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Improving Clinical Trial Efficiency: Top Tech Trends In 2023

December 22, 2022 No Comments

By Robert Rogers

Clinical trials are studies performed to evaluate the effects of modern surgical, medical, and behavioral interventions on humans. With these, researchers can determine if novel treatments (e.g., medications, medical tools, or diet) are effective and safe in humans. 

Clinical trials can also be used to determine if novel treatments are less or more effective than standard ones. In some cases, they’re used to detect diseases as early as possible before symptoms occur, preventing more serious complications.

Researchers also depend on clinical trials to make the lives of people with life-threatening health problems or chronic conditions better. For clinical trials to proceed, researchers need people to participate, especially those with life-threatening conditions. 

However, clinical trials are too expensive and complicated. That’s why improving the process is necessary. If you’re a researcher who wants to boost the efficiency of clinical studies, consider consulting various industry leaders for guidance and keep your eyes open for tech trends. 

Technology plays a crucial role in improving clinical trials, making the process simple, efficient, and cost-effective. Here are the top tech trends your research team can take advantage of to address the common problems in conducting clinical trials: 

1. Artificial Intelligence

Artificial intelligence (AI) is one of the most advanced and highly-anticipated types of technology. It’s developed to perform tasks that mostly require human intervention, such as decision-making, speech recognition, translation, and visual perception.

In other words, AI is created to reduce human intervention and manual processes to streamline workload and promote efficiency by completing tasks in a short period. This is why many industries are focused on applying AI in their operations.

In clinical research, AI can help automate tedious clinical trial processes, reducing workload and percentage errors. It can mine vast amounts of data, accelerate data collection, improve data analysis, and evaluate trial candidates efficiently.

With AI’s predictive analytics, drug producers and developers can create forecasts to prevent unwanted side effects and potential emergencies. 

2. Clinical Data Management

Clinical data is expanding at an extremely faster rate, making it difficult to manage over time. This is why data management tools are becoming increasingly necessary. 

Here are some advances in clinical data management that can be useful in the years to come:

E-DICT: This is a digital health analytics application developed by a US-based startup company, Acclimate, to improve the diversity and representation of various populations in clinical trials and genomic research. 

MediC: This is a digital platform developed by a South Korean startup Mediaiplus to manage the data of participants in a clinical trial. It can also collect data from different sources to provide useful clinical trial information.

High data volumes help research organizations create better predictive models for biological processes and medical products. Researchers also monitor and evaluate electronic health records (EHRs) to determine the ideal candidates for clinical trials. 

Product development teams can also use data analytics to look for potential candidates from different cultures and populations. This can improve the effectiveness of treatment procedures for unrepresented groups of people.

3. Decentralized Clinical Trials

Research organizations are trying to adopt new technology to improve clinical trial processes to make them more efficient and convenient for healthcare professionals and patients. This has paved the way for the decentralization of clinical trials. 

Clinical trial decentralization is made possible by tech advances, particularly in digitization, data transmission, and electronic communication. This enables research organizations to collaborate with a more diverse population and reduce the workload of clinical trial assessors. 

4. Cloud Computing

Cloud-based clinical trials help clinical researchers to store and retrieve large amounts of data without putting exorbitant data volumes on the existing IT infrastructure. With cloud-enabled data collection and processing, researchers can safely store clinical data from various sources in centralized archives. 

Cloud-based solutions offer cost-efficient means to effectively and rapidly scale clinical trial processes to serve patients across varying regions. With its instant data transfer and cleaning, cloud computing enables research organizations to make cost-effective and efficient clinical trials.

5. Cybersecurity

The healthcare industry is one of the key targets of malicious cyberattacks, thanks to its repositories of vast sensitive patient information. To address such problems, startups are developing advanced security measures to identify and prevent potential cybersecurity risks.

Security measures include advanced encryption infrastructures, cryptography, and novel authentication procedures. By developing new preventive measures, research teams can establish trust with trial participants and protect their organizations from costly data breaches.

Final Words

Clinical trials are performed to test and develop novel medical procedures and drugs to improve patients’ quality of life. However, they’re complicated and expensive, encouraging researchers across the globe to develop advancements for more efficient and cost-effective clinical trials. These include AI, advanced data management, clinical trial decentralization, cloud computing, and novel cybersecurity measures.

About the Author

Robert Rogers is a clinical assistant and medical researcher. He is also an author and contributor to blogs and websites. Outside work, Robert loves to go biking around the city.

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