Chemobots: Digital-Chemical-Robotics to Convert Code to Molecules and Complex Systems

Lead Research Organisation: University of Glasgow
Department Name: School of Chemistry


Our aim is to develop an approach to make and discover molecules using a chemical programming language that is run in a modular Chemical-Robot or Chemobot. To do this we need to develop a 'Universal Chemical Synthesis Machine' architecture which we will refer to here as 'the Chemputer'. The Chemputer represents a new architecture for running chemical synthesis, and will be realised by the development of a portable and modular approach to chemistry. To do this we must establish the ontological relationships and abstractions to allow the development of a code that will drive machine-independent universal synthesis. This ontology will connect a high-level chemical programming language we will develop to the low-level machine code to run the modular Chemobots. The Chemobots will be designed and built around batch 'flask' synthesis and can be networked together allowing the molecules to be made in steps.

By establishing the framework and building the underlying firmware, software, and abstractions, we will demonstrate the Chemputer by developing modular robots capable of chemistry, Chemobots. These will be built around batch 'flask' synthesis and can be networked together allowing the molecules to be made discretely in steps. Although synthetic chemistry is complex and demanding, a chemical reaction only requires five operations: i) addition of reagents; ii) reaction process; iii) work-up; iv) separation; v) purification. We will take our Chemputer standard, comprising five modules for batch operations, and enlist our expert pioneer collaborators and industrial stake holders, to test and validate our approach. Importantly, we have already validated the concept of chemical digitization, and the platform approach highlighted by our recent publications in Science and Nature earlier this year. Also, this work builds on our previous programme grant 'digital-synthesis' in terms of our technical abilities to build platforms and write software. However, the vision of the Chemputer architecture represents a step change, resulting in practical Chemobots. We will use the systems of modular Chemobots to also explore reproducibility, and to improve the environment for the chemist from a workflow, safety, and pedagogical point of view. In addition, the ability to individually validate and digitize reactions one by one should allow for the ability to synthesize very complex molecules autonomously as the stability and usability of the systems improve. We will start using our preliminary platform as a 'generation 0' to enable the development of the abstraction, architecture, and ontologies for digital chemistry. As the Chemobots are developed we will explore new reactions using sensors and statistics driven design of experiments to target unknown molecules with target-assay driven search algorithms.

Planned Impact

This programme will translate the technological developments into scientific and industrial impact by delivering on the following aims:

Establishing the Chemputer architecture standard as the route by which chemistry can be digitized and automated with Chemobots, maintaining compatibility with current academic and industry research standards. We will define the Technology Readiness Levels of our Chemobot generations and identify and prioritise future opportunities, especially within the context of Dial-A-Molecule and Digital Chemistry Roadmap.

Ensure uptake of the Chemputer standard and the Chemobots initially in collaboration with our five industrial and five academic pioneer partners; we will install Chemobots within each of their laboratories (10 in total) which will be upgraded during the lifetime of the grant (see below).

Beyond our partners, we will facilitate uptake of the Chemputer and Chemobots both within our established network of academic and industrial partners, translational organisations and manufacturing research centres, and by new partners engaged through workshops and other work of the Impact Champion.

Utilize the flexibility of the Programme Grant scheme, and its particular scope for exchange visits and multi-disciplinary problem-solving, as a career development vehicle for staff at all levels, but emphasising the postdoctoral researcher cohort.

Digital technologies have a high profile in the media, and we will exploit this by detailing our research in mass audience media as often as possible. We have an excellent track record of public engagement having featured in media such as CNN, TED, The Guardian, and on popular science TV programmes. We will also hold local outreach events at schools and host school children for short internships within the Cronin Group.

The major Path to impact for this grant will be establishing a unique 'Pioneer Programme' where up to 12 academic groups and industrial project partners will be provided with the hardware modules, full schematics, instructions, software, and the expertise necessary to build Chemobot platforms for practical use in their own labs. This programme will be vital to the impact achieved through this grant. These pioneers will have privileged access to the robotic platforms produced during this research and will provide a feedback mechanism to ensure that the developing the capability, in conjunction with software / hardware architectures are capable of addressing real chemical challenges. The pioneers will receive Chemobot platforms from generation 1, ready around 24 months into the programme. Direct interaction with the pioneer participants will take the form of an initial workshop around month 24 to introduce the Chemobot systems, giving training and initial set up advice, followed by 4-monthly meetings to track progress. The other two pioneer workshops (held concurrently with our annual conference) will be at 36 and 48 months to allow dissemination of subsequent generations and for the pioneers to exchange experience, best practice and to feedback. Working closely with the pioneers, including funding secondments of our RAs to the pioneers, we will ensure that the impact of our work is immediate. We will disseminate our work as widely as possible through publication in high impact, interdisciplinary journals, in collaboration with the pioneers' groups. Engagement with companies through the pioneer programme will also allow us to make a road map developing Chemobot systems into a new, open standard for laboratory scale chemical robotics. The pioneer companies will be able to 'embed' researchers in the team for collaborative workshops / projects as well as allowing some of our team to second to industrial sites to develop Chemobot systems in industrial settings with training and knowledge exchange.


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Gromski P (2019) How to explore chemical space using algorithms and automation in Nature Reviews Chemistry

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Surman AJ (2019) Environmental control programs the emergence of distinct functional ensembles from unconstrained chemical reactions. in Proceedings of the National Academy of Sciences of the United States of America

Title The Chemputer 
Description A universal modular robotic synthesiser which can undertake ca. 60% of the batch reactions in the chemical literature. This also includes the XDL language and ontology for translating chemical procedures into universally readable actionable code which can potentially be implemented in any robotic system. 
Type Of Material Improvements to research infrastructure 
Year Produced 2017 
Provided To Others? Yes  
Impact 19 News outlets have reported on this discovery. Plans are underway to setup a spinout and patent aspects of the discovery. 
Description Chemobots Program Grant 
Organisation University of Cambridge
Country United Kingdom 
Sector Academic/University 
PI Contribution In this project new sensors have been developed and incorporated into devices to detect and follow the evolution of droplets in a robotic platform. The platform also allowed us to demonstrate the effectiveness of algorithm-driven discovery and crystallization of new polyoxometalate clusters by pitting Humans against Robots. Machine learning is already changing the world but has barely impacted chemistry. Now we have shown that the use of machine learning can dramatically improve the exploration of a crystallization space as well as improving prediction accuracy and minimizing the time needed to search for good crystals. The effectiveness of our approach has been demonstrated by the discovery and crystallisation of a new polyoxometalate cluster, Na6[Mo120Ce6O366H12(H2O)78]· 200H2O which has a trigonal-ring type architecture. This compound features a dodecameric ring with an inner diameter of 17 Å and an outer of 31 Å. Our research shows that humans are inconsistent in their exploration, following different strategies depending on their own perceptions and biases, and that robots can explore more chemical space than humans including the boundaries of the crystallisation space,.
Collaborator Contribution Alexei Lapkin [AL] is a Professor in Sustainable Reaction Engineering with interests in machine learning for process optimisation, sustainable manufacturing and clean chemical synthesis.He has recently demonstrated for the first time the direct application of mechanistic models for in silico process design and optimisation and the use of model-based design of experiments in self-optimisation. The Lapkin group will apply these models to Chemobots initially by further investigating the behaviour of droplets to fully understand and reproduce their complex behaviours.
Impact Too early presently. Manuscripts in preparation and experiments are being carried out.
Start Year 2019