Clinical Trial

Drug Development has evolved by leaps and bounds over the past decade. As seen during the pandemic, the appropriate use of digital technologies has significantly accelerated the drug development process. Clinical researchers across the world are slowly adapting to this transition. Apart from the conventional sources of Clinical trial data, they are learning to depend on sources of real-world evidence to gain new insights and make vital research decisions.

Real-world datasets don’t undermine the data gathered from Randomized Clinical Trials (RCT) that are well structured. Rather they strengthen the existing evidence (collected from sources such as, wearable devices and technologies, Smartphone applications, Electronic Health Records (EHR), lab and pharmacy reports, insurance claims, social media) and make the trial process more agile and efficient.

The dynamic nature of real-world data makes it even more appealing to researchers as they can continuously build on evidence about the product’s safety and effectiveness throughout its life cycle.  

The large quantum of real-world data gained from electronic health records and other sources has to be studied carefully for meaningful inferences. In today’s age, this is possible with the help of advanced analytic tools.

Following are the discussions on how digitalization helps each area of Real World Data Trial execution.

  • Increased Data Availability: The digitization of healthcare records has increased the availability of data for drug development. Electronic health records, claims data, and patient-generated data are all potential sources of RWD that can be used in drug development.
  • Improved Data Analytics: Technologies have enabled more sophisticated analytics tools to analyse RWD. Advanced analytics tools such as machine learning and artificial intelligence can be used to extract insights from RWD.
  • Faster and More Efficient Data Processing: Automations using AI & ML have significantly improved data processing times, allowing for faster and more efficient analysis and organizing of RWD to be unparalleled evidence for the trial. This has reduced the time and cost associated with drug development.
  • Better Patient Recruitment: Online Resourcessuch as social media and patient communities have made it easier to identify and recruit right volunteers/patients pool for clinical trials. This has allowed for larger and more diverse patient populations to be included in drug development process.
  • Improved Collaboration: Groupware tools have enabled improved collaboration between different stakeholders involved in drug development. This includes researchers, clinicians, patients, and regulators. Improved collaboration can lead to unbiased drug development with reduced timelines and improved outcomes for patients.

Finally, it is imperative to understand that Real World Data (RWD) is not only helpful in the post-marketing monitoring aspect of drug development, but also has the potential for usage in evaluating drug effectiveness. RWD also has scope for utilization in revising drug labelling with additional safety and efficacy information. Overall, we are moving in the right direction to utilize RWD as the important complementary arm of the drug development process.

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