Deep Learning-assisted On-patient Medical Record and mRNA Therapeutics Delivery using Microneedles

Abstract

Medical interventions often require timed series of doses, thus necessitating accurate medical recordkeeping. In many global settings, these records are unreliable or unavailable at the point-of-care, leading to less effective treatments or disease prevention. Here, we present an invisible-to-naked-eye on-patient medical recordkeeping (OPMR) technology that accurately stores medical information in the patient skin as part of microneedles for intradermal therapeutics. We optimise microneedle design for a reliable delivery of mRNA therapeutics and near-infrared fluorescent microparticles that encode for OPMR. Deep learning-based image processing enables encoding and decoding of the information with excellent temporal and spatial robustness. Long-term studies in a swine model demonstrate the safety, efficacy and reliability of this approach for co-delivery of OPMR and mRNA vaccine encoding for SARS-CoV-2. This technology could facilitate healthcare workers in making informed decisions in circumstances where reliable record keeping is unavailable, thus contributing for global healthcare equity.

Nature Materials [accepted]

Acknowledgement

This work was also supported in part by the Koch Institute Support (core) Grant P30-CA14051 from the National Cancer Institute. We would like to thank the Bill & Melinda Gates Foundation (BMGF) for (INV-007842) supporting this project. This work was supported, in whole or in part, by the Bill & Melinda Gates Foundation [INV-007842; A.J., R.L.], and Takeda Fellowship from MIT-Takeda Program [Y.L.].

The authors would like to thank Alejandro Lancho and Alexander Fengler for discussion about error-correction codes.

bibtex

@article{Han24OPMR,
   author    = {Han, Jooli and Kanelli, Maria and Liu, Yang and Daristotle, John and Pardeshi, Apurva and Forster, Timothy and Karchin, Ari and Folk, Brandon and Murmann, Lukas and Tostanoski, Lisa and Carrasco, Sebastian and Zhang, Linzixuan and Eshaghi, Behnaz and Alsaiari, Shahad and Pyon, Sydney and Perkinson, Collin and Bawendi, Moungi and Barouch, Dan and Durand, Fr{\'e}do and Langer, Robert and Jaklenec, Ana},
   title     = {Deep Learning-assisted On-patient Medical Record and mRNA Therapeutics Delivery using Microneedles},
   journal   = {Nature Materials},
   year      = {2024},
   month     = {12},
   type      = {Journal Article}
}