Common pitfalls in assay development (and how to avoid them)

Beyond the core challenges described, there are several other factors that can affect assay success during development.

Poor Design and Lack of Fit-for-Purpose Thinking: Among the most significant early mistakes in assay development include poor design and a lack of fit-for-purpose (FFP) thinking. The FFP approach is applied to guarantee that the  performance of an analysis is sufficiently analytical to produce data suitable to the intended  use, based upon a well-defined context of use: what analyte, in what matrix, with what  concentration range, and to inform what decision. Assays that are to be used to support  regulatory decision-making in pivotal trials must be fully validated, and those  that are to be used to support internal go/no-go decisions may reasonably be subjected to a smaller scope  of validation. Misaligning rigor with the development stage is a waste of resources and an exposure to regulatory risk, and biomarkers may fail not due to the science at the basis, but due to a poor assay selection and lack of initial validation.

Predefined Acceptance Criteria: The concept of fit-for-purpose design cannot be discussed outside of predefining the set of acceptance criteria prior to the generation of data. Pass/fail levels and go/no-go decision levels should be based on previous scientific reasoning, not adjusted in retrospect, when results are poor. Post hoc criterion modification is a pressing issue to regulatory authorities that undermines the validity of the whole validation exercise. The requirement of well characterised and suitably validated methods in a transparent acceptance criteria is a prerequisite of data that can reliably serve regulatory decisions as reinforcement under the current bioanalytical guidance. The administrative formality of documenting scientific justification of each threshold should not be ignored, but it is a fundamental protection both against regulatory challenge and against unintentional analytical bias.

Robustness Testing: Robustness, the assay’s capacity to remain reliable under small, deliberate variations in procedural conditions, must be assessed in the initial phases, not discovered during method transfer or a critical study. Rigorous testing of robustness in early stages can result in fewer problematic validations, easier sample analysis, and improved downstream results, without the expensive redevelopment cycles. Factors like incubation temperature, reagent lots, pH variations, operator variations, etc., may also present significant variability unless specified and constrained during development. One common technique used in ligand binding experiments is a Design of Experiment (DOE) to systematically reveal which parameters are really critical and which can be tolerated with a reasonable degree of variation, information that has the direct benefit of reinforcing the validation package itself and de-risking the transfer of technology before it happens.

The Hook Effect and Dilution Assessments: There are some potential risks to the analytical process that are well-established and must be assessed in advance. Among these, the hook effect, observed in sandwich immunoassays, occurs when very high analyte concentrations saturate both capture and detection antibodies independently, preventing sandwich complex formation and producing an unexpectedly false low signal. Left uncharacterized, this can result in a highly concentrated sample being reported at a dangerously underestimated value. ICH M10 in particular demands the use of dilution linearity to be evaluated to establish that concentrations above the upper limit of quantification are not affected by this signal suppression.

Incurred Sample Reanalysis: Of all the reproducibility checkpoints in bioanalytical development, ISR is the one that most reliably demonstrates how an assay performs in practice. In contrast to precision measurements based on spiked quality controls, ISR measures reproducibility on authentic study samples, real biological matrices with endogenous analyte, and all associated complexity. ISR is a prerequisite to all pivotal comparative bioavailability bioequivalence studies, first-in-human trials, and pivotal early patient studies, failure to complete ISR or incomplete ISR reporting are major submission deficiencies. Since the pharmacokinetic modeling, exposure-response relations, and vital dosing choices rely on ISR-supported datasets, it is necessary that ISR should be designed beforehand as a study component, but never as an afterthought. ^16-24

Lack of validation remains one of the top causes of regulatory non-acceptance. Submissions continue to fail due to inadequate reporting and/or concealment of adverse outcomes. A validation strategy needs to be fully inclusive regarding specificity, linearity, accuracy, precision, analytical range, and detection and quantitation limits, as per current regulatory requirements. Matrix effects can also reduce the detection of analytes through signal suppression and enhancement. Although compound-specific and unavoidable, these effects can be avoided through appropriate sample dilution, isotopically labeled internal standards, and selective sample preparation, with parallelism testing providing a quantitative assessment of interference. Poor documentation practices are major areas of risk from a regulatory perspective. Accurate documentation of reagent purity, handling of samples, storage of samples, and any changes to the protocol are important aspects of ensuring traceability and reproducibility of the assay throughout the entire process. Best practices include the early integration of quality risk management and statistics, the use of controls and pilot studies to manage variations, QbD to establish targets and critical attributes, and continuous monitoring to prevent assay drift. ^25,26