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Pencil Beam Laser Could Help Researchers Design Brain-Targeted Therapies

Scientists at MIT say they made a finding in optical physics that could enable a new bioimaging method that’s faster and higher-resolution than existing technology. They discovered that, under the right conditions, laser light clutter can spontaneously self-organize into a highly focused “pencil beam.”

Using this self-organized pencil beam, the team captured 3D images of the human blood-brain barrier 25 times faster than the gold-standard method, while maintaining comparable resolution, according to the scientists.

By showing individual cells absorbing drugs in real-time, this technology could help scientists test whether new drugs for neurodegenerative disease like Alzheimer’s or ALS reach their targets in the brain, with greater speed and resolution, they add.

“The common belief in the field is that if you crank up the power in this type of laser, the light will inevitably become chaotic. But we proved that this is not the case. We followed the evidence, embraced the uncertainty, and found a way to let the light organize itself into a novel solution for bioimaging,” says Sixian You, PhD, assistant professor in the MIT department of electrical engineering and computer science (EECS), a member of the research laboratory for electronics.

You is senior author of a paper “Self-localized ultrafast pencil beam for volumetric multiphoton imaging” on this imaging technique in Nature Medicine.

A better beam

When the researchers performed characterization experiments of this pencil beam, it was more stable and high-resolution than many similar beams. Other beams often suffer from “sidelobes,”  blurry halos of light that can distort images.

Their beam was more pristine and tightly focused, according to You. Building on those experiments, the researchers demonstrated the use of this pencil-beam in biomedical imaging of the human blood-brain barrier.

Scientists and clinicians often want to see how drugs flow inside the vasculature of the blood-brain barrier and whether they reach their targets within the brain. But with standard optical settings, the best one can do is capture one 2D section of the vasculature at a time, and then repeat the process multiple times to generate a fuller image, You explains.

Using this new technique, the researchers created an ultrafast, high-precision pencil beam that enabled them to dynamically track how cells absorb proteins in real-time.

“The pharmaceutical industry is especially interested in using human-based models to screen for drugs that effectively cross the barrier, as animal models often fail to predict what happens in humans. That this new method doesn’t require the cells to have a fluorescent tag is a game-changer,” notes Roger Kamm, PhD, the Cecil and Ida Green Distinguished Professor of Biological Science and Mechanical Engineering.

“For the first time, we can now visualize the time-dependent entry of drugs into the brain and even identify the rate at which specific cell types internalize the drug.”

“Importantly, however, this approach is not limited to the blood-brain barrier but enables time-resolved tracking of diverse compounds and molecular targets across engineered tissue models, providing a powerful tool for biological engineering,” points out postdoctoral fellow Sarah Spitz, PhD.

The team reports that it captured cellular-level 3D images that were higher quality than with other methods, and generated these images about 25 times faster.

“Usually, you have a tradeoff between image resolution and depth of focus—you can only probe so far at a time. But with our method, we can overcome this tradeoff by creating a pencil-beam with both high resolution and a large depth of focus,” You says.

In the future, the researchers want to better understand the fundamental physics of the pencil-beam and the mechanisms behind its self-organization. They also plan to apply the technique to other scenarios, such as imaging neurons in the brain, and work toward commercializing the technology.

The post Pencil Beam Laser Could Help Researchers Design Brain-Targeted Therapies appeared first on GEN – Genetic Engineering and Biotechnology News.

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STAT+: Erasca touts strong, though preliminary, results in trial of pancreatic and lung cancer therapy

The drugmaker Erasca said Monday that its RAS-targeting pill shrank tumors in 40% of patients with advanced pancreatic cancer and 62% of patients with advanced non-small cell lung cancer, results that the company said exceeded its expectations. 

The new data, collected from studies done in the U.S. and China, are still preliminary. However, Erasca said the clinical benefit and tolerability of its drug, called ERAS-0015, compared favorably to daraxonrasib, a similar RAS-targeting drug from Revolution Medicines that recently showed a doubling of overall survival in patients with advanced pancreatic cancer. 

