- Oral peptide delivery is advancing beyond semaglutide's absorption-enhancer approach to small-molecule mimetics and nanoparticle carriers.
- AI and machine learning are being used to design novel peptide sequences with predicted therapeutic properties, dramatically accelerating discovery.
- Multi-agonist approaches (dual, triple, and beyond) are expanding from weight loss into cardiovascular, liver, and neurological applications.
- Peptide-drug conjugates — attaching peptides to antibodies or small molecules — are creating entirely new therapeutic categories.
- The total addressable market for peptide therapeutics is projected to exceed $90 billion by 2030, driving unprecedented R&D investment.
Oral Peptide Delivery
The biggest practical limitation of peptide therapeutics is the needle. Most peptides are destroyed by stomach acid and digestive enzymes, requiring injection for delivery. Solving oral delivery would dramatically expand patient acceptance and market size.
Current approaches: Novo Nordisk's oral semaglutide (Rybelsus) uses SNAC, a sodium salcaprozate permeation enhancer, achieving ~1% oral bioavailability. The next generation — oral semaglutide at 25-50mg for weight management — is in late-stage trials.
Beyond absorption enhancers, researchers are exploring nanoparticle encapsulation, intestinal patch technologies, and most promisingly, small-molecule GLP-1 agonists (like Lilly's orforglipron) that aren't peptides at all but mimic peptide receptor activity with oral bioavailability built in.
AI-Designed Peptides
Machine learning is transforming peptide discovery. Traditional peptide design is iterative: synthesize, test, modify, repeat. AI approaches can screen millions of virtual sequences for predicted receptor binding, stability, and manufacturing feasibility before a single molecule is synthesized.
Google DeepMind's protein structure prediction (AlphaFold) has been extended to peptide-receptor interactions. Startups like Peptone and Nuritas are using AI to discover novel bioactive peptides. The timelines from concept to lead compound are compressing from years to months.
The limitation: AI can predict structure and binding, but biological activity in a living system involves pharmacokinetics, tissue distribution, metabolism, and off-target effects that current models can't fully capture. AI accelerates discovery but doesn't replace validation.
Multi-Agonist Expansion
The success of dual (tirzepatide) and triple (retatrutide) agonists in weight management is opening the door to multi-agonist approaches in other therapeutic areas. The principle — targeting multiple related receptors simultaneously — is being explored for: MASH/NAFLD (liver disease), cardiovascular risk reduction, neurodegeneration (combined neuroprotective pathways), and chronic kidney disease.
The challenge is managing the complexity. More receptor targets mean more potential side effects and more complicated dose-finding. But when the biology supports it, the results can be dramatically better than single-target approaches.
Peptide-Drug Conjugates
Amgen's MariTide (an antibody-peptide conjugate) represents a new paradigm: combining the specificity of peptides with the pharmacokinetic advantages of antibodies. The antibody component provides a weeks-long half-life, potentially enabling monthly dosing for weight management.
Peptide-drug conjugates (PDCs) are also being developed for oncology, where peptides that bind to tumor-specific receptors can deliver cytotoxic payloads directly to cancer cells — the same targeted delivery concept behind antibody-drug conjugates but with the cost and manufacturing advantages of peptides.
The Market
Peptide therapeutics are experiencing explosive growth. The GLP-1 agonist class alone generated over $35 billion in revenue in 2024. The total peptide therapeutics market is projected to exceed $90 billion by 2030.
This investment is fueling R&D across the field. Research peptides that were academic curiosities five years ago are now entering clinical development with serious pharmaceutical backing. The research community's early work on many of these compounds is being validated (or in some cases, disproven) by rigorous clinical trials — which is ultimately how science is supposed to work.
References
- Muttenthaler M, et al. Trends in peptide drug discovery. Nat Rev Drug Discov. 2021;20(4):309-325. PubMed
- Henninot A, Collins JC, Nuss JM. The current state of peptide drug discovery. J Med Chem. 2018;61(4):1382-1414. PubMed
- Lau JL, Dunn MK. Therapeutic peptides: Historical perspectives. Bioorg Med Chem. 2018;26(10):2700-2707. PubMed
- Fosgerau K, Hoffmann T. Peptide therapeutics: current status and future directions. Drug Discov Today. 2015;20(1):122-128. PubMed