UMass Amherst researchers have developed a groundbreaking nanoparticle-based cancer vaccine that prevented melanoma, pancreatic, and triple-negative breast cancers in mice—with up to 88% remaining tumor-free. The vaccine triggers a multi-pathway immune response, producing powerful T-cell activation and long-term immune memory that stops both tumor growth and metastasis. By combining cancer-specific antigens with a lipid nanoparticle “super adjuvant,” it overcomes key challenges in cancer immunotherapy.
Vast amounts of valuable research data remain unused, trapped in labs or lost to time. Frontiers aims to change that with FAIR² Data Management, a groundbreaking AI-driven system that makes datasets reusable, verifiable, and citable. By uniting curation, compliance, peer review, and interactive visualization in one platform, FAIR² empowers scientists to share their work responsibly and gain recognition.
Amid the turbulence of the wider global economy in recent years, the pharmaceuticals industry is weathering its own storms. The rising cost of raw materials and supply chain disruptions are squeezing margins as pharma companies face intense pressure—including from countries like the US—to control drug costs. At the same time, a wave of expiring patents threatens around $300 billion in potential lost sales by 2030. As companies lose the exclusive right to sell the drugs they have developed, competitors can enter the market with generic and biosimilar lower-cost alternatives, leading to a sharp decline in branded drug sales—a “patent cliff.” Simultaneously, the cost of bringing new drugs to market is climbing. McKinsey estimatescost per launch is growing 8% each year, reaching $4 billion in 2022.
In clinics and health-care facilities, norms and expectations are evolving, too. Patients and health-care providers are seeking more personalized services, leading to greater demand for precision drugs and targeted therapies. While proving effective for patients, the complexity of formulating and producing these drugs makes them expensive and restricts their sale to a smaller customer base.
The need for personalization extends to sales and marketing operations too as pharma companies are increasingly needing to compete for the attention of health-care professionals (HCPs). Estimates suggestthat biopharmas were able to reach 45% of HCPs in 2024, down from 60% in 2022. Personalization, real-time communication channels, and relevant content offer a way of building trust and reaching HCPs in an increasingly competitive market. But with ever-growing volumes of contentrequiring medical, legal, and regulatory (MLR) review, companies are struggling to keep up, leading to potential delays and missed opportunities.
This content was produced by Insights, the custom content arm of MIT Technology Review. It was not written by MIT Technology Review’s editorial staff. It was researched, designed, and written by human writers, editors, analysts, and illustrators. AI tools that may have been used were limited to secondary production processes that passed thorough human review.
Front Med (Lausanne). 2025 Sep 26;12:1648612. doi: 10.3389/fmed.2025.1648612. eCollection 2025.
ABSTRACT
Small airways-defined as bronchioles <2 mm in internal diameter that lack cartilaginous support-are frequently involved in the earliest stages of chronic obstructive pulmonary disease (COPD). While COPD is defined per GOLD by persistent post-bronchodilator airflow limitation, small-airway dysfunction can precede spirometric abnormality, motivating earlier, imaging- and physiology-based detection (Agustí et al., 2023). Pathological progression typically begins with loss and stenosis of terminal bronchioles, followed by mucus retention/plugging, fibrotic remodeling, chronic inflammation, microvascular abnormalities, and cellular senescence, ultimately resulting in irreversible impairment of gas exchange. Early diagnosis remains difficult, but a suite of advanced non-invasive modalities-including impulse oscillometry system/forced oscillation techniques (IOS/FOT), single- and multiple-breath washout tests, high-resolution CT with parametric response mapping (PRM), nuclear medicine approaches (e.g., SPECT), dynamic measurements of lung compliance, and Fluorine-19 (19F) MRI-combined with artificial intelligence markedly improve the sensitivity and specificity for detecting small-airway disease. Therapeutic strategies that target cellular senescence and fibrotic pathways-such as senolytics and antifibrotic interventions-are showing promise, particularly approaches that clear senescent cells or block pro-fibrotic signaling. The integration of single-cell omics, high-resolution microvascular imaging, and molecularly targeted therapies is expected to accelerate precision diagnostics and enable personalized early interventions. This review summarizes recent insights into small-airway physiology, key pathophysiological and molecular mechanisms, and current pharmacological strategies, and emphasizes the clinical principle of "early detection, early diagnosis, early intervention" for managing COPD-related small-airway disease.
