Background: Visuospatial neglect (VSN) is a cognitive disorder following a stroke, where individuals fail to perceive or respond to stimuli on the contralesional side of space. Visual scanning training (VST) is the recommended treatment in clinical guidelines. Objective: This qualitative study explored how patients (N=10) and informal caregivers (N=8) perceived the usability and potential implementation of 3 extended reality (XR)–based serious games to enhance VST—1 in virtual reality and 2 in augmented reality—as tools for VST. These technologies not only enhance patient engagement but also enable detailed data collection to monitor therapeutic progress. Methods: The themes and feedback were compared with themes and feedback from VSN therapists from a previous study: (1) suitability for VSN rehabilitation, (2) applicability, (3) motivation, (4) guidance, (5) versatility, and (6) detailed insights in game performance. Results: Highlights were that patients reported high engagement and enjoyment, with many expressing willingness to use the games in both clinical and home settings. Informal caregivers supported these findings and emphasized the motivational value of the games. Additionally, both groups noted the importance of accessible instructions and technical support. Conclusions: Although XR technology offers potential in neurorehabilitation, a uniform solution may not suit all users. This study showed the importance of including diverse end-user groups in development for usability, acceptance, and implementation. Successful integration of XR in rehabilitation requires customizable features, structured support, and attention to the differing roles of caregivers. Further research is needed to evaluate the clinical effectiveness and optimize patient-tailored applications of XR in VSN treatment.
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Opportunities for Digital Health to Support Early Psychosis Care in Ghana: Qualitative Study Among Patients, Caregivers, and Clinicians
Background: Youth experiencing early psychosis in West Africa often face delays in accessing evidence-based treatment. Digital mental health interventions may offer an acceptable and scalable approach to improve access to early psychosis care in West Africa; however, few data exist on the experiences and perspectives of patients with early psychosis and their caregivers to inform digital intervention development. Objective: This study aims to explore current experiences of early psychosis care, identify barriers and facilitators to in-person early psychosis care within health facilities, and identify opportunities for digital interventions to support patients with early psychosis and caregivers in Ghana. Methods: We conducted qualitative focus group discussions among patients with early psychosis, their caregivers, and their mental health care providers recruited at Accra Psychiatric Hospital in Accra, Ghana. Trained qualitative researchers facilitated discussions using a structured qualitative interview guide, exploring current care practices for early psychosis in Ghana, barriers and facilitators to facility-based care, and perceptions of digital mental health interventions. Transcripts were translated, transcribed, and analyzed thematically using a hybrid inductive and deductive approach grounded in the theoretical framework of acceptability. Results: Overall, we conducted 4 focus group discussions (N=31) among 7 patients with early psychosis (median age 28, IQR 21‐41 years), 6 caregivers (median age 58, IQR 29‐34 years), and 18 clinicians (median age 30, IQR 29‐34 years). Participants described current early psychosis care practices in Ghana, including seeking spiritual and traditional healing, the dearth of information and resources about psychosis, and the integral role of caregivers in facilitating treatment engagement and continuation (often at the cost of caregiver mental distress and burnout). Common barriers to facility-based mental health care included stigma associated with mental illness, lack of prior knowledge about early psychosis and treatment options, and practical constraints (eg, financial, logistical, and health care system limitations). Motivating factors for facility-based care included success stories from community members and strong rapport and trust in mental health clinicians. Technology (eg, mobile phones, laptops, radio, and television) was commonly used among participants in typical daily tasks, health information seeking, and stress reduction. Participants expressed support for digital tools that could deliver psychoeducation about early psychosis, support treatment adherence, and extend patient-provider communication between clinic visits. Conclusions: Digital mental health interventions have the potential to complement facility-based early psychosis services in Ghana by addressing misinformation, reducing access barriers, and supporting caregiver roles. These qualitative findings inform potential integration points, content, attributes, and strengths of digital modalities that could be leveraged to support patients with early psychosis and their caregivers in Ghana.
