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Details of Grant 

EPSRC Reference: EP/W004801/1
Title: AMBITION: AI-driven biomedical robotic automation for research continuity
Principal Investigator: King, Professor R
Other Investigators:
Soldatova, Professor L
Researcher Co-Investigators:
Dr O Orhobor
Project Partners:
Chalmers University of Technology
Department: Chemical Engineering and Biotechnology
Organisation: University of Cambridge
Scheme: Standard Research
Starts: 01 October 2021 Ends: 31 May 2023 Value (£): 302,752
EPSRC Research Topic Classifications:
Artificial Intelligence Control Engineering
Design Engineering
EPSRC Industrial Sector Classifications:
Related Grants:
Panel History:
Panel DatePanel NameOutcome
01 Jul 2021 Transformative Healthcare Technologies Full Proposals 2nd Call Announced
Summary on Grant Application Form
Artificial Intelligence (AI) is transforming the world. AI is the core technology of many of the biggest companies in the world, Amazon, Google, Facebook, etc. that effect all our lives. AI is now starting to transform science and technology.

Most people in the EU now live better than Kings did in the past: they have better food, medical care, transport, etc. This miracle has been made possible through better technology based on science. To meet the great challenges the 21st century world faces: climate change, food insecurity, disease, etc., we need to make science and technology even more efficient.

We propose the AMBITION project to harness the power of AI and laboratory robotics to provide researchers in the UK, and beyond, with continuous, uninterrupted, remote access to AI/robotic augmented biomedical research capabilities.

This will enable more robust, efficient and reproducible biomedical research. The UK's life sciences, biotechnological and pharmaceutical industry are world-leading. However, the Covid-19 pandemic has clearly demonstrated the vital importance of biomedical research and the critical need to maintain research continuity at all times. Yet, lockdowns and social distancing pose a severe threat to research continuity, forcing laboratories to shut down, risking loss of years of research. Integrating AI with laboratory automation will also enable the automation of routine parts of scientific theory formation and experimentation. This will enable results to be obtained both more efficiently and faster compared to the state-of-the-art where human scientists must make all the decisions. AMBITION does not aim to replace humans, but empower them by reasoning and data processing capabilities to better support their decision making.

Biomedical science is facing a 'reproducibility crisis'. Despite reproducibility being fundamental to science, the reproducibility of few biomedical results is currently tested, and when reproducibility is tested, the results are dismal, with only 10 to 20% of published biomedical research found to be reproducible. Finally, automated laboratories will make scientific results more reproducible, as AI systems describe experiments in more clearly than human scientists, and robots execute experimental protocols more accurately than human scientists.

The project will focus on the development of the AI part of the system and iterative testing in real-world laboratory settings employing state-of-the-art robotics equipment. We will initially focus on cancer drug discovery as a first demonstration case, bringing together the power of AI and laboratory robotics.

In the medium-term (3-5 years horizon). We plan to extend the approach to clinical patient care, and to provide real-time cancer treatment decision support system for patients in the UK and beyond based on automated testing of hundreds of treatment options on patient-derived tumour material, thereby leading to a reduction in animal experimentation, and giving clinicians an evidence-based, real-time input for their expert treatment decision.

In the long-term (5-15 years horizon) we will rollout automated research capabilities and real-time treatment guidance across all of biomedicine, especially fields such as antibiotic treatment/ antimicrobial resistance, inflammatory diseases, etc.

In 30 years, autonomous laboratories will transform the health sector. They will lower the costs of laboratory experiments, augment researchers' technical capabilities (making more elaborate and complex tests possible), reduce the risks associated with the presence of humans in the labs (working with hazardous substances, risk of infections), ensure reproducibility, increase accuracy of results, and ensure overall accountability and trust in the process. Autonomous laboratories will speed up and scale up the development of new drugs, remote testing of patients, and will be an enabler for personalised medicine.
Key Findings
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