Company is developing CellDetect for cancer research, drug discovery, and clinical diagnostics.

Israeli company Zetiq Technologies reported the clinical validation of its CellDetect® technology to identify and diagnose bladder cancer in biopsies. The clinical trial involved the testing of 58 control and cancerous biopsy samples.

Results showed that diagnoses using the CellDetect technology correlated 100% with that made using H&E staining, the firm claims. Zetiq says that it now plans to push on with the development of products for both diagnosing and monitoring bladder cancer.

Previous clinical studies demonstrated the utility of CellDetect in the diagnosis of cervical cancer, comments Adi Elkeles, Ph.D., the company’s CEO. “We are bringing forth a powerful tool for dual analysis of color and morphology to the bladder cancer setting. Alongside our previous positive clinical data on diagnosis of cervical cancer, these results prove our long-standing statement that CellDetect technology has the ability to identify a broad range of cancer indications.”

Zetiq is a subsidiary of the life science investment company Bio-Light. Its CellDetect platform has been developed as a functional cell-based in vitro assay that Zetiq claims uses a unique metabolic signature to pinpoint cancer cells. The approach involves both color discrimination and morphological analysis to differentiate neoplastic from non-neoplastic cells.

CellDetect is being exploited for cancer research, drug discovery, and diagnostic applications. Zetiq maintains the paltform has particular promise for cancer diagnostics, where a large cell population may contain a small number of target cells that are otherwise hard to spot either due to their scarcity or because they are not easily distinguishable from normal cells.

Zetiq already offers its CellDetect kit for staining HT-29 colorectal carcinoma cell lines and for observing phenotypic changes following treatment to these cells. The company is also developing additional tools for cancer research and drug development by applying optimization protocols to different cancer cell lines.

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