“I’m excited about both datasets, but I think lung is more definitive at this point. The pancreatic results are maturing, but are very, very promising,” Erasca CEO Jonathan Lim told STAT. “All options are on the table.” 

Continue to STAT+ to read the full story…

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Obesity Leaves Lasting DNA Methylation Memory in Immune Cells

A new study suggests that obesity leaves a durable molecular imprint on the immune system, one that persists long after weight loss and may continue to influence disease risk. Researchers at the University of Birmingham report that key immune cells retain an “epigenetic memory” of obesity, potentially sustaining inflammation and metabolic dysfunction even after patients return to a healthy weight.

The findings, published in EMBO Reports, provide a mechanistic explanation for a long-standing clinical observation: that individuals who lose weight often remain at elevated risk for conditions such as type 2 diabetes, cardiovascular disease, and certain cancers.

Immune cells retain a “memory” of obesity

The study focuses on CD4+ helper T cells, central regulators of immune coordination. By analyzing patient samples across multiple cohorts, including individuals undergoing pharmacological weight loss, rare genetic obesity syndromes, and lifestyle interventions, the researchers identified persistent epigenetic modifications in these cells.

Specifically, obesity was associated with changes in DNA methylation, a process in which chemical tags are added to DNA and alter gene expression without changing the underlying sequence. These modifications effectively encode a molecular memory of prior metabolic state.

As explained by the authors, these epigenetic marks can persist for years after weight loss. “The findings suggest that short-term weight loss may not immediately reduce the risk of some disease conditions associated with obesity,” said Claudio Mauro, PhD, senior author of the study. Instead, the immune system appears to retain a record of past metabolic stress that continues to influence cellular behavior.

Persistence beyond weight loss

The durability of this imprint is striking. The study estimates that obesity-associated DNA methylation patterns in T cells may persist for five to ten years after successful weight reduction. This suggests that immune remodeling lags far behind metabolic normalization.

Supporting this, the team observed similar patterns across diverse experimental systems, including human clinical samples and mouse models of diet-induced obesity. Together, these data point to a conserved biological mechanism rather than a transient or context-specific effect.

This persistent immune memory may help explain why relapse and long-term complications are common in obesity. As noted by Belinda Nedjai, PhD, of Queen Mary University of London, “the immune system retains a molecular record of past metabolic exposures, which may have implications for long-term disease risk and recovery.”

Disruption of cellular housekeeping and aging

At the functional level, the epigenetic changes identified in T cells appear to disrupt two critical biological processes: autophagy and immune senescence.

Autophagy, the process by which cells degrade and recycle damaged components, is essential for maintaining cellular health. The study suggests that obesity-associated DNA methylation impairs this pathway, reducing the cell’s ability to clear waste and maintain homeostasis.

In parallel, the researchers observed effects on immune aging, or senescence. Dysregulated T cells exhibited features of premature aging, potentially contributing to chronic inflammation and reduced immune resilience.

Together, these alterations could create a persistent pro-disease environment, even after weight loss. This reframes obesity not simply as a reversible metabolic state, but as a condition capable of inducing long-term immune reprogramming.

Implications for treatment strategies

The findings have direct implications for how obesity is managed clinically. If immune dysfunction persists for years after weight loss, then short-term interventions may be insufficient to fully restore health.

Instead, sustained weight maintenance—and potentially additional therapies targeting immune reprogramming—may be required. Mauro noted that “ongoing weight management following loss will see the ‘obesity memory’ slowly fade,” though this process may take years.

The study also points to potential therapeutic strategies. Drugs such as SGLT2 inhibitors, already used in diabetes treatment, may help accelerate the reversal of these epigenetic changes by reducing inflammation and promoting clearance of dysfunctional cells.

Rethinking obesity as a chronic immuno-metabolic disease

Beyond its immediate clinical implications, the study contributes to a broader conceptual shift in how obesity is understood. Rather than being defined solely by excess adiposity, obesity emerges as a condition that induces lasting systemic changes, particularly within the immune system.

