Clinical trial management software is a digital tool that is used by pharmaceuticals and researchers to track, plan, and manage trials efficiently. It simplifies the process of clinical trials – participant enrollment, budgeting, scheduling, and regulatory compliance. It simplifies communication between team members, to assure collaboration and productivity. CTMS can minimize errors by tracking real-time progress, thus preventing unnecessary delays in work.
The growth of the clinical trial management system (CTMS) is governed by aspects such as the rise in the complexity of clinical trials and the generation of surplus data. The CTMS market is expected to grow at a CAGR of 14.55 percent, reaching $2,656.43 million by 2029.
Advanced healthcare technology solutions such as AI and ML, along with industry-academic partnerships are bolstering the need for clinical trial management software innovations in the market. In addition, the rise in government funding for research trials is also affecting the need for advanced CTMS solutions. All of these aspects are driving the need for compelling clinical trial management system innovations. Let’s have a look at the top three.
3 Crucial CTMS Innovations to Look Out For
1. AI-Driven Innovations
Artificial intelligence technology is disrupting the clinical trial landscape in many ways. Starting with every clinical trial requires patient enrollment and this is usually a time-consuming process. Researchers are required to identify subjects, collect information, and filter out patients based on clinical trial needs.
High-quality patient recruitment is crucial for a trial’s success. So, to handle this issue, recently Elligo Health Research and Avallano have partnered to launch myTrialsConnect platform. It is an AI-driven clinical trial recruitment and engagement platform. It allows participants to join as both – patients in a provider’s network and part of a clinical trial.
Furthermore, clinical trials involve repetitive tasks that can be a cause for errors. AI-driven clinical trial management system innovations accelerate the time-to-market for drugs and free up man-hours for more advanced tasks. AI-based CTMS is utilized for analyzing past and present data and suggesting better research designs. Recently, AstraZeneca, a pharmaceutical giant launched Evinova, a tech-focused on streamlining clinical trial design and delivery to decrease costs and time in drug development.
Apart from this, artificial intelligence plays a key role in automating tasks such as text categorization, stratifying corpora of words, or parsing. In addition, with the use of EDC (Electronic Data Capture), AI removes the need for paper-based documentation.
2. CTMS for Wearables and Sensors
Wearables such as fitness trackers, smartwatches, and other gadgets are helping researchers in gathering vital real-time data from participants. Clinical trial management systems in wearables and sensors can help to continuously monitor physiological parameters such as sleep patterns, heart rate, blood pressure, oxygen levels, activity levels, etc., allowing researchers to gather, collate, and analyze data at a faster rate.
In addition, CTMS in wearables and sensors can be used to capture medication adherence, which is important for understanding the efficacy of treatments on patients. One of the major challenges faced during clinical trials is participant engagement, but this can be resolved by allowing participants to play an active role in their healthcare.
One of the innovations by Northwestern University researchers displays how wearables track vital sounds within the body. These wearable devices, which are attached to the skin, provide more than just episodic measurements during routine medical check-ups. They provide real-time wireless monitoring at multiple sites throughout the body.
The technology captures sounds like air moving through the lungs, heartbeats, and digestive movements, providing valuable information about a person’s health. The devices are effective in newborn intensive care (NICU) settings where premature babies with breathing and gastrointestinal problems are continuously monitored. If this device is coupled with a clinical trial management system then it can produce good results.
3. Innovations for Clinical Data Management
Data management is one of the major features of clinical trial management systems as it leads to the generation of high-quality research and the desired outcome. It helps to reduce the time from drug development to marketing drastically.
Data management involves steps such as building case reports, annotations, data entry, database design, discrepancy management, data validation, coding, extraction, and much more. All of this is managed by a robust clinical trial management system. To ensure that data is safe and secured, CTMS is designed to meet regulatory compliance standards. Some of the major clinical trial management system innovations for data management are:
- In January 2023, Curebase, a company dedicated to democratizing access to clinical trials announced the launch of its integrated software and services package for DTx trials. This platform is developed to support extensive patient data capture and allow hybrid and remote trials.
- In March 2023, Cloudbyz, a leading provider of unified clinical trial management solutions introduced Cloudbyz EDC 2.0 – an electronic data capture solution. This product is designed to offer a secure, seamless, and efficient cloud platform for managing, capturing, and analyzing clinical trial data. Thus, empowering researchers in conducting and delivering life-changing treatments faster.
CTMS Industry Challenges
One of the pressing concerns is the use of legacy CTMS platforms. A report states that 17 percent of the organizations don’t have plans to modernize their clinical trial systems, including CTMS. This poses an issue because the current legacy systems aren’t qualified to keep up with the demands of today’s technology.
A majority of the legacy systems are deployed on-premise, so incorporating a cloud-based solution seems like the only solution. However, a shift to the cloud means a major overhaul – creating new workflows, roles, team coordination, and processes. Not to forget the issue of interoperability with other systems. One of the best ways to solve these issues is to plan and estimate what could be the future of clinical management trial systems and look at the latest innovations.
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