# Combinatorial Chemistry

> **NIH NIH P30** · UNIVERSITY OF CALIFORNIA AT DAVIS · 2020 · $107,570

## Abstract

PROJECT SUMMARY/ABSTRACT
Combinatorial library methods not only offer great potential for facilitating the drug discovery process but also
provide powerful tools for basic research in various disciplines. These methods enable investigators to
generate large number of chemical compounds that can be used as valuable sources for the discovery of drug
leads, molecular imaging agents, and capturing agents for molecular markers. In the past five years, the
Combinatorial Chemistry Shared Resource (CCSR) has been assisting many cancer center investigators in the
application of combinatorial chemistry to their research. These efforts have resulted in the submission and
funding of several extramural grants, peer-reviewed publications. The CCSR provides high-number, low-cost
library screening for novel compounds using one-bead-one-compound and one-bead-2-compounds methods,
and a variety of on-bead and solution-phase functional assays. To expand the scope of the chemistry services
provided by the CCSR, we have now added two new technology platforms that are useful to many cancer
center members. The first technology is the use of amphiphilic telodendrimers to nanoformulate hydrophobic
drugs for in vivo applications. The second technology is the development of Genetically Encoded Small
Illuminants (GESIs) as novel reporters for cellular imaging of protein functions.

## Key facts

- **NIH application ID:** 9993294
- **Project number:** 5P30CA093373-18
- **Recipient organization:** UNIVERSITY OF CALIFORNIA AT DAVIS
- **Principal Investigator:** KIT S LAM
- **Activity code:** P30 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2020
- **Award amount:** $107,570
- **Award type:** 5
- **Project period:** — → —

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/9993294

## Citation

> US National Institutes of Health, RePORTER application 9993294, Combinatorial Chemistry (5P30CA093373-18). Retrieved via AI Analytics 2026-05-22 from https://api.ai-analytics.org/grant/nih/9993294. Licensed CC0.

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