that allows clinicians and researchers to compare individual patient data with population-based reference values. According to Weiss, this tool could be applied to existing imaging studies. “A dedicated whole-body MRI is not necessarily required. If a routine CT or MRI body scan already exists, the information can be extracted for benchmarking against the reference values,” he said.

The study has limitations, including a cohort of primarily White Western European adults, which may impact the generalizability of the findings. The researchers also pointed out that whole-body MRI is not routinely performed in clinical practice, although they provided reference values for commonly imaged regions such as the chest, abdomen, and pelvis to address this.

The team will continue their work by seeking to validate the reference curves in clinical populations and exploring their use in predicting treatment outcomes, including toxicity, survival, and recurrence in cancer patients. The team also plans to develop disease-specific reference values for broader patient groups to broaden the use of body composition analysis into clinical care.

The post Muscle Quality and Fat Distribution Predict Mortality Risk Better than BMI appeared first on Inside Precision Medicine.

May 4, 2026

Cultural Relevance and Acceptability of Cognitive Behavioral Therapy Techniques Adapted by AI or a Human Psychologist: Experimental Study

Background: Evidence-based psychological interventions are usually not accessed by marginalized groups such as refugees. Culturally adapted psychological interventions have reported larger effect sizes than nonadapted psychological interventions. However, the cultural adaptation of interventions is a lengthy process, entailing a challenge. One potential solution to overcome this challenge is the use of artificial intelligence (AI). Objective: The aim of this study was to investigate and compare the perceived cultural relevance and acceptability of 2 common cognitive behavioral therapy (CBT) techniques when translated and culturally adapted by AI versus a human psychologist. Methods: In a 2×2 factorial design, the text generator type (AI vs human psychologist) and the CBT technique (cognitive restructuring vs behavior modification) were compared. CBT technique texts translated and culturally adapted either by AI or by a human psychologist were blindly rated using the Cultural Relevance Questionnaire and the Theoretical Framework of Acceptability. Raters were Arabic-speaking refugees and immigrants, aged between 18 and 69 years, residing in Sweden, Denmark, and Germany. Raters were randomly allocated to 1 of 4 conditions. Each condition consisted of 2 stimuli. Two-factor between-subject design analyses were used to analyze the data. Results: A significant main effect of the text generator domain type (=.02; η²=0.045) was found in the first rating, with texts adapted by the AI domain perceived as more culturally relevant than those adapted by the human domain. No significant main effect of the CBT technique was found in the first rating (=.10; η²=0.022). There were no differences in the second rating. Regarding acceptability, no significant main effects of text generator domain type (=.09; η²=0.024) or the CBT technique (=.88; η²=0.001) were found in either of the ratings. Conclusions: CBT technique materials adapted by AI may be perceived as similarly culturally relevant as those adapted by a human psychologist. This finding implies the potential to accelerate the cultural adaptation of psychological interventions. However, AI still needs to be used with caution and in accordance with rigorous safety standards and robust frameworks.
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May 4, 2026

Optical Pooled CRISPR Screen Reveals Regulators of NF-κB Dynamics in Human Cells

Tilmann Buerckstuemmer, PhD

CSO
Myllia Biotechnology

Jens Durruthy Durruthy, PhD

Director of Product Management
Element Biosciences

Broadcast Date: Wednesday, June 10, 2026

Time: 08:00 PDT, 11:00 EDT, 15:00 GMT

Integrated pooled CRISPR screening linked to imaging readouts accelerate target identification and functional characterization of signaling pathways. A good example of this can be found in studies of NF-κB signaling, which is central to inflammatory responses and driven by rapid nuclear translocation of the p50/p65 complex to activate transcriptional programs following cytokine stimulation.

In this GEN webinar, Tilmann Buerckstuemmer, PhD, CSO at Myllia Biotechnology will show how high-throughput pooled CRISPR screening combined with cell painting readouts characterized important signaling pathways using NF-κB nuclear translocation as a case study. During the webinar, you will learn how the AVITI24 platform from Element Biosciences profiled ~440,000 cells in a pooled CRISPR screen targeting 195 genes. Linking genetic perturbations to p65 subcellular localization and cell painting features in a single workflow enabled identification of known pathway components, uncovered regulatory roles for chromatin-modifying complexes, and improved interpretation of phenotypic outcomes using morphological features.