As Andy Hogan, PhD, of Maynooth University emphasized, “obesity is a chronic progressive and relapsing disease,” and these findings help explain the biological basis of that persistence.

By identifying an epigenetic “memory” within immune cells, the work highlights a previously underappreciated dimension of metabolic disease: its capacity to reprogram immune function over the long term.

Looking ahead

The discovery of obesity-induced immune memory raises new questions about reversibility and intervention. Can these epigenetic marks be actively erased? And if so, how can therapies be designed to accelerate immune recovery?

Future research will likely focus on targeting these pathways directly, with the aim of restoring normal immune function and reducing long-term disease risk.

For now, the findings underscore a key message: losing weight is only part of the story. Fully reversing the biological impact of obesity may require sustained intervention—not just at the metabolic level, but at the level of the immune system itself.

The post Obesity Leaves Lasting DNA Methylation Memory in Immune Cells appeared first on Inside Precision Medicine.

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The Power of Multimodality in Multimodal Large Language Models, Unimodal ChatGPT 5.0, and Human Clinical Experts on a Wound Care Certification Examination: Cross-Sectional Comparative Study

Background: Multimodal large language models (MLLMs) capable of integrating visual and textual information represent a promising advancement for clinical applications requiring image interpretation. Wound care assessment, which demands simultaneous analysis of wound photographs and clinical data, provides an ideal domain to evaluate multimodal vs unimodal artificial intelligence capabilities against human expertise. Objective: This study aims to compare the performance of MLLMs, unimodal ChatGPT 5.0, and human clinical experts on a standardized wound care certification examination. Methods: This cross-sectional comparative study evaluated 3 participant groups on a 25-question wound care certification examination spanning 4 clinical domains (Diagnosis, Treatment, Complication Management, and Wound Subtype Knowledge). Participants included 3 MLLMs (Med-PaLM 2, LLaVA-Med, and BioGPT), 1 unimodal large language model (ChatGPT 5.0), and 4 human clinical experts (general surgeon, wound care nurse, and 2 internal medicine physicians). Statistical analyses included one-way ANOVA with Tukey post hoc tests and domain-specific Kruskal-Wallis comparisons. Results: Human experts achieved the highest accuracy (mean 86%, SD 9.1%), followed by MLLMs (mean 78.7%, SD 12.2%), while ChatGPT 5.0 achieved 64% accuracy, failing the 70% certification threshold. Significant overall group differences were observed (=8.42, =.02, η²=0.74). MLLMs significantly outperformed ChatGPT 5.0 (difference=14.7 percentage points, =.03, Cohen =1.38), with the multimodal advantage most pronounced in visually dependent domains: Diagnosis (81% vs 43%, =.008) and Complication Management (72% vs 50%, =.03). No multimodal advantage was observed for text-based Wound Subtype Knowledge (both 67%). Med-PaLM 2 achieved 92% accuracy, matching that of the wound care nurse, while the general surgeon achieved the highest overall performance (96%). Conclusions: MLLMs demonstrate significant performance advantages over unimodal artificial intelligence in wound care assessment, particularly for visually dependent clinical tasks. While human experts with specialized wound care experience maintain overall superiority, the point estimate of the top-performing MLLM (Med-PaLM 2, 92%) fell within the observed range of human scores; however, the underpowered comparison (power=0.52) and wide CIs preclude definitive conclusions regarding noninferiority or equivalence to human experts. These findings support the potential role of MLLMs as clinical decision-support tools, warranting further adequately powered validation studies.
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Surgeons’ Perceptions on the Utility of a Conceptual Novel Force Sensor at the Surgeon-Tool Interface: Formative Interview Study

