Studies with clinical trial endpoints are not always the best options for assessing the risk or efficacy of an intervention. It is common to use biomarkers as proxies or intermediary indicators of diseases or therapeutic outcomes.
With any bioanalytical approach, thorough method validation is crucial to demonstrate an adequate efficiency of the desired approach.
Let us focus on the conditions and requirements that will lead to a successful biomarker method validation.
How To Achieve a Successful Biomarker Validation?
A thorough biomarker assay development and validation ensures that generated results are accurate and reliable. A biomarker passes through three levels of stages till its regulatory acceptance, explorable, probable valid, and known valid biomarkers.
Valid biomarkers are also called fit-for-purpose assays. From the perspective of Biomarker Validation, the closer a biomarker is to known valid space; the greater is the degree of validation.
The success of a biomarker validation depends on the level of assurance generated during biomarker analysis. There are some basic questions a biomarker validation should address. These include the assay’s intended use, the degree of certainty, assumptions made, and clinical endpoints. Biomarker validation is not a single process but an ever-evolving space that changes with the influx of more complex data. Many parameters can be wholly or partially met, and the degree of biomarker method validation varies from one case to another.
Researchers should introduce associated Biomarker Testing methods in the drug discovery and development phase as early as possible. The primary goal of a biomarker assay development and validation is to introduce a biomarker as a clinical trial endpoint. It has shown a link between the biomarker and its corresponding clinical outcome.
There are multiple aspects to biomarker method validation. There are various ways through which bioanalytical scientists can approach biomarker validation.
Validation is a continuous process with data incoming from preclinical, early clinical, and late phase clinical studies. The crucial factors that need to be optimized and tested in biomarker validation studies are sensitivity, specificity, probability of false positives and false negatives, and pharmacokinetic/pharmacodynamic testing.
Must Read: Biomarker Approaches That Impact the Implementation of Drug Development
Validation of surrogate biomarkers is a more challenging task. There are two criteria in surrogate biomarker validation.
- To demonstrate clinical correlation with the clinical endpoint
- A surrogate biomarker should entirely incorporate an intervention’s effect on the clinical endpoint.
Scientists must fulfil all assay conditions to meet these criteria for efficient biomarker validation.
Surrogate biomarker validation should ideally include empirical evidence and clinical insights. Researchers should completely understand the disease mechanism and the intended effects a candidate drug will have on the system.
It is well understood among scientists that achieving such expertise is extremely difficult. Researchers usually conduct a meta-analysis of randomized controlled trials for efficient surrogate biomarker validation.
Conclusion
It is a shared belief that developing newer and efficient applications is necessary for biomarker assay development and validation. It will be crucial that different players from the industry, academia and government bodies come together and work in tandem to build processes and infrastructure for biomarker analysis.