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Popular Online Content as a Treatment-as-Usual Control in Digital Mental Health Intervention Trials: Secondary Analysis of Two Online Randomized Controlled Trials With Repeated Measures
Background: Treatment-as-usual (TAU) conditions are intended to reflect the support typically received in routine treatment settings. For digital mental health interventions (DMHIs) delivered online, TAU conditions should reflect the usual patterns of online help-seeking. The lack of ecologically valid TAU control conditions has been a gap in effectiveness trials of online DMHIs. In this study, mental health–related popular online content (eg, advice TikToks, lived experience vlogs, and self-care infographics) was examined as a valuable TAU control condition. Objective: This study examined the feasibility of popular online content as a TAU control condition in DMHI trials. Methods: This study was a secondary analysis of two randomized controlled trials. Both trials recruited participants online, primarily via an online study recruitment platform. In study 1 (N=916), US adults with elevated depression or anxiety were randomized to either (1) complete a single-session DHMI for depression and anxiety (n=291), (2) search the web for popular online content relevant to their struggles (n=312), or (3) search a curated library of mental health–related popular online content (n=313). In study 2 (N=431), US adults with elevated loneliness were randomized to (1) complete a single-session DHMI for loneliness (n=136), (2) search a curated library of popular online content related to loneliness (n=145), or (3) complete an attention-matched control condition (n=150). All 6 programs took approximately 10 to 20 minutes to complete and were entirely self-guided. Participants rated each program’s credibility and expected benefit, as well as their feelings of distress (study 1) and loneliness (study 2). The studies did not involve interaction between participants and the research team. Results: In study 1, dropout during the treatment was 4.8% (14/291) for the single-session intervention, 25.9% (81/312) for online help-seeking, and 9.6% (30/313) for the curated library. The curated library’s credibility and expected benefit score did not differ from that of the single-session intervention (Cohen =0.08; =.88) and was higher than that of unguided help-seeking (Cohen =0.23; =.01). In study 2, dropout was higher in the curated library condition (7/145, 4.8%) than in the single-session intervention and the attention-matched control condition (0/136, 0.0% and 0/150, 0.0%). The mean credibility and expected benefit score for the curated library was comparable to that of the attention-matched control condition (Cohen =0.00; >.99) but lower than that of the single-session intervention (Cohen =0.32; =.02). Changes in distress and loneliness from baseline to 8-week follow-up did not differ across the conditions in study 1. All effect sizes were small in study 1 (Cohen <0.15 and no comparisons were statistically significant >.06). Similarly, in study 2, all effect sizes were small (Cohen <0.12), and no comparisons were statistically significant (>.25). Conclusions: Curated libraries of popular online content are a feasible, ecologically valid TAU benchmark for effectiveness trials of online DMHIs. Future research on TAU conditions in online help-seeking contexts should better align with observed DMHI attrition rates and account for the increasingly central role of conversational artificial intelligence in online mental health support. Trial Registration: OSF Registries 3DYMA; https://osf.io/3dyma and NVD79; https://osf.io/nvd79; ClinicalTrials.gov NCT05687162; https://clinicaltrials.gov/study/NCT05687162
Lilly to Acquire Kelonia for Up to $7B, Expanding Cancer Cell Therapy Pipeline
Eli Lilly has agreed to acquire Kelonia Therapeutics for up to $7 billion, the companies said today, in a deal that would bolster the buyer’s oncology pipeline with an early clinical phase lentiviral in vivo chimeric antigen receptor T-cell (CAR T) therapy under study in relapsed/refractory multiple myeloma.
Kelonia’s lead program KLN-1010 is a one-time intravenous gene therapy designed to generate anti-B-cell maturation antigen (BCMA) CAR T cells, targeting the BCMA protein expressed on the surface of multiple myeloma cells.
In December at the American Society of Hematology (ASH) 2025 Annual Meeting, Kelonia presented positive early clinical data for KLN-1010 from the Phase I inMMyCARTM trial (NCT07075185). The data showed the CAR T therapy to have 100% minimal residual disease (MRD)-negative response rate across four patients, all of whom remained in response through the longest follow up of five months.