Background: Real-time force feedback is essential in many surgical specialties. While previous research has focused on force measured at the tool-tissue interface, little work has explored the benefits, limitations, or opportunities of measuring force at the surgeon-tool interface. Objective: This study aims to explore scenarios in which surgeons from different medical specialties and experience levels could benefit from receiving feedback on the force exerted at the surgeon-tool (or surgeon-tissue) interface. Methods: Exploratory qualitative research was conducted through interviews with medical practitioners (N=15). This study explored perceptions of a conceptual novel force-sensing surgical glove that could provide real-time feedback in terms of usability, utility, value, and limitations. Opportunities and barriers to implement a sensor of this type in clinical practice were also explored. Participants had experience in anesthetics, dental surgery, plastic and dermatological surgery, general surgery, and obstetrics and gynecology, as these surgical fields all require precise feedback on exerted forces. Results: Participants identified two key areas where a force sensor could yield significant benefits: (1) it could enhance surgical training through objective skill assessment and quantifiable feedback, and (2) it could provide valuable insights into the forces applied during practice, particularly in scenarios where other sensory feedback is masked. Participants appreciated that a sensorized glove that can provide real-time force sensing at the surgeon-tool interface would allow for continued feedback irrespective of the instrument, and integrate seamlessly into their current surgical workflow. Furthermore, as surgeons in some specialisms, for example, dental or obstetrics and gynecology, perform manual tasks, having a sensorized glove would provide feedback in instances where they are physically manipulating tissue. However, participants expressed concerns about accurately defining safe force ranges due to the variability in patients’ anatomical structures and the potential interference with tactile sensation. Conclusions: Surgeons from various clinical practices agreed that force sensing at the surgeon-tool interface could be valuable and provide them with optimal versatility as to when they would adopt force sensing. A sensorized glove could improve decision-making and surgical outcomes when other sources of information guiding force exertion are masked. Conversely, it could be detrimental when the organic information to guide force exertion is distorted when using the sensor. While the choice between interaction modalities is dependent on the accessibility of different senses during surgery, design suggestions as to where sensors are best placed on a sensorized glove are dependent on the instrument used or the type of manual procedure conducted.
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RoBuster—Corpus Annotated With Risk of Bias Text Spans in Randomized Controlled Trials in Physiotherapy and Rehabilitation: Corpus Development and Annotation Study

Background: Risk of bias (RoB) assessment of randomized clinical trials (RCTs) is vital to answering systematic review questions accurately. Manual RoB assessment for hundreds of RCTs is a cognitively demanding and lengthy process. Automation has the potential to assist reviewers in rapidly identifying text descriptions in RCTs that indicate potential risks of bias. However, no RoB text span annotated corpus could be used to fine-tune or evaluate large language models (LLMs), and there are no established guidelines for annotating the RoB spans in RCTs. Objective: The revised Cochrane RoB 2 test (RoB 2) tool provides comprehensive guidelines for RoB assessment; however, due to the inherent subjectivity of this tool, it cannot be directly used as RoB annotation guidelines. The study aimed to develop precise RoB text span annotation instructions that could address this subjectivity and thus aid the corpus annotation. Methods: We leveraged RoB 2 guidelines to develop visual instructional placards that serve as annotation guidelines for RoB spans and risk judgments. Expert annotators used these visual placards to annotate a dataset named RoBuster, consisting of 41 full-text RCTs from the domains of physiotherapy and rehabilitation. We report interannotator agreement (IAA) between 2 annotators for text span annotations before and after applying visual instructions on a subset (n=9) of RoBuster. We also provide IAA on bias risk judgments using Cohen κ. Moreover, we used a portion of RoBuster (n=10) to evaluate an LLM using a straightforward evaluation framework. This evaluation aimed to gauge the performance of an LLM (here GPT 3.5) in the challenging task of RoB span extraction and demonstrate the utility of this corpus using a straightforward framework. Results: We present a corpus of 41 RCTs with fine-grained text span annotations comprising more than 28,427 tokens belonging to 22 RoB classes. The IAA at the text span level calculated using the F1 measure varies from 0% to 90%, while Cohen κ for risk judgments ranges between –0.235 and 1.0. Using visual instructions for annotation increases the IAA by more than 17 percentage points. LLM (GPT-3.5) shows promising but varied observed agreements with the expert annotation across the different bias questions. Conclusions: Despite having comprehensive bias assessment guidelines and visual instructional placards, RoB annotation remains a complex task. Using visual placards for bias assessment and annotation enhances IAA compared to cases where visual placards are absent; however, text annotation remains challenging for the subjective questions and the questions for which annotation data are unavailable in RCTs. Similarly, while GPT-3.5 demonstrates effectiveness, its accuracy diminishes with more subjective RoB questions and low information availability.
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Sun Pharma Aims for Top 3 in Women’s Health with $11.75B Organon Purchase