Key takeaways include:

Strategies for linking CRISPR perturbations to protein localization and morphological features at single-cell resolution

Identification of hitherto poorly characterized chromatin modifying complexes in regulating NF-κB signaling

The value of multimodal readouts, including morphology, in adding depth and confidence to recovered biology

How this approach supports mechanism-of-action studies and enables identification of both positive and negative regulators of signaling pathways

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

Produced with support from:

The post Optical Pooled CRISPR Screen Reveals Regulators of NF-κB Dynamics in Human Cells appeared first on GEN – Genetic Engineering and Biotechnology News.

May 1, 2026

Data-Driven Tool Identifies Individuals at Highest Risk of Obesity-Related Disease

A new clinical risk model may transform how obesity is managed, by identifying which individuals are most likely to develop serious complications, regardless of their body mass index (BMI).

Developed by researchers at Queen Mary University of London and the Berlin Institute of Health, the tool, called OBSCORE, uses just 20 routinely collected clinical variables to predict the future risk of 18 obesity-related conditions, ranging from type 2 diabetes to cardiovascular disease.

Published in Nature Medicine, the study challenges the long-standing reliance on BMI as the primary metric for assessing obesity-related health risk.

Moving beyond BMI

BMI has long served as a simple proxy for obesity, but it fails to capture the biological heterogeneity of patients. Two individuals with similar BMI can have vastly different risks of developing complications.

The new model addresses this limitation directly. As described in the study, it “provides information beyond BMI” by integrating multiple dimensions of health into a unified risk score.

These include demographic data, clinical biomarkers, disease history, and lifestyle factors, variables already commonly available in healthcare settings.

The findings show that BMI alone is a poor discriminator of risk. The model consistently outperformed BMI-based approaches across all tested outcomes.

Large-scale data enables precision risk prediction

To build the model, researchers analyzed health data from nearly 200,000 individuals with overweight or obesity from the UK Biobank.

Using an interpretable machine learning framework, they screened more than 2,000 potential predictors and distilled them into a core set of 20 features that best predicted long-term health outcomes.

The resulting OBSCORE model estimates the 10-year risk of developing 18 conditions, including cardiovascular disease, kidney disease, sleep apnea, and metabolic disorders.

The model demonstrated strong predictive performance, with median concordance indices around 0.75 across outcomes, indicating robust discrimination between high- and low-risk individuals.

Hidden high-risk individuals

One of the most striking findings is that high-risk individuals are not always those with the highest BMI.

A substantial proportion of individuals classified as high risk fell into the “overweight” category (BMI 27–30 kg/m²), rather than obesity. In some outcomes, up to ~40% of those in the highest risk group had BMI below the obesity threshold.

This reveals a critical gap in current clinical practice: individuals who may benefit from intervention could be overlooked simply because they do not meet BMI-based criteria.

On the other hand, some individuals with obesity may have relatively low risk and may not require intensive intervention.

Strong risk stratification across diseases

Beyond prediction, the scientists believe that OBSCORE enables meaningful risk stratification. Individuals in the highest risk group showed dramatically higher rates of disease compared to those in the lowest group.

For example, the study reports:

Up to 89-fold higher risk for chronic kidney disease
42-fold higher risk for type 2 diabetes
47-fold higher risk for cardiovascular mortality

These differences exceed those observed when comparing individuals based solely on BMI categories, underscoring the added value of multidimensional risk assessment.

Clinical and healthcare implications

The implications of these findings are significant, particularly in the context of emerging obesity therapies.

Highly effective drugs such as GLP-1 receptor agonists and dual incretin therapies have transformed treatment options, but their high cost and limited availability make patient prioritization essential.

As the authors note, current systems lack robust frameworks to identify which patients should receive treatment.

OBSCORE offers a potential solution by enabling risk-based allocation of interventions, ensuring that treatment is directed toward those most likely to benefit.

This could improve clinical outcomes while optimizing healthcare resource use.

Toward implementation in clinical practice

One of the key strengths of OBSCORE is its practicality. Unlike many predictive models, it relies on a small number of variables that are already routinely collected, making it suitable for integration into electronic health records.

The researchers envision the model being used as a decision-support tool in clinical settings, complementing rather than replacing existing frameworks.

External validation in independent cohorts—including populations of different ancestry, demonstrated strong generalizability, further supporting its potential for real-world deployment.

Limitations and next steps

Despite its promise, the model requires further validation in broader populations, including younger individuals and more diverse healthcare settings.