Those and other results, according to the company, provided initial clinical validation of KLN-1010 and demonstrated promising tolerability. In January, Kelonia won FDA clearance for an investigational new drug (IND) application for KLN-1010, enabling the trial to expand from Australia into multiple clinical sites across the United States.
“The early clinical data for KLN-1010 are highly encouraging, both as a potential step forward for patients with multiple myeloma and as proof of concept for Kelonia’s platform,” Jacob Van Naarden, executive vice president and president of Lilly Oncology and head of corporate business development, said in a statement.
Investors appeared more sanguine about the Kelonia acquisition as Lilly shares were all but flat in early Monday trading as of 11 a.m. ET, to $927.16 from Friday’s close of $927.03. Kelonia is privately held.
KLN-1010 applies the company’s in vivo gene placement system (iGPS®), which uses engineered lentiviral-based particles designed to efficiently and selectively enter T-cells inside the body, enabling a patient’s own body to generate CAR T therapies designed to treat underlying disease.
Lilly and Kelonia reason that KLN-1010 could transform treatment of multiple myeloma by eliminating challenges associated with both ex vivo patient-specific cell therapy manufacturing, and pre-administration chemotherapy.
“Autologous CAR T therapies have meaningfully improved outcomes for patients with various cancers, but significant manufacturing, safety, and access barriers mean that only a fraction of eligible patients actually receive them,” Van Naarden added. “Kelonia’s in vivo platform has the potential to change that by delivering rapid, durable responses in a far simpler, off-the-shelf format.”
Kelonia marks Eli Lilly’s fourth announced acquisition of a smaller biotech this year:
- In March, Lilly committed up to $7.8 billion to acquire Centessa Therapeutics, a developer of sleep disorder drugs.
- A month earlier, Lilly announced plans to buy out circular RNA cell therapy developer Orna Therapeutics for up to $2.4 billion, targeting advancements in cell therapy.
- And in January, Lilly inked a $1.2 billion acquisition of Ventyx Biosciences, an NLRP3-targeting oral drug developer focused on inflammatory diseases.
Behind the deals
Behind all the deals is the pharma giant’s desire to capitalize on the billions of dollars it is generating from sales of its obesity and diabetes drugs based on glucagon-like peptide 1 (GLP-1) receptor analysts alone or in tandem with a glucose-dependent insulinotropic polypeptide (GIP). Lilly markets tirzepatide, a GLP-1/GIP dual agonist, in obesity as Zepbound® ($13.542 billion in 2025 sales) and in diabetes as Mounjaro® ($22.965 billion).
Lilly stands to generate even more in obesity-related sales in coming years once it brings to market its oral obesity drug Foundayo
(orforglipron), a small molecule GLP-1 receptor agonist—though analysts predict the drug’s 2026 sales will likely be lower than once expected because of the price war Foundayo faces competing head to head with Lilly’s arch-rival in obesity drugs, Novo Nordisk. In December, Novo Nordisk got a jump on Lilly when the Danish biotech giant won FDA approval for oral Wegovy® (semaglutide), a once-daily 25 mg GLP-1 receptor agonist tablet indicated for chronic weight management.
A Lilly buyout of Kelonia could compel Johnson & Johnson to take a closer look at acquiring Legend Biotech, Kostas Biliouris, PhD, a managing director on the biotechnology research team of Oppenheimer, wrote Sunday in a research note. He cited the fact J&J’s Janssen Biotech successfully partnered with Legend to develop Carvykti® (ciltacabtagene autoleucel), a B-cell maturation antigen (BCMA)-directed CAR T-cell therapy indicated for adults with relapsed or refractory multiple myeloma who have received at least one prior line of therapy. Carvykti generated $1.877 billion in sales last year, up nearly double (96%) from $963 million in 2024.
Also, Biliouris cited the presence in Legend’s pipeline of LUCAR-G39D, a clinical in vivo CAR T program designed to treat B-cell non-Hodgkin’s lymphoma by targeting CD19xCD20. LUCAR-G39D showed positive first-in-human safety and efficacy data from a Phase I trial (NCT06395870) at ASH last December.
