Biomarker Testing and Analysis

Biomarkers are the indicators that measure the normal vs. abnormal biologic and pathogenic processes, as well as pharmacologic responses to therapeutic intervention in the body. Biomarker analysis plays a critical role in medical science to administer patient health and improve drug development. Scientists can measure the response of investigational drugs during preclinical studies and clinical trials with biomarker testing. For example, the life sciences community relies on several well-characterized biomarker assays to demonstrate expected clinical outcomes for various treatments. Thus, Biomarkers are useful in identifying the probability of disease recurrence or progression and predict the favorable or unfavorable response towards any treatment. Examples of biomarkers include:

• Susceptibility/Risk Biomarkers – evaluate the risk of developing diseases
• Diagnostic Biomarkers – detect diseases
• Monitoring/Staging Biomarkers – determine the status/stage of diseases
• Pharmacodynamic/Response/Predictive Biomarkers – assess response to treatment
• Prognostic Biomarkers – estimate recurrence or progression of diseases
• Safety Biomarkers – indicate toxicity in response to treatment

NorthEast BioLab offers an extensive biomarker menu for qualifying, developing, validating, analyzing, and multiplexing high-quality biomarker testing for large and small molecules. We use LC-MS/MS, ELISA, MSD, Luminex, Western Blot, and qPCR, among other platforms for customized and GLP-compliant biomarker analysis. The level of method validation for biomarker analysis is fit-for-purpose, such as whether we are working with i) exploratory biomarkers for pharmacodynamics information vs. ii) confirmatory biomarkers for pivotal determination of drug safety and efficacy. Given our 15+ years experience in biomarker analysis, we provide novel and established biomarker testing services in numerous biological species and matrices, including most bodily fluids and tissue homogenates.

NorthEast BioLab performs biomarker testing using LC-MS/MS, ELISA, MSD, Luminex, qPCR, and Western Blot, among other technologies. LC-MS/MS offers a highly sensitive and specific biomarker assay with multiplexing potential for a similar class of small molecules. ELISA is a versatile platform for biomarker analysis of large molecules such as proteins, peptides, antibodies, and hormones in the biological samples. Biomarker assay development commonly applies the three major ELISA types: Sandwich ELISA with matched antibody pair for complex and unpurified biological samples, Indirect ELISA for determining total concentration for multiple antibodies in the sample, and competitive ELISA for small antigens or when only one antibody is available.

Furthermore, our scientists offer testing from the entire biomarker menu of Meso Scale Discovery (MSD) and Luminex Multiplex kits to quantify 40+ analytes within the single sample. Advantages of biomarker analysis using these state-of-the-art multiplex platforms include –

• Availability of comprehensive and component wise prevalidated kits
• Highly accurate biomarker testing for Human, Non-human Primate (NHP), Rodent (Mice, Rat), Porcine, Canine, Feline, Bovine, and Equine samples
• Small sample volumes for analytes with normal and elevated levels given broad dynamic range
• High tolerance for complex biological matrix, serum, plasma, and tissue homogenates
• Ability to compare the expression of cytokines, chemokines, and several other biomarkers in the sample

Biomarker research can be performed on multiple platforms. Genetic biomarker analysis is carried out using DNA from bodily fluids or tissues. Biomarker labs use DNA sequencing, quantitative polymerase chain reaction (qPCR), microarray-based comparative genomic hybridization (CGH), and gene expression array. Cytogenetic biomarker testing commonly employs karyotyping and fluorescence in situ hybridization. Biochemical biomarker testing generally uses mass spectrometry techniques such as MALDI-TOF-MS and ESI-MS/MS, immunology techniques like MSD, Luminex multiplex, ELISA immunoassay, and Western blot. NorthEast BioLab offers LC-MS/MS, ELISA, MSD, Luminex, qPCR, and Western Blot platform for biomarker development and validation.

The platforms for biomarker research and analysis are commonly categorized based on their purpose to examine exploratory biomarkers that are potential endpoints to be validated or confirmatory biomarkers that explain significant drug safety and efficacy. Biomarker development provides both diagnostic tools and contextual data interpretation in clinical research. For example, biomarker research platforms could measure therapeutic responses against drug treatment. These platforms can help screen the patient group that would likely have adverse effects from the therapy. Furthermore, biomarker analysis can measure the toxicity associated with drug treatment. Thus, biomarker testing services are pivotal for drug development from establishing proof-of-concept (POC) in vivo to demonstrating drug potential in clinical trials.