A run-in with some artefact-laden AI-generated analyses convinced Lei Zhu that machine learning wasn’t making his role irrelevant, but more important than ever.
In a recent research paper, OpenAI suggested that the tendency of LLMs to hallucinate stems from the way standard training and evaluation methods reward guessing over acknowledging uncertainty. According to the study, this insight could pave the way for new techniques to reduce hallucinations and build more trustworthy AI systems, but not all agree on what hallucinations are in the first place.
MIT and Harvard scientists have designed an advanced type of immune cell called a CAR-NK cell that can destroy cancer while avoiding attack from the body’s own immune defenses. This innovation could allow doctors to create “off-the-shelf” cancer treatments ready for use immediately after diagnosis, rather than waiting weeks for personalized cell therapies.
Scientists identified two types of brain cells, neurons and microglia, that are altered in people with depression. Through genomic mapping of post-mortem brain tissue, they found major differences in gene activity affecting mood and inflammation. The findings reinforce that depression has a clear biological foundation and open new doors for treatment development.
Background: Globally, the number of illegal drug users is rising, posing mental and physical health challenges and increasing societal burdens. Despite a significant need for treatment, only about 10% of these individuals receive it worldwide, often with poor adherence. Traditional treatments, while effective, suffer from high dropout rates due to limitations. The COVID-19 pandemic has spurred the growth of digital interventions like apps and online platforms, offering flexibility and cost-effectiveness that better meet patient needs and improve engagement. However, addressing the persistently high dropout rates in these online treatments is crucial and necessitates further research. Objective: This study aimed to estimate dropout rates among adults with illicit drug use participating in digital psychosocial intervention trials, and to identify factors associated with attrition. Methods: We conducted a systematic search of five major databases for English-language randomized trials published up to January 27, 2025. A total of 40 studies (80 arms; 9,563 participants) reporting 46 dropout rate estimates were included. A random-effects model was used to calculate pooled dropout rates, with meta-regression and subgroup analyses exploring potential moderators. The study was registered on PROSPERO (CRD42024534389). Results: At post-test, the pooled dropout rate in the intervention group across 17 studies was 22.4% (95% CI: 12.4%–37.2%). Dropout was significantly associated with education level, employment status, baseline clinical diagnosis, intervention frequency, and initial medication use. During the longest follow-up (29 studies), the dropout rate was 27.9% (95% CI: 18.8%–39.3%), with marital status, recruitment source, medication frequency, and intervention modality as significant predictors. Control group dropout rates were 25.9% and 28.3%, both higher than those in the intervention group. Conclusions: This meta-analysis revealed substantial dropout among adults with illicit drug use receiving digital psychosocial interventions. Targeted modifications to intervention design may improve engagement and long-term retention. Clinical Trial: The study was registered on PROSPERO (CRD42024534389).