“We believe in vivo CAR T technology has strong potential, as treatment process is fast and circumvents the need for lymphodepletion, but think it will likely take ~6-8years before safety/durability questions are addressed, and regulatory approval is granted,” Biliouris predicted.
Lilly has agreed to acquire Kelonia for $3.25 billion upfront plus up to $3.75 billion in future payments tied to achieving specified clinical, regulatory, and commercial milestones. The acquisition deal is subject to regulatory approvals and other customary closing conditions, and is expected to close in the second half of 2026.
Upon closing, Lilly said, it will determine how to account for the transaction in accordance with Generally Accepted Accounting Principles (GAAP), then reflect the deal in future financial results and financial guidance.
“Kelonia’s leadership in advancing the immense promise of in vivo cell therapy is unmatched, extending its reach and impact beyond the traditional boundaries of personalized medicine,” Kelonia CEO Kevin Friedman, PhD, stated. “We have demonstrated the ability to achieve deep multiple myeloma remissions with significantly reduced complexity and cost relative to ex vivo CAR T-cell approaches.”
“In combination with Lilly’s strengths, our in vivo iGPS platform is positioned to broaden the reach of cell therapy beyond the current CAR T landscape in hematologic malignancies and to transform treatment across a far wider range of cancers and other serious diseases,” Friedman added.
The post Lilly to Acquire Kelonia for Up to $7B, Expanding Cancer Cell Therapy Pipeline appeared first on GEN – Genetic Engineering and Biotechnology News.
Distinct Nature of Parkinson’s Disease Gut Microbiome Identified
Research led by University College London has characterized a specific gut microbiome signature found in people with Parkinson’s disease.
Writing in Nature Medicine, the researchers also found that people carrying a genetic mutation in the GBA1 gene that put them at risk of developing Parkinson’s disease had gut microbiomes similar to people with the condition.
Parkinson’s is the second most common neurodegenerative disease in the U.S. after Alzheimer’s disease affecting more than one million people across the country. By the time full-blown motor symptoms emerge, a large degree of neurological damage has already occurred, so much work is underway to find ways to predict and diagnose early disease, as well as to develop more effective treatments.
“In recent years there has been a growing recognition of the links between Parkinson’s disease—a brain disorder—and gut health,” said co-lead author Anthony Schapira, MD, a professor at UCL Queen Square Institute of Neurology, in a press statement.
“Here we have strengthened that evidence and shown that microbes in the gut can reveal signs of Parkinson’s and may be an early warning signal… years before symptom onset.”
For this study, the researchers evaluated gut microbiome samples from 271 Parkinson’s disease patients, 43 people carrying GBA1 risk variants who did not yet have disease symptoms and 150 healthy controls. They also validated their findings in a further 638 people with Parkinson’s and 319 healthy controls from the U.K., Korea, and Turkey.
Schapira and team used DNA sequencing to see which bacterial species were present in each person’s gut. Comparing people with Parkinson’s disease to healthy controls, they found 176 bacterial species that were more or less common in people with the condition.
For example, people with Parkinson’s had more potentially pro‑inflammatory bacteria, including Bifidobacterium longum and B. dentium, Streptococcus mutans, and Lactobacillus paragasseri, than healthy controls.
In contrast, healthy controls had more helpful, butyrate‑producing gut bacteria from including Roseburia intestinalis, R. inulinivorans and some Faecalibacterium species and less pro-inflammatory species.
Notably, people in the at-risk group who carried a GBA1 risk variant had a gut microbiome somewhere between healthy controls and people with Parkinson’s, suggesting that the composition of microbes in the gut may change over time as the disease develops. In this group, 142 of the 176 species that differed in people with Parkinson’s versus healthy controls also showed changed abundance.
“For the first time we identify bacteria in the gut of people with Parkinson’s that can also be found in those with a genetic risk for the disease, but before they develop symptoms. Importantly, these same changes can be found in a small proportion of the general population that may put them at increased risk for Parkinson’s,” said Schapira.
“This discovery opens the way not only to see if the bacteria are a way to identify those at risk of Parkinson’s, but also to see if changing the bacterial population, through dietary changes or medication, can reduce a person’s risk for Parkinson’s.”
