Cell Viability Analyzer Co-developed by LTTS with a Medical OEM

Author photo: Sharada Prahladrao
By Sharada Prahladrao
Project Success Story

Industry and Client:  The client is a leading medical OEM. They were looking to replace their legacy algorithms and Cell Viability Analyzelaunch a new cell viability analyzer with enhanced features and capabilities. L&T  Technology Services (LTTS) was the partner of choice for this project.

Client Requirement and Expectations: The LTTS team was onboarded to replace the legacy and proprietary image processing algorithm in use for over 15 years. The team was expected to:

  • Introduce new solution capabilities including bubble and dust particle detection, and indication of large cell sample clusters
  • Minimize deviation from ground truth
  • Streamline instrument control
  • Ensure security and trust

LTTS’ Solution: LTTS helped develop a new cell counting algorithm for the customer. The automated cell viability analyzer was based on Trypan Blue Exclusion principle using bright field flow cell image. LTTS’ algorithm provided statistical information of cells in the image like cell concentration, size, circularity and viability, helping the client achieve better performance and accuracy as compared to the legacy algorithm.

Several market first features, including anomaly detection capabilities, bubble and dust particle detection, and indication for large cluster sample of cells present in the sample were included in the enhanced solution. LTTS also implemented motor, fluidics and LED control, and enabled a tamper-proof RFID solution to avoid counterfeit reagent use, securing against the revenue leak in reagent stream. Security aspects of firmware was taken care of not just by design, but also in manufacturing and servicing aspects too.

LTTS’ Key Differentiators:

  • Cell intensity calculation and cell area calculation on fluorescence images to quantify the stage of cell death and productivity of cell
  • Deep learning -based automatic cell classification
  • Process automation
  • Machine learning algorithms and workflows to determine morphological properties like cell phenotypic drift and spread
  • Instrument control backend software development with key module responsibilities across camera autofocus, automatic background intensity correction, and system control for sample processing
  • Security control across design, manufacturing and servicing

Quantifiable Benefits: 

  • Cell classification with less than 10 percent deviation from ground truth
  • Revenue savings
  • Best in market overall sample processing time of 118 seconds for quick wash assay


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