The deployment of effective Clinical Trial Systems (CTS) stands at the forefront of innovation and efficiency. The growing complexity of clinical trials underscores the importance of several key factors. Firstly, there’s a pressing need for easier access to well-organized scientific data. As a result, the challenges of recurring subject enrollment are becoming more evident.
Next, there is a significant demand for optimized budgeting and effective monitoring. The need to compile results efficiently is also critical. All these factors collectively highlight the crucial role of integrating multi-user technology in research. The in-built logic behind innovative software developments truly revamps how researchers, sponsors, monitors, and other medical practitioners see and carry out their projects. That’s why choosing and deploying the right software development methodology becomes critical in the first place when building sustainable clinical trial systems. But before you’re able to do that you need to learn about the way that clinical trial systems operate.
Understanding clinical trial systems
Clinical trial systems (CTS) are extremely important in the realm of clinical research since they are comprehensive enterprise software systems designed to manage and monitor clinical research activities. They play a pivotal role in the clinical trial process as they encompass various aspects from study setup and data management to compliance and reporting. (1) A CTS serves as a centralized hub for managing all trial-related activities and ensures that each phase of the trial is conducted efficiently, ethically, and in compliance with regulatory standards.
That’s exactly why it’s important for you to become familiar with CTS’ key components and functionalities. The first key component is planning, as CTS enables researchers to define clinical trials, including site selection, recruitment strategies, and trial protocols. This feature exists with the aim of ensuring that the objectives of your trial are clear and achievable.
The next features that define CTSs are the efficient identification and tracking of trial participants. Its purpose is to ensure informed consent and alignment with the study’s budget and timeline. This includes the handling of extensive data generated in clinical trials together with its safety and accessibility.
The system also assists in creating and managing regulatory documents, ensuring that each trial adheres to the required legal and ethical standards. It efficiently monitors site performance and ensures that investigators comply with study protocols. From a financial perspective, the CTMS oversees the trial budget, manages payments, and facilitates financial reporting, providing a comprehensive view of the trial’s fiscal health.
Discover the role and significance of Clinical Trial Systems
Learn more about the essential aspects like planning, participant tracking, compliance, and reporting within Clinical Trial Systems.
Finally, the monitoring and reporting feature of the CTMS offers real-time monitoring of the trial to address issues promptly and maintain regulatory compliance. Dashboards and detailed reports generated by the system provide valuable insights into various aspects of the study. They enable more informed decision-making and enhance the overall efficiency of the clinical trial process.
Development methodologies for clinical trial systems
Now that we have reviewed the various features that make up the CTSs, it’s time to focus on the methodologies that will help you reach of your goals. In the development process of CTSs, many models can be employed, each with its unique approach and benefits. The most common ones include Agile, Waterfall, and some hybrid models that are suited to different aspects of CTS development.
The Agile methodology is a flexible approach that focuses on adaptive planning, evolutionary development, and continual improvement that responds to changes rapidly. It emphasizes early software release with minimal risk of bugs, constant feedback, and continual communication. Its main limitation is its lack of focus if the brief is unclear as minimal documentation may increase the risk of miscommunication.
The waterfall methodology, on the other hand, is the more traditional approach. It is more plan-driven, which makes it less common in modern software development. It involves gathering all the necessary information upfront in order to make an informed plan of action that follows a step-by-step process. Its rigidity offers less room for adjustments and makes it difficult to adapt to new circumstances. This can be tricky if you’re working in a more dynamic environment where changes are more frequent.
Lastly, hybrid models combine elements of both agile and waterfall methodologies. They seek to balance the flexibility of the agile methodology with the structured planning of the waterfall one. This approach can be beneficial in clinical trial systems where certain aspects of the project require rigorous planning and others benefit from iterative development.
The choice of methodology largely depends on the specific requirements, scope, and complexity of the clinical trial system that you are looking to develop. That consideration should also include the working style and preferences of your development team and tech partner.
