PerkinElmer
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PerkinElmer Signals Translational Professional

Effectively select cohorts and enhance patient stratification for improved clinical trials, and perform exploratory analysis to test (and adapt) your Biomarker based hypothesis. Learn more.

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Overview

Aiming to apply best-practices to patient stratification strategies, analytics in PerkinElmer Signals Translational are designed to take the complexity out of analytics - so that, more users (not just those with expertise in statistical tools) can test and adapt their hypothesis - Gain insights faster - and make informed decisions earlier in the patient stratification process.

Powered by TIBCO Spotfire® and specifically addressing Translational use cases, a scientist can easily ‘stitch’ together repeatable analytics’ protocols using an ever-expanding set of Signals Translational Apps. These protocols can then be shared across the organisation to enable a broader user base with consistent and repeatable analytics for Patient stratification!

Perform cross-study analysis and establish best-practices for patient stratification with PerkinElmer Signals Translational Professional. Amongst its many benefits it includes:

  • Analytics designed specifically for Translational use cases and powered by TIBCO Spotfire
  • Stitch together an ever-expanding set of configurable Signals Translational Apps to create re-useable analytics protocols;
  • An integrated cohort selection panel to effectively stratify your patient population and manage analyses
  • Shareable protocols to broaden your user base and reduce the burden on data scientists
  • Leverage TIBCO Spotfire platform and extend your analysis further to harness the power of statistical engines like R

Resources, Events & More
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White Paper

Using PerkinElmer Signals™ Translational to Leverage the Cancer Genome Atlas (TCGA) Data for Biomarker Discovery

Success of clinical trials is increasingly reliant on better informed patient stratification strategies, which can be beset by inefficiencies related to collaborative data access, ad-hoc querying, aggregation and repeatable analytics for cross-study biomarker analysis.

Using datasets from The Cancer Genome Atlas (TCGA), this white paper details how PerkinElmer Signals™ Translational is designed precisely to address the above- mentioned inefficiencies by providing scientists with user friendly applications that enable:

  • Self-service access to data
  • Intuitively query data and create cohorts
  • Guided analytics protocols
  • Biomarker Discovery & Patient stratification
  • PDF 4 MB