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4 Benefits Of Automating Clinical Trials With The Help Of Annotated CRF SDTM

Clinical Trial

When it comes to clinical trials, annotated Case Report Forms (CRFs) are critically important as they’re a mandatory requirement of the Food and Drug Administration (FDA). Containing pertinent information about each trial subject, CRFs are indispensable in evaluating the safety and potency of clinical products. The annotations in the CRF are essential because they point out where the data gathered for each question may be found in the database.

On the other hand, the study data tabulation model (SDTM) refers to the framework used to organize data collected in clinical trials. This standardized format is optimized for FDA review.

Automating clinical trials with the help of annotated CRF SDTM makes all reports from your clinical trials suitable for inclusion in all the regulatory submissions. Clinical trials have to abide by those metrics, given the significance of research studies in the healthcare sector today.

Listed below are the compelling benefits of automating clinical trials with the help of annotated CRF SDTM. For a better understanding of how it works, click now for some examples.

1. It Ensures Data Consistency

Automating clinical trials ensures consistency of data throughout. The CRF annotations enable you to specifically indicate where data is represented in your SDTM. When this is set right from the initial stage of the process, the converted raw dataset into SDTM follows through until the very end of the analysis.

Note that in clinical trials, the process of analyzing data involves several parties. The correct specifications should be established at the start of the process to ensure consistency.

With data consistency, the stakeholders of the data gathered in the clinical trial are on the same page.

2. It Results In Higher Efficiency

The good news with automating clinical trials is that it can result in higher efficiency across various areas of your clinical trial. Those areas include:

  • Dataset Conversion Process

In every phase of the clinical trial, data has to be submitted and resubmitted multiple times to conform with the correct format acceptable to the FDA. This is not only expensive but also time-consuming. Often, this is where delays in arriving at results with the clinical trials can ensue.

Through automation, there’s no need for complex programming in the dataset conversion process. It also takes less time to get clinical products out to the market when regulatory requirements are met with ease.

  • CRF Development

The CRF contains the data gathered during the clinical trial. Now, the process of developing CRFs is automated. It’s a far cry from the laborious manual process that was previously practiced.

Because validation is now built-in through automation, there’s a higher percentage that forms are actually correctly completed, with all regulatory requirements met.

3. It Improves Speed And Accuracy Of Clinical Trials

Time is of the essence, especially for something as important and pressing as clinical trials. If anything, this fact has been proven in recent years with the global pandemic sending pharmaceutical companies on speedy clinical trials for solutions. With automation through annotated CRF SDTM, the speed of clinical trials is improved. And, that’s achieved without sacrificing accuracy.

The improved speed brought about by automating clinical trials is critical to the healthcare industry, where the health of patients is at stake. The faster clinical trials can bring results, the sooner the healthcare sector can benefit from new discoveries.

4. It’s Easier To Give Instructions To Team Members

For senior researchers, one crucial function they need to perform is giving out specific instructions from the initial stage of the clinical trial until the end. With automated CRF SDTM, it’s easier for them to direct the team across various stages of the research process. This makes for better and smoother communication, preventing the likelihood of mistakes due to human error.

The instructions being passed down from one stage of the research to the succeeding step include annotations that give directives on what to do next. Through the annotations, the senior researchers will feel that they have more control over the whole analysis and clinical trial process.

Conclusion

In simple terms, the process of automating clinical trials through annotated CRF SDTM involves converting annotated SDTMs to digital form. That way, machines used in automating clinical trials can read and understand the CRF field’s SDTM annotations in much the same way that a human being does so manually.

From improved efficiency to fewer chances of human error, automation offers numerous benefits for clinical trials. If you’re engaged in clinical research, consider switching to automated annotations to achieve better results and complete your research in less time.

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