Sun Pharmaceutical Industries has agreed to acquire Organon, the women’s health drug developer spun out of Merck & Co., for $11.75 billion in a deal intended to catapult the buyer into a top 25 global biopharma—top three in women’s health—by growing its innovative medicines business and expanding its product offerings into biosimilar drugs, the companies said today.

Headquartered in Jersey City, NJ, Organon was spun out of Merck in 2021 and has since then grown its portfolio to more than 70 women’s health and general medicines products, including biosimilars, that have been commercialized in the U.S. and some 140 countries worldwide. In addition to the U.S., Organon’s largest markets include Brazil, Canada, China, and the countries of the European Union. Organon said it has six manufacturing facilities across the EU and emerging markets.

Sun Pharma said the combined company created by the deal will have annual revenue of $12.4 billion, a figure the company said would propel it into a top 25 global pharma—though the company was ranked No. 14 in GEN’s most recent A-List of Top 25 Biotech Companies Heading Into 2026, compiled last December, based on its market capitalization (share price times the number of outstanding shares) of INR 4.31 trillion ($50.8 billion).

Sun Pharma said Organon’s portfolio was similar to its own, and that the acquisition of Organon was aligned with its strategies of growing its Innovative Medicines business (to a 27% revenue share) and expanding into biosimilars as a Top 10 global company.

The combined company, Sun Pharma and Organon said, would be top three in global women’s health, creating a commercial platform for future growth; the seventh largest global biosimilar player; and a presence in 150 countries worldwide, with 18 large markets that would each generate more than $100 million in revenues.

“This transaction represents a significant opportunity for Sun Pharma to build on its vision of Reaching People and Touching Lives,” Sun Pharma executive chairman Dilip Shanghvi said in a statement. “Organon’s portfolio, capabilities, and global reach are highly complementary to our own, and we believe that bringing the two organizations together can create a stronger and more diversified platform. We have deep respect for Organon’s mission and look forward to building on its legacy while driving sustainable long‑term growth.”

Deal speculation

The deal ends two weeks of speculation that began with an April 10 report in the Indian news outlet The Economic Times stating that Sun Pharma had submitted a $12 billion all-cash offer for Organon. On Friday, the news outlet followed up with a report stating that Sun Pharma had submitted a revised $13 billion offer.

Investors appeared to support the deal, as Sun Pharma shares on India’s National Stock Exchange rose about 7% to INR 1,733.50 ($18.41) at the close of trading today.

Sun Pharma has agreed to acquire 100% of Organon’s issued and outstanding shares for cash. Sun said it planned to fund the acquisition through a combination of available cash resources and committed financing from banks.

“Together, we will become a partner of choice for acquiring and launching new products,” stated Kirti Ganorkar, managing director of Sun Pharma. “Our immediate priorities will be business continuity, disciplined integration, and responsible value creation. We see strong potential in leveraging Organon’s talent pool. In addition, there is a scope for synergies including significant revenue upside opportunities to be realized over the coming years.”

Those synergies were later quantified by Sun Pharma as approximately $350 million within two to four years of the deal’s completion.

Sun Pharma did say, however, that the acquisition of Organon will strengthen its generation of cash, with its earnings before interest, taxes, depreciation, and amortization (EBITDA) and cash flow set to nearly double, supporting future efforts to reduce the net debt/EBITDA of 2.3x resulting from the deal.

