Sample Prep Automation Will Increase Adoption of Proteomics

While proteomics can offer the healthcare industry incredible insights into disease, it has not yet seen the widespread success of high-throughput genomics. A major reason for this has to do with the procedural bottleneck in proteomics that occurs at the front end: sample preparation. 

For proteomics to provide deeper insights into disease, we need higher throughput methods to analyze larger sample cohorts, such as can be offered with sample prep automation. The initial steps of proteomics involve numerous time-consuming sample preparation steps, necessitating countless transfers using traditional manual pipetting. This may be easy for a handful of samples for an experienced lab technician. 

However, when hundreds or even thousands of samples need to be processed and analyzed, that sample prep work can get tiring and monotonous, characteristics which lead to higher human error rates and subsequent wasted resources. High-throughput proteomics must be capable of processing thousands of samples that come into the lab, as was the case during the height of the COVID-19 pandemic. 

Tech advances push proteomics forward

When compared to genomics, proteomics is a more recent addition to life sciences that has been garnering significant attention, particularly over the last several years due to recent technological and methodological advances. While we know that the genome offers insights into what may happen to a patient in regard to developing disease (i.e., the genotype), the proteome provides information on what is physiologically occurring now to a patient (i.e., the phenotype).

Today, the excitement for proteomic research stems from the ability to detect and quantify proteins and protein modifications that drive disease and then utilize that information to develop diagnostic disease biomarkers. Through these markers, clinicians can better tailor therapeutic strategies for a patient’s specific phenotype. 

A concrete example is the use of kinase and protein phosphorylation information to guide the members of tumor boards in selecting the best therapies for cancer patients. Going after proteins is especially important since most of today’s therapies using small molecules and/or antibodies are targeting disease-associated proteins.

Sample prep automation addresses standardization

During the early days of proteomics, labs would spend hours focused on manual sample processing. Because each lab had its own methods, there was a lack of standardization for these steps in proteomic research. By commoditizing proteomics sample preparation, similar to the sample preparation of other omics research processes—such as genomics and transcriptomics sample preparation—we can create a set of standard operating procedures that are straightforward, easily implemented, and performed in “every lab.” Sample prep automation also helps address the challenges of reproducibility and comparability of results. 

Liquid handling robots, which don’t get tired or lose focus, will be key for such commoditization efforts. They offer automated sample handling, which allows labs to:

• Expedite processes;
• Reduce the rate of errors that arise from repetitive manual pipetting; and
• Decrease the loss of precious samples.

Today’s liquid-handling robots fit nicely onto any lab bench, are affordable, and can process hundreds of samples within a day at the push of a button.

Sample prep automation boosts the future of proteomics research

For labs to increase their ability to perform translational and clinical proteomic research, they need to put into place high-throughput workflow pipelines where processes can be streamlined. The use of automation and robotics can act as just one way to accelerate sample prep, addressing a major bottleneck on the front end.

Proteomics offers the life sciences and biopharma industry immense opportunities to dig deeper into disease that was never before possible. To bring about widespread adoption, we need to identify the bottlenecks that prevent the scalability of proteomics research. By doing so, we can advance the discovery of novel biomarkers and create safer and more effective life-saving medicines for patients.