OUR TECHNOLOGY
High-performing non-invasive bladder cancer detection test that integrates life science, physics, and data science.
CANCER CELLS DETECTION
A non-invasive bladder cancer detection test
Cellens uses a proprietary AFM imaging method to precisely show that the cell surfaces could be used to uncover the difference in cells of patients with active cancer vs. non-active cancer
We differentiate the
CANCER CELLS | NORMAL CELLS
This is a CELL
SCANNED CELL
We check the cell’s ADHESION & SOFTNESS
Cancer cells are less ADHESIVE & SOFT
Normal Cells are ADHESIVE & SOFT
WE RE-THOUGHT CANCER DIAGNOSTIC TESTS AND THEIR COSTS
The cell surface is not flat and covered with long flexible molecules, such as glycocalyx, which alters at cancer progression and immune system regulation.
Our cell scanning assay to detect surface biophysical markers based on nanoscale imaging and machine learning techniques.
VOIDED URINE FIXATION
STANDARD PROCESSING
ATOMIC FORCE MICROSCOPE IMAGES 5~10 CELLS (30 MINS)
TRAINED MACHINE LEARNING ANALYSIS
PATIENT MONITORING
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A collaboration that proves
94% ACCURACY
WHY OUR TECH?
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Accuracy
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Time-Saving
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Money-Saving
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WHO ARE WE?
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NEWS & BLOGS
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2021 | Atomic Force Microscopy Detects the Difference in Cancer Cells of Different Neoplastic Aggressiveness via Machine Learning
A novel method based on atomic force microscopy (AFM) working in Ringing mode (RM) to distinguish between two similar human colon epithelial cancer cell lines that
Cellens to receive “Bit to Bytes” award from Baker-Polito Administration and the Massachusetts Life Sciences Center
Fourteen projects receiving funding to support R&D, innovation in addressing challenges in therapeutic delivery and unlocking potential of data science to answer pressing life sciences questions