Sun Pharma finished the first nine months of its fiscal year ending March 31, 2026, with a net profit of INR 87.654 billion ($931.5 million) and EBITDA of INR 137.772 billion ($1.464 billion; up 19.2% from the year-ago period), on sales of INR 436.604 billion ($4.64 billion), up 11.3% year over year.

During its fiscal year ending March 31, 2025, Sun Pharma reported adjusted net profit (excluding one-time items) of INR 119.844 billion ($1.274 billion), up 19% from a year earlier, on sales of INR 520.412 billion (about $5.53 billion). Reported net profit for FY 2025 was INR 109.290 billion ($1.161 billion), vs. Rs. 95.764 billion ($1.017 billion) during FY 2024.

Organon finished last year with adjusted EBITDA of $1.9 billion on revenue of $6.2 billion. The company reported debt of $8.64 billion—down from the $9.5 billion in debt it reported when it separated from Merck—and a cash balance of $574 million.

Planned sale

In November, Organon announced plans to sell its JADA® System, designed to control and treat abnormal postpartum uterine bleeding or hemorrhage, to Laborie Medical Technologies for up to $465 million—$440 million to be paid at closing, subject to adjustments, and up to $25 million tied to achieving 2026 revenue targets. Net proceeds from the divestiture will contribute to Organon’s cash balance as of March 31, 2026.

Organon will merge with a subsidiary of Sun Pharma, with Organon surviving the merger. The transaction is expected to close in early 2027 subject to customary conditions, including regulatory approvals and Organon stockholder approval.

The boards of both Sun Pharma and Organon have approved the deal.

“Following a comprehensive review of strategic alternatives, our Board determined that this all‑cash transaction offers compelling and immediate value to Organon stockholders,” stated Carrie Cox, executive chair of Organon. “We believe Sun Pharma is well positioned to support Organon’s businesses, employees, and patients globally, and to further advance our commitment to delivering impactful medicines and solutions.”

The post Sun Pharma Aims for Top 3 in Women’s Health with $11.75B Organon Purchase appeared first on GEN – Genetic Engineering and Biotechnology News.

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STAT+: Dems say RFK Jr. has a pattern of failing to answer their questions

WASHINGTON — Last week, Sen. Ben Ray Luján (D-N.M.) asked health secretary Robert F. Kennedy Jr. whether he would release — by Friday — the contract of a longtime vaccine critic who was hired by the Department of Health and Human Services.

“Yeah, I’m happy to,” Kennedy responded.

But Friday came and went without a response from Kennedy. On Monday, Luján’s office said they plan to follow up with HHS.

Continue to STAT+ to read the full story…

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Frugal-Oriented Information and Communication Technology for Development Framework Toward Low-Cost Digital Maternal Health in Low- and Middle-Income Countries: Quantitative Descriptive Study

