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Artificial Feeding Systems for Vector-Borne Disease Studies.

Olayinka M OlajigaSamuel B JamesonBrendan H CarterDawn M WessonDana MitzelBerlin Londono-Rentería
Published in: Biology (2024)
This review examines the advancements and methodologies of artificial feeding systems for the study of vector-borne diseases, offering a critical assessment of their development, advantages, and limitations relative to traditional live host models. It underscores the ethical considerations and practical benefits of such systems, including minimizing the use of live animals and enhancing experimental consistency. Various artificial feeding techniques are detailed, including membrane feeding, capillary feeding, and the utilization of engineered biocompatible materials, with their respective applications, efficacy, and the challenges encountered with their use also being outlined. This review also forecasts the integration of cutting-edge technologies like biomimicry, microfluidics, nanotechnology, and artificial intelligence to refine and expand the capabilities of artificial feeding systems. These innovations aim to more accurately simulate natural feeding conditions, thereby improving the reliability of studies on the transmission dynamics of vector-borne diseases. This comprehensive review serves as a foundational reference for researchers in the field, proposing a forward-looking perspective on the potential of artificial feeding systems to revolutionize vector-borne disease research.
Keyphrases
  • artificial intelligence
  • machine learning
  • deep learning
  • risk assessment
  • drug delivery
  • drug release