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Machine-intelligent multimodal algebot for intracavitary chemotherapy

  • Lin Lin
  • , Haohui Li
  • , Qi Zhou*
  • , Qi Ding
  • , Xiang Sun
  • , Jing Hu
  • , Zhangli Zhao
  • , Yaning Qin
  • , Tiancheng Jiang
  • , Honghao Ye
  • , Xiaozhen Wu
  • , Honghan Liu
  • , Lu Huang
  • , Chenghao Huang
  • , Yahui Gao
  • , Jinyao Tang*
  • , Xing Ma*
  • , Xiaohui Yan*
  • *Corresponding author for this work
  • Xiamen University
  • University of Edinburgh
  • School of Integrated Circuits, Harbin Institute of Technology Shenzhen
  • The University of Hong Kong
  • State Key Laboratory of Synthetic Chemistry

Research output: Contribution to journalArticlepeer-review

Abstract

Intracavitary drug instillation is a crucial therapeutic strategy for treating bladder cancer. However, current methods are limited in efficacy due to insufficient tumour targeting and drug penetration across tissue barriers in pathophysiological conditions. Here we devise biohybrid magnetic algae microrobots with hierarchical nanoporous structure and develop an ‘algebot’-mediated, non-contact convective transport strategy to synergistically integrate targeted carrier transport, selective drug release and ultrafast tissue penetration. Our approach leverages machine-intelligent image feedback for autonomous navigation, magnetite-endowed multimodal control for reconfigurable swarming and flow-tuned convective diffusion for on-demand therapeutic delivery. We exemplify this approach with doxorubicin-loaded magnetic Coscinodiscus granii evaluated in a murine model of bladder tumour, demonstrating an over tenfold increase in drug permeation and substantially reduced tumour burden to less than 3% compared with conventional intravesical instillation in a preclinical trial of 1-week therapy without inducing systemic toxicity. Our drug delivery system offers a non-invasive solution to overcome complex biological barriers, advancing the efficacy and safety of intracavitary chemotherapy.

Original languageEnglish
Pages (from-to)996-1007
Number of pages12
JournalNature Nanotechnology
Volume21
Issue number7
DOIs
StatePublished - Jul 2026
Externally publishedYes

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

  1. SDG 3 - Good Health and Well-being
    SDG 3 Good Health and Well-being

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