Additionally, while OBSCORE effectively stratifies risk, translating these predictions into actionable treatment thresholds will require clinical consensus and cost-effectiveness analyses.

The authors also emphasize that the model identifies predictive, not necessarily causal, factors, and should be interpreted accordingly.

Taken together, the findings mark a shift toward precision medicine in obesity, moving from simplistic metrics like BMI to data-driven, individualized risk assessment.

By capturing the complex interplay of metabolic, clinical, and behavioral factors, OBSCORE could enable earlier intervention, better targeting of therapies, and improved long-term outcomes for patients living with overweight and obesity.

The post Data-Driven Tool Identifies Individuals at Highest Risk of Obesity-Related Disease appeared first on Inside Precision Medicine.

April 30, 2026

Exploring Benefits of and Barriers to Patient Involvement Through Digital Tools in Psycho-Oncology: Qualitative Study Within the Reduct Trial

Background: Patient and public involvement is essential for developing patient-centered and acceptable eHealth interventions, yet little is known about how digital collaboration with patient representatives can best be implemented in psycho-oncological research. Objective: This study aimed to identify the benefits and barriers of digital collaboration in the development of an e-mental health application and provide recommendations to optimize digital collaboration with patient representatives in psycho-oncology research. Methods: Conducted from July to September 2023, this study involved digital semistructured interviews with 5 patient representatives from the Reduct trial, a multicenter randomized controlled trial to evaluate the efficacy of the web-based psycho-oncological training Make It. The interviews were analyzed using qualitative content analysis. Results: The findings highlighted multiple advantages of digital collaboration. These included significant reductions in travel costs and effort, personal acceptance and preference for digital methods, enhanced flexibility and accessibility, a reduced health burden, increased efficiency, and scalability. Conversely, several challenges were identified: social impacts or impediments due to less face-to-face interaction, technical difficulties, compromised effectiveness and quality of communication, diverse personal preferences and acceptance levels, organizational issues, cognitive demands, socioeconomic barriers, and safety concerns. The following recommendations to optimize digital collaboration were identified: maintaining regular communication and information exchange, valuing and committing to the collaboration, using diverse communication channels, ensuring comprehensible communication, integrating feedback, fostering openness and understanding, diligent documentation and recordkeeping, and providing targeted training and support for patient representatives. Conclusions: These findings confirm and specify previously known opportunities and challenges of digital collaboration, adding crucial insights for its implementation in psycho-oncological research. This research contributes to enhancing patient-centered approaches in psycho-oncology. Trial Registration: German Clinical Trials Register DRKS00025213; https://drks.de/search/en/trial/DRKS00025213
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April 29, 2026

Errors in AI-Transformed Patient-Centered Mental Health Documentation Written by Psychiatrists: Qualitative Pre-Post Study

Background: Patients’ digital access to their personal health data is becoming increasingly common worldwide. However, medical documentation often contains technical language and sensitive information, which can lead to potential misunderstandings and distress among patients. These issues may be particularly impactful in mental health contexts. Large language models (LLMs) offer a promising approach by transforming clinician-generated health notes into language that is more patient-centered, nonmedicalized, and empathetic. However, risks related to accuracy and clinical safety have not been adequately investigated in psychiatry. Objective: This study aimed to qualitatively analyze the errors introduced by LLMs when transforming notes written by psychiatrists into patient-facing formats. It also highlights the implications for clinical communication and patient safety. Methods: Clinical notes (n=63) written by 19 psychiatrists in an outpatient treatment setting were collected, anonymized, and translated from German to English by humans. OpenAI GPT-3.5 Turbo was used to develop a preprompt that transformed these notes into a patient-centered, lay-readable form through an iterative process. Three psychiatrists qualitatively analyzed the LLM-revised documentation using Kuckartz content analysis. They compared the preconversion and postconversion notes to systematically identify and categorize LLM-induced errors. Results: Five categories of clinically relevant errors were identified: (1) clinical misinterpretations, particularly in critical assessments such as suicidality, where nuanced terminology was oversimplified or inaccurately represented; (2) attribution errors, where behaviors or roles within family dynamics or interactions were incorrectly attributed to different individuals; (3) content distortion errors, which were characterized by speculative additions, emotional exaggerations, and inappropriate contextual assumptions; (4) abbreviation and terminology errors, which resulted from inaccurate expansions of medical abbreviations and terms; and (5) structural and syntax errors, which resulted in ambiguity, particularly when the original notes were brief or bulleted. Despite significant improvements in the readability and overall linguistic fluency of the converted notes, these errors occurred. Conclusions: LLMs have the potential to transform psychiatric notes into patient-friendly formats. However, critical errors remain prevalent and can impair clinical judgment, understanding of patient circumstances, clarity of medication regimens, and interpretation of clinical observations. To safely integrate artificial intelligence–generated documentation into psychiatric care, clinician oversight and targeted model refinement are essential. Future research should explore strategies to mitigate these errors, assess their comprehensive clinical impact, and incorporate patient and provider perspectives to ensure robust implementation.
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April 26, 2026

