The accepted definition of a biomarker is a “defined characteristic that is measured as an indicator of normal biological processes, pathogenic processes, or responses to an exposure or intervention, including therapeutic interventions.” This definition was derived from a 2016 partnership between the U.S. FDA and the National Institutes of Health (NIH). Biomarkers are not diagnostic tools—they do not assess how a patient feels, functions or survives—they are simply indicators. At present, seven categories of biomarkers provide various indications:
- Monitoring: measured continuously to assess disease status.
- Response: demonstrating a beneficial or harmful biological response.
- Predictive: identifying individuals more likely to have a disease than similar individuals.
- Safety: measuring the presence or extent of toxicity before or after exposure to a drug.
- Diagnostic: confirming the presence of a disease or condition.
- Risk: indicating an individual’s potential for developing a disease or condition.
- Prognostic: identifying the likelihood of a clinical event, such as disease recurrence.
Thousands of biomarkers exist in humans, but testing them means identifying and quantifying existing proteins, choosing the correct reagent, optimizing the assay, and validating the methodology. In drug development, biomarkers are used more frequently to assess how new drugs and therapeutic biological products affect patients. They play essential roles in evaluating a new drug’s safety and efficacy, and as such, the data used to measure them must be accurate. Therefore the U.S. FDA recommends using a fit-for-purpose approach. And if the data is used to support a regulatory application, assay validation is a must-have.
Defining fit-for-purpose in a drug development context
Biomarkers are used for many things in drug development and are not subject to formal regulatory oversight. Therefore, a “fit-for-purpose” (FFP) approach is essential when determining their validation methods. FFP is a general approach used to develop and validate ligand binding-based biomarker assays—i.e., those in which the rigor of analytical validation depends on the intended use of the data.
In the preclinical phase of drug development, biomarker data are used to understand the drug’s mechanism of action or biochemical pathway of interest. This is considered an exploratory method validation. Biomarker data are used in early clinical development for proof of mechanism and proof of concept, as well as for dose selection in Phase I and in dose-range finding analyses in Phase II. Exploratory method validation may be sufficient before quantifying biomarkers that demonstrate the mechanism of action, proof of mechanism or proof of concept and some exploratory safety biomarker discovery work.
Safety and diagnostic biomarkers may play a critical role in all phases of drug development. Quantifying these biomarkers may require advanced method validation combined with exploratory biomarker validation before use. Moreover, most biomarker data generated during the late phases are derived from pivotal trials. The data for safety assessments and proof of efficacy are intended to support drug applications, contributing to drug label and dosing information. These data should be suitably reliable, and the methods should be fully validated.
The Simoa approach
The Simoa Joint Laboratory — a partnership between WuXi AppTec and Quanterix — uses cutting-edge technology to develop biomarker assays. The U.S. FDA says validating bioanalytical methods for biomarker assays should be like validating drug assays, addressing accuracy, precision, sensitivity, selectivity, parallelism, range, reproducibility and stability. The Simoa platform offers distinct advantages over conventional platforms to achieve these endpoints.
Researchers are using Simoa technology in oncology, neurology, cardiology, inflammation and infectious disease. To date, the laboratory has validated nine biomarkers according to Good Laboratory Practices (GLP) and distinguished itself in myriad other ways.
Most biomarker expression is very low, and the concentration of a biomarker in the blood is much lower than the limit of detection used in conventional platforms. Consequently, the landscape and application of immunoassay platforms have changed dramatically. The introduction of bead-based methods, coupled with single-molecule detection standardization and the ability to amplify assay signals, has improved the sensitivity of many immunoassays, sometimes by several logs of magnitude.
The Simoa platform detects proteins and nucleic acids with 1,000 times more analytical sensitivity than ELISA, MSD and Luminex assay kits. The technology can also identify changes in neuro markers that were once thought to be undetectable. Biomarkers closely associated with Alzheimer’s and Parkinson’s diseases and some brain diseases and injuries include Tau, P-Tau, NFL, Amyloid β-40 and Amyloid β-42. These biomarkers are found in cerebrospinal fluid, which is minimally traceable in blood and undetectable using existing protein assays. Often, it is too dangerous to collect or screen.
