HOW TO ACCELERATE CLINICAL DATA ANALYSIS AND REPORTING

In shipping, last-mile delivery is the final and arguably most important step of the journey. Drug development has a last mile of its own: the journey from data analysis and reporting (A&R) to regulatory submission.

Both scenarios demand an efficient process to ensure on-time delivery. However, just like shippers get bogged down by traffic and disorganized delivery routes, drug developers get bogged down by data and incompatible systems.

The 2020 Tufts CSDD–IBM Watson Health benchmarking study found the average cycle time to convert raw data to analysis-ready data was 15.5 days for larger companies and 21.4 days for smaller companies *. That’s reasonable. But what about the analysis itself? If manual workarounds and IT issues are holding you back, consider a new approach.

Accurate clinical data A&R and on-time regulatory submission require a centralized, cloud-based statistical computing environment. In this environment, biostatisticians, clinical programmers, and other analysts can travel the last mile faster and with fewer complications.

* https://www.appliedclinicaltrialsonline.com/view/characterizing-clinical-data-management-challenges-and-their-impact

Get in touch

    Asset 1 (2) 1

    HOW TO ACCELERATE CLINICAL DATA ANALYSIS AND REPORTING

    In shipping, last-mile delivery is the final and arguably most important step of the journey. Drug development has a last mile of its own: the journey from data analysis and reporting (A&R) to regulatory submission.

    Both scenarios demand an efficient process to ensure on-time delivery. However, just like shippers get bogged down by traffic and disorganized delivery routes, drug developers get bogged down by data and incompatible systems.

    The 2020 Tufts CSDD–IBM Watson Health benchmarking study found the average cycle time to convert raw data to analysis-ready data was 15.5 days for larger companies and 21.4 days for smaller companies 1. That’s reasonable. But what about the analysis itself? If manual workarounds and IT issues are holding you back, consider a new approach.

    Accurate clinical data A&R and on-time regulatory submission require a centralized, cloud-based statistical computing environment. In this environment, biostatisticians, clinical programmers, and other analysts can travel the last mile faster and with fewer complications.

     

    *https://www.maxisit.com/how-to-accelerate-clinical-data-analysis-and-reporting/

    Get in touch

      Share:

      This article explains how to streamline Clinical Data Analysis and Reporting for faster time to submission.

      Challenges that impact Clinical Data Management
      and A&R

      How to Improve A&R
      Through a Data Pipeline

      Key Features of Statistical Computing Environment

      Share:

      This article explains how to streamline Clinical Data Analysis and Reporting for faster time to submission.

      Challenges that impact Clinical Data Management and A&R

      How to Improve A&R Through a Data Pipeline

      Key Features of Statistical Computing Environment

      This website uses cookies to help us give you the best experience when you visit. By using this website you consent to our use of these cookies. For more information on our use of cookies, please review our cookie policy.