StockWatch: Trump Order Lifts Psychedelic Drug Shares

Stocks of most publicly traded psychedelic drug developers jumped when President Donald Trump signed Executive Order 14401, directing the FDA and other federal agencies to accelerate research and improve access to psychedelic drugs, citing their potential as promising treatments for serious mental illnesses.

Among its provisions, the order directs the FDA to provide Commissioner’s National Priority Vouchers (CNPVs) to “appropriate” psychedelic drugs that were granted the agency’s Breakthrough Therapy designation and met the voucher program’s criteria. The FDA’s parent agency, the Department of Health and Human Services (HHS), is required to spend at least $50 million through the Advanced Research Projects Agency for Health (ARPA-H) “to support and partner with” state governments that have enacted or are developing programs to advance psychedelic drugs for serious mental illnesses.

“This is an unmet public health need and potentially promising treatments. That’s why there’s a sense of urgency around this, and why we’re doing it now,” FDA Commissioner Martin A. Makary, MD, said at the ceremony where Trump signed the order. “Applications are about to come in, and this is the perfect timing for this announcement.”

At least one analyst agreed that the timing was right for Washington to spur the development of psychedelic drugs.

“Investor mindshare should rise meaningfully ahead of pot’l approvals in 2027–30,” Andrew Tsai, equity analyst with Jefferies, observed in a research note. “As we approach the first pot’l FDA approval of a psychedelic in 2027, President Trump is providing an official stamp of validation to the class in the form of an executive order, reassuring us that the FDA/HHS/White House’s support of psychedelics is real/actionable (not rhetorical).”

Proving correct

Makary said the FDA planned to issue CNPVs to three serotonin 2a agonists, a class that includes LSD and other psychedelic drugs. While he did not reveal specific companies and drugs by name, market watchers immediately speculated that one of the drugs was COMP360 synthetic psilocybin, the lead clinical candidate of Compass Pathways (NASDAQ: CMPS)—speculation that proved correct when COMP360 won a CNPV on Friday.

COMP360 is expected, according to Tsai, to be the first psychedelic drug to win FDA approval in 2027. In February, Compass announced what it called statistically significant and clinically meaningful data from two Phase III trials assessing COMP360 in treatment-resistant depression (TRD), COMP005 (NCT05624268) and COMP006 (NCT05711940). The data showed positive effects for COMP360 within one day, lasting at least through six months after just one or two doses among those who have a clinically meaningful response.

COMP360 is also in Phase II trials for both PTSD and anorexia nervosa.

Compass fueled speculation about an FDA voucher approval by issuing a statement supporting the executive order: “Today’s announcement aligns regulatory urgency with patient need, and we applaud the Administration for taking this important step forward in accelerating access, without compromising rigorous science.”

Investors celebrated with Compass, whose shares soared 42% from $6.66 to $9.46 on April 20, the first trading day after the order signing. Shares yo-yoed the rest of the week, sliding 7.5% to $8.75 Wednesday before rebounding nearly 5% to $9.15 Thursday and rising another roughly 5% to $9.58 Friday on news of the voucher approval. Year-over-year, Compass shares have more than doubled, soaring about 140% from $5.22 on April 24, 2025.

FDA names additional voucher grantees

The FDA indeed issued three CNPVs on Friday—one to Compass as previously mentioned, one to Usona Institute, a nonprofit medical research organization, for psilocybin for major depressive disorder (MDD), and one to Otsuka Pharmaceutical (Tokyo Stock Exchange: 4578) for methylone (TSND-201) for post-traumatic stress disorder (PTSD). Otsuka is acquiring the methylone program as part of its up-to-$1.225 billion ($700 million upfront) purchase of privately held Transcend Therapeutics, announced last month.

