AI Article Synopsis

  • Personalized nanomedicine has advanced significantly over the past decade, focusing on tailoring disease diagnosis and treatment to individual patient characteristics, particularly using iron oxide nano-biomaterials in oncology for targeted drug delivery and MRI.
  • The study proposes a Systems Thinking (ST) approach to better understand the complexity of theranostic agents by creating a stock-flow diagram that illustrates the interactions between diagnosis and therapy in cancer treatment, highlighting the importance of feedback loops.
  • This approach aims to improve understanding of complex systems in personalized nanomedicine and has potential applications in enhancing knowledge in other areas like nanosafety.

Article Abstract

Personalized nanomedicine has rapidly evolved over the past decade to tailor the diagnosis and treatment of several diseases to the individual characteristics of each patient. In oncology, iron oxide nano-biomaterials (NBMs) have become a promising biomedical product in targeted drug delivery as well as in magnetic resonance imaging (MRI) as a contrast agent and magnetic hyperthermia. The combination of diagnosis and therapy in a single nano-enabled product (so-called theranostic agent) in the personalized nanomedicine has been investigated so far mostly in terms of local events, causes-effects, and mutual relationships. However, this approach could fail in capturing the overall complexity of a system, whereas systemic approaches can be used to study the organization of phenomena in terms of dynamic configurations, independent of the nature, type, or spatial and temporal scale of the elements of the system. In medicine, complex descriptions of diseases and their evolution are daily assessed in clinical settings, which can be thus considered as complex systems exhibiting self-organizing and non-linear features, to be investigated through the identification of dynamic feedback-driven behaviors. In this study, a Systems Thinking (ST) approach is proposed to represent the complexity of the theranostic modalities in the context of the personalized nanomedicine through the setting up of a stock-flow diagram. Specifically, the interconnections between the administration of magnetite NBMs for diagnosis and therapy of tumors are fully identified, emphasizing the role of the feedback loops. The presented approach has revealed its suitability for further application in the medical field. In particular, the obtained stock-flow diagram can be adapted for improving the future knowledge of complex systems in personalized nanomedicine as well as in other nanosafety areas.

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Source
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8339728PMC
http://dx.doi.org/10.3389/fbioe.2021.709727DOI Listing

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