The real story is that we're approaching the ability to read, interpret and eventually intervene in the human body's operating system.
KJ Dhaliwal, Forbes Councils Member
Forbes
3 min read
8/10
Key Takeaways
Proteomics enables the simultaneous analysis of thousands of proteins from a single blood sample, with mass spectrometry now achieving throughput of over 5,000 proteins per run.
AlphaFold2 and subsequent AI models have predicted structures for over 200 million proteins, covering nearly all known protein sequences.
The Human Proteome Project has mapped approximately 90% of the 20,000 protein-coding genes, aiming for complete coverage by 2028.
Cancer detection using proteomic panels has shown sensitivity above 90% for early-stage lung and ovarian cancers in recent studies.
Investment in proteomics startups surpassed $3.5 billion in 2025, with major pharma companies including Novartis and Roche launching dedicated proteomics divisions.
We are approaching the ability to read, interpret, and eventually intervene in the human body's operating system. That is the real story behind the peptides-to-proteomics revolution, according to a recent Forbes Tech Council article. For decades, biology fixated on the genome—the static blueprint of life. But proteins are the dynamic machinery that carries out instructions, and understanding them has long been out of reach. Now, breakthroughs in mass spectrometry, artificial intelligence, and data analytics are flipping that paradigm, promising a future where medicine is predictive, personalized, and preemptive. The shift from genomics to proteomics matters because proteins are the direct actors in health and disease. While DNA tells us what could happen, proteins tell us what is actually happening in the body at any moment. The Forbes piece underscores that we are nearing the capability to decode the proteome—the complete set of proteins expressed by a genome—and to interpret those signals in real time. This is not speculative; technological convergence is making it possible. Key drivers include high-resolution mass spectrometers that can identify thousands of proteins in a single blood sample, and AI models like AlphaFold that predict protein structures with atomic accuracy. Companies such as Seer, SomaLogic, and Bristol Myers Squibb are investing heavily in proteomic platforms. The human proteome remains only partially mapped—about 90% of the roughly 20,000 protein-coding genes have been characterized, according to the Human Proteome Organization—but the pace is accelerating. The implications are vast. Oncology stands to benefit first: protein biomarkers can detect cancers years before symptoms appear. Neurodegenerative diseases like Alzheimer’s are increasingly understood through protein misfolding patterns. Drug development gains speed when target proteins are identified and validated in silico. Informed observers liken the proteomics revolution to the early days of genomics, but caution that the complexity is an order of magnitude higher because proteins are dynamic, modified, and interact in networks. Still, the trajectory is clear. Within the next decade, routine proteome analysis could become as common as a blood panel. Health monitoring will shift from reactive to continuous risk assessment. The peptides-to-proteomics revolution is not just a scientific milestone—it is the beginning of truly reading the body's operating system. The outlook is forward-looking: the first complete draft of the human proteome is expected by 2028. AI-driven design of therapeutic proteins is already in clinical trials. For investors, policymakers, and healthcare providers, the message is to pay attention—because the biology of the 21st century will be written in proteins, not letters.
Frequently Asked Questions
The proteomics revolution refers to the rapid advancement in technologies and methods to study the entire set of proteins (the proteome) expressed by a genome. It promises to transform medicine by enabling real-time reading of the body's functional state, leading to early disease detection and personalized treatments.
Genomics analyzes the static DNA sequence of an organism, while proteomics studies the dynamic expression, structure, and interactions of proteins. Proteins are the functional molecules that carry out cellular processes, so proteomics provides a more direct readout of health and disease than DNA alone.
Artificial intelligence is critical for predicting protein structures (e.g., AlphaFold), identifying proteins from mass spectrometry data, and modeling protein interactions. AI accelerates the interpretation of large proteomic datasets and enables the design of novel therapeutic proteins.
Proteomics will enable early detection of diseases like cancer and Alzheimer's through protein biomarker panels, inform drug target discovery, and support personalized treatment plans based on a patient's proteomic profile. It moves medicine from reactive to predictive and preventive care.
Peptides are short chains of amino acids that are the building blocks of proteins. In proteomics, proteins are often digested into peptides before analysis by mass spectrometry, allowing identification and quantification of the original proteins.
The Human Proteome Project aims to complete the mapping of all protein-coding genes by 2028. Current coverage is around 90%, with ongoing efforts to characterize protein isoforms and post-translational modifications.
