In the last few years, clinical trials have given birth to remarkable developments in medical science. The research conducted in clinical trials paves way for the introduction of innovative therapies and medications round the year. Importantly, the infusion of artificial intelligence, machine learning, and digital health technologies have increased the efficiency of clinical trials tenfold. Before learning more about the benefits of clinical trials automation, let’s see what it is and how it is being used.
What are automatic clinical trials?
Simply put, clinical trials automation is the integration of modern-day technology in regular clinical trials. In contrast to which, traditional, human-operated clinical trials are laborious, inefficient, and error prone. Moreover, they include extensive paperwork and the need to safely handle large databases of information.
Therefore, a clinical trial which solely relies on manual effort might take years to reach the potential clientele. Taking all these concerns into account, clinical trials automation is being incorporated in the healthcare sector. It is a blessing for clinicians and data scientists who long for accurate, efficient, safe, and timely clinical trials.
How does it work?
According to research-based statistics, a pharmaceutical company enjoyed a remarkable 80% decline in the number of patients required to conduct a clinical trial. This shows how adapting to technological advancements and pursuing automation in clinical trials can simplify research.
For example, these are some technologies used in clinical trials automation:
Digital health technologies (DHTs):
Digital health technologies are the foundation of telemedicine. Precisely, they include a range of operations such as mobile applications, wearable sensory devices, and electronic data management systems. Without a doubt, DHTs are of great benefit when it comes to remote health management and clinical trials.
Artificial intelligence:
The backbone of clinical trials automation is Artificial Intelligence. Technically, machines and systems can be trained to perform human-like activities to lower human employment. Such as applications like chat bots and artificially intelligent supervising devices help researchers to foster their attention in other, more important domains of research.
Electronic clinical outcome assessment (eCOA):
At core level, eCOA refers to an automatic system of collecting and reviewing patient data. This debunks the need for lengthy manual effort to assess huge gigabytes of data. Not only this, but it also eliminates the chances of human error.
Case report form development (CRF):
Case report forms are questionnaires that every patient is required to fill out. These help the researchers to keep track of their history, illness, and treatment progress. Fortunately, in clinical trials automation, these forms are electronically collected, allowing for hassle-free and flawless data handling.
Sensor-collected performance outcome data (PerfO):
These are highly sensitive devices which detect chemical, electrical, or sensory changes in their surroundings. For instance, changes in temperature, humidity, pH, light, flowrate, or zinc powder dosage.
Dataset conversion processes:
SDTM automation involves leveraging technology to simplify the conversion of raw clinical trial data into the standardized SDTM format. This includes automating activities like data mapping, terminology, normalization, validation, and conversion. Typically, it strives to minimize manual intervention and enhance the accuracy of data.
Trial site management:
Clinical experts agree that selection of a proper trial management site is one of the most strenuous aspects of medical research. Well-prepared, properly managed, and standardized sites are integral to a successful clinical trial. Which is why robotic machine intelligence has made it a lot easier to select sites that are compliant with regulatory standards.
Limitless advantages of clinical trial automation
Faster outcome:
With lower human input and increased automation, the time frame required to complete a study is drastically narrowed. In a traditional setting, one scientist will have to produce 50-60 case report forms. This can take weeks and there is still a chance of error. With automatic technology, the same tasks can be completed within minutes. As a result, the final outcome of research reaches the stakeholders and patients much sooner than usual.
Reduced cost:
One initial investment is all you need to save a lot of expenses in future. In clinical trials automation, lower human employment and less time is needed to get things done. Clearly, this means that the overall costs instantly come down.
Improved efficiency:
Efficient, quick, and seamless transition from step of research to another cannot be achieved easily with human input only. The well-designed data management systems and swift clinical outcome assessments ensure an overall boost in efficiency.
Low human error:
Due to the pressure of completing tasks in time, it is normal for humans to commit errors. This is not the case with clinical trials automation. Hence, machine learning and artificial intelligence are trained to multitask without making mistakes. That too, within the allotted time constraints.
Improved handling of repetitive tasks and tracking:
Let’s agree, performing the same tasks repeatedly can be exhausting and time-consuming. How about letting an artificially intelligent system do it for you? Yes, automated clinical trials can help you with that. AI can help you track and evaluate thousands of participant records. Customer support automation eliminates the need to call or email each participant individually.
Compliance with modern-day advancements:
In order to ace the race of modern-day advancements, it is important to be aware of the use of technology. By instilling automatic procedures in medicinal research, one can ensure growth and productivity. This way, you can attract a competent clientele and keep the quality of your research up to the mark.
Conclusion:
Modern technology is shaping our future and those who fail to adapt with it are bound to be left behind. Moreover, with an increasing demand for clinical trials in medical research, the amount of work required is also multiplying. Clinical trials automation is helpful in ensuring seamless, efficient, rapid, and error-free experience for both scientists and patients.
To conclude, the process of clinical trials automation involves prevalent use of artificial intelligence, machine intelligence, and digital health technologies. Furthermore, these help in streamlining the storage and management of enormous subject databases. Also, these technologies promote customer satisfaction by producing the end-result faster.