Background: The Sustainable Development Goals (SDGs) aim to eradicate poverty and inequality while ensuring that all individuals enjoy good health. Among these, target 3.1 seeks to reduce the global maternal mortality ratio to less than 70 per 100,000 live births. However, progress toward this target has been limited, particularly in low- and middle-income countries (LMICs), where health care delivery remains constrained by limited resources. While digital innovations have increasingly been adopted to improve health care access and service delivery, a significant proportion of populations in LMICs continues to experience inadequate access to essential maternal health services. This gap underscores the need for affordable, sustainable, and contextually appropriate strategies that are cost-effective in improving maternal health outcomes in underserved communities. Objective: This study leverages the principles of frugal innovation and information and communication technologies for development (ICT4D) to propose a frugal-oriented ICT4D framework to deliver low-cost digital maternal health solutions in LMIC settings. The framework seeks to optimize the use of available resources, foster equitable access to maternal health care, and contribute toward achieving SDG 3, particularly target 3.1. Methods: The study was conducted in both rural and urban-poor settings in Kenya using a 2-phased quantitative approach. In phase 1, eight theoretical themes relevant to maternal health uptake were explored. These themes were represented on color-coded sorting cards, which participants ranked according to perceived importance. Phase 2 involved administering structured survey questionnaires to collect empirical data. The study included a total of 32 participants, whose insights provided a foundation for analyzing the significance of contextual factors influencing maternal health service utilization. Results: The weighted scores for 3 of the 8 predetermined theoretical themes—such as resources, information services, and social support programs—emerged as the most influential factors shaping maternal health promotion (N=32). Resources ranked highest (n=6, 18.81%), followed by information services (n=6, 17.99%), while social support programs accounted for 9.64% (n=3) of the overall influence. These findings highlight critical enablers and barriers within the maternal health care landscape and provide a nuanced understanding of contextual dynamics that affect the uptake of maternal health services. The results informed the design of a frugal-oriented ICT4D framework that prioritizes low-cost digital interventions tailored to resource-limited settings. Conclusions: Despite increasing recognition of digital innovations as tools for health care transformation in LMICs, adoption of existing capital-intensive solutions remains low due to financial and infrastructural constraints. This study emphasizes the importance of adopting frugal innovation and ICT4D principles in designing low-cost, scalable digital health interventions to improve access to maternal health care. Implementing such approaches can address resource limitations, enhance maternal health outcomes, and support progress toward SDG 3, particularly target 3.1. The proposed framework provides a foundation for future research and practical interventions aimed at sustainable, equitable maternal health service delivery in LMIC contexts.
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Enhancing Sleep and Mental Health: Longitudinal, Observational, Real-World Study From a Digital Mental Health Platform

Background: Poor sleep is closely linked to mental health challenges and workplace burnout. Mental health and workplace stressors can impair sleep, while good sleep quality supports cognitive and emotional resources to cope with daily challenges. Despite positive outcomes of maintaining good sleep, many people struggle to get enough restorative sleep at night. Given the bidirectional relationship between sleep and mental health, evidence-based digital mental health solutions may offer an accessible and scalable approach to improving sleep quality. Objective: This study examines whether engagement with an employer-sponsored, multimodal digital mental health platform is associated with improvements in sleep quality over time, and whether changes in sleep quality are associated with concurrent changes in mental health and burnout outcomes. Methods: This 12-month prospective, observational study followed working adults who were newly registered to an employer-sponsored digital mental health platform (Modern Health). The platform leveraged technology (mobile and web) to connect employees with comprehensive provider-led and self-guided care through therapy, coaching, on-demand digital resources, and group psychoeducational sessions. Participants [N=578; 61.1% (n=353) women; mean age 33.88, SD 8.73 years; 40.3% (n=233) people of color] completed measures of self-rated sleep quality, depression, anxiety, and burnout (exhaustion, cynicism, and professional efficacy) at baseline and after 3 and 12 months of accessing the platform. Upon registering for the platform, participants were given an initial care recommendation, but could flexibly engage in any combination of services. Participants in this study engaged with at least one care modality, including therapy, coaching, psychoeducation sessions, and self-guided mental health resources. We examined perceived sleep quality and associations with other study variables at baseline, changes in perceived sleep quality over time, and whether changes in sleep quality correlated with concurrent changes in mental health and burnout. Results: At baseline, 42% (243/578) reported poor sleep quality and were more likely to have higher levels of depression, anxiety, and burnout. A generalized linear mixed-effects model showed that each additional month of platform access was related to an increased odds of having good sleep quality by 3.7% (=.02). Linear mixed-effects models found that higher sleep quality over time was associated with lower depression, anxiety, exhaustion, cynicism, and efficacy (all <.001). Among participants reporting poor sleep quality at baseline, 44% (62/141) reported good sleep quality at 12 months. Within this subgroup, paired sample tests showed significant reductions in depression (−48.3%) and anxiety (−38.3%), and increased cynicism, burnout, though cynicism levels remained below the cutoff for high burnout (23.9%; all <.01). Conclusions: Use of an employer-sponsored digital mental health platform was associated with meaningful improvements in self-reported sleep quality over 12 months. These gains were associated with significant reductions in depression, anxiety, and burnout symptoms, highlighting broader well-being benefits of comprehensive mental health care.