Launched in October by Makary, CNPVs are awarded to drug developers whose work is deemed to address a health crisis in the United States, deliver more innovative cures, address unmet public health needs, and increase domestic drug manufacturing as a national security issue. The vouchers entitle companies to reviews of their final applications within a target timeframe of 1–2 months, rather than the current 10–12 months.

“Ultimately, we do not see the FDA’s issuance of the first set of CNPVs as precluding other psychedelic players from also obtaining CNPVs in the future—so we think the FDA’s action today bodes well for the space broadly,” Tsai wrote after the FDA announced the voucher recipients. “Net-net, the macro backdrop for psychedelics is improving.”

That improvement, Tsai added, reflects Trump’s endorsement of psychedelic drugs, a collaborative FDA, and growing interest in the space by big pharma giants such as Johnson & Johnson (NYSE: JNJ), which generated $1.696 billion in 2025 sales and $468 million in first quarter sales from Spravato (esketamine), an NMDA receptor antagonist indicated for treatment-resistent depression (TRD) and depressive symptoms in adults with MDD with acute suicidal ideation or behavior in conjunction with an oral antidepressant.

The voucher decision hardly budged Otsuka shares, which dipped nearly 1% Friday from ¥10,870 ($68.18) to ¥10,810 ($67.80).

However, Compass was one of several psychedelic drug companies to see their shares surge on news of the executive order.

AtaiBeckley (NASDAQ: ATAI), formed last November by the merger of atai Life Sciences and Beckley Psytech, jumped 22% from $4.03 to $4.90 on April 20, then plateaued the rest of the week, finishing Friday at $4.63 and a 15% one-week gain. AtaiBeckley shares year-over-year have more than tripled, rocketing 204% from $1.53 a year ago Friday.

Definium Therapeutics (NASDAQ: DFTX) shares rose 5% over two days, from $22.68 the Friday before Trump signed the order to $23.84 on Tuesday, but gave back all the week’s gain, finishing Friday at $22.48. Long-range investors have fared better, as Definium shares have more than tripled, zooming 249% from $6.43 on April 24, 2025.

GH Research (NASDAQ: GHRS) shares climbed 17% from $18.34 to $21.50 the first day after the executive order, only to drop 6% the rest of the week, closing Friday at $20.25 and settling for a 10% one-week gain. GH’s shares doubled year-over-year, growing 101% from $9.50 a year ago Friday.

Showing volatility

The executive order wasn’t enough to boost shares of Cybin, which operates under the name Helus Pharma (NASDAQ: HELP). Helus showed the most volatility in the days following the order signing, tumbling 12% from $5.61 to $4.93 on April 20. The drop followed Helus’ announcement that its CEO, Michael Cola, stepped down immediately at the request of its board, succeeded by interim CEO Eric So, while the board carries out a search for a permanent chief executive.

“It’s like they can’t give investors a break,” fumed “SamZaki320” on a Reddit chat board. “The only positive is that the executive order sentiment is pushing back against a total disaster. Not that it’s a good thing, other companies are up double digits.”

Helus shares bounced back 17% to $5.77 Wednesday and dipping 0.35% to $5.75 Thursday despite the company announcing two powerhouse additions to its scientific advisory board—Robert Langer, ScD, the David H. Koch Institute professor at MIT and a co-founder of Moderna (NASDAQ: MRNA); and Stephen Brannan, MD, a neuroscience drug development expert with over 20 years of experience designing and implementing clinical programs for psychiatric and neurological disorders. Shares fell 2% Friday, closing at $5.61.

In a statement, interim CEO So lauded Trump’s order: “The Executive Order reflects growing recognition of the urgent need for new treatment options in serious mental health conditions and the importance of advancing innovative therapies through rigorous, research-based development.”

Looking beyond Washington

Yet So acknowledged that Washington alone can’t advance psych drug development beyond what its science can accomplish: “Policy momentum is meaningful, but the future of this field will ultimately be determined by the strength of the clinical evidence and the ability to deliver safe, reliable treatments at scale.”

As did Helus and Compass, Definium also praised the executive order: “We applaud the Administration’s recognition that psychedelic medicines may represent meaningful new treatment options for patients,” Definium CEO Rob Barrow stated. He cited his company’s clinical development program for DT120 (lysergide tartrate) for conditions that include generalized anxiety disorder (GAD) and MDD.

