Nanorobotics in cancer care: innovation without translation?

Abstract

Cancer remains a leading global health burden, with approximately 19.3 million new cases reported worldwide. Limitations of conventional therapies have accelerated interest in nanobots as precision tools for cancer diagnosis and treatment. Their nanoscale dimensions allow targeted drug delivery, reduced systemic toxicity, and enhanced therapeutic efficiency, including hyperthermia-based interventions. Advanced nanobot designs, such as isotope-labeled nanocarbon constructs, three-dimensional DNA nanobots, DNA-origami carriers, and magnetically propelled systems, demonstrate promising capabilities in biomarker detection, controlled drug release, and tumor-specific coagulation. However, despite these innovations, significant translational challenges persist, including safety concerns, off-target effects, and difficulties in external magnetic control. Bridging these gaps will require robust regulatory frameworks, improved nano-tumor biology insights, scalable manufacturing, and the integration of artificial intelligence-driven personalization. Addressing these issues will be pivotal for the clinical incorporation of nanobots in cancer therapy.

To the Editor,

Cancer is a global public health concern and continues to rise beyond expectations due to changes in people’s lifestyle and growth patterns, with an estimated 19.3 million cases reported according to Global Cancer Observatory data^[1^]. Due to the limited efficacy of traditional therapies, such as chemo and radiotherapy, nanobots are a potential candidate for cancer treatment, having access to target, high medicinal precision, and related hyperthermia in diagnosed cancer cases, with realization of real-world use of them from in vitro to in vivo settings because of their nano size and reduced systemic toxicity^[2^]. For early detection, advanced designs of nanobots are proposed. To avoid potential toxicity, nanobots are fabricated with isotope-labeled nanocarbons, which are injected into the body. After performing their task without imposing any harm, they will defecate outside in the form of excrement. Similarly, three-dimensiona DNA nanobots were designed for the detection of highly expressed biomarkers on cancer cells, loading anti-tumor drugs through blood circulation under driving forces, ultimately performing Boolean operations, offering their promising reliability in clinical cancers^[3^]. DNA origami-based nanobots are an exciting research area in cancer therapy, as they passively target tumor cells via doxorubicin. They attach themselves to tumor-specific molecules, load thrombin in circulation, causing malignant cells to coagulate, leading to tumor necrosis and growth inhibition^[4^]. Another excellence is the use of magnetically derived propulsive nanobots conjugated to carbon nanotubes with loading of tumor antibodies and doxorubicin, directed onto colorectal carcinoma stimulated by pH change and cellular H₂O₂ levels through utilization of an external magnetic field in rotational and translational motion^[5^]. However, there are translational barriers that need to be addressed before their practical use in clinical cancer treatment. One of the major issues is the use of external magnetic fields in magnetic nanobots, in where there is difficulty in achieving precise control of electromagnetic waves and their interference with wrong targeting of tumors, posing a risk to tissue and organs^[6^]. Regarding their safety, there are valid concerns for their biomedical application, like whether tubular DNA nanobots with thrombin employed for treating malignant tumors with poorly established blood vessels may be inefficient, resulting in failed target therapy^[7^]. For their safe and effective employment in clinical trials and post-market monitoring, regulatory bodies should file guidelines based on their innovation and formulation, data curation among researchers and industry experts, which will lead to successful incorporation of nanobots for clinical cancer therapy^[8^]. As nanobots are a sophisticated approach for malignancy treatment, they can be further improved by well-executed merging of AI algorithms in individual patient data in order to optimize the therapeutic dosage, minimizing off-target sites, thus lowering the side effects. More recent innovations in nanobots are nanodrones, which not only filter out specific tumorous tissues but also pass through the physiological barriers like the matrix and blood. But the big gap relies on efficient cancer targets being obtained in vitro settings only, while the tumor microenvironment represents their heterogeneous nature, rendering their inaccuracy in vivo, posing a major challenge that limits their translational approach in clinical routes. Real-time treatment plans can come into practice if the concerns on tumor heterogeneity, advanced knowledge of nano-tumor biology, and bringing scalable and mass production of nanobots are resolved. This study followed the Transparency in the Reporting of Artificial Intelligence guidelines 2025^[9^].

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Consent for publication is not applicable as this study involves publicly available data.

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The authors received no funding.

Author contributions

Conceptualization, methodology, software, data curation, writing original draft preparation, reviewing and editing: H.T.: writing Original draft preparation, reviewing and editing: M.S.M.: writing original draft preparation, reviewing and editing: F.H.

Conflicts of interest disclosure

The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

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