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Without a new and disruptive technology on the horizon, the proteomics market growth has stalled. In contrast, the genomics market has evolved rapidly over the past 10 years due to the arrival of next-generation sequencing (NGS). NGS has emerged as a platform that offers relatively low cost, high sensitivity, high throughput, and high plex (plex is defined as the number of analytes that can be measured e.g., 50 proteins or hundreds of DNA fragments).
At the moment, the proteomics market doesn’t have a “silver bullet” like NGS that hits all four of those performance markers. However, there are a handful of technologies that are poised to push capabilities forward. The first 2 technologies have been around for quite some time, and gained traction in niche markets.
The SOMAscan platform from SomaLogic offers high sensitivity, acceptable throughput, and high plex (with an ability to assess ~1,300 proteins), but it is expensive to use. As a result, you’re likely to use it for single-use niche applications. If you want to discover something, you might start with SOMAscan and then simplify the signature of interest (a.k.a.., “deplex”) to move on to something that’s less expensive, more broadly adopted and easier to use like ELISA testing, so you can look at a high number of samples in production mode.
The Simoa technology from Quanterix is a digital ELISA technology offering high sensitivity, decent throughput, and high plex. Simoa has been demonstrated to detect biomarkers associated with breast cancer, myocardial infarction, and inflammatory diseases. Its high cost is one thing that keeps it from becoming a widely adopted platform in the life science research tools and clinical diagnostics markets.
Imaging mass cytometry (IMC) from Fluidigm offers high plex (~50 proteins) and high sensitivity. In some cases, IMC can get down to the single-cell level to reveal the subcellular localization of specific proteins. Such high sensitivity comes with lower throughput and a significantly higher cost.
The IMC instrument costs upward of $800,000 and introduces a fifth performance marker to consider: workflow complexity. IMC has a complicated workflow and requires a trained expert to run the machine.
Digital spatial profiling (DSP) from Nanostring has high sensitivity and high plex (~800 proteins or RNAs). DSP enables you to look at proteins in a spatial context to better understand the relationship between particular cells; that is, you can look at additional analytes at the same time. This technology could be interesting to better understand complex interactions between multiple cell types, as is the case in the tumor microenvironment. The trade-offs are lower throughput and higher cost.
In some sense, these technologies already have a major impact in small niche markets. Broader adoption is harder to forecast, as no single technology does everything well. Most technologies in the proteomics sector require users to make trade-offs among key selection attributes. This pattern is also tied to the fact that there’s no central model that describes protein behavior. Proteins have complex 3D structures and functions. In some sense, they live in an analogue world, more complex than the digital nucleic acid world. Nevertheless, the proteomics market will continue to evolve, albeit more slowly than the genomics market, and people will continue to study proteins as they are ultimately responsible for cell function, and in turn health and disease.
Miguel specializes in identifying industry trends in the life science research tools and clinical diagnostics spaces. He has evaluated the market opportunity for several emerging research tools and diagnostic technologies, characterizing market dynamics to provide strategic insights for companies in these spaces. He is the lead author of DeciBio’s single cell genomics report and holds a Ph.D. in molecular biology from UCLA.
Contact Miguel and the DeciBio team to get the insights you need to accelerate innovation in your market.
Disclaimer: Companies listed above may be DeciBio Consulting clients and/or customers.