At the ceremony where he signed the executive order, Trump acknowledged being asked to address psych drug development by podcaster Joe Rogan and others, which the president said led to talks with Makary as well as HHS Secretary Robert F. Kennedy Jr., NIH Director Jay Bhattacharya, MD, PhD, and Mehmet Oz, MD, administrator for the Centers for Medicare & Medicaid Services.

“Research has been going on for quite some time. But usually with things like this, nothing ever happens, no matter how the research ends up. We’re changing that,” Trump said. “Why would we wait three or four years to get it done? Or 10 years? Frankly, let’s get it done immediately—and that’s what happened.”

Leaders and laggards

Daiichi Sankyo (Tokyo Stock Exchange: 4568) shares slipped 10% from ¥2,790 ($17.50) to ¥2,499 ($15.67) on Friday after the drug developer announced it was delaying the release of its annual earnings results for the fiscal year that ended March 31, from April 27 to May 11, “as additional time is required to finalize the financial figures.” May 11 is the day when Daiichi Sankyo plans to release its five-year business plan. “The company is currently reviewing the supply plans for its oncology products portfolio and development pipeline in light of rapidly changing business conditions. As a result, additional deliberation is required to reasonably estimate the amount of loss provisions to be recorded in connection with contracts with contract manufacturers,” Daiichi Sankyo added in a statement.
Inhibrx Biosciences (NASDAQ: INBX) shares leaped 37% from $84.08 to $115.09 Wednesday after Reuters reported, citing unnamed sources, that Merck & Co. (NYSE: MRK), Merck KGaA (XETRA: MRK), and Ono Pharmaceutical (Tokyo Stock Exchange: 4528) were in talks with Inhibrx for a joint spinoff of two precision-engineered cancer candidates, INBRX-106 and ozekibart (INBRX-109). The treatments could have a combined value of more than $9 billion if their clinical trials prove successful, the report stated. Inhibrx declined to comment, while the other companies cited did not respond to Reuters queries. INBRX-106 is a hexavalent sdAb-based, OX40-targeting candidate being studied as monotherapy and in combination with Merck & Co.’s cancer immunotherapy blockbuster Keytruda® (pembrolizumab). Ozekibart is a tetravalent death receptor 5 (DR5) agonist antibody designed to exploit the tumor-biased cell death induced by DR5 activation. On Tuesday, Inhibrx announced ozekibart showed positive data in a Phase I/II trial (NCT03715933) assessing the drug plus Folfiri in patients with locally advanced or metastatic, unresectable colorectal cancer.
Organon (NYSE: OGN) shares surged 31% from $8.60 to $11.26 Friday after the Indian news outlet The Economic Times reported that Sun Pharmaceutical Industries (NSE: SUNPHARMA and BSE: 524715) had submitted a $13 billion offer for the women’s health drug developer spun out of Merck & Co. (NYSE: MRK) in 2021. The deal would be Sun’s largest ever merger-and-acquisition (M&A) deal—if Sun can prevail over at least two other would-be suitors for Organon, German-based private family-owned drug developer Grünenthal, and EQT (Nasdaq Stockholm: EQT), a Swedish-based global investment organization. The latest surge comes two weeks after Organo shares zoomed 28% on an April 10 Economic Times report stating that Sun Pharma had submitted a $12 billion all-cash offer for Organon.
Spruce Biosciences (NASDAQ: SPRB) shares tumbled 26% from $69.89 to $51.69 Tuesday after the neurological disorder drug developer priced a $69 million offering of common stock and pre-funded warrants that generated $64.4 million in net proceeds. The offering consisted of 1.15 million shares of common stock priced at $50 per share and pre-funded warrants to purchase 50,000 shares at $49.99 per share. Al shares and pre-funded warrants were sold, and underwriters of the offering exercised in full their option to purchase up to an additional 180,000 shares at the public offering price on Tuesday. “We intend to use the net proceeds from this offering to advance the company’s pre-commercial and launch activities, for planned clinical trials, and for working capital, capital expenditures, and other general corporate purposes,” Spruce stated in its prospectus supplement filed Tuesday. Leerink Partners, Guggenheim Securities, and Oppenheimer & Co. acted as joint book-running managers, while Jones and Craig-Hallum acted as co-managers for the offering.

The post StockWatch: Trump Order Lifts Psychedelic Drug Shares appeared first on GEN – Genetic Engineering and Biotechnology News.

