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Staffing Needs for RWE Delivery

When an expert statistician is paired with an experienced set of data managers, opportunities to capitalize on quantitative strategy are spotted more quickly. Statisticians can determine whether datasets can strengthen study findings by being presented in a way that uses the available data in a scientifically objective way that is at the same time in line with the clients’ strategic objectives.

The practice of combining statistical needs with the processes of data management and other related services for real world evidence, we will henceforth call RWE-Delivery. There are several models for RWE-delivery that can similarly vary with the needs of a study. Questions about process, management and timelines are just as key for this choice of delivery model, as the objectives of the delivery. Therefore, it is important to work closely with delivery teams to determine the possible needs for study completion.

Sponsors might have a number of different RWE-delivery needs based on their size and strategic positioning of their assets. Large pharmaceuticals will likely have staffing needs that fluctuate over time and will benefit from working with teams that can switch from one project to another with seamless efficiency. Smaller biotechs and biopharma might not have in-house capabilities to conduct entire RWE projects, and might be seeking a partner to work as an extension of their team. A number of staffing models can be used for accelerated RWE analyses. There are four models that reflect various needs of trial sponsors. The contingent resourcing model can be used by teams that have realized that staffing is lower than necessary. Working with an RWE-delivery ensures that these staffing needs fluctuate as project needs fluctuate. A higher set of staff members can be incorporated into projects when timelines are busy, and then sponsors can quickly decrease staff through coordination with the provider.

Staff augmentation is an RWE-delivery model quite similar to the contingent resourcing model, but the RWE-delivery staff begins to integrate more with a sponsor’s team for longer term partnerships. This ensures that when new projects arise, there is a team available who already understands how the sponsor organization operates. Though overall, both the contingent resourcing model and the staff augmentation model relies on the sponsor for management, SOPs and so forth. The RWE-delivery provider acts as an extension of the sponsor’s team and distributes resources amongst sponsors.

The other models of RWE-delivery engage more autonomous management on the part of the delivery team. Through strategic capacity management and functional service provision, delivery teams take charge of both delivery and management.

The most highly sought RWE-delivery teams have both expert statisticians and experienced data managers. Much of the work that needs to be done for observational studies is tactical, which means that these two functions need to work together to identify opportunities as they arise. Conducting network meta-analyses might make sense from a statistical perspective for example, but a data manager might advise that the storage of data in a complex trial would not be able to process such a study or require a simpler comparative design. Similarly, a data manager might have stored data for a traditional trial, and a statistician might identify ways to optimize it for a different population. As the specifics of the context matter heavily, sponsors should identify RWE-delivery teams that supply both.

You can learn more on this topic in Cytel’s upcoming white paper. Contact us to learn more and schedule a meeting with our experts.

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