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Related Experiment Video

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Constructing and Visualizing Models using Mime-based Machine-learning Framework
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Nanomedicine Ex Machina: Between Model-Informed Development and Artificial Intelligence.

Mônica Villa Nova1, Tzu Ping Lin2, Saeed Shanehsazzadeh3

  • 1Department of Pharmacy, State University of Maringá, Maringá, Brazil.

Frontiers in Digital Health
|March 7, 2022
PubMed
Summary

Artificial intelligence and modeling are advancing nanomedicine development. Combining human and artificial intelligence offers smart solutions for drug delivery, overcoming data limitations and defining future research challenges.

Keywords:
PBPK/PKPD modeling and simulationsartificial intelligence - AIdesign of experiment - DoEdrug deliveryliposomesmachine learning - MLnanomedicinenanoparticles

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Area of Science:

  • Computational science and nanomedicine
  • Artificial intelligence in drug discovery

Background:

  • Computational aids and simulations are increasingly used in model-informed drug development.
  • Nanomedicine offers innovative drug delivery but has limited patient reach and data sources.
  • Big data approaches are not always feasible due to limited data.

Purpose of the Study:

  • To review modeling and artificial intelligence applications in nanomedicine development and manufacturing.
  • To elucidate the role of these methods in facilitating breakthroughs.
  • To highlight important limitations of machine learning in nanomedicine development.

Main Methods:

  • Review of current literature on modeling and artificial intelligence in nanomedicine.
  • Analysis of applications in drug development and manufacturing processes.
  • Identification of challenges and limitations in machine learning implementation.

Main Results:

  • Artificial intelligence and smart combinations of human and artificial intelligence are emerging trends.
  • These methodologies have the potential to transform nanomedicine research and development.
  • Limited data sources pose a challenge for big data approaches.

Conclusions:

  • Modeling and AI are crucial for advancing nanomedicine.
  • Hybrid approaches combining human and artificial intelligence are key.
  • Addressing limitations is essential for future progress in nanomedicine development.