April 23, 2026

Expected Competencies and Personal Attributes of Digital Health Navigators to Support Digital Mental Health Care: Focus Group and Interview Study With Patients and Health Care Professionals

Background: Digital mental health apps (DMHAs), and in particular digital therapeutics (DTx), offer promising opportunities to support mental health care. However, their effective use in outpatient settings in Germany remains limited. To overcome this gap, the role of digital health navigators (DHNs) has been introduced. DHNs are trained individuals who support patients and health care professionals in selecting, using, and integrating DMHAs into care. Despite increasing interest in this role, there is limited evidence on the competencies, knowledge, and personal attributes required for DHNs to work effectively in mental health settings. Objective: The study aims to explore the expected competencies, knowledge areas, and personal attributes that DHNs need to effectively support the implementation and use of DTx in outpatient mental health care. Methods: As part of the prestudy of the Digital Navigators for Acceptance and Competence Development with Mental Health Apps (DigiNavi) study, a qualitative study was conducted involving 35 participants (7 general practitioners, 8 patients in general practice, 11 outpatient psychiatrists/psychologists, and 9 patients in psychiatric outpatient clinics) from different general practices and psychiatric outpatient clinics in Germany. A total of 17 semistructured interviews and 4 focus groups were conducted to explore expectations of DHNs. Data were analyzed using qualitative content analysis. Results: Participants emphasized that DHNs should combine strong interpersonal skills (empathy, patience, and sensitive communication) with technical and basic clinical competencies. Most favored DHNs as integrated clinical team members (eg, medical assistants), citing their existing patient relationships, but noted time and training constraints. Key expectations included the ability to support patients with DTx use, adapt communication to individual needs, and convey data privacy information clearly. Foundational knowledge of mental health conditions and sensitivity to crises were considered important for identifying warning signs and escalating concerns. While DHNs were seen as essential intermediaries between patients, health care professionals, and DTx, participants highlighted the necessity for clearly defined roles, structured training, and realistic expectations to prevent role overload and enable sustainable implementation in outpatient mental health care. Conclusions: DHNs require a specialized skill set that bridges clinical understanding, digital expertise, and interpersonal competence. Our results lay the groundwork for developing training curricula and implementation strategies that align with real-world expectations for the DHN role. Defining these core competencies is essential for supporting the sustainable and effective integration of DMHAs into mental health care. Trial Registration: German Clinical Trials Register DRKS00034327; https://drks.de/search/en/trial/DRKS00034327 and ClinicalTrials.gov NCT06575582; https://clinicaltrials.gov/study/NCT06575582 International Registered Report Identifier (IRRID): RR2-10.2196/67655
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April 23, 2026

Regenerative Medicine: Promise, Hype, and What Actually Works

From stem cells to platelet-rich plasma, regenerative medicine is often positioned as the future of healthcare. But not all approaches deliver on that promise. As interest grows, so do questions regarding what actually works. GEN’s Editor in Chief John Sterling spoke with Thomas Buchheit, MD, founder and medical director of the Triangle Regen Medicine and Biologics Center in Chapel Hill, NC, in relation to the science, the hype, and the realities shaping the field today.

GEN: How do you define regenerative medicine?

Buchheit: Many people think of regenerative medicine as growing new organs, but I define it more broadly as any therapy that improves tissue health or function. With that definition, we can include platelet-rich plasma (PRP), stem cells, and autologous conditioned serum (ACS). These approaches aim to enhance tissue health and improve function.

GEN: The field is promising, but also sometimes criticized as overhyped. Which areas deserve that criticism, and which have gained credibility through clinical validation?

Buchheit: Some criticism is valid, especially around stem cells. We’ve all seen claims over “miracle” stem cells that regrow cartilage. In reality, while these cells can be therapeutic, they typically don’t survive long after injection. Instead, they work by activating the body’s immune-based healing mechanisms. They can improve tissue health, but they’re not the miracle cures they were once portrayed to be.

On the other hand, therapies like PRP and ACS have gained credibility when properly applied and studied, particularly in musculoskeletal conditions.

GEN: How do you incorporate regenerative medicine into your practice?

Buchheit: I focus on patient function—what people can do now and what they want to achieve. Then tailor therapies accordingly. I prioritize treatments with strong evidence. One example is ACS, also known as the Regenokine* program. It’s highly standardized and supported by over 20 years of research in osteoarthritis, sciatica, and radiculopathy.

