Nature reviews bioengineering最新文献

{"title":"What closed-loop insulin delivery can — and cannot — teach us","authors":"","doi":"10.1038/s44222-026-00497-5","DOIUrl":"10.1038/s44222-026-00497-5","url":null,"abstract":"Closed-loop insulin delivery is one of the great success stories of autonomous medicine. Its legacy, however, is not a universal blueprint, but the recognition that each closed-loop system must be designed around the biology, risks and lived realities of each condition.","PeriodicalId":74248,"journal":{"name":"Nature reviews bioengineering","volume":"4 10","pages":"937-938"},"PeriodicalIF":42.7,"publicationDate":"2026-10-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.nature.comhttps://www.nature.com/articles/s44222-026-00497-5.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149133327","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"AI-enabled clinical trials","authors":"Marc Raynaud, Natalia Trayanova, Roslyn B. Mannon, Fabrice André, P. Murali Doraiswamy, Alexandre Loupy","doi":"10.1038/s44222-026-00487-7","DOIUrl":"10.1038/s44222-026-00487-7","url":null,"abstract":"Randomized controlled trials remain the gold standard for evaluating the benefits and risks of new interventions, yet they face persistent challenges including high costs constraining sample sizes, complex eligibility criteria, recruitment difficulties, prolonged follow-up periods to capture hard end points, and the growing prevalence of poorly designed studies that create noise in literature. This Review proposes an artificial intelligence (AI)-enabled clinical trial engineering framework, applicable across medical specialties. This framework builds on four stages: assembling and harmonizing multimodal data to develop and validate tools for enabling trials; matching fit-for-purpose tools to the research question and target outcome; AI-supported trial conduct, including patient-to-trial matching, surrogate end points, externally matched comparator arms, digital twins, and automated data collection and curation; and faster, evidence-based go/no-go decisions that flag non-promising drugs early. Three overarching principles operate throughout: fit-for-purpose validation, continuous regulatory engagement and human oversight. This Review illustrates the framework through representative case studies, with the iBox surrogate in transplantation, the annualized relapse rate in multiple sclerosis, heart digital twins for ventricular tachycardia, AI-assisted histology (AIM-MASH) in hepatology and a large language model for patient-to-trial matching. It further maps the evolving regulatory landscape for AI-enabled clinical trials (EMA, FDA and the EU AI Act). Applied judiciously, AI-enabled clinical trials could shorten timelines, reduce costs and accelerate both the identification of effective therapies and the earlier elimination of futile ones. Artificial intelligence is poised to reshape clinical trials, addressing challenges in design, recruitment, monitoring and conduct. This Review outlines a framework built on deeply phenotyped cohorts, validated surrogate end points, digital twins and agentic AI systems that could shorten timelines and support the trial life cycle, highlighting opportunities to accelerate drug development while maintaining rigorous regulatory and benefit–risk assessment.","PeriodicalId":74248,"journal":{"name":"Nature reviews bioengineering","volume":"4 10","pages":"970-983"},"PeriodicalIF":42.7,"publicationDate":"2026-09-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149130657","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"How to propose a Review article","authors":"","doi":"10.1038/s44222-026-00490-y","DOIUrl":"10.1038/s44222-026-00490-y","url":null,"abstract":"At Nature Reviews Bioengineering, most of our content is commissioned. However, we also consider carefully developed proposals — but only if they follow a certain structure and approach. Here is how to pitch a Review that could capture our attention.","PeriodicalId":74248,"journal":{"name":"Nature reviews bioengineering","volume":"4 9","pages":"805-805"},"PeriodicalIF":42.7,"publicationDate":"2026-09-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.nature.comhttps://www.nature.com/articles/s44222-026-00490-y.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148910052","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Opioid overdose detection and reversal with closed-loop systems","authors":"Leonardo M. Angelone, Elena Koustova","doi":"10.1038/s44222-026-00492-w","DOIUrl":"10.1038/s44222-026-00492-w","url":null,"abstract":"Opioid overdose is a leading cause of preventable mortality, particularly in cases where no bystander is present to initiate timely intervention. Closed-loop opioid overdose reversal (CLOOR) systems have been proposed as a solution for solitary overdose events. In this Perspective, we outline the scientific, technological, regulatory and translational challenges unique to these systems. We provide an integrated assessment of CLOOR technologies through a three-component framework: sensing strategies for detecting overdose; feedback-controlled antidote-delivery architectures; and control algorithms for interpreting physiological data. Importantly, we examine key gaps in the translation of CLOOR systems, including the