From Discovery to Clinical Studies, Biomarkers Require Multiplex Assays

At virtually every stage of the processes required to bring a new drug to market—from early discovery through clinical trials—biopharma scientists would like more information. More insight into the disease, more data about the target, a deeper characterization of the drug candidate, and many more layers of information about how that candidate performs in animal models and trial participants.

Additional data could improve success rates, make it easier to eliminate bad candidates early, identify the best study participants more effectively, and clarify any adverse events or unexpected outcomes.

To achieve these goals, higher-performance biomarkers are essential. Identifying, developing, validating, and querying those biomarkers requires highly efficient assays—ideally, multiplex assays capable of quantifying dozens or even hundreds of analytes at a time.

Multiplexing is essential for creating flexible, cost-effective assays and for gleaning the most from each sample or analysis. This approach could prove beneficial across many areas in the drug discovery and development process. 

Multiplexing applications in biopharma

Throughout drug discovery pipelines, multiplex biomarker assays are widely used to characterize disease biology, identify and learn more about new targets, and identify biomarkers that will drive drug development and clinical studies forward.

It’s those later stages where multiplex assays are attracting new interest among biopharma scientists. In preclinical development, multiplex testing can generate a great deal of information from animal model samples to help elucidate toxicology, dosing levels, and more. The ability to query hundreds of biomarkers from a single sample can provide a far more comprehensive view than conventional testing allows.

In early-stage clinical studies, learning as much as you can from precious human samples is essential. A broad cytokine panel, for example, can be used to inform dosage decisions that must be made during phase 1 and 2 trials, while other biomarkers can help detect off-target effects and predict patient response. This approach has already been quite successful for vaccine testing, where multiplex methods enabled in-depth measurement of the immune response elicited by vaccination.^1-3 

Assay development factors to consider

Of course, any assay selection depends on the biomarker that must be measured and how it will be used. In general, there are several elements that should be factored into the assay development or selection process.

• Context of Use. Defining the way a biomarker is to be used, and its intended purpose, determines the selection of the assay. This “Context of Use” (COU) includes the identity of the biomarker, the biomarker category, how it will be applied, a description of how the biomarker functions, a hypothesis on how the biomarker will change during the study, and finally, a description of how the measured changes will be utilized.⁴
• Biomarker measurement. The selection of the assay is based on the nature of the biomarker to be measured [protein (cytokine), molecular (RNA), radiographic (tumor size), physiologic (blood pressure), etc.].  Additionally, the assay must be able to measure the specific changes in the biomarker as defined by the COU and be rigorous enough to deliver reliable data.
• Biomarker quantity. In the earliest stages of drug discovery, scientists may need to measure hundreds of biomarkers to better understand their target or candidate molecule. In clinical trials, a small number of biomarkers might be sufficient. Having a single assay platform capable of cost-effectively querying everything from a handful of markers to hundreds of markers is a good way to maintain consistent and reliable results across discovery and development phases.
• Sample volume. When more biomarkers would be useful during the clinical trial phase, sample volumes can be quite limiting. Multiplex technologies that can produce results for large numbers of analytes from a single low-volume sample can greatly expand the amount of data that can be generated from clinical studies without requiring larger amounts of samples that may not be feasible or available.
• Lab specialization. Even when assays are developed in-house, they are typically transferred to and run by external labs for clinical studies. The technology required can make a big difference in whether there will be many labs available to run the assay, or whether only a small set of specialty labs can do the work. In general, having to run any kind of custom assay instead of an “off-the-shelf” commercially available research use only test reduces the number of labs capable of serving as a partner.
• Future clinical use. In some cases, biomarker testing may be required beyond clinical trials, such as with companion diagnostics that must be run to match patients with the right therapy. When this occurs, the selected assay and assay platform must be approved or cleared by the FDA as an in vitro diagnostic test.

This list is intended to serve as a high-level overview for considering assay selection and development needs. For more specific information, biopharma scientists will no doubt look to the FDA’s M10 guidelines, protocols for fit-for-purpose validation, and industry white papers providing best practices for biomarker validation tailored to the context of use.^5-10 

Multiplexing options

Furthermore, it’s also important to consider the benefits of a multiplex assay approach. For most situations, it will be useful to query more than one biomarker at a time. Without multiplex assays, researchers may have to make difficult choices based on the sample volumes available. Having to compromise research goals by skipping certain biomarkers is a familiar concept to most biopharma scientists.

Multiplex technologies can overcome this problem, making it feasible to measure dozens or even hundreds of analytes from a single sample in a single test. This approach allows users to generate richer data sets from clinical studies, or to test hundreds of potential analytes to identify promising biomarkers in the discovery and development phases.

There are several multiplex platforms available, but they fall into two general categories: solid-phase or planar arrays, and bead-based suspension assays. The first category multiplexes biomarkers very nicely, although it’s more limited for protein targets, and its pitfall is its fixed format, which cannot be changed if a biomarker needs to be added or subtracted anywhere in the process.

Bead-based multiplexing technology, on the other hand, allows for the analysis of as many as 500 analytes (either proteins or nucleic acids) from a single sample and is highly flexible when changes are desired.

Ultimately, bead-based multiplexing technology offers many benefits for biopharma researchers, enabling them to generate substantially more information from each analysis or sample.