Life Science Analytics Cloud

See how the LSAC platform supports your Study Planning needs

  • Patient Registries
  • EDC
  • CTMS
  • EMR/EHR
  • Claims
  • eTMF
  • Safety
  • Financial
  • Resource Mgmt.
  • Trial Registry
  • Site Registry
  • IRT/IVRS RTSM
  • Site Performance
  • Trial Performance
  • Operations
  • Physician
  • Patient
  • Investigation
  • Lab
  • Documents
  • Biomarker
  • Budget
  • Supply Chain

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Governance, Curation, Harmonization, Orchestration, Unified Data Model, Metrics

Business Outcomes

  • Site Selection

  • Principal Investigator Selection

  • Build Patient Cohorts

  • Optimized Protocol Design/Trial Feasibility

LSAC for Study Planning

Life Science Analytics Cloud enables protocol optimization and investigator site selection. Use Real World Data to evaluate:

  1. Study Design by identifying inclusion-exclusion criteria that can have a significant impact on the number of eligible patients.
  2. Complexity issues that can negatively impact patient recruitment and retention.
  3. Identification of eligible patient and Principal Investigator populations.

Life Science Analytics Cloud identifies patient populations based on inclusion-exclusion criteria. LSAC organizes real-world patient information based on diagnosis, drug therapy, and procedures, to pinpoint population groups easily that fit specified criteria. LSAC summarizes incidence rates and co-morbidities of disease and various other target metrics across a target cohort.

Site Selection
LSAC’s augmented Machine Learning helps you choose sites more carefully based on predicted performance for a trial's phase and therapeutic area.

Principal Investigator Selection
Find the PI that best complement the needs of a given trial and therapeutic area. Leverage LSAC’s advanced capabilities to recommend the most appropriate PIs for your study.

In-Depth Planning Leads to More Valuable Studies

Build Patient Cohorts
Build cohorts for downstream analysis in related studies. Evaluate impact of specific inclusion - exclusion criteria on eligible patient populations.

Optimized Protocol Design/Trial Feasibility
Modeling inclusion - exclusion criteria in a dynamic fashion enables optimization of protocol design to better assess screen failure rates

Latest Resources: Study Planning

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Trial Feasibility Predication: The Key to Designing Optimized Clinical Trials

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Life Science Analytics Cloud for Study Planning

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