Simoa technology can detect and analyze these biomarkers with coefficients of variation below 10%. This allows Simoa researchers to obtain baseline analytes from healthy subjects and disease indicators for greater biomarker exploration and enhanced pharmacokinetic/pharmacodynamic (PK/PD) studies.
Small sample sizes and quick turnaround
In addition to sensitivity requirements, quantifying low abundant analytes (i.e., biomarkers) often requires relatively large sample volumes. This amount of biological material can be challenging to collect. Therefore, technologies requiring low sample volumes or multiplexing capabilities are desirable. Simoa technology can use smaller sample sizes than ELISA platforms.
“Singleplex” assays target a single analyte in a single reaction tube. On the other hand, multiplex assays measure the presence, concentration, activity and quality of multiple analytes in a single test. These assays measure this data simultaneously, increasing efficiency and turnaround times for sample testing.
Adding multiple biomarker assays to a single test run alleviates the need to measure samples and run individual assays from the beginning. Even most multiplex platforms are calibrated to test three- or four-plex—i.e., three or four biomarkers—but Simoa can also test up to 10 unique target molecules in the same reaction.
High throughput and reduced human error
Throughput is another critical factor to consider. From sample spiking and washing plates to monitoring incubation and biomarker detection, the process is deliberate and can be time-consuming. The Simoa platform is entirely automated, requiring less hands-on work compared to conventional platforms. The technology also detects signals and generates data quicker than ELISA and MSD platforms. Simoa’s miniaturization also improves sensitivity and throughput. A process that might take up to five hours to complete manually takes as little as 45-60 minutes using the Simoa platform.
A final word on biomarkers
Biomarkers are like the Wild West—they have great potential but little oversight. The U.S. FDA recommends three ways drug sponsors and developers can use biomarkers in their drug development program:
- Scientific community consensus.
- A specific drug development and approval process.
- The Biomarker Qualification Program at the U.S. FDA’s Center for Drug Evaluation and Research (CDER).
It is often up to drug sponsors and developers to voluntarily share their biomarker data with the rest of the industry. But once a biomarker is validated and qualified for a particular context of use (COU), it is publicly available for other drug sponsors and developers to use in their programs without re-reviewing the data.
The Simoa platform is one way to achieve the accuracy, precision, sensitivity, selectivity, parallelism, range, reproducibility and stability needed to gather data and validate biomarkers in new and unprecedented ways. Collaboration between drug developers and sponsors, regulatory bodies, academia and laboratory testing partners is how to advance the industry as a whole.
Yumeng Tan graduated from Shanghai Jiao Tong University with a Ph.D. in biochemistry and molecular biology. She is engaged in large molecule bioanalysis and participates in Simoa HD-X validation, method development, method validation and sample analysis of preclinical and clinical biomarkers and pharmacokinetic studies.
Congbin Jin joined WuXi AppTec in 2016 as Group leader in the Simoa Joint Lab. He has extensive experience in preclinical/clinical PK PD method development, method validation and homebrew capabilities on the Simoa platform in the large molecule group.
Jing Shi, Ph.D., joined WuXi AppTec (Shanghai, China) in 2014 as Vice President and Global Head of Bioanalytical Services in the Laboratory Testing Division. She has extensive experience across various stages of drug development – including preclinical/clinical bioanalytical analysis, toxicology, cell line development, process development, biologics drug substance/drug product characterization and more. Dr Shi brings this wide-ranging experience to her work leading WuXi AppTec’s Immunochemistry Bioanalytical department while managing multisite operations. Together with her team, Shi provides bioanalytical method development, validation, and sample testing services following Good Laboratory Practice (GLP)/Good Clinical Practice (GCP) guidelines.