What's Happening?
Viva Biotech, through its Multi-Modality AI-Rooted Solutions (MARS) division and Chief Technology Officer Dr. Susan Chen, is addressing significant challenges in peptide drug development, particularly for cyclic peptides. Peptides, small chains of amino
acids, are gaining traction in drug development, exemplified by the GLP-1 obesity market. However, their production is notoriously sensitive to factors like reactor geometry, resin swelling, and temperature fluctuations, leading to issues such as low bioavailability and unpredictable impurities. Complex or long-chain peptides are especially difficult to develop and produce reproducibly due to obscure reaction mechanisms and challenging structure characterization. Viva Biotech is tackling these bottlenecks by integrating AI and computational tools with hybrid synthesis strategies, combining solid-phase and liquid-phase approaches. This allows for more efficient synthesis and scale-up, producing fragments with high purity and greater throughput, which can be scaled to hundreds of kilograms. The company has successfully applied this hybrid approach to GLP-1 analogues, achieving kilogram-scale preparation with purity of 99% or higher.
Why It's Important?
The advancements by Viva Biotech are crucial for the pharmaceutical industry, particularly in the U.S., as they promise to unlock new drug frontiers that were previously considered 'undruggable' by traditional small molecules or antibodies. Cyclic peptides offer unique advantages, such as the ability to block multiple signaling pathways, provide selectivity, and potentially replace antibody therapies with oral administration. This could lead to more effective and patient-friendly treatments for a range of diseases. The current challenges in peptide manufacturing, including low bioavailability and high production costs, have limited their widespread adoption. By improving reproducibility, controlling impurities, and enhancing bioavailability predictability through AI and hybrid synthesis, Viva Biotech is making peptide therapeutics more viable and cost-effective. This could accelerate the development of novel drugs, reduce R&D expenses for pharmaceutical companies, and ultimately provide patients with better treatment options, especially for conditions where existing therapies are insufficient or have significant side effects.
What's Next?
Viva Biotech anticipates further investment in high-throughput automation and the introduction of more building blocks and amino acids into the market. The company plans to continue developing novel synthesis technologies, including continuous flow, TAG technology, crystallization after tag, and new modalities like PDC, APDC, RDC, and POA. These innovations are expected to further enhance the field of peptide therapeutics. The integration of AI-enabled peptide discovery and optimization with advanced synthesis, process development, analytics, formulation, and manufacturing capabilities positions Viva Biotech's CRDMO platform to support drug programs from early discovery through scalable development and commercial manufacturing. This comprehensive approach aims to streamline the drug development pipeline, making it faster and more efficient to bring new peptide-based therapies to market. The focus on improving bioavailability and reducing production risks suggests a future with a broader range of orally available and cost-effective peptide drugs.
Beyond the Headlines
The deeper implications of Viva Biotech's work extend to a paradigm shift in drug discovery and manufacturing. The reliance on extensive human interaction and practical training in peptide synthesis, as noted by Dr. Chen, highlights a significant bottleneck that AI and automation are beginning to address. By reducing the need for manual intervention and improving predictive modeling, these technologies can mitigate the 'money into the drain' scenario associated with failed batches. This shift not only makes drug development more economically feasible but also raises ethical considerations regarding the role of human expertise versus AI in complex scientific processes. Furthermore, the ability of cyclic peptides to target previously 'undruggable' surfaces and cross cell membranes could revolutionize treatment strategies for diseases like cancer and autoimmune disorders, where current therapies face limitations. The emphasis on robust pharmacokinetic and clearance data, alongside binding affinity, underscores a move towards more holistic drug design, prioritizing real-world efficacy and patient safety over isolated molecular properties.
