Key Takeaways
- •Dr.
- •His work directly contributed to the discovery and development of multiple clinical drug candidates and first-in-class peptide medicines.
- •Beyond drug development, Dr.
Leadership in Peptide Research
Dr. Ved Srivastava holds the position of Chief Scientific Officer at Perpetual Medicines, a biotechnology company that uses computational artificial intelligence (AI) and machine learning to create next-generation peptide therapeutics. His career also includes co-founding Phoundry Pharmaceuticals, serving as Vice President of Chemistry at Aktis Oncology and Intarcia Therapeutics, and heading peptide chemistry at GlaxoSmithKline and Amylin Pharmaceuticals. These roles placed him at the intersection of peptide science and drug development for over three decades.
His work directly contributed to the discovery and development of multiple clinical drug candidates and first-in-class peptide medicines. Most notably, these include Byetta (exenatide), Bydureon (a long-acting formulation of exenatide), and Symlin (pramlintide). Byetta and Bydureon are based on exendin-4, a peptide originally isolated from the venom of the Gila monster, and act as glucagon-like peptide-1 (GLP-1) receptor agonists. They fundamentally changed the treatment of type 2 diabetes by enhancing insulin secretion, slowing gastric emptying, and promoting satiety. Symlin is a synthetic analog of amylin, a neuroendocrine hormone co-secreted with insulin that helps regulate blood glucose and body weight. Together, these drugs demonstrated that peptides could be viable, long-acting therapies for chronic metabolic diseases, shifting long-held skepticism about peptide therapeutics.
Beyond drug development, Dr. Srivastava served as President of the American Peptide Society and currently chairs the Peptides Expert Committee for the United States Pharmacopeia (USP), where he helps set quality and purity standards for peptide drugs used in clinical settings. In recognition of his scientific contributions, he received the American Chemical Society North Carolina Section’s Distinguished Lectureship Award for significant research achievements in the chemical sciences. He has authored numerous peer-reviewed papers and patents, and edited six books covering peptide-based drug discovery and the critical field of Chemistry, Manufacturing, and Control (CMC) for peptides. His editorial work underscores the importance of robust, reproducible synthesis and purification methods in bringing peptide drugs to market.
Origins of Interest in Peptides
Dr. Srivastava’s entry into peptide research was neither obvious nor easy. Early in his career, he focused on small molecules for anti-diabetic agents during his PhD. At that time, in the mid-1980s, peptide science was only beginning to emerge as a serious discipline. The field gained major momentum after Bruce Merrifield won the Nobel Prize in Chemistry in 1984 for developing solid-phase peptide synthesis, which made it possible to assemble peptides in a systematic, automated fashion.
Seeing the potential to contribute to this new area, Dr. Srivastava contacted a peptide expert at the Central Drug Research Institute in India. “I want to work on peptides,” he said. The expert was surprised, as small-molecule chemistry was the dominant path at that time. Determined to switch fields, Dr. Srivastava accepted a salary cut to one-third of his previous pay to gain experience in peptide chemistry.
Later, while in the United States, he collaborated with Professor Charles Stammer on non-canonical amino acids in peptides. Non-canonical amino acids are not among the standard 20 proteinogenic building blocks. Incorporating them can improve a peptide’s stability, target binding, and resistance to enzymatic degradation, broadening the drug design space. Professor Stammer then connected him with John Stewart, whose book “Solid-Phase Peptide Synthesis” has served as the field’s standard reference for decades. Stewart worked alongside Merrifield and contributed key advances in synthesis methodology. Dr. Srivastava continued his career in peptides, particularly focusing on the development of GLP-1 and amylin analogues, which eventually led to the approved drugs Byetta, Bydureon, and Symlin.
Changes in Peptide Science Over Time
When Dr. Srivastava began his work, peptide synthesis was a labor-intensive, manual process. In the 1980s and 1990s, researchers had to prepare Boc-protected amino acids, Fmoc-protected amino acids, and t-butyl esters themselves, because these building blocks were not commercially available in the variety seen today. Progress in assembling a single peptide could take weeks or months. Purification and characterization were also difficult, as analytical tools for peptides were less advanced.
Today, the situation is radically different. Researchers can purchase pre-protected amino acids and load them into automated peptide synthesizers that carry out the chain assembly steadily and reproducibly. The process is largely automated, freeing scientists to focus on design and optimization rather than repetitive manual steps.
