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Optimize clinical trial planning to drive trial success

Leverage big data sets, natural language processing, and predictive modeling to generate actionable insights and make informed decisions.


Data analytics-driven clinical trial planning, operations, and site management 


Data-driven global site selection, protocol feasibility assessment, and effective site management are imperative to improve clinical trial timelines and outcomes. Life sciences companies are leveraging real-world data, machine learning, natural language processing, and predictive modeling to:

  • optimize the clinical trial setup and operations right from site selection to regulatory submission.
  • establish virtual controls for early-stage trials to model outcomes without treatment/estimate efficacy.
  • react sooner with more information through accelerated signal detection.

Leverage multiple data sources and technology to optimize trial planning, site selection, and enrollment decision and get real-time insights into ongoing trials!

Read Blog / The innovative path forward in clinical trials

Advanced analytics for clinical trial optimization

Protocol feasibility

Trial optimization

Real-time monitoring

Better decisions

Service offering

Key results

Business outcomes

Site selection and patient recruitment

Natural language processing

Predictive insights

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Comprehensive insights on study design, setting, and participants

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Optimization that directly reflects in the cost of running a trial

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Advanced automation for early warning

Clinical program access

  • Diversity in clinical trials without geographic barriers, with focus on developing countries.

Digital trials

  • Securely manage data sources and harmonize with performance analytics and remote monitoring.
  • Reimagine the process to drive automation for clinical data, from protocol to submission.

Analyzing R&D strategy

  • Global regulatory and compliance insight for fast regulatory approval.