High Performance Computing for High Content Screening – A Case Study


Using today’s data analysis systems, researchers conducting phenotypic screening campaigns at pharmaceutical companies processing approximately 500,000 compounds estimate image and data analysis time of at least three months.

Furthermore, multiple disparate software systems are used at various stages of the workflow including image analysis, cell level data analysis, well level data analysis, hit stratification, multivariate/machine learning data analysis and visualization, reporting, collaboration, and persistence.

In this webinar, PerkinElmer and AMRI will present a case study wherein high-performance computing (HPC) was leveraged for ultimate performance in image and data analysis of High Content Screening experiments.

  • Key Learning Objectives
  • Complete Batch re-analysis jobs in days
  • Complete Clustering and other machine learning methods in minutes
  • Balance flexibility, automation, and scalability for large and small organizations and more