In the drug development landscape, biomarkers are important tools that are used as strategic drivers of decision-making. From target engagement to safety monitoring and patient stratification, biomarkers accelerate clinical development and increase the probability of success. But not all biomarkers are created equal, and their value depends heavily on context of use (COU). In bioanalytical development, defining the COU early and clearly is the foundation for building assays that are both scientifically valid and regulatory-ready.

Defining Context of Use

The Context of Use (COU) is the specific description of how a biomarker is intended to be used in drug development or regulatory decision-making. It defines the purpose of the biomarker, the biological matrix, the population, and how the data will influence key decisions. Without this clarity, assay development risks being unfocused, generating data that is neither actionable nor acceptable to regulators. Depending on the COU, different sets of bioanalytical assessments are needed during development of the assay for it to support the intended use in a clinical study.

Examples of COUs include:

  • Intended application (e.g., patient stratification, dose selection, efficacy monitoring, safety monitoring, exploratory)
  • Pharmacodynamic marker to demonstrate target, proof of mechanism of action.
  • Safety marker detects/prevents drug-induced toxicity, early warning signals
  • Monitoring marker tracks disease progression or treatment effects over time
  • Decision-making impact (e.g., internal decision making, go/no-go decisions, trial enrichment, regulatory submission)

Why COU Is Critical in Bioanalytical Development

Assay Design

  • Context of use – If the biomarker is exploratory, a multiplex panel set up according to the manufacture’s protocol may be sufficient without the need for further development while a biomarker supporting safety may require validation.
  • Study design and how this will impact the life of the assay, considering critical reagents
  • Expected levels of biomarkers and how those levels change over time.  What sensitivity is required to monitor those markers

Validation Parameters

  • Calibration range – The range of concentrations over which the method provides signals that are directly proportional to the concentration of the analyte. Range should cover the expected biomarker concentrations in study samples.
  • Parallelism – Demonstrates that the sample dilution–response curve is parallel to the standard concentration–response curve as an indication that the assay is suitable for measurement of the analyte in the biological matrix.
  • Selectivity- Demonstrate the method can specifically measure the biomarker without interferencefrom endogenous matrix components, co-medications, or metabolites
  • Accuracy – The closeness of agreement between a measured value and the true value or accepted reference value, also referred to as the nominal value.  If no certified reference material exists (common for biomarkers), relative accuracy can be shown via spike-recovery or cross-platform comparison
  • Precision – Repeatability (intra-run) and intermediate precision (inter-run).
  • Sensitivity – The lowest reliably quantifiable concentration with acceptable accuracy and precision. Important if biomarker baseline levels are low.
  • Dilutional linearity – Ability to dilute samples with high biomarker concentrations into the validated range without losing accuracy/precision.
  • Stability – short term stability (freeze/thaw, benchtop, 4C) and long-term stability evaluations
  • Robustness – For LBA-based methods using commercial kits, multiple lots may not be available from the manufacturer at the time of method validation. In that case, lot-to-lot bridging will be assessed during in-study sample analysis, testing QC samples in parallel on the old and new lot

Impacts Regulatory Interactions

  • Agencies like FDA and EMA evaluate biomarkers differently depending on COU.
  • A biomarker proposed as a surrogate endpoint will undergo intense scrutiny, while an exploratory biomarker used to guide internal decisions may not.

Biomarkers have enormous potential to transform drug development, but their impact depends on context. Defining a biomarker’s context of use early enables efficient bioanalytical assay development and ensures the resulting data are actionable for regulators and clinical teams alike.  

For more than 45 years, KCAS Bio has delivered expert bioanalytical support across every stage of drug development. Our scientists are agnostic to drug type or disease indication and bring deep experience across a wide range of matrices, few we haven’t validated or tested in support of biomarker studies. With a robust portfolio of ‘off the shelf’  assays and extensive expertise in custom biomarker method development, KCAS Bio is equipped to meet even the most complex analytical challenges.