# A platform to identify in vivo targets of covalent cancer drugs in 3D tissues > **NIH NIH R33** · SCRIPPS RESEARCH INSTITUTE, THE · 2023 · $450,690 ## Abstract Abstract Covalent inhibitors represent some of the most successful drugs in human history, including aspirin and penicillin. Recently, targeted covalent drugs have taken center stage as a compelling approach for achieving major goals in oncology that have proven elusive for more classical reversible small molecules, including, for instance, the selective inactivation of oncogenic kinases (BTK, EGFR, FGFR, JAK3) and, most notably, the inhibition of the once-deemed undruggable KRAS protein. We are now in the midst of a resurgence of interest in covalent drugs for their demonstrated capability to engage cancer targets that have been historically considered undruggable. However, despite their proven success and inherent advantages of potency, there has been a general reluctance to develop covalent drugs due to the concern of potential irreversible off-target toxicity across different organ systems. Hence, a comprehensive understanding of both on and off-targets in vivo is critical for covalent drugs. Currently, it is impossible to determine drug binding across a whole animal with cellular and molecular resolution in mammals. Building upon a recent breakthrough in tissue imaging termed CATCH (Clearing-Assisted Tissue click Chemistry), we propose to develop a general platform for in vivo imaging of drug-target interactions with unprecedented spatial precision by integrated applications of high-resolution whole-body imaging and chemoproteomics (such as Activity-Based Proteomic Profiling, or ABPP) through the same covalent probes. This way, every cell in a living mammal targeted by the drug (both on- and off-target) can be revealed in situ and registered onto a defined protein map to screen and identify in vivo drug targets. The data stream generated by this platform could rapidly link the rich knowledge of drug affinity to the therapeutic index, therefore accelerating the translation of chemical activities into cancer therapies. Our team has well-established and complementary expertise in chemoproteomics and tissue imaging to ensure the successful execution of the project. In this IMAT R33 application, we plan to further develop CATCH to profile in vivo targets of covalent kinase inhibitors. First, we will adapt CATCH to 3D somatic tissues (Aim 1). Next, we will expand CATCH to an array of covalent BTK (Bruton’s tyrosine kinase) inhibitors (Aim 2). Finally, we will profile dose-dependent in vivo cellular targets of BTK inhibitors in the mouse cardiovascular system (Aim 3). We anticipate that these studies will establish in vivo CATCH methods for identifying targets of covalent BTK inhibitors to better understand their efficacy and toxicity. More generally, the established platform can be broadly applied to any covalent cancer drug for unbiased in vivo target identification. The pipeline, analytics, and high-resolution drug target data will be rapidly disseminated for public access and exploration, releasing an immediate, direct, and profound impact on c... ## Key facts - **NIH application ID:** 10714543 - **Project number:** 1R33CA281918-01 - **Recipient organization:** SCRIPPS RESEARCH INSTITUTE, THE - **Principal Investigator:** BENJAMIN F CRAVATT - **Activity code:** R33 (R01, R21, SBIR, etc.) - **Funding institute:** NIH - **Fiscal year:** 2023 - **Award amount:** $450,690 - **Award type:** 1 - **Project period:** 2023-09-19 → 2026-08-31 ## Primary source NIH RePORTER: https://reporter.nih.gov/project-details/10714543 ## Citation > US National Institutes of Health, RePORTER application 10714543, A platform to identify in vivo targets of covalent cancer drugs in 3D tissues (1R33CA281918-01). Retrieved via AI Analytics 2026-05-26 from https://api.ai-analytics.org/grant/nih/10714543. Licensed CC0. --- *[NIH grants dataset](/datasets/nih-grants) · CC0 1.0*