The post Distinct Nature of Parkinson’s Disease Gut Microbiome Identified appeared first on Inside Precision Medicine.
STAT+: Trump order to advance psychedelic treatments generates excitement — and worries
President Trump’s executive order aimed at loosening restrictions on psychedelics as mental health treatments was largely applauded by advocates. But some also quietly worry the White House’s role in trying to bolster the field risks politicizing it and undermining the credibility of research.
The order, which was reported to have stemmed at least in part from a text podcaster Joe Rogan sent Trump about psychedelics research, directs the Food and Drug Administration to expedite the review of some compounds and calls for the establishment of a new regulatory pathway for experimental psychedelics to be tried by terminally ill patients. It also allocates funding to states developing research programs.
While the order does not actually reschedule any drugs or change legislation, many advocates and researchers welcomed the move, saying it signals the administration’s interest in advancing psychedelics as treatments and could help ease bottlenecks in expanding access.
Opinion: The contradiction at the heart of Republicans’ embrace of psychedelics
On Saturday, with podcaster and psychedelics fan Joe Rogan standing over his shoulder, President Trump signed an executive order intended to expand access to psychedelics for mental health treatment.
For some, it may come as a surprise to see a Republican president embrace psychedelics. But he’s only the most recent member of the GOP to hop on the psychedelics bandwagon.
AACR 2026: Cancers of Unknown Primary Identified by DNA Methylation AI Model
SAN DIEGO – Researchers from Kindai University in Japan have developed a machine learning model that accurately predicts the origin of diverse cancer types in patients with cancers of unknown primary (CUP) by analyzing CpG-based DNA methylation. Results showed that the model correctly identified the cancer type in about 95% of cases in the test cohort, and achieved 87% accuracy when applied to an independent validation cohort from 31 cases representing 17 different cancer types. The work was presented at the American Association for Cancer Research (AACR) Annual Meeting.
“Our findings suggest that DNA-based approaches can help identify where a cancer may have started, even when the original tumor is not visible,” said Marco A. De Velasco, PhD, a faculty member in the department of genome biology at Kindai University in Japan.
CUP are metastatic malignancies in which the primary cancer site could not be identified. These cancers are often associated with poorer outcomes, as patients are typically treated with broad, nonspecific chemotherapy regimens rather than therapies targeted to a specific cancer type.
Approximately only 15-20% of patients with CUP show features that allow site-specific therapies. Patients receiving site-directed therapy can survive up to 24 months, compared with six to nine months for those receiving standard treatment.
Patterns in tumor biology, such as gene activity or chemical modifications to DNA, can differ between cancer types and persist even after the cancer has spread and guide development of these therapies. While some methods have shown promise, they have yet to demonstrate clear survival benefits in clinical trials.
The model was developed using methylation data from nearly 7,500 patients with 21 different cancer types obtained from The Cancer Genome Atlas Program and other public datasets. Using machine learning, the researchers identified CpG methylation and built methylation profiles that were associated with different tumor types.
Del Velasco emphasized that the study achieved high accuracy in predicting the origin of diverse cancer types using a small subset of DNA markers, about 1,000 CpG regions selected from hundreds of thousands across the genome. “This is important because it shows that we can simplify complex molecular data while still maintaining strong predictive performance,” he said.
As a limitation, the model was developed using cancers with known origins, rather than true CUP. Testing in CUP patients is important to understand how well the model performs in clinical settings. Additionally, not all tumors are easily accessible for genetic testing, particularly tumors in advanced stage. Looking ahead, the authors aim to adapt and evaluate the model using blood-based biopsy to analyze circulating tumor DNA instead of relying on DNA from tissue samples.
The post AACR 2026: Cancers of Unknown Primary Identified by DNA Methylation AI Model appeared first on GEN – Genetic Engineering and Biotechnology News.
Correction: Promoting Sustained Real-Life Benefits of Virtual Reality–Based Interventions in People With Mental Health and Substance Use Disorders: Qualitative Study
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<![CDATA[ASAM’s new youth SUD criteria help clinicians deliver developmentally tailored, prevention-first care with coordinated family and community supports.]]>