Background: Stroke frequently leads to various functional impairments. Both virtual reality (VR) and mirror therapy (MT) have shown efficacy in stroke rehabilitation. In recent years, the combination of these two approaches has emerged as a potential treatment for stroke patients. Objective: This systematic review and meta-analysis aim to evaluate the efficacy of combined immersive and non-immersive VR with MT in stroke rehabilitation. Methods: Five electronic databases were systematically searched for relevant articles published up to Jan. 2025. Randomized controlled trials (RCTs) that investigated combination treatment of VR and MT for participants with stroke were included. A grey literature search was also conducted. The risk of bias and the certainty of the evidence were assessed using the Cochrane collaboration’s tool and the Grading of Recommendations Assessment, Development, and Evaluation (GRADE) guideline, respectively. Results: A total of 475 participants from 14 RCTs were included, of which 7 were eligible for meta-analysis. Meta-analysis revealed significant improvements in upper extremity (UE) motor function and hand dexterity, as evidenced by Fugl-Meyer assessment of upper extremity (FMA-UE) (MD 3.50, 95% CI 1.47 to 5.53; P=0.0007), manual function test (MFT) (MD 2.15, 95% CI 1.22 to 3.09; P6 months or not) revealed significant differences in the FMA-UE outcome. However, the pooled FMA-UE improvement did not consistently exceed the established minimal clinically important difference (MCID; 4.25–7.25), indicating that while statistically significant, the clinical meaningfulness of the observed effect remains uncertain. Narrative evidence also suggested potential benefits for lower extremity function, dynamic balance, and quality of life, though these findings were not meta-analyzed and should be interpreted with caution. Conclusions: Moderate-quality evidence supports VR-MT as a promising nonpharmacological intervention to improve upper extremity function and hand dexterity in stroke rehabilitation. While the intervention demonstrates statistically significant effects, it does not reach the minimum clinically important difference for the FMA-UE outcome. Preliminary descriptive evidence indicates possible advantages for lower extremity function, balance, and quality of life. Clinical Trial: PROSPERO CRD42024572150
This paper explores the integration of generative artificial intelligence (AI) into psychotherapeutic practice through the lens of mentalization theory, with a particular focus on epistemic trust—a critical relational mechanism that facilitates psychological change. We critically examine AI’s capability to replicate core therapeutic components, such as empathy, embodied mentalizing, biobehavioral synchrony, and reciprocal mentalizing. Although current AI systems, especially large language models, demonstrate significant potential in simulating emotional responsiveness, cognitive empathy, and therapeutic dialogue, fundamental limitations persist. AI’s inherent lack of genuine emotional presence, reciprocal intentionality, and affective commitment constrains its ability to foster authentic epistemic trust and meaningful therapeutic relationships. Additionally, we outline significant risks, notably for individuals with complex trauma or relational vulnerabilities, highlighting concerns regarding pseudo-empathy, mistaking phenomenal experience for objective reality (psychic equivalence), fruitless ungrounded pursuit of social understanding (hypermentalization), and epistemic exploitation of individuals in whom artificial understanding by AI triggers excessive credulity. Nonetheless, we propose ethically informed pathways for integrating AI to enhance clinical practice, therapist training, and client care, particularly in augmenting human capacities within group and adjunctive therapy contexts. Paradoxically, AI could support psychotherapists in improving their capacity to mentalize, improve their understanding of their clients, and provide such understanding within the moral constraints that normally govern their work. This paper calls for careful ethical regulation similar to that limiting genetic manipulation, interdisciplinary research, and clinician involvement in shaping future AI-based psychotherapeutic models, emphasizing that AI’s role should complement rather than replace the irreplaceable relational core of psychotherapy.
Researchers have cracked the code behind how plants make mitraphylline, a rare cancer-fighting molecule. Their discovery of two critical enzymes explains how nature builds complex spiro-shaped compounds. The work paves the way for sustainable, lab-based production of valuable natural medicines. Supported by international collaborations, the findings spotlight plants as powerful natural chemists.
An experimental gene therapy from Sarepta Therapeutics increased levels of the gene missing in an ultra-rare form of muscular dystrophy, according to data the company presented Friday.
The company has said it plans to file for approval in the disease, known as limb-girdle muscular dystrophy (LGMD) 2E. That would make it the first approved treatment in LGMD, a broad collection of highly rare diseases that can deprive patients of the ability to walk and in some cases shorten life. But it is likely to face a significant uphill battle.
The LGMD 2E therapy relies on the same gene-ferrying virus that Sarepta uses in its other treatments, including its approved gene therapy for Duchenne muscular dystrophy, Elevidys, and experimental gene therapies for several other LGMD subtypes.
DNA methylation is an epigenetic modification that regulates gene expression by adding methyl groups to DNA, affecting cellular function and disease development. Machine learning, a subset of artificial intell...
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