Identification of new classes of antibiotics based on bicyclic peptides (Bicycles)

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"Resistance to antibiotics is a major public health threat that could have huge impact on medicine and indeed our way of life. Reports have suggested that without substantial interventions, 100 million people could die from infection from antibiotic-resistant bacteria by 2050\. The issue is not just deaths from untreatable infection but the inability to carry out other medical procedures such as elective surgery, transplantation and cancer chemotherapy without effective antibiotics. It has been estimated that the economic cost could be $100 trillion or 2.5% of World GDP.Development of new antibiotics has stalled partly for economic reasons in that antibiotic development in recent years has not provided a sufficient return on investment, but partly also for technical reasons in that it has proved extremely difficult to develop new antibiotics. Some success has been achieved in developing new members of existing classes of antibiotics, but only three new classes of antibiotics have been introduced in the last 40 years.Bicycle Therapeutics has developed a game-changing new lead discovery technology which has proven extremely productive in the oncology field and is also being exploited in collaboration with major pharmaceutical companies in ophthalmology, respiratory, cardiovascular and metabolic diseases. This platform has tremendous potential for application to development of new antibiotics.Development of new antibiotics has been extremely difficult because the compound collections of pharmaceutical companies are not well-suited to antibacterial applications. Furthermore, the ideal targets for development of new antibacterials are complex and recalcitrant to traditional drug discovery approaches. Only natural molecules optimised over millions of years by evolution have tended to be successful, but new ones are proving harder and harder to find.The Bicycle technology employs bacteriophage (viruses of bacteria) to generate and present drug-like molecules in huge numbers, many orders of magnitude greater than could be achieved by synthetic chemistry, and test them for target binding while still attached to the bacteriophage. The population can therefore be enriched for promising leads through multiple evolutionary cycles.The power of the approach is similar to natural selection in evolution, but conducted over months rather than millennia. Our goal is to generate proof-of-principle data for this approach against antibacterial targets and, if successful, to establish a spin-off company to utilize the technology against a broad range of antibacterial targets. We believe that this innovative technology, new to the antibacterial field but proven elsewhere, could have a major impact on the antimicrobial resistance problem."