Thomas Buchheit, MD

I also use PRP, which can be effective, but only when properly dosed. That’s been a major challenge since there are many ways to prepare PRP. We now know that dose matters. For example, treating knee osteoarthritis typically requires close to 10 billion platelets. At our clinic, we measure platelet counts before and after preparation to ensure accuracy, something often not done enough or at all.

GEN: Where did these approaches originate, and how widely are they used?

Buchheit: ACS originated in Germany in the 1990s with Dr. Peter Wehling. It was initially developed as an alternative to steroids for treating sciatica. The process involves incubating whole blood under controlled conditions, which stimulates the release of anti-inflammatory proteins, growth factors, and exosomes.

It became popular as patients, including athletes, traveled to Germany for treatment. Today, it’s available in the United States, though still more common in Europe. We now better understand how it works. Our research shows that exosomes play a key role in long-term benefits. If you remove them, effectiveness drops significantly.

GEN: Your new book Healing Joints and Nerves—who is it for?

Buchheit: It’s written for patients and a broad audience. I focused on authoring a book on regenerative medicine based on scientific accuracy and depth. I wanted to create a resource that explains these therapies clearly and truthfully—what they can and cannot do. It took over six years to complete. The book covers the history of stem cells and concludes with ACS, including both research and my personal experience with it as an avid runner and bicycle rider.

GEN: You often mention “good” vs. “bad” inflammation. What’s the difference?

Buchheit: Chronic inflammation is harmful. It damages tissue, drives pain, and contributes to diseases like osteoarthritis. But acute, controlled inflammation is essential for healing. It triggers the body’s repair processes. Exercise is a good example. It creates cycles of inflammation and recovery that make us stronger. Regenerative therapies aim to harness this same mechanism.

Interestingly, suppressing inflammation too aggressively can backfire. Studies show that patients who take anti-inflammatories after acute injuries may have a higher risk of chronic pain. Repeated steroid injections can also worsen joint damage over time.

GEN: Does all PRP work for osteoarthritis?

Buchheit: No. PRP must contain a sufficient platelet dose to be effective. Research shows that below approximately three billion platelets, it’s unlikely to work. Above four billion, effectiveness improves, and near 10 billion provides optimal results.

A practical tip: patients should ask how much blood is drawn. If only 10 mL is used to produce PRP, it’s mathematically impossible to achieve a high dose. Proper preparation typically requires 60–120 mL. Patients should also ask whether platelet counts are measured.

GEN: Please talk a bit more about Regenokine.

Buchheit: The program is based on ACS, enhanced through a controlled incubation process. This stimulates cells to release anti-inflammatory proteins, growth factors, and exosomes. Treatment typically takes roughly a week. Patients often come to the clinic for that duration. We’ve seen strong results in osteoarthritis and spine conditions, especially in patients who haven’t responded to other treatments, including stem cells.

GEN: What about safety, efficacy, and durability of results?

Buchheit: Outcomes vary by patient, but the primary goal is restoring function—whether that’s walking a dog or running a marathon. My approach is to stay as evidence-based as possible. That’s critical in a field where there is some overpromise or poorly validated treatments.

There are real concerns regarding product quality, sourcing, and transparency in some parts of the market. We need to know exactly what we’re using, how it works, and what evidence supports it. That’s how regenerative medicine will continue to advance responsibly.

Thomas Buchheit, MD, founded the Triangle Regen Medicine and Biologics Center in Chapel Hill, NC, to bring a range of regenerative therapies to patients. He now serves as an adjunct associate professor at Duke and continues to work with scientists at the Center for Translational Pain Medicine.

Buchheit began studying nerve injury pain and served as chief of pain medicine at Duke University Medical Center. He investigated the immune basis of pain relief following injury and the mechanisms behind regenerative therapies, including platelet-rich plasma, stem cells, and autologous conditioned serum. He has led several studies funded by the NIH and the Department of Defense.

*Regenokine was developed by Peter Wehling, MD, in Germany, originally in the 1990s. It utilizes a patient’s own blood to create a serum rich in anti-inflammatory proteins, particularly the interleukin 1 receptor antagonist (IL-1Ra), which helps reduce inflammation and promote healing in joints and tendons. The treatment is used for conditions like osteoarthritis and has gained popularity among athletes seeking pain relief. While it has shown promise in small studies, it is not yet FDA-approved and is not covered by insurance in the United States.

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