# A comprehensive platform for low-cost screening and image-guided photodynamic therapy (PDT) of pre-malignant and malignant oral lesions in low resource settings

> **NIH NIH U01** · MASSACHUSETTS GENERAL HOSPITAL · 2024 · $29,163

## Abstract

Motivated by the bleak situation of oral cancer in India and encouraged by our successes in the UH2/UH3
mechanism for diagnosing and treating pre- and early cancers, a new integrated “Screen, Image and Treat
Optical System” (SITOS) is proposed in the current application which combines the expertise of 3 US sites in
collaboration with 2 clinical Indian teams. All sites were participants in the previous NCI awards as 2 individual
UH2/UH3 projects focused on either detection or therapy. The treatment continues to be photodynamic therapy
(PDT), a photochemistry-based, FDA approved modality while the detection is based on fluorescence and white
light imaging combined with a cloud-based deep-learning AI approach for image classification. The SITOS
enables image guided PDT, while a topical application of the dual property flourophore/photosensitizer precursor
to the oral cavity, more suitable for LMICs and designed to achieve better tumor penetration than previous topical
deliveries, is also developed. The goals will be accomplished in 3 Specific Aims. Aim 1 builds on previous
successful development and clinical validation of separate low-cost devices for intraoral imaging, and intraoral
PDT to produce a new, handheld, low-cost, easy-to-use, SITOS. The integrated platform enables the use of the
same hardware for initial imaging, and a single thernostic molecule for image-guided PDT and online monitoring
during therapy. Incorporated is an ergonomic intraoral light delivery for PDT and preliminarily validated in optical
phantoms and in vitro 3D tumor models. Aim 2A establishes conditions for topical photosensitization using an
adhesive ALA patch provided by Photonamic GmbH in ex vivo porcine mucosa model. Based on data from 2A,
Aim 2B establishes optimal PDT parameters in a murine xenograft model. Aim 2C validates the best of these
parameters in a carcinogen-induced hamster cheek pouch model which recapitulates transition from pre-
malignant to malignant lesions. Aim 3 applies SITOS to identify and treat high-risk oral potentially malignant
lesions (OPML), and early-stage oral cancer using broad guidance from the preclinical studies. Screening of
patients will take place at camps and remote villages led by the clinical teams in India as in the UH effort. Patients
with histologically confirmed HGD/OPML (and meeting other inclusion criteria) will be eligible. Patients will be
treated using the ALA topical patch, (after a small cohort establishes safety and optimal contact time, based on
Aim 2). Finally, PDT of high-risk OPML and early cancer in patients using light delivery and simultaneous image
guidance with the new intraoral probe will be performed.
Impact and relevance: The study provides, for the first time, a comprehensive low-cost approach that enables
not only detection of pre-malignant/malignant oral lesions, but also an effective, monitored therapy in LMIC
settings. The SITOS platform is mobile, handheld and appropriate for point of care applicati...

## Key facts

- **NIH application ID:** 11030564
- **Project number:** 3U01CA279862-02S1
- **Recipient organization:** MASSACHUSETTS GENERAL HOSPITAL
- **Principal Investigator:** Jonathan P Celli
- **Activity code:** U01 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2024
- **Award amount:** $29,163
- **Award type:** 3
- **Project period:** 2023-06-15 → 2025-05-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/11030564

## Citation

> US National Institutes of Health, RePORTER application 11030564, A comprehensive platform for low-cost screening and image-guided photodynamic therapy (PDT) of pre-malignant and malignant oral lesions in low resource settings (3U01CA279862-02S1). Retrieved via AI Analytics 2026-05-24 from https://api.ai-analytics.org/grant/nih/11030564. Licensed CC0.

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