Podcast | March 25, 2025

Code, Cells, and the Golden State Podcast: “Disease is solvable & the year of proteomics”

“Genomics was supposed to transform drug development, and it certain cases, it did. But in many cases, it did not. And part of the problem is that going from a DNA variant to a drug is a huge leap. If we can start from a protein target, it is a much faster process, and gives us multi-omics data to better understand disease mechanisms. And with the innovations happening in the proteomics field now, I truly believe that 2025 is the year of proteomics.

It comes down to two main reasons. The first is there is finally an understanding that we can actually make these direct measurements on a protein target as a discovery tool for target identification, drug screening, biomarkers, etcetera. That understanding is now firm in the biopharma space, especially as we have been able to greatly expand the ‘druggable space‘ of proteins we can use therapeutically in the last decade. The second is a really important push that’s coming from the industry as a whole: the underlying sentiment that drug development has to become more effective. The business model of 90% failure no longer makes sense. The fact that we have not yet solved for so many diseases is frankly unacceptable. And I think these two ideas – that we can finally measure proteins effectively, and that drug development can be done much better – have come together.

Hear the full discussion as Sapient’s Dr. Mo Jain sits down with the Code, Cells, and the Golden State podcast to detail the innovations driving the growth of proteomics in 2025.

The conversation touches on several timely topics including:

  • Why multi-omics data is needed to further enable precision drug development
  • Traditional challenges with measuring proteins at scale
  • Recent innovation cycles in mass spectrometry that are enabling broader measure, greater specificity, better reproducibility, and higher throughput protein assays
  • How these evolutions are driving novel actionable insights from early discovery to clinical phases to develop more efficacious drugs, faster

An interesting theme centered around the confluence of several innovation cycles, including in sample processing, bioanalytical instrumentation, and software, particularly cloud-based distributed computing, that have enabled a rapid step-change in the scale and quality of multi-omics data generation and analysis, particularly as it relates to proteomics.

Listen above or by searching “Cells, Code, and the Golden State” on your favorite podcast platform!