Leveraging Data for Efficient and Intelligent Budget Creation and Negotiation
Investigator budget planning and negotiation has long been a point of contention in the study-start up process of a clinical trial. Challenges in budget creation and negotiation are often borne out of a lack of valuable data, siloed decision making with little collaboration, and/or disjointed systems and processes.
When used in a meaningful way, data can help to reduce timelines, align expectations, and give key stakeholders confidence in decisions made to support the trial. During trial planning, investigator grants (total spend on out-of-pocket expenses for study conduct onsite) are a significant driver of overall trial cost; it is critical to start with the right assumptions to allow for a more seamless start-up process. There are several key factors that drive successful planning for investigator grants.
Being Informed Is Key
First, it is imperative to understand trial conduct and expectations. Having as much information available to build a comprehensive and thorough investigator grant is ideal and often can be overlooked. For instance, lab and imaging manuals – critical components of defining nuanced study conduct onsite with significant cost impact – are generally not available during the budget creation process. When considering investigator grants, ensuring the availability of these resources during the planning phase will drive truer investigator grants and in turn, faster budget negotiations.
For example, it is not uncommon for a protocol to require labs to be done centrally, which would be noted in the protocol accordingly. However, as part of that same trial, some labs may require additional tech support and handling (i.e., freezing before shipping, sitting at room temperature for a stated amount of time before aliquoting, numerous tubes to be processed separately), any of which would be noted in the lab manual and could significantly impact the budget based on time and effort alone.
Similarly for imaging, many trials leverage a central reader (removing local site cost for interpretation & reporting of imaging), which again would be stated in the protocol. What is often uncovered, however, once an imaging manual is available, is that institutions would still be required to do their own interpretation and reporting for data purposes prior to sending to the central reader. Again, this is additional staff time and effort that could potentially be missed in the planning phase but would likely be uncovered during site level negotiations. These missed items will either require increased site level investigator grants and more back and forth during negotiations, or an uptick in ad-hoc site requested amendments to account for and incorporate cost items they now know to be required.
Site intelligence is often overlooked in detail during the feasibility process and if leveraged properly could support planning and negotiations. Knowing which sites are being considered for the trial helps to drill down to a much more realistic cost estimate from the start. Certain sites, especially in the U.S., have quite an extensive list of itemized administrative fees that have the potential to change the trajectory of the total overall investigator grant budget. Understanding standard overhead rates for the sites being considered can also significantly impact the total budget; knowing if the site is a private versus public institution has its impacts, especially in Europe. In the U.S., understanding how sites account for Medicare coverage analysis and how or if any standard of care can be applied in other parts of the globe for the trial are all crucial factors in overall cost planning. A secondary item of site intelligence is understanding how the sites performed on similar trials. This would be another “arrow in the quiver” to allow for informed decision making when it comes to site selection.
For example, if site intelligence data indicate a particular site has considerable administrative fees both at start-up and annually, while also having a track record of low enrollment rates on similar trials, that would allow for a more informed decision about selecting or choosing to pass on that site. It is understood that no two studies are the same and there are numerous factors at play with respect to a site’s success but having a tangible and detailed site intelligence and history is a value add to sponsors and CROs and better positions them from site selection down to individual contract negotiations.
Source FMV Data
In addition to having as much information available to build out a comprehensive investigator grant budget, it is imperative to leverage a current fair market value (FMV) data set. As with everything else, costs in clinical research have significantly changed in the last couple of years. The dynamic in calculating reasonable investigator grants is simply different than it was just a few years ago: additional considerations must be made with regard to timing of trial participant visits; missed visits due to Covid, costs to support safe transportation to institutions for trial participants to accommodate scheduled visits, and residual cost increases due to inflation and supply and demand.
All of these factors impact the investigator grants, so having a current FMV data set that is regularly updated and captures the nuances of these changes on a global scale allows for better planning and less contentious negotiations. Utilizing a current FMV data set with the known history of site-specific costs and negotiations will better position both sponsors and CROs to reduce the cycle timelines from final protocol to first site initiated to last site initiated.
A data-driven, detailed approach on the front-end can help steer a new trial towards long-term success. As clinical research data currently lives in multiple systems (most of which do not always communicate), cross-functional collaboration is critical. Clinicians need to support in investigator grant template development, provide insight into actual trial conduct, and offer details around labs, imaging, and dosing when corresponding manuals are not available. Feasibility and clinical operations team members need to reference historic data on similar studies when geographic footprints overlap and rely upon colleagues who work in contract negotiation, and finalization of regulatory documents to craft a more realistic picture of timelines and overall cost burden in selected countries and sites. Leveraging a timely FMV data set will also lend to the success of the trial by knowing current data is being utilized to represent current actuals vs. data from 2-3 years ago.
Overall, if more can be done upfront to ensure key study startup stakeholders are more collaborative and better informed, have access to site intelligence and up-to-date FMV data, cognizant that trial timelines are always aggressive, it will be mutually beneficial for all parties involved. Both CROs and pharmaceutical and device companies will be able to make better, more informed decisions, leading to increased budget confidence and startup efficiency.
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