Biomarker discovery ultimately helps measure vital drug safety and efficacy data in clinical treatments accurately. There are genomic biomarkers for gene expression and specific gene sequences for disease identification, with treatment based on these biomarkers. Proteomic biomarkers include highly specific and sensitive protein biomarkers that help explain disease pathways, identify high-risk individuals for developing a disease, or explain therapeutic response towards intervention including any side effects. Cellular biomarkers utilize multiparameter analysis for differentiating large and rare sample cell types to provide meaningful information for supporting proteomic and genomic biomarker workflow.

Biomarker discovery is a multistep process that involves biomarker identification, qualification, assay development, validation, and clinical implementation. Biomarker qualification entails identifying biomarkers or biomarker assay, whereas assay development and validation establish fitness for use and implementation in the clinical setting. The outcome of a clinical trial using biomarkers as a surrogate endpoint requires high confidence biomarker analysis with valuable information on how crucial proteins behave during diseases. Comprehensive biomarker assay validation requires many patients to cover the broader spectrum of outcomes.

In modern medicine, biomarker development is utilized as a drug approval tool and undergo thorough discovery, validation, and qualification steps. Biomarker development could span multiple years throughout the drug development and clinical diagnostic use approval. Thus, biomarker development and validation comprise of a challenging multistep process with only a ~10% estimated success rate of entering in phase I trial. Generally, the biomarker development success rate is affected by pharmacogenetic heterogeneity of patients to treatments and biologic response, the efficacy of administered drugs, and the lack of well-established biomarker assays.

Biomarker Development has many phases –

• Experimental – sample size should be large enough to identify potential biomarkers; techniques include – protein arrays, antibody arrays, ELISA, and Immuno PCR-ELISA
• Screening and Validation – designing validated probes is challenging and expensive; ready-made immunoassays available – ELISA, MSD, Luminex, or quantitative antibody arrays
• Clinical Approval – biomarker candidates make way into clinical use approval applications to regulatory agencies

Biomarker validation involves establishing documented evidence of assurance that a specific biomarker will consistently produce an outcome in keeping with its predetermined specifications. Biomarker validation follows the “fit-for-purpose” principle that includes the many distinct stages from a typical assay validation process. Biomarker assay development and validation are broadly categorized into analytical and clinical validations. Analytical validity signifies how well the biomarker measures/assays what it is supposed to measure, ensuring sensitivity, specificity, accuracy, and precision, among other criteria. Clinical validity addresses how well the biomarker fulfills its purpose in predicting a clinically significant outcome, ensuring the diagnostic test or device performs as intended.

Biomarker qualification entails the development and regulatory acceptance of biomarkers for use in drug development. The traditional route for biomarker acceptance by regulatory authorities is through data submission during a single drug program. In contrast, the Center for Drug Evaluation and Research (CDER) established a Biomarker Qualification Program (BQP) to review biomarkers for a specific context of use (COU) and release relevant information publicly. The qualified biomarker can then be used in multiple drug programs for this COU without re-review, accelerating the drug development paradigm. The US FDA maintains this list of qualified biomarkers to be used by drug developers without re-evaluating their validity. For additional context, biomarker discovery is the process of qualifying the biomarker, demonstrating biomarker assay for specific use in multiple drug programs without reconfirming the suitability, and verifying that the biomarker testing is feasible and reliable. Qualified biomarkers must fulfill their stated context of use (COU).

Biomarker testing plays an essential role in drug development and help evaluate drug efficacy and safety in clinical trials to facilitate regulatory decision making. Examples of biomarkers that we use in everyday life include tracking blood pressure or monitoring the blood glucose level. Biomarker testing services help evaluate molecular pathways leading to diseases, and biomarkers assay development helps in target identification and mechanism of action (MOA). In preclinical development, biomarker assays enable dose selection, MOA, and safety assessment. In the clinical phase, biomarker assays support dose selection, stratification, enrichment, as well as safety and efficacy examination. Generally, select biomarker assay development can identify drug efficacy much effectively than traditional clinical endpoints. That said, multiple data points needed to understand these biomarkers.