Getting the right outcomes from your clinical trials is all about the data and insights they provide. Biostatistics in clinical trials isn’t just a necessity, it can be a real competitive advantage.
GlobalFSPGTM@iqvia.com or visit <a rel="noopener noreferrer" href=https://www.iqvia.com/blogs/2022/11/"https://iqvia.com/biostatistics" target="_blank">iqvia.com/biostatistics</a>.</p><p> </p><p></p>" /> GlobalFSPGTM@iqvia.com or visit <a rel="noopener noreferrer" href=https://www.iqvia.com/blogs/2022/11/"https://iqvia.com/biostatistics" target="_blank">iqvia.com/biostatistics</a>.</p><p> </p><p></p>" />
For sponsors developing oncology drugs or planning adaptive trial strategies, a master protocol design approach can accelerate progress and eliminate downtime between studies.
Master protocol design is a relatively new approach to protocol design that emerged with the adoption of basket, umbrella and platform studies where sponsors test a single drug for multiple diseases, or multiple drugs for a specific indication. It gives sponsors a more agile approach that reduces the time spent creating a novel set of protocols for every study while imparting uniformity to the overall data collection process.
It gained credence in March, 2022, when FDA issued a guidance on using Master Protocols for oncology studies offering advice on the design and conduct of clinical trials intended to simultaneously evaluate more than one drug and/or cancer type within the same overall trial structure as a way to “expedite development of oncology drugs and biologics”.
It also aligns with the benefits of using Functional Service Models (FSPs) for study management. FSPs are designed to be agile in order to meet the evolving needs of studies. In adaptive trials that use a master protocol, sponsors using FSPs are able to rapidly scale teams to support new studies under a Master Protocol umbrella, in much less time than with a traditional outsourcing model. It complements the flexibility that FSPs bring to sponsors, further streamlining the study environment.
Master protocol design provides a broad protocol framework that is approved by an Institutional Review Board (IRB). The master protocol describes the goals and strategy of the trial but includes no subject group information or schedule of assessments associated with it and is far less detailed than sub protocols.
That master protocol is then used as a basis to build sub-protocols for each study. The sub-protocols sit under the Master Protocol, providing detailed information about the subject group, investigational product, schedule of assessments, population requirements, disease, etc.
These are filed as independent documents with the IRB as sub protocols to the master protocol, essentially making them sub-studies. Using the master protocol as the copy source helps to accelerate development of documentation, allowing sponsors to rapidly adopt the existing protocol framework for each new study, rather than building a set of protocols from scratch.
The objectives will vary from study-to-study, and can include one or more investigational product, disease type, or population, but they will all live under the original master protocol. Each subprotocol is an independent document to the master protocol.
The time savings and consistency achieved through this approach can be a huge benefit for sponsors, giving them the agility to rapidly launch studies in response to new information. However, it does introduce added complexity to the study environment.
When sponsors decide to adopt this approach, they make time up front to gather input and support from multiple internal and external stakeholders, including the internal data management teams to ensure the existing digital environment can handle multiple study databases.
Once the trials begin, the data team must be ready to manage a constantly shifting flow of data from studies that have varying schedules, populations, and details. It will require a fit for purpose Electronic Data Capture (EDC) system that is built to accommodate adaptive study designs and to provide continuity to capture data across studies. When there are multiple drugs or drug combination being tested simultaneously, database matrices can quickly get complicated requiring sophisticated data validation processes, and efficient data reconciliation and cleaning.
These complications are amplified when multiple sub-studies all stream to the same database. For this reason, developing and releasing one database ahead of others provides a copy source that can be used for subsequent databases, speeding delivery of downstream databases.
It also eliminates the complexity of having multiple sub-protocols in a single database and provides the flexibility to easily pull individual study results without impacting studies still in flight. And, if sub-protocols need to be amended, it will not impact other sub-protocols or databases, providing a path of least disturbance.
This is an important early decision that often gets overlooked. If sponsors assume they will only run a handful of sub-studies, they may determine that a single database is sufficient. However, adaptive studies are never clear cut, and in many cases new data warrants additional studies, which can overwhelm a single database environment. Planning ahead by implementing a database for each new study prevents this risk while maintaining the desired agility that master protocols design brings.
As more sponsors focus on oncology, master protocol designs will become a common tool for adaptive clinical research. Leveraging this approach, in combination with FSP models, gives sponsors the flexibility to link the right treatments to the right patient populations, and speed those drugs to market. It’s one more way the clinical research environment is evolving to meet the demands for more efficient drug development.
To learn more about IQVIA’s approach to Master Protocol Design and FSP models, contact GlobalFSPGTM@iqvia.com or visit iqvia.com/biostatistics.
Getting the right outcomes from your clinical trials is all about the data and insights they provide. Biostatistics in clinical trials isn’t just a necessity, it can be a real competitive advantage.
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