title: Validation of immunoassay for protein biomarkers: bioanalytical study plan implementation to support pre-clinical and clinical studies.
abstract: Biomarkers have emerged as an important tool to optimize the benefit/risk ratio of therapeutics. The scientific impact of biomarker studies is directly related to the quality of the underlying data. It is therefore important that guidance be established for validation of assays used to support drug development. This paper specifically focuses on validation of immunoassay for protein biomarker to support pre-clinical and clinical studies. Therapeutics (small- and macro-molecules) and their respective target/ligand are out of scope. This paper describes the implementation of a bioanalytical study plan for the validation of immunoassays to support decision-making biomarkers and biomarker selection during preclinical and clinical studies. It establishes the complete operating procedure as well as the parameters and their respective acceptance criteria and defines milestones and decision points to be followed during the assay validation that should result in high quality bioanalytical data in a limited timeframe and with reduced costs. The bioanalytical study plan can be applied to the validation of a wild range of immunoassay technology such as monoplex ELISA, automated analyzer, multiplex assays or cutting edge technology. Before any validation, a feasibility study is performed to assess the performance of the immunoassay using biological samples which should mimic the clinical population. The feasibility study addresses the likelihood that an assay will be able to achieve its intended purpose with parallelism being the most critical element (milestone 1). At the end of the feasibility study, a decision is taken to either continue with the validation or change the assay (milestone 2). The milestone 3 consists of the establishment of the nominal value of quality control to be used during the validation. The quality controls used to validate an assay should preferentially be prepared using neat (non-spiked) biological matrix (ideally derived from the specific trial population). The last milestone (milestone 4), the formal validation, includes demonstration of the assay performance meeting accuracy and precision acceptance criteria within (intra-run) and between (inter-run) validation runs for each QC sample. Validation also includes the assessment of stability of the protein biomarker in the biological matrix. It is recognized that the extent of the validation should be correlated to the intended use of the data and the assay acceptance criteria should take into consideration the study objective(s), nature of the methodology and the biological variability of the biomarker.
authors.affiliation: Department of Marker Localization and Assays, Novartis Institute for Biomedical Research, CH-4056 Basel, Switzerland. marie-anne.valentin@novartis.com
authors.forename: Marie-Anne
authors.initials: MA
authors.lastname: Valentin
authors.forename: Shenglin
authors.initials: S
authors.lastname: Ma
authors.forename: An
authors.initials: A
authors.lastname: Zhao
authors.forename: François
authors.initials: F
authors.lastname: Legay
authors.forename: Alexandre
authors.initials: A
authors.lastname: Avrameas
mesh_terms: D001331:Automation; D015415:Biomarkers / Q000032:analysis / Q000378:metabolism*; D035843:Biomedical Research; D002138:Calibration; D002623:Chemistry Techniques, Analytical / Q000379:methods; D003661:Decision Support Techniques; D004797:Enzyme-Linked Immunosorbent Assay / Q000379:methods; D006801:Humans; D007118:Immunoassay / Q000379:methods*; D011506:Proteins / Q000032:analysis* / Q000737:chemistry; D011786:Quality Control; D015203:Reproducibility of Results; D013048:Specimen Handling
chemical_list: D015415:Biomarkers; D011506:Proteins