Biomarkers: Navigating Fit-For-Purpose
The importance of method in defining the robustness and reliability of an assay
Biomarkers play an important role in the development of therapeutics from small molecules to cellular therapies. The right biomarkers can accelerate progress and aid decision making at multiple steps. Modifications to physiology and metabolism induced by a disease state will alter a range of biological process, and those changes can be tracked with biomarkers. Similarly, the action of a therapeutic molecule will result in changes to biomarkers that can be used to interrogate diverse pharmacodynamic responses. These often focus on measures such as target engagement and desired response. But, biomarkers can also be applied to the monitoring of safety endpoints, both to monitor general physiological considerations and specific aspects of a given therapeutic. Therapeutic specific safety biomarkers can be indicated in cases where there is a concern that adverse events may be driven by exaggerated pharmacology.
Usually there are many potential biomarkers to choose from. The challenge arrives in moving from the consideration of what may be relevant biomarkers to demonstrating the utility of a given Biomarker for driving a specific decision-making process; be it related to safety, exposure, response or prognosis. The challenges presented by this process, where a biomarker moves from candidate to decision making tool, means that the bioanalytical approaches used for biomarkers are driven by a fit-for-purpose approach. Success requires considering the biomarker and the Bioanalytical Method in tandem.
Unfortunately, the identities of the key biomarkers that can expedite the development of a therapeutic are rarely clear at the start of the process: promising candidates will fall by the wayside, and new challengers will emerge. Dealing with this dynamic process is not simple, but the fit-for-purpose approach provides a way of managing it. By adjusting the Bioanalytical Methods used in the migration from an investigative to a decision making endpoint, time and money can be saved.
The Flexibility of Fit-For-Purpose: From Investigational Biomarker to CDx
A guiding principle in bioanalysis is that the method employed is fit-for-purpose. The robustness of the method, and hence the understanding of the quality and the limits of the data, determines the decision making it is reasonably used for. For any decision-making involving Biomarkers the specification of the analytical workflow and the included analytical methods will be driven by the different uses of the data at different times.
In the early stages the goal is to determine if a given biomarker should be retained or excluded from a candidate list. The primary goal is to rank order and narrow down the set of biomarkers that may be suitable for critical decision making as the therapeutic moves forward. Consideration of the complete workflow employed is vital. This begins with study design and sourcing of samples, the handling of those samples and the analytical process employed, of which the computational aspects will be a critical factor for any application of -omics approaches. For this stage, where the goal is candidate biomarker identification, the robustness of the analytical approach is very much of equal consideration with other factors.
As a biomarker moves from simply one name on a list to an aspect of a decision-making process then the performance and robustness of the bioanalytical method becomes more critical. This requires regular appraisal of the analytical method used to ensure that the method, and its limitations, do not impact decision making.
One area that can often appear challenging is the use of platforms, such as flow cytometry or qPCR/ddPCR. This challenge can be overstated, as for any platform it is possible to build workflows that can provide robust data to support decision making. The key is to understand the limitations of the analytical approach and what a given method can and cannot tell you. A platform such as flow cytometry can provide highly nuanced data on target engagement and pharmacological response, but is not a platform where a six-point calibration line, or incurred sample reanalysis (ISR) can be readily performed. This is to emphasise the importance of understanding the limitations of any technology. The range of platforms that are now available means that if the question is clearly framed, a bioanalytical approach can be designed to answer it.
The key driver of the fit-for-purpose approach is that while the biomarker remains the same the decisions made based on its changes will differ. This then informs Bioanalytical Method validation: the requirement to define the robustness and reliability of an assay. This in turn determines how we interpret the resultant data. The same analytical platform and reagents may be used throughout a process with modifications to ensure, for example, that the method works with changing sample types and collection methods, or that the analyte shows appropriate stability under clinical trial conditions. There is an ongoing extension of the method, and in some cases the requirement of the method may be used to inform study design.
A more significant challenge arises when changes to analytical platforms, or fundamental aspects of the assay must occur. A requirement to improve assay sensitivity may involve the generation of new reagents that show lower background or allow a shift to a different analytical approach. This places a significant emphasis on project planning and cross team communication. It is always best to let your bioanalytical team know well in advance if they will need to improve sensitivity by 100-fold while also maintaining acceptable accuracy and precision.