absence of validated biomarkers and limited clinical evidence, and address important translational factors, such as patient acceptability, stigma and the regulatory landscape for autonomous overdose-reversal devices. By synthesizing engineering, clinical, regulatory and public health perspectives, we aim to clarify priority areas for innovation and outline considerations essential for advancing these life-saving systems towards practical implementation. Opioid overdose remains a major cause of preventable death, particularly in solitary cases, motivating the development of closed-loop opioid overdose reversal (CLOOR) systems. This Perspective outlines the key scientific, technological, regulatory and translational challenges facing CLOOR technologies, highlighting crucial gaps, such as limited clinical evidence, lack of validated biomarkers, and issues of acceptability and implementation.","PeriodicalId":74248,"journal":{"name":"Nature reviews bioengineering","volume":"4 10","pages":"1041-1054"},"PeriodicalIF":42.7,"publicationDate":"2026-09-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149130662","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Matrix-bound extracellular vesicles","authors":"Lara Ece Celebi, Lauren Hawthorne, Natalia Higuita-Castro, Daniel Gallego-Perez, Mei He, Pieter Vader, Devika Soundara Manickam, Lola Eniola-Adefeso, Ke Cheng, Pinar Zorlutuna","doi":"10.1038/s44222-026-00477-9","DOIUrl":"10.1038/s44222-026-00477-9","url":null,"abstract":"Extracellular vesicles (EVs) are key mediators of intercellular communication, carrying bioactive cargo that can reprogramme cellular states in health and disease. EVs can be conceptualized by spatial distribution and site of action as liquid-phase EVs, which disseminate through biofluids and support systemic signalling, and matrix-bound EVs, which are retained within the extracellular matrix to enable site-specific, context-dependent signalling. Research on liquid-phase EVs has driven biomarker discovery, clarified disease mechanisms and enabled the development of EV-based therapeutic strategies. In contrast to liquid-phase EVs, which circulate and are subject to dilution, clearance and non-specific biodistribution, matrix-bound EVs act as spatially confined reservoirs of molecular cargo that encode local tissue states in both homeostasis and disease. In this Review, we position matrix-bound EVs within the broader EV landscape and examine their defining properties and roles in tissue homeostasis and disease pathogenesis. We discuss opportunities to harness matrix-bound EVs for tissue engineering, diagnostic and therapeutic applications, and outline key translational challenges. This framework aims to guide the development of diagnostic and therapeutic platforms that leverage the distinct biological functions of matrix-bound EVs. Extracellular vesicles (EVs) are central mediators of intercellular communication. This Review reframes EVs by spatial distribution and function, distinguishing liquid-phase EVs, which disseminate through biofluids and enable systemic signalling, from matrix-bound EVs that are retained within the extracellular matrix and mediate localized, tissue-specific communication, evaluating their properties, functions and translational potential.","PeriodicalId":74248,"journal":{"name":"Nature reviews bioengineering","volume":"4 10","pages":"984-1006"},"PeriodicalIF":42.7,"publicationDate":"2026-08-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149130658","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Machine learning for biomaterials design","authors":"Xiaoqiong Xia \u0000 (, ), Tianang Leng \u0000 (, ), Andrés J. García, Cesar de la Fuente-Nunez","doi":"10.1038/s44222-026-00476-w","DOIUrl":"10.1038/s44222-026-00476-w","url":null,"abstract":"Biomaterials underpin diverse clinical and technological applications, including orthopaedic implants, resorbable scaffolds, soft-tissue hydrogels and biosensing interfaces. Their design remains challenging because performance depends on the simultaneous optimization of mechanical, chemical and biological properties across composition, processing conditions and multi-scale structure. Machine learning (ML) and deep learning (DL) can be used to accelerate this process by modelling process–structure–property relationships, prioritizing informative experiments and supporting more systematic, data-guided design. These approaches can accelerate biomaterials discovery by enabling rapid property prediction, candidate generation and experiment prioritization across diverse material classes. In this Review, we survey these core methodologies alongside public datasets to illustrate their applications across four major biomaterial classes: metals, polymers, ceramics, and biological materials. Although ML models enable rapid optimization of material properties, their effectiveness is limited by challenges related to data scarcity, protocol heterogeneity, model interpretability and multi-scale integration. The combination of self-driving laboratories, multimodal data fusion and federated Findable, Accessible, Interoperable and Reusable (FAIR)-compliant infrastructures, together with physics-informed and explainable AI, offers the potential for autonomous, sustainable pipelines for personalized, high-performance