GENINVO Blogs

Big Save on Time > 60%, A case Study: DocQC™ Tested on 25 Studies.

Medical Writers have provenly spent a lot of time historically, in reviewing the Clinical Study Reports. Clinical Study Reports, or the CSRs, are comprehensive documents providing detailed information about the design, methodology, results, and analysis of clinical trials. 

These study reports take about 40 hours to complete a round of quality check, and eventually multiple rounds of review are conducted. 

Let’s get to know DocQC. 

DocQC™– Medical Writing Automation Tool for Quality Control Checks 

DocQC™ is a tool that automates Quality Control or the QC checks, which historically required multiple, time-consuming cycles of manual review. The application is programmable for various complexities, supported by AI and ML algorithms, developed by your document SMEs. It increases the efficiency and effectiveness of your QC process with each use. 

DocQC™ enables your medical writers to maintain their focus on the science, analysis, and presentation of results. 

THE 25 Studies! 

The question – 25 studies? What are these and how these studies came into picture? 

During the development and testing of DocQC, 25 studies were selected. Downloaded from different websites, these 25 studies belonged to different pharmaceutical companies/clients, further containing different formats of documents.  

DocQC has been tested on these 25 sets of clinical study documents, to validate the artifacts and content, and check for the accuracy of the tool before its delivery. Ranging from TFLs to Narratives to CSR Protocols, and many more, DocQC is built to validate the consistency and accuracy of the clinical documents and reports.  

With different Quality Control Checks, DocQC caters to different sections of the CSR using different QC checks, few namely: 

  • In-text match post-text: This is a text to table value comparison, for both internal CSR data and external source data. This saves about more than 18 hours of manual efforts; and can be performed in under maximum of 2 hours with DocQC. 
  • CSR Match Protocol SAP: This works on the methodology section of the CSR against Protocol/Template/SAP. This is a very critical part of the CSR to focus on and provides an overview of what was planned and what happened in the study. Depending upon the length and complexity of the methodology section, DocQC can help save almost more than 5 hours of medical writers on this check; and can be performed within 2 hours. 
  • SOF match data source including reverse check/ Threshold Table: These checks QCs the tables of the result section against the relative source tables. These checks save about 4 hours of the medical writer’s review time, enabling them to QC these tables within a maximum of 2 hours. 
  • Abbreviation Match List: This manages the abbreviation listed in the List of Abbreviations and the CSR content along with the expanded forms. This simple yet time consuming check usually takes about 4-5 hours for a medical writer to perform manually, and DocQC reduces this time to less than even an hour. 
  • Reference Match Format List/ Reference Match Content: These help to check for the listed references and related publications. These two checks combine the complete list of references, ranging from references listed in CSR to references from the reference list and the relative publications. DocQC helps save more than 3 hours on checking how accurately these references are maintained throughout the clinical documents. 

AND MANY MORE! 

Let’s look at few more features of DocQC to ease Medical Writer’s life. 

  • DocQC helps automate QC checks to reduce time spend by medical writer on CSR review. More than 60% time is reduced by incorporating DocQC into reviewal process.  
  • DocQC being tested on 25 studies, is robust and more accustomed to understanding different document formats and provide better results. 
  • With offline reports, DocQC provides user with an option to QC the results during the run-time or at a later time. 
  • DocQC also provides the user with ability to edit the study report and save the updated document. These changes by the user can also be tracked. 
  • With the complete QC automated, the potential errors to human eye are highly reduced. 
  • DocQC also has inbuilt configuration settings enabled to help provide user results as per their requirement. 
  • With the process automated, medical writers have more time in hand to concentrate on more critical tasks, involving their expertise and critical thinking. 
  • Medical writers can now conclude the results in better decision making, based on the generated results and visualizations. 

To conclude, DocQC caters to the multiple, time consuming cycles of manual review, reducing the medical writer’s review time by more than 60%. It is enabled with complex quality control checks to handle both internal and external QC checks. The technology is built by our document SMEs and supported by AI and ML algorithms, with a variety of complex checks, not just to reduce time, but also to maintain the consistency through automation, and QC the references and artifacts. 

By Hargun Kaur Sethi 
Software Development and Business Growth, GENINVO

More Blogs

Python’s Future in Clinical Trials: Innovations and Collaborative Advancements

Python’s Future in Clinical Trials: Innovations and Collaborative Advancements

The Changing Role of the Clinical Programmer in an Open-Source World

The Changing Role of the Clinical Programmer in an Open-Source World

Beyond the Buzzwords: How GenInvo’s AI/ML Tools Are Transforming Life Sciences

Beyond the Buzzwords: How GenInvo’s AI/ML Tools Are Transforming Life Sciences

Empowering the Future of Life Sciences: A GenInvo Perspective from the Inside

Empowering the Future of Life Sciences: A GenInvo Perspective from the Inside

GenInvo’s CIS Tool: Safeguarding Confidential Company Information in Life Sciences.

GenInvo’s CIS Tool: Safeguarding Confidential Company Information in Life Sciences.

Why Clinical Data Transparency Matters: Benefits for Patients, Researchers, and Industry

Why Clinical Data Transparency Matters: Benefits for Patients, Researchers, and Industry

How Meaningful Synthetic Data Generation Tools Are Transforming AI Development 

How Meaningful Synthetic Data Generation Tools Are Transforming AI Development 

Empowering Clinical and Regulatory Writing: Harnessing AI as Your Assistant  

Empowering Clinical and Regulatory Writing: Harnessing AI as Your Assistant  

The Impact of AI on Medical Writing: How Artificial Intelligence is Revolutionizing Medical Content Creation 

The Impact of AI on Medical Writing: How Artificial Intelligence is Revolutionizing Medical Content Creation 

CDISC Standards and Data Transformation in Clinical Trial.

CDISC Standards and Data Transformation in Clinical Trial.

Transforming Document Creation in Life Sciences with DocWrightAI™ – GenInvo’s Advanced AI Assistant!

Transforming Document Creation in Life Sciences with DocWrightAI™ – GenInvo’s Advanced AI Assistant!

Embracing the Digital Era: The Transformative Power of Digitalization in Medical Writing

Embracing the Digital Era: The Transformative Power of Digitalization in Medical Writing

Data Masking and Data Anonymization: The need for healthcare companies

Data Masking and Data Anonymization: The need for healthcare companies

Artificial Intelligence in the Healthcare Domain: How AI Reviews Clinical Documents

Artificial Intelligence in the Healthcare Domain: How AI Reviews Clinical Documents

Importance and examples of usage of Data Anonymization in Healthcare & Other sectors

Importance and examples of usage of Data Anonymization in Healthcare & Other sectors

Data Anonymization and HIPAA Compliance: Protecting Health Information Privacy

Data Anonymization and HIPAA Compliance: Protecting Health Information Privacy

Automation of Unstructured Clinical Data: A collaboration of automation and Medical Writers

Automation of Unstructured Clinical Data: A collaboration of automation and Medical Writers

Quality Control of the Methods and Procedures of Clinical Study

Quality Control of the Methods and Procedures of Clinical Study

Automated Quality Control: Get the best out of your Clinical Study Report Review 

Automated Quality Control: Get the best out of your Clinical Study Report Review 

Clinical Study Results: Quality Control on study findings and outcomes

Clinical Study Results: Quality Control on study findings and outcomes

Contact Us​

Skip to content