5 Benefits of Clinical Trial Automation

Clinical trials are done for various reasons. Most of these scientific studies aim to assess whether a new treatment is effective and safe for human consumption. Clinical research may cover new vaccines, oral drugs, devices, behavioral interventions, or specific medical interventions.     

Because it takes several participants and methods to establish a product’s efficacy and safety, clinical trials also take substantial time and high costs. Average clinical trial spending is pegged at USD$48 million. Comparatively, the costliest research was valued at USD$ 102 million, according to a 2020 study of 101 new therapeutic products approved by the Food and Drug Administration (FDA) from 2015 to 2017.   

Cost considerations aside, not all clinical trials are successful for many reasons. Challenges include a lack of participants or poor data collection, processing, and results. For the latter, clinical trial automation offers the best solution.  

But what does clinical trial automation mean? And how can pharmaceutical or biotech companies benefit from it? Let’s find out in this blog.  

Understanding Clinical Trial Automation

Automating clinical research means using specific tools that can help reduce or completely get rid of repetitive and complex manual tasks. These could include printing, distributing, and collecting case report forms (CRF), reviewing and annotating these forms, typing the entries onto the database or spreadsheet, and so on.

Several automation tools are available for clinical studies, including software, machine learning or artificial intelligence, and robotic process automation. Read more here to improve your understanding of clinical trial automation.

Below are the most compelling reasons for automating clinical trials. 

1.  Ensures Data Accuracy

Digitizing the clinical trial process means there’s less human intervention. Because machines are involved in data collection and processing, there’s minimal risk of human errors, making key study processes more accurate.  

For instance, creating a case report form (CRF) can be digitized to align with the trial objectives, design, and methods. Doing so makes validation easier and compliant with regulatory rules. Automating CRF also improves the data quality and hastens the collection process.     

2. Makes Data Processing More Reliable 

Some applications use machine learning models to process large volumes of data and predict potential outcomes. These results are then fed back to the system to notify researchers of actions that need to be taken. This procedure improves the speed and quality of processing and handling complex datasets.  

Automation also ensures that the data stays consistent throughout the study. To establish a reliable data processing system, the CRF must have annotations indicating in which sections they appear in the study data tabulation model, or STDM. These tabulations are one of the main requirements for a product application, which is then submitted to the FDA for review. Even minor errors can alter the results and question the clinical trial processes.     

3. Saves Time And Costs

Because clinical trials aim to address pressing health concerns, they must be done in the shortest time possible –while ensuring safety and efficacy.  

Based on the 2020 study mentioned above, the significant number of patients required to establish treatment efficacy and the number of trial clinic visits are the main reasons for costly clinical trials. Meanwhile, it takes a drug company about 10 years to develop a treatment and secure approval for prescription medication and other therapies.  

With automation, researchers can log into their accounts and process or upload the forms securely online. They can also acquire participants with software that filters individuals according to variables such as age and culture. This method saves time and costs in gathering suitable samples for research. In addition, research teams can be freed of repetitive manual tasks to focus on core activities that add more value to the study.

4. Improves Data Management And Compliance 

Besides making the data gathering easier, clinical trial automation can organize the entire data management process. Once available, the collected data is forwarded to the clinical data repository and clinical metadata repository. These centralized storage systems contain the forms, edit checks, datasets, and other data used in the trial.  

Because the access between these two systems becomes seamless with automation, the data can be reused in other studies and used to decide how to proceed with the research. In addition, laboratories are required to submit data regularly to the FDA in the correct format. Automation makes the dataset conversion process less time-consuming and costly, as it doesn’t require complex programming.

5. Provides Faster Results  

From CRF development to data compilation, processing, and management, automation can make the entire process reliable and efficient. Digitization can also help eliminate primary research bottlenecks, such as identifying the ideal participants and facilitating regular clinic visits.   

For instance, some clinical trial automation software uses specific tools to pinpoint suitable patients and employ direct-to-patient trials that skip the need for frequent clinic schedules.      

It’s unsurprising then that researchers can analyze the results faster, leading to the earlier release of safe and effective medical treatments. 

Concluding Thoughts 

Clinical trial automation streamlines the processes involved in drug, device, or treatment development. More importantly, it cuts time and costs without compromising data integrity, allowing for more accurate results.

Automation also makes it easier for laboratories to comply with regulatory standards, increasing the chances of product approval within reasonable costs and timeframes.