biomaterials. This Review surveys machine learning methods, including surrogate modelling, generative design and active learning loops, for predicting and optimizing properties across metals, polymers, hydrogels, ceramics and biological biomaterials. Additionally, key datasets, challenges (such as data scarcity, heterogeneity and interpretability) and future autonomous discovery pipelines are outlined.","PeriodicalId":74248,"journal":{"name":"Nature reviews bioengineering","volume":"4 9","pages":"881-899"},"PeriodicalIF":42.7,"publicationDate":"2026-08-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148910047","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Cellular assemblies as living therapeutics","authors":"Vítor M. Gaspar, José Almeida-Pinto, Beatriz S. Moura, Ana F. Cunha, Mariana B. Oliveira, Maria V. Monteiro, João F. Mano","doi":"10.1038/s44222-026-00470-2","DOIUrl":"10.1038/s44222-026-00470-2","url":null,"abstract":"Multicellular assemblies can sense and respond to biochemical and biophysical cues. They can also self-regulate and self-organize, giving rise to emergent behaviours over time. These features make cellular assemblies interesting therapeutic tools for applications such as tissue regeneration and immunomodulation. In this Review, we discuss the design space for therapeutic cellular assemblies, outlining hierarchical building blocks, including single cells and linear, planar and volumetric units, as well as physical and biological toolboxes for their fabrication and functional programming. We examine the biological features of hierarchical cell assemblies, analysing their potential therapeutic benefits, when benchmarked in relation to free-cell suspensions and dispersed cells delivered in biomaterials. Finally, we highlight applications of cellular assemblies in regenerative medicine, immunomodulation and production of biological mediators and discuss translational considerations, including scalable manufacturing, longitudinal characterization and predictive modelling approaches required to engineer cellular assemblies with programmable biological functions. Multicellular assemblies can be programmed to exhibit emergent behaviours that make them promising therapeutic tools, particularly for tissue regeneration and immunomodulation. This Review outlines the design principles, biological advantages and translational requirements for engineering hierarchical cellular assemblies with programmable functions and emphasizes the need for benchmarking them against single-cell and biomaterial-based approaches.","PeriodicalId":74248,"journal":{"name":"Nature reviews bioengineering","volume":"4 10","pages":"1024-1040"},"PeriodicalIF":42.7,"publicationDate":"2026-08-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149130660","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Temperature as an active parameter in nanopore sensing","authors":"Muhammad Sajeer Parambath, Ashok Keerthi, Manoj Varma, Boya Radha","doi":"10.1038/s44222-026-00485-9","DOIUrl":"10.1038/s44222-026-00485-9","url":null,"abstract":"Temperature is an underutilized parameter in nanopore sensing, yet it strongly influences electrolyte properties as well as biomolecular stability, folding and transport. Here, we explore how temperature can be harnessed as an active design parameter to advance nanopore technologies.","PeriodicalId":74248,"journal":{"name":"Nature reviews bioengineering","volume":"4 10","pages":"947-949"},"PeriodicalIF":42.7,"publicationDate":"2026-08-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149130661","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Antifibrotic biomaterials","authors":"Léo-Paul Tricou, Charles Hwang, Simon Talbot, Brian Hibler, Benjamin D. Leaker, Joshua Tam, Benjamin R. Freedman","doi":"10.1038/s44222-026-00489-5","DOIUrl":"10.1038/s44222-026-00489-5","url":null,"abstract":"Fibrosis is a major cause of organ dysfunction and mortality, yet current therapies rarely reverse established disease. Biomaterials offer new opportunities to locally modulate tissue-specific repair environments and guide healing away from scar formation and toward regeneration.","PeriodicalId":74248,"journal":{"name":"Nature reviews bioengineering","volume":"4 10","pages":"944-946"},"PeriodicalIF":42.7,"publicationDate":"2026-08-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149130653","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Sustainable cold-chain technology","authors":"Giovanna Danies, Carolina Obregón, Paola Camacho","doi":"10.1038/s44222-026-00483-x","DOIUrl":"10.1038/s44222-026-00483-x","url":null,"abstract":"Cold chains are essential to food security and global health. At NanoFreeze, a Colombian start-up, we are developing a sustainable cold-chain preservation and energy-efficient refrigeration technology based on a bacterial ice-nucleation protein. Here, we reflect on how intellectual property, regulatory validation and strategic partnerships shaped our path from biological insight to translation in an emerging economy.","PeriodicalId":74248,"journal":{"name":"Nature reviews bioengineering","volume":"4 10","pages":"950-952"},"PeriodicalIF":42.7,"publicationDate":"2026-08-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149130659","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}