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The Promise of Next-Generation Proteomics in Revolutionizing Cancer Research and Treatment

by Andrii Buvailo, PhD  (contributor )   •   May 17, 2022  

Disclaimer: All opinions expressed by Contributors are their own and do not represent those of their employers, or BiopharmaTrend.com.
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Artificial intelligence (AI) is undoubtedly a big deal in the pharmaceutical industry, bringing the unprecedented abilities of modeling biology at a scale of not just separate biological processes, but whole cells and even tissues and organs (e.g. “network biology”, multi omics modeling, etc). 

There is a plethora of of various drug design companies that managed to create sophisticated AI-driven platforms for novel target discovery, lead generation, NLP-supported drug repurposing, biomarker discovery, and clinical trial improvement (e.g. better patient stratification, predicting drug responders vs. non-responders based on unique molecular markers, etc). For example our report "The Landscape of Artificial Intelligence (AI) In Pharmaceutical R&D" profiles more than 340 such companies, accross various stages of drug discovery pipeline and various therapeutic modalities -- small molecules, peptides, antibodies, RNAi therapeutics, mRNA, etc. 

However, let’s face it, at the heart of the modern “AI revolution” are oftentimes deep neural networks and those are extremely data-greedy. Besides, “garbage-in garbage-out” is a known principle. An AI drug discovery platform will only be as good as the data used for training systems. Therefore, the importance of various techniques and technologiese for generating quality biological data is paramount. In this article, let's review one such "enabling" technology --  Next Generation Proteomics (NGP).

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AI in Drug Discovery Report 2025

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Recently, I came across this article on GenomeWeb: “Next-Generation Proteomics Delivers Insights Across the Oncology Pipeline: Highlights from the AACR 2022 Annual Meeting”. Nowadays, proteomics technologies such as mass spectrometry are coming into prominence as powerful tools to deliver insights across every stage of the oncology drug discovery pipeline, for instance, helping uncover and validate novel drug targets, helping to understand drug mechanisms of action, and helping identify novel diagnostic, prognostic, or predictive biomarkers, and so on.

The authors of the above article, Biognosys, is a notable company active in development of new technologies and methods in mass spectrometry proteomics across the oncology pipeline, they presented their quite promising next-generation proteomics approach at the recent American Association for Cancer Research (AACR) Annual Meeting.

As Dr. Basem Goueli, a key opinion leader in Hematology and Oncology, commented for BiopharmaTrend: “Biognosys is by no means alone here. Somalogic and Quantum-Si both IPOd relatively recently. 908 Devices will have something to say about this once they realize the true opportunity with their table top mass spec machines. Seer, Inc, Nautilus Biotechnology, etc., are also in this space. Precision proteomics companies, once we can figure out the cost issues, will become as ubiquitous as genomics. To this end, consider that we started largely with FoundationOne. Now, off the top of my head, we have: Tempus, Caris, Neogenomics, Guardant Health, OmniSeq, Invitae, SEMA4. Exact Science is moving into this space, Protean Biodiagnostics is a new entrant in this space.

Indeed, many institutions have their own genomics and proteomics facilities, including some outside of academia (e.g. Intermountain Health). This same phenomenon is coming to oncology, but it will be much more complicated. After all, there are numerous protein posttranslational modifications that are going to be very difficult to fully account for with proteomics.”

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You may also be interested to read:

Conducting a Cellular Symphony With Life Saving Combination Therapies
by Basem Goueli, MD, PhD, MBA
Playing Chess Against Cancer: A Pharmaceutical, Biotechnological, and Clinical Guide to Modern Day Oncologic Treatment Cartography
by Basem Goueli, M.D., Ph.D., MBA

 

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