The project aims to take a critical look at our current state-of-the-art robotic and automated systems used for the chemical synthesis of pharmaceutical and agrochemical molecular targets. The project will involve organic synthesis and catalysis on a day to day basis, assessing how robotic systems can aid and assist reaction optimisation and discovery.
Sign up for our launch event on Tuesday 20 June 2 - 3pm UK time
Background. The principal motivation for the ALBERT mini-CDT is to develop the science, engineering, and socio-technology that underpins the building of a laboratory-based robotic system for use in applied experiments across the physical sciences. Automated laboratory experiments are revolutionizing the way that we conduct synthetic organic chemistry, from a productivity, performance and efficiency perspective. Creating a Chemistry-based eco-system that is cleaner, greener, safer, and cheaper than anything achievable by current conventional techniques and technologies, is a key driver for this research.
In this project we would like to take a critical look at our current robotic and automated systems in operation with a Chemistry research environment. How can we improve our approaches, workflows and systems for the betterment of organic synthesis and catalysis?
Objectives.
The following objectives are provided. We anticipate these evolving during the project.
● Examine the design of current robotic / automated systems – take a step back – to deduce whether we are already in an optimized space, or as is more likely, in a ‘what works’ space.
● To examine sustainable catalytic chemical reactions (with a focus on earth abundant metal catalysts and organocatalysts) and fully assess workflow procedures, processes and how they segway into downstream data analyses.
● To determine feasible adaptions that can be made to current robotic / automated systems, with accessibility and ease of use as key drivers.
Experimental Approach
The research employs a robotic reaction screening platform (Chemspeed), linked to instrumentation enabling data from a given reaction to be gathered (e.g. HPLC, LC-MS, IR). The ability to vary multiple reaction variables such as temperature and concentration, while gathering information (mechanistic) in tandem, provides rich data that can be harnessed, aiding optimisation of academically and industrially valuable reactions. The robotic platform allows target compounds to be synthesised in the most efficient and sustainable way, minimising side product formation while also allowing new transformations (discovery) to be fully scoped-out. The research will require synthetic chemistry experimental expertise, practical know how and a deep interest in employing a high-instrumented approach to solving challenging synthetic problems. The successful candidate will have a strong interest in data analysis and machine learning techniques although previous experience is not necessary (full training will be given).
Novelty
Unlocking the true potential of any given chemical transformation is dependent on high-quality reaction data (i.e. outcomes, reproducibility and sensitivities) and its examination by multi-variate data analyses. These data can be fed back, refined, and tested in iterative cycles, enabling reaction improvement and the ultimate prediction of reaction outcomes – the ‘holy-grail’ in chemical synthesis. We expect novelty in detailed reaction understanding and/or new reaction discovery.
Training
The project will be led by Ian Fairlamb and supported by colleagues (co-supervisors) from Chemistry (Charlotte Willans), Mathematics (Jessica Hargreaves) and Sociology (Darren Reed). Each provide unique, complementary expertise and skills that are key to delivering this ambitious project. From rigorous mechanistic understanding of pharma-relevant catalysis, automated synthesis and rich data analysis, medicinal chemistry-related methodology, assessment of reaction outcome data through to statistical analysis. Moreover, the sociological context of how the robotic systems are interacting with chemists will be examined – are we doing this in the right way and are there any interactions that we are missing out on?
There will be cohort-based training for the ALBERT mini-CDT, where other students working on related projects (across a range of York-based Departments) will meet to exchange ideas, solve problems and discuss alternative ways to improving automated laboratory experiments going-forwards.
Our current in-lab Chemspeed ISYNTH robotic system enables automated reaction screening and monitoring (full-training will be provided by a dedicated highly trained research technician). We will further provide full training in Principal Component Analysis and other data analysis tools. The team have supervised well >40 PhD students to completion. High quality, supportive and inclusive mentoring will be given, and the student will be involved in all of our research activities.
Given the increasing number of job opportunities in Industry in data science and automated reaction optimisation, we believe that the graduated PhD candidate will be placed well, moreover will have the chance to grow their future careers in this space.
What is ALBERT?
Doctoral Training in Autonomous Robotic Systems for Laboratory Experiments
A cohort of students will be part of a mini, pilot Centre for Doctoral Training (CDT) focused on developing the science, engineering, and socio-technology that underpins building robots required for laboratory automation, e.g. in chemistry and related sciences. The first cohort will begin their PhD projects in 2023, and the second cohort in 2024. Albert represents an autonomous robot that conducts laboratory experiments that are cleaner, greener, safer, and cheaper than anything achievable with today's conventional techniques and technologies. Developing Albert offers significant socio-technical problems for science, engineering, social sciences, and the humanities. The YorRobots Executive and the Institute for Safe Autonomy will provide international leadership for this research area.
When completing your application form, please select CDT Autonomous Robotic Systems for Lab Experiments from the drop down menu for How will your studies be funded?
The Department of Chemistry holds an Athena SWAN Gold Award and is committed to supporting equality and diversity for all staff and students. The Department strives to provide a working environment which allows all staff and students to contribute fully, to flourish, and to excel: https://www.york.ac.uk/chemistry/ed/
This PhD will formally start on 1 October 2023. Induction activities may start a few days earlier.
To apply for this project, submit an online PhD in Chemistry application: https://www.york.ac.uk/study/postgraduate/courses/apply?course=DRPCHESCHE3