Photosis is a technology platform that incorporates high-speed optical scanning of biological samples, image analysis, and computer-controlled laser-irradiation of specific targets within the sample for the purpose of inducing a biological response. Specific cells to be treated within a mixed population are identified by parameters such as size, shape, fluorescence, or other distinguishing features. Once identified, individual cells are targeted with a laser to induce a desired response, such as cell death, optoporation (for gene transfer), or even inactivation of a specific mRNA transcript within the cell. The current beta1-prototyle system can process hundreds of millions of cells in an hour under sterile conditions, making it useful for several research and clinical applications. In fact, this prototype has several advantages over other methods of cell processing such as flow cytometry, and this conclusion is supported by preliminary data shown within. Photosis has many potential uses, and this proposal brings together a number of institutions and researchers to investigate and define the possible applications of this novel technology. In its current configuration, the instrument uses a single color for cell detection and a laser to induce necrosis in every targeted cell. These capabilities enable the first application, which is tumor cell purging from autologous NHL stem cell transplants, because such contaminating tumor cells are known to contribute to disease relapse. Additional applications will be developed, some of which will require modifications to the system design and building of new prototypes. The prototypes will be placed at four partnership sites where the basic and clinical applications research will be carried out, including: 1) in vivo study of purified stem cell subpopulations in the xenogeneic fetal sheep transplant model; 2) human clinical trials to assess NHL purging in autologous stem cell transplantation; 3) purification of genetically- modified stem cells and T-cells expressing a selectable transgene, as well as selective transduction of specific cells in a mixture via optoporation; and 4) accurate mRNA expression profiling from purified primary human prostate cancer cell populations.

Proposed Commercial Applications

The proposed work will result in several types of novel bioengineering instrumentation for advancing the state-of-the-art in cell processing. These instruments will be used in this program to advance basic and clinical research in stem cell biology, cancer, immunology, and genomics. Once developed, the resulting technology will be useful in other areas as well, some of which are described within.

Agency
National Institute of Health (NIH)
Institute
National Center for Research Resources (NCRR)
Type
Small Business Innovation Research Grants (SBIR) - Phase II (R44)
Project #
4R44RR015374-02
Application #
6363988
Study Section
Special Emphasis Panel (ZRG1-SSS-I (06))
Program Officer
Farber, Gregory K
Project Start
2000-09-30
Project End
2003-08-31
Budget Start
2001-09-01
Budget End
2002-08-31
Support Year
2
Fiscal Year
2001
Total Cost
$2,094,963
Indirect Cost
Name
Cyntellect, Inc.
Department
Type
DUNS #
City
San Diego
State
CA
Country
United States
Zip Code
92121
Szaniszlo, Peter; Rose, William A; Wang, Nan et al. (2006) Scanning cytometry with a LEAP: laser-enabled analysis and processing of live cells in situ. Cytometry A 69:641-51
Clark, Imran B; Hanania, Elie G; Stevens, Janine et al. (2006) Optoinjection for efficient targeted delivery of a broad range of compounds and macromolecules into diverse cell types. J Biomed Opt 11:014034
Hanania, Elie G; Fieck, Annabeth; Stevens, Janine et al. (2005) Automated in situ measurement of cell-specific antibody secretion and laser-mediated purification for rapid cloning of highly-secreting producers. Biotechnol Bioeng 91:872-6
Koller, Manfred R; Hanania, Elie G; Stevens, Janine et al. (2004) High-throughput laser-mediated in situ cell purification with high purity and yield. Cytometry A 61:153-61
Szaniszlo, Peter; Wang, Nan; Sinha, Mala et al. (2004) Getting the right cells to the array: Gene expression microarray analysis of cell mixtures and sorted cells. Cytometry A 59:191-202