Nov 2026· MedComm· Vol 7 11, pp.
e71047
· 0 citations· 155 references
Medicine
TL;DR
This review examines how disease biology informs pulmonary delivery design across pulmonary fibrosis, lung cancer, chronic obstructive pulmonary disease, pulmonary infections, and acute lung injury/acute respiratory distress syndrome and outlines anatomical and biological barriers.
Abstract
Respiratory diseases remain major causes of morbidity and mortality; however, inadequate pulmonary drug exposure and systemic toxicity continue to limit treatment efficacy. Inhaled nanomedicines offer opportunities for localized, sustained, and targeted therapy. This review examines how disease biology informs pulmonary delivery design across pulmonary fibrosis, lung cancer, chronic obstructive pulmonary disease, pulmonary infections, and acute lung injury/acute respiratory distress syndrome. It outlines anatomical and biological barriers and compares liposomes, lipid nanoparticles, polymeric and hybrid systems, biomimetic carriers, and stimuli-responsive formulations. Particular attention is given to matching therapeutic cargo and carrier properties to fibroblasts, macrophages, tumor cells, and alveolar type II cells. Emerging approaches include mRNA delivery, siRNA-mediated gene silencing, antisense oligonucleotides, and CRISPR-based editing, alongside alveolar regeneration and biomarker-guided treatment. These strategies are evaluated in relation to their delivery requirements and stage of development. The review also addresses aerosol-device compatibility, manufacturing, repeated-dose safety, regulatory considerations, and clinical outcomes. By connecting delivery mechanisms with disease-specific applications and clinical evidence, this review identifies both therapeutic opportunities and barriers to translation. This integrated perspective can guide the development of inhaled nanomedicines with more reproducible pulmonary delivery, improved treatment efficacy, and acceptable safety.
Some claim that especially in the field of agile software development the research lags years behind of the practice. In this paper, we characterize the status and main challenges for research on agile software development, and propose a preliminary roadmap, focusing on providing more empirical research, primarily on e...
Torgeir Dingsøyr, T. Dybå, P. Abrahamsson· Agile Conference· 92 citations· ⚡7
The results indicate that software developers are a slightly happy population, but the need for limiting the unhappiness of developers remains, and 219 factors representing causes of unhappiness while developing software are identified.
D. Graziotin, Fabian Fagerholm, Xiaofeng Wang et al.· International Conference on...· 84 citations· ⚡6
This study investigates how Lean internal startup facilitates software product innovation in large companies and identifies its enablers and inhibitors, and shows the potential of the method-in-action framework to investigate the Lean startup approach in non-startup context.
Henry Edison, Nina M. Smørsgård, Xiaofeng Wang et al.· Journal of Systems and Softw...· 78 citations· ⚡6
The goal is to not only refine the accuracy of the LLM-based tool but also to underscore its potential in streamlining the software development lifecycle through proactive code improvement and education.
Z. Rasheed, Malik Abdul Sami, Muhammad Waseem et al.· arXiv.org· 62 citations· ⚡3
Agile methods continue to gain popularity. In particular, the Scrum method appears to be on the verge of becoming a de-facto standard in the industry, leading the so called Agile movement. While there are success stories and recommendations, there is little scientifically valid evidence of the challenges in the adoptio...
A. Marchenko, P. Abrahamsson· Agile Conference· 59 citations· ⚡11
A comprehensive overview of how enhanced sampling methods are reshaping the field, with a particular focus on the data-driven construction of collective variables, is provided.
Kai Zhu, Enrico Trizio, Jintu Zhang et al.· Chemical Reviews· 58 citations
AI agents can generate code at a scale that’s hard for humans to review line-by-line. PDD Kit helps ensure the code is doing what the developer intended by creating formal specifications and testing against them. It converts developer intent into a Verus specification, proves AI-generated code meets it for every input, and uses tests where proofs aren't practical. Developers review intent, not every line. The post Formally verifying agent-written full-stack web apps with PDD Kit appeared first o…
Microsoft Research Blog· microsoft.comOct 29, 2026
Host Sowbhagya Suresh shares some of the latest news and cutting-edge research from across Microsoft—from understanding the challenges facing coding agents to uncovering how people use AI at work and improving extended-range weather forecasting. The post Microsoft Research Focus – Edition #97 appeared first on Microsoft Research.