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Updated: Apr 17, 2026

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Nanotrap-AI Integration Enables Ultra-Sensitive Point-of-Care HIV Testing.

Jeong Soo Park1,2,3, Seungmin Lee1,4, Hyowon Woo1

  • 1KU-KIST Graduate School of Converging Science and Technology, Korea University, 145 Anam-ro, Seongbuk-gu, Seoul 02841, Republic of Korea.

ACS Nano
|April 16, 2026
PubMed
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This summary is machine-generated.

A new diagnostic platform, BE-SMART-HIV, enhances early HIV detection from oral fluid. It uses a bioengineered nanotrap and AI reader to improve sensitivity and accuracy for noninvasive screening.

Area of Science:

  • Biomedical Engineering
  • Infectious Disease Diagnostics
  • Artificial Intelligence in Healthcare

Background:

  • Early HIV detection is crucial for effective treatment and prevention.
  • Current noninvasive methods using oral fluid face challenges due to low antibody concentrations and inhibitors.
  • Lateral-flow assays (LFAs) lack sensitivity for early HIV detection in oral samples.

Purpose of the Study:

  • To develop a novel diagnostic platform, BE-SMART-HIV, for sensitive and early HIV detection using noninvasive oral fluid samples.
  • To overcome the limitations of low antibody levels and inhibitors in oral fluid for HIV diagnostics.
  • To improve the accuracy and speed of HIV screening in resource-limited settings.

Main Methods:

  • Integration of a BEETLES^2-inspired bioengineered enrichment (BE) nanotrap for antibody concentration and inhibitor removal.
Keywords:
HIVLFAdeep learningnanotrapsample preparation

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  • Utilization of a smartphone-based deep-learning reader (SMART) for automated test line interpretation.
  • Validation using a longitudinal seroconversion panel and sample dilutions up to 1,000-fold.

    • Main Results:

    • The BE nanotrap achieved approximately 20-fold antibody enrichment and effective inhibitor removal.
    • The AI model demonstrated 98.6% accuracy in interpreting weak test lines, surpassing human performance.
    • BE-SMART-HIV detected antibody emergence up to 8 days earlier than conventional LFAs, capturing IgM and IgG kinetics.

    Conclusions:

    • BE-SMART-HIV offers a practical and noninvasive approach for high-fidelity HIV screening.
    • The platform enables early detection by capturing systemic antibody kinetics from enriched oral fluid specimens.
    • This technology holds significant potential for repeated HIV testing in resource-limited settings.