Sample analysis explained
Sample analysis forms part of our bioanalysis process for discovery, pre-clinical and clinical studies. Here we explain more about how we approach sample analysis to support GLP pre-clinical and GCP clinical projects.
A matrix-based standard curve should be generated for each analytical batch for each analyte and should be used for calculating the concentration of analyte in the unknown samples analysed with that run. Estimation of unknowns by extrapolations of standard curve below the LLOQ or above the ULOQ is not advised. Instead, it is recommended that the standard curve be re-determined or samples be reanalysed after dilution with the matrix.
Typically, the same curve fitting should be used for the standard curve within study. Changes in response function relationship between the validation and routine sample analysis are indicative of potential problems.
QC samples with a priori acceptance criteria should be used to accept or reject the run. These QC samples are matrix spiked with a known amount of analyte.
System suitability samples should be defined in a specific standard operating procedure. These should be run at the start of every study batch to assure the optimum operation of the system employed.
Any required sample dilutions must utilise like matrix eg. human to human.
Incurred sample reanalysis
In most instances, ISR is required for GLP pre-clinical and GCP clinical bioanalysis to demonstrate assay accuracy and reproducibility. ISR verifies that variables that could affect the analytical results are adequately controlled when the method is applied to study samples.
Approximately 10% of study samples are re-analysed. The acceptance criterion is two-thirds of reportable values must be within 20% of initial values. The ISR data is presented separately.
The assessment should be conducted at least once for each matrix for each species used for GLP toxicology studies.
In practice, ISR may not be feasible for pre-clinical studies with very small collected sample volume, or when the method requires a large aliquot size that consumes the collected sample volume. For clinical studies, the extent and nature of ISR is left to the analytical investigator; however, it is recommended that ISR be assessed for every clinical study. Factors such as concentration, patient population, special population, concomitant medication, and metabolites, should all be considered during ISR sample selection. First in human, proof of concept in patients, special population, and bioequivalence studies are examples of factors to be considered for ISR.
In instances of ISR failure, investigation is mandatory. ISR failure can be caused by contamination after initial analysis, drug instability, metabolites conversion to the parent drug, protein binding differences, concomitant medication interference, variable recovery, sample inhomogeneity, matrix effects, etc. ISR needs to be conducted in a timely manner after the initial analysis to avoid potential complication from drug instability and potential metabolite conversion.
Investigations of ISR failure
A well-documented study will include investigations that must be performed using sound scientific judgment and an SOP driven process. The investigations must be well documented and unbiased. The ultimate goal is to identify the root cause of the failure. When the cause is uncovered, corrective action must be implemented and the potential impact on previously generated data evaluated.
The project logistics for conducting bioanalysis for a clinical study require different considerations than those for a pre-clinical study. For a pre-clinical study, the method development, validation, and sample analysis are often handled by the same analyst or same group due to the relatively small study size. Because clinical studies are typically larger, multiple individuals, or instruments may be employed. During validation, robustness of the assay may be evaluated to demonstrate equivalence of multiple analysts, instruments, and or LC columns.
Sample chain of custody, sample shipment, sample storage, inventory, temperature monitoring should all be in place and documented prior to the study start date.