Debates on the safety and effectiveness of vaccines have captured the public’s attention recently. A vaccine is a preventative strategy for certain diseases and has helped in the eradication of diseases such as Smallpox. But did you know how long it usually takes to get a vaccine to the market? On average, a vaccine may reach target users 15-20 years after their discovery. However, this changed tremendously during the COVID-19 pandemic.
In August 2021, less than 2 years after the virus was discovered; the COVID-19 vaccine was made available to the public. How was this made possible? The innovators of the vaccines (e.g., Pfizer, Moderna, etc.) followed an Adaptive Trial Design. This shift from the conventional trial process has dramatically shortened the vaccine timeline. Adaptive Trial Design uses a change-as-you-go strategy where the parameters and conditions are changed and adjusted depending on the new data gathered during the study. Several hypotheses can be tested simultaneously through this design which means data collection can be tedious and complex. However, not only does this complex trial design shorten the timeline but it is also a cost-effective alternative. So Adaptive Trial Design is a new approach that helps reach clinical trial goals – providing safe and effective intervention (drugs, vaccines, therapies) – that saves time and money.
How can the process be streamlined without trading off its reliability and effectiveness? Efficient Data Management. The bottleneck in almost every complex research is how the data is collected, segregated, managed, and utilized. However, this can also lay the groundwork for a successful trial if done with efficiency. Adaptive clinical trials can have the most complex data possible, so here are ways to help you streamline your data management:
- Construct your database before the study starts. Some parameters, variables, and constants in the database are interdependent. Engineering the database such that one change in information automatically changes another improves productivity.
- Smart Data Capture. Some data need not be gathered or stored, or they can be gathered but not stored for analysis. Nonetheless, that would confuse the database–and might even slow it down by consuming memory. Hence, it is crucial to practice choosing which data to collect and input into the system for analysis.
- Collaborate. Let the experts be the experts. Everyone has their niche. A Contract Research Organization (CRO) is a team of experts from different fields who can give different perspectives and help lay the foundation for the research with certainty. Moreover, a pivotal step in the adaptive trial is the adjustment of parameters in between. Because there are multiple variables–dependent or not– in adaptive trials, a small error can create a network of errors in the downstream process. With a team of experts, one can ensure zero to minimum error when designing and updating the parameters.
- Maintain a global library of standard database forms. Some information on your database can be topic-specific, while others can be standard or fundamental. Keeping an electronic record of these databases enables a cost and time-efficient study by simply tweaking some parameters as appropriate.
- Review data continuously. Again, a small error can create a network of errors downstream. It is crucial to review the data in each step to resolve possible mistakes before proceeding to the next steps. Reviewing the data only after the trial is almost complete, and then finding out a data issue in between could become a huge bottleneck. Hence, data must be reviewed after entry, ensuring a cleaner downstream process.
The goal of any therapeutic such as a vaccine/drug is to be effectively delivered and distributed to the general population as quickly as possible to prevent and treat various diseases. Among others, Data Management is one of the critical aspects to consider during the development of such therapeutics.