The ultimate manifestation of the Chemputer^® (chemical computer) is a system able to synthesise a molecule in a completely automatic way (without any human intervention). Ask the Chemputer^® to produce a sample of a given molecule, come back a few days later, and get a sample of the molecule you requested, produced in total autonomy by the Chemputer^® with high yield and purity. The Chemputer^® will enable fast discovery of new molecules and development of cost-effective and sustainable processes to produce these molecules. The economic, societal and environmental impact of such a technology is obviously immense.

The Chemputer^® will be composed of several parts:

• Data, to power predictive and prescriptive Machine Learning algorithms
   
• Software, (including machine learning algorithms), that designs experiments, controls the hardware to run the experiments and processes the data produced by the experiments
   
• Hardware, to perform chemistry experiments (by executing machine-readable code) and measure their outcome

As of today, deepmatter^® already has a strong technology base, protected by granted patents, that is precursor for full Chemputation. That technology comprises:

• Synthetic accessibility scoring, allowing to estimate how easy/difficult a molecule will be to synthesise
   
• Synthetic route design (retrosynthesis), suggesting a several putative synthetic routes for a given molecule, with the ability to filter these routes based on criteria including the price of chemicals or their sustainability
   
• Database searches, to identify previous instances of a given reaction
   
• Bayesian optimisation to find optimal reaction parameters within a design space chosen by the user, either in open-loop (with intervention of a human to run the suggested experiments) or in closed-loop (fully automated)
   
• Rich data collection (including recipes, time-course data collected by sensors and events), allowing to build more accurate machine learning models and better data analysis
   
• Algorithms that generate machine-readable code to enable robotic control
   
• A proprietary data set of several millions of chemical reactions, powering deepmatter^®’s machine learning algorithms

The fact that we are able to automatically perform retrosynthetic analysis and that we have already performed closed-loop optimisation of chemical reactions, in batch and continuous reactors, is a demonstration that the Chemputer^® will become a reality in the coming years. 

However, we have not yet achieved true and complete Chemputation. We are working hard on it and have several important milestones ahead of us:

• At the end of each experiment, feed back the data to the reaction database so that it gets used during further retrosynthetic analyses, thus augmenting them
• Wider automation capabilities, including lab orchestration and integration of more robotic hardware
• Integration of more analytical equipment (online and offline)
• Integration with common Electronic Lan Notesbooks (ELNs)
• Inventory management
• Account for sustainability for predictions/suggestions
• And many more..

Stay tuned for news about our progress towards the Chemputer^®. If you want to be part of that journey and join our industrial and academic partners, please contact our team of experts.

“CHEMPUTER” is a registered trademark of deepmatter^®