An exciting young Cambridge company is raising fresh capital and seeking talented new recruits as it bids to revolutionise drug target selection.
Oppilotech Ltd has homed in on what it calls the most critical decision made in drug discovery and developed a high-resolution computational platform based on systems biology and machine learning to model biological processes in cells.
The platform is used to identify first-in-class viable drug targets and develop novel modes of action drugs modulating these. The high level of detail it can generate allows Oppilotech to reveal new biology and identify first-in-class non-intuitive drug targets, It initially focused its modelling efforts on the bacteria E.coli and is in the process of constructing a whole cell model of E. coli based on Machine Learning – a world first.
Oppilotech has several early stage antibacterial drug discovery programmes which it intends to develop towards the clinic and in an exciting development is now also working on modelling pathways involved in cancer.
Co-founder and CEO Ajay Mistry says the company is looking to finalise a seed funding round of £2 million to expand the team, further develop antibacterial programmes and progress working on cancer pathways.
Currently funded by angels such as Sunil Shah and David Ford, Oppilotech has already raised £1.1m. It wants to recruit three computational biologists and a biologist as a matter of priority.
Mistry has a proven track record in building value in biotechnology businesses through assets, platforms and partnerships. Co-founders John George, the chief scientific officer, and Tony Raynham – director of medicinal chemistry – also have stellar CVs. George is a leader in applying systems biology to modelling living cells, building a world-first whole cell model of bacteria based on machine learning.
Raynham has extensive experience in drug discovery gleaned with Millennium, Roche and CRT, focused on oncology. He has taken drug programmes from target discovery into first-in-man trials.
Mistry said: “Drug target selection is the most important decision we make in drug discovery; a selective high-quality molecule will never become a drug if it is modulating the wrong target, which is a key contributor to the high failure rates of drug discovery programmes.
“Current approaches to target selection are based on limited, narrow spectrum analysis of cellular processes. Our vision is to become a leading biopharmaceutical company with a pipeline of first-in-class medicines that will have a meaningful impact on addressing human diseases worldwide. We aim to emulate companies like Galapagos NV.
“When modelling cellular processes, Oppilotech goes into higher levels of details than traditional approaches. Included in our modelling are detailed input parameters like protein abundance levels, mRNA levels, transcription and translation rates, catalytic rates of enzymes etcetera.
“This higher level of detail provides insights to discover new biology and, importantly, viable target selections. We have proved our approach works.”
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