Methodological advances have been equally transformative. Stapling fixes peptide conformations by covalently linking side chains, often with hydrocarbon bridges, to stabilize helical structures. Cyclization, joining the peptide’s ends or side chains to form a ring, reduces flexibility and improves metabolic stability. These techniques have made peptides more drug-like, countering earlier perceptions that peptides were unsuitable as drugs due to their short half-lives, poor solubility, and manufacturing difficulties.
Rules for stabilization and half-life improvement have emerged through systematic research. Strategies include replacing natural amino acids with D-amino acids, attaching polyethylene glycol (PEG) chains, fusing peptides to albumin or antibody fragments, and developing sustained-release formulations like the microsphere technology used in Bydureon. Purification methods advanced from simple precipitation to high-performance liquid chromatography (HPLC) and medium-pressure liquid chromatography (MPLC), enabling high-purity products at scale. Nuclear magnetic resonance (NMR) capabilities grew, allowing detailed structural analysis of peptides and peptide-receptor complexes.
Discovery methods expanded dramatically. Combinatorial libraries containing millions of different peptide sequences can now be screened in a single experiment. Techniques such as mRNA display covalently link each peptide to its encoding mRNA, enabling iterative rounds of selection and amplification. Artificial intelligence and machine learning algorithms now guide the design of peptide sequences, predict interactions, and filter poor candidates before any synthesis or screening takes place. These computational tools allow early elimination of compounds with low chance of success, accelerating the development pipeline. All these shifts have changed the technology, therapeutic scope, and discovery methods of peptide science.
Peptide Therapeutics in 2026
As former President of the American Peptide Society, Dr. Srivastava offers an informed assessment of the field in 2026. He identifies three key drivers shaping the future of peptide therapeutics. The first is the rise of macrocyclic peptides. Macrocycles are peptides whose overall structure is stabilized by one or more large ring systems. This architecture combines high target affinity and selectivity with improved resistance to proteolysis. Macrocycles can modulate protein-protein interactions, a class of targets previously considered undruggable by small molecules or linear peptides. Researchers are now developing oral macrocyclic peptides, a major achievement because peptides are typically degraded in the gut.
The second driver is AI-driven design. Machine learning models trained on large datasets of peptide sequences, structures, and biological activities can propose entirely new candidates with optimized binding, permeability, and stability. AI can also predict off-target effects and toxicity early in the process, saving time and resources. The third driver is target. Dr. Srivastava emphasizes that selecting the right biological target remains critical. Advances in genomics, proteomics, and structural biology have uncovered many new disease-related proteins and interactions that can be addressed with peptides. As the field matures, the combination of macrocyclic chemistry, computational design, and careful target selection promises to yield a new generation of peptide therapeutics with improved efficacy, safety, and patient convenience.
Frequently Asked Questions
Q: What led Dr. Ved Srivastava to switch from small-molecule chemistry to peptide science?
A: After Bruce Merrifield won the Nobel Prize in 1984 for solid-phase peptide synthesis, Dr. Srivastava saw the potential of the emerging field. He contacted a peptide expert at the Central Drug Research Institute in India, stating “I want to work on peptides,” and accepted a salary cut to one-third of his previous pay to gain experience in peptide chemistry.
Q: How has peptide synthesis evolved since Dr. Srivastava began his career?
A: In the 1980s and 1990s, researchers had to manually prepare Boc and Fmoc amino acids and t-butyl esters. Today, automated synthesizers use commercially available building blocks. Advances like stapling, cyclization, improved purification, and NMR characterization have made peptides more stable and drug-like.
Q: What are the three key drivers of peptide therapeutics in 2026 according to Dr. Srivastava?
A: The three key drivers are macrocyclic peptides (which stabilize structure and target protein-protein interactions), AI-driven design (which accelerates candidate optimization and filtering), and careful selection of biological targets (enabled by genomics and structural biology).
Q: Which first-in-class peptide medicines did Dr. Srivastava help develop?
A: He contributed to the discovery and development of Byetta (exenatide), Bydureon (long-acting exenatide), and Symlin (pramlintide). These drugs, targeting GLP-1 and amylin receptors, changed the treatment landscape for metabolic diseases such as type 2 diabetes and obesity.