O DIGITAL CHEMISTRY, WHERE ART THOU?
To emerge from the time of alchemy, where the transformation of matter from one form into another was seen as an art or magic, a new abstraction and theory of matter had to be developed for modern chemistry to emerge. This abstraction led to relative atomic weights, and in turn allowed chemists to explore chemical reactions by elucidating the reaction stoichiometry. For this to happen chemistry had to be standardised and this needed a new theory, atomic theory, and suddenly reactivity, new reactions, and the ability to build complex molecules was possible. But the standards were not just theoretical, the acceleration of practical chemistry was vastly aided by the development of standardised glassware and in the 1900s this found its way into schools, undergraduate laboratories, research laboratories and industry alike. Chemistry as a field was transformed and arguably without standardised laboratory glassware, this transformation would not have happened.
Fast forward to today, and everyone seems to be claiming that digital chemistry centres on the use of machine learning or other statistical magic to invent new molecules in-silico or interpret reaction data. However, the use of machine learning in chemistry today is hindered by the lack of a digital-chemical standard approach to practical experiments. It is akin to alchemists using standardised glassware without atomic theory. Therefore, the digitization of chemistry is not simply about using machine learning or artificial intelligence systems to process chemical data, nor the development of ever more capable automation hardware; instead, digital chemistry requires the creation of a hard link between an abstracted process ontology of chemistry and bespoke hardware for performing reactions or exploring reactivity.
Chemical digitization is therefore about the unambiguous development of an architecture, a chemical state machine, that uses this ontology to connect precise instruction sets to hardware that performs chemical transformations. This approach enables a universal standard for describing chemistry procedures via a chemical programming language and facilitates unambiguous dissemination of these procedures. I predict this standard will revolutionize the ability of chemists to collaborate, increase reproducibility and safety, as we all as optimise for cost and efficiency, but it won’t be easy. This is because, unlike in molecular biology where the synthesis of proteins is controlled by genomic data, chemistry is not intrinsically digital and hence there are many ways that digitization could be achieved.
Through the invention of DigitalGlassware™, DeepMatter is helping in the quest to develop a new standard not only in recording manual reactions, but allowing the digital collaboration, establishing ways to record and structure data so that the context can be later used for the development of insights. Not only will this lead to reproducibility, but more importantly for reliability and therefore for faster development and dissemination. The future for chemistry is digital, but the infrastructure must be created so that chemists don’t miss out. I’m proud to have founded DeepMatter and helped invent DigitalGlassware™, and I’m excited how we can help modern day chemists avoid a fuzzy era of machine learning alchemy.
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Heading back to the lab in the New Year?
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