# High throughput optical coherence tomography (OCT)-based imaging platform for label-free, non-invasive characterization of 3D tumor spheroids. > **NIH NIH R01** · WASHINGTON UNIVERSITY · 2021 · $347,287 ## Abstract Project Summary More than 90% of the drugs being developed fail because of lack of efficacy or unexpected toxicity in clinical trials. This failure rate in the late stages of clinical development is in large part due to the use of overly simplistic in vitro cell assays, and in vivo animal models with limited predictive value during the various stages of drug discovery. Three-dimensional (3D) tissue models are expected to provide novel physiological and pharmacological data that will be more predictive of drug efficacy and toxicity in the clinic, and will therefore have a significant immediate and long-lasting impact in shortening of the timelines, reducing the costs, increasing the return on investment of drug discovery, and bringing new medicines to more patients more efficiently. Although high content fluorescence imaging, both confocal and non-confocal, is heavily used for this purpose in high throughput screening (HTS) laboratories, low penetration of fluorescent reagents and light scattering from 3D tumor spheroid models of a size of >50 μm diameter hugely limits the measurements of the morphology and physiology inside the spheroids, and requires significant manipulation of the samples, including fixation, clearing and staining, which limits its practical use for HTS of large collections of compounds. Recently, we have demonstrated that optical coherence tomography (OCT) can image and obtain morphological and physiological information of an entire 3D tumor spheroid over 1 mm in size without presumptions about its shape. Furthermore, we developed a parallel OCT imaging technology and achieved over 10-fold speed improvement compared to state-of-the-art commercial OCT technologies. In this program, in collaboration with Dr. Marc Ferrer’s group at the NIH National Center for Advancing Translational Sciences, we plan to: 1) Develop and optimize a label-free, non-invasive high throughput OCT (HT-OCT) imaging platform capable of performing parallel imaging (16 channels) on a 384-well plate. We expect that the entire plate can be scanned within less than 5 minutes, including time needed for stage translation and data storage; 2) Perform live, longitudinal studies to characterize the morphology and physiology of single- and multi-cell type tumor spheroids (SCTS and MCTS) using the HT- OCT system; and 3) Evaluate the effects of oncology drugs, which encompass a broad range of mechanisms from targeted therapies modulating cellular signaling pathways to standard of care chemotherapeutics, on 3D tumor spheroids. The 3D and longitudinal information about development of various tumor spheroid models will be the first of its kind. Successful completion of these development and validation studies will establish a label- free, non-invasive HT-OCT imaging platform that can be used to accurately and quantitatively analyze 3D morphological and physiological information of various types of tumor spheroids. The techniques developed in this proposal will also be ap... ## Key facts - **NIH application ID:** 10225615 - **Project number:** 5R01EB025209-05 - **Recipient organization:** WASHINGTON UNIVERSITY - **Principal Investigator:** Chao Zhou - **Activity code:** R01 (R01, R21, SBIR, etc.) - **Funding institute:** NIH - **Fiscal year:** 2021 - **Award amount:** $347,287 - **Award type:** 5 - **Project period:** 2019-08-15 → 2023-07-31 ## Primary source NIH RePORTER: https://reporter.nih.gov/project-details/10225615 ## Citation > US National Institutes of Health, RePORTER application 10225615, High throughput optical coherence tomography (OCT)-based imaging platform for label-free, non-invasive characterization of 3D tumor spheroids. (5R01EB025209-05). Retrieved via AI Analytics 2026-05-24 from https://api.ai-analytics.org/grant/nih/10225615. Licensed CC0. --- *[NIH grants dataset](/datasets/nih-grants) · CC0 1.0*