How can companies get the most from their data to empower drug development with better results for patients?

Harnessing the power of data can enhance the quality of clinical research leading to higher success rates and better outcomes for patients. The FDA and EMA are stressing the importance of a data science approach to protect integrity through ongoing data monitoring.

Responding to ICH GCP E6(R2) and Oversight Requirements

Regulatory authorities and international standards are making data quality and integrity a priority with the Sponsor ultimately responsible for compliance.

The ICH GCP E6(R2) addendum is the most important update to the ICH guidelines in 20 years with the goal of:

  • Having Sponsors adopt a risk-based approach in design and execution of clinical trials
  • Increase safety for patients by increasing vigilance of potential misconduct and ensuring better data quality and more efficient monitoring
  • Not allowing Sponsors to also outsource the responsibility for quality and integrity of data collected from sites
  • New Responsibilities for Investigator and Sponsor
  • Sponsor’s control of CRF and essential documents
  • Quality Management
  • Vendor Management
  • Risk Assessment
  • Monitoring Plan: definition and implementation
  • Changes to IT in Clinical Research: computer validation and electronic records
  • Extended requirements to minimum contents of TMF

B.O.S. – Biometrics Optimization Solution uses data science and biometrics expertise to optimize processes and guarantee data quality. It is an end-to-end solution for biometrics implementation and management, resourcing and eClinical selection and vendor oversight designed to take the place of an internal biometrics department and mitigate risk for the Sponsor.

How can Sponsors understand and organize biometrics processes?

How can Sponsors guarantee expert and adequate resourcing?

How can Sponsors ensure oversight and data quality?







  • Gap Analysis
  • SOP & Process Evaluation
  • System Review
  • Data Risk Analysis
  • Data Managers
  • Statistical Programmers
  • Statisticians
  • Medical Writers
  • Project Management & Vendor Oversight
  • Centralized Statistical Monitoring
  • Central Data Repository
  • Data Visualization & Business Intelligence tools