ArticleProceedings of the National Academy of Sciences of the United States of America2025
Modeling feasible locomotion of nanobots for cancer detection and treatment.
Article in Proceedings of the National Academy of Sciences of the United States of America, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
1 citing paper in PubMed.
- Modeling feasible locomotion of nanobots for cancer detection and treatment.Proceedings of the National Academy of Sciences of the United States of America · 2025Article
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Authors and funding
5 authors.
Funding
Abstract
Deploying motile nanosized particles, also known as "nanobots," in the human body promises to improve selectivity in drug delivery and reduce side effects. We consider a swarm of nanobots locating a single cancerous region and treating it by releasing an onboard payload of drugs at the site. At nanoscale, the computation, communication, sensing, and locomotion capabilities of individual agents are extremely limited, noisy, and/or nonexistent. We present a general model to formally describe the individual and collective behavior of agents in a colloidal environment, such as the bloodstream, for cancer detection and treatment by nanobots. This includes a feasible and precise model of agent locomotion, inspired by actual nanoparticles that, in the presence of an external chemical gradient, move toward areas of higher concentration by means of self-propulsion. We present two variants of our model: the first assumes an endogenous chemical gradient fixed over time and centered at the cancer site; the second is a more speculative, dynamic variant in which agents themselves create and amplify a gradient centered at the cancer site. In both settings, agents sense the gradient and ascend it noisily, locating the cancer site more quickly than by simple Brownian motion. For the first variant, we present simulation and analytical results to bound the time it takes for agents to reach the cancer site. For the second, simulations highlight collective benefit from agent-generated signaling, showing significant runtime improvement via chemical signal amplification.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.