BGO’s considerations for effective clinical trial system development
At BGO, when we approach a new project centered on the development of clinical trial systems, our experts first examine the specific requirements of the client. They analyze the suggested features of the system to be developed or modernized and then decide on the right technical approach. What matters the most is to select a development methodology that eliminates the risk of project failure, addresses market dynamics, and ensures stability, security, high performance, timely delivery, and excellent return on investment.
Traditional models, however, fail to provide the ultimate solution. Despite the fact that they are able to reduce additional expenses and development time, such approaches are not flexible enough to adapt to unanticipated changes in the clinical trial setting. It is common practice that key requirements during trials may change due to newly introduced guidelines, local legislation, or international regulations. An agile development view on the project, on the other hand, becomes a widely preferable option. It not only allows the medical app to respond to different events but also helps researchers perform risk-based monitoring, achieve operational efficiency, and reach faster problem resolutions, thanks to the presence of comprehensive metrics.
Sometimes, a successful clinical trial system depends on the combination of more than just one development model. In this sense, when we developed our own Clinicubes CTMS, the team of developers customized the development model to avoid certain limitations that the traditional development approach may pose on the project.
Find out more about Clinicubes CTMS and explore its features.
Instead, they proposed a new software development methodology and brought together the agile and the waterfall model. In consequence, they were able to construct individual software features, an intuitive back-end, and a specific cycle for complete data collection and site management.
Factors to consider in choosing the right development methodology
Now that we have reviewed the way that BGO recommends, you need to understand the mechanism behing choosing the best software development methodology for you. Firstly, you need to understand the unique requirements and constraints of a clinical trial. These include the scale and complexity of the trial, the particularities of the disease or condition being studied, and the trial’s duration.
The complexity of such trials is the next factor you need to consider. Each trial has its own technical challenges, patient recruitment strategies, and data collection processes, that can influence the choice of development methodology. For example, agile methodologies are known for handling complex projects by breaking them down into smaller, more manageable units, thus allowing for incremental progress and early identification of issues.
The timeline and budget should also be taken into account. Agile methodologies can be more cost-effective due to their adaptability, but methodologies like waterfall offer predictability that can simplify budget management. Rapid application development (RAD) might be suitable for projects needing quick delivery, while lean development emphasizes reducing waste and costs.
Understand the monitoring and reporting features of CTS
Find out how Clinical Trial Systems enable real-time monitoring and reporting of trials.
Lastly, since clinical trials are heavily regulated, compliance with regulatory requirements is non-negotiable. Some methodologies, like the V-model, emphasize quality assurance testing at every stage, which might align well with the stringent regulatory environment of clinical trials.
Conclusion
In conclusion, the tendency towards technologies and their adoption into clinical research doesn’t seem to fade away any time soon. On the contrary. The connection between these two fields is becoming stronger over time. To match the needs of the dynamic clinical landscape, to stay compliant with digital-accustomed regulations, to optimize trial processes from the ground up and to respond to customer-centric requirements, experts look for help from the software sector. There are mHealth devices, wearable technologies that track and monitor treatments, large CTMSs that eliminate complexities when working with voluminous data, and LMSs that streamline e-learning and certification programs. But this healthcare-technology dependency won’t stop here for life science is at the edge of a complete digital evolution.
In conclusion, the tendency towards technologies and their adoption into clinical research doesn’t seem to fade away any time soon. On the contrary. The connection between these two fields is becoming stronger over time. To match the needs of the dynamic clinical landscape, to stay compliant with digital-accustomed regulations, to optimize trial processes from the ground up and to respond to customer-centric requirements, experts look for help from the software sector. There are mHealth devices, wearable technologies which track and monitor treatments, large CTMSs that eliminate complexities when working with voluminous data and LMSs that streamline e-learning and certification programs. But this healthcare-technology dependency won’t stop here for life science is at the edge of a complete digital evolution.
