Tools for Synthesis Planning, Automation, and Analytical Data Analysis.

Computer-aided synthesis design, automation, and analytics assisted by machine learning are promising resources in the researcher's toolkit. Each component may alleviate the chemist from routine tasks, provide valuable insights from data, and enable more informed experimental design. Herein, we highlight selected works in the field and discuss the different approaches and the problems to which they may apply. We emphasize that there are currently few tools with a low barrier of entry for non-experts, which may limit widespread integration into the researcher's workflow.

Standardization and Control of Grignard Reactions in a Universal Chemical Synthesis Machine using online NMR.

A big problem with the chemistry literature is that it is not standardized with respect to precise operational parameters, and real time corrections are hard to make without expert knowledge. This lack of context means difficult reproducibility because many steps are ambiguous, and hence depend on tacit knowledge. Here we present the integration of online NMR into an automated chemical synthesis machine (CSM aka. "Chemputer" which is capable of small-molecule synthesis using a universal programming language) to allow automated analysis and adjustment of reactions on the fly. The system was validated and benchmarked by using Grignard reactions which were chosen due to their importance in synthesis. The system was monitored in real time using online-NMR, and spectra were measured continuously during the reactions. This shows that the synthesis being done in the Chemputer can be dynamically controlled in response to feedback optimizing the reaction conditions according to the user requirements.

Fine-tuning the nucleophilic reactivities of boron ate complexes derived from aryl and heteroaryl boronic esters.

Boron ate complexes derived from thienyl and furyl boronic esters and aryllithium compounds have been isolated and characterized by X-ray crystallography. Products and mechanisms of their reactions with carbenium and iminium ions have been analyzed. Kinetics of these reactions were monitored by UV/Vis spectroscopy, and the influence of the aryl substituents, the diol ligands (pinacol, ethylene glycol, neopentyl glycol, catechol), and the counterions on the nucleophilic reactivity of the boron ate complexes were examined. A Hammett correlation confirmed the polar nature of their reactions with benzhydrylium ions, and the correlation lg k(20 °C)=sN (E+N) was employed to determine the nucleophilicities of the boron ate complexes and to compare them with those of other borates and boronates. The neopentyl and ethylene glycol derivatives were found to be 10(4) times more reactive than the pinacol and catechol derivatives.

An integrated self-optimizing programmable chemical synthesis and reaction engine.

Robotic platforms for chemistry are developing rapidly but most systems are not currently able to adapt to changing circumstances in real-time. We present a dynamically programmable system capable of making, optimizing, and discovering new molecules which utilizes seven sensors that continuously monitor the reaction. By developing a dynamic programming language, we demonstrate the 10-fold scale-up of a highly exothermic oxidation reaction, end point detection, as well as detecting critical hardware failures. We also show how the use of in-line spectroscopy such as HPLC, Raman, and NMR can be used for closed-loop optimization of reactions, exemplified using Van Leusen oxazole synthesis, a four-component Ugi condensation and manganese-catalysed epoxidation reactions, as well as two previously unreported reactions, discovered from a selected chemical space, providing up to 50% yield improvement over 25-50 iterations. Finally, we demonstrate an experimental pipeline to explore a trifluoromethylations reaction space, that discovers new molecules.

Enterovirus 71-Associated Infection in South Vietnam: Vaccination Is a Real Solution.

Hand-foot-and-mouth disease (HFMD) is the most common enteroviral infection in South-East Asia. When evaluating the role of enterovirus 71 (EVA71) as an etiological agent of infectious disease in South Vietnam, we revealed a high proportion of EVA71 among identified species A enteroviruses found in 3542 samples from HFMD cases; 125 samples from cases of enteroviral meningitis; and 130 samples from acute flaccid paralysis (AFP) cases. These represent 50%, 54.8%, and 51.5%, respectively. According to molecular analysis, 90% of EVA71 were attributed to genotype C4 and 10% were attributed to genotype B5. The predominance of EVA71 circulation among the population proves the need to strengthen surveillance (with monitoring of enterovirus circulation for facilitation of HFMD outbreak prediction) and to increase the effectiveness of preventative measures by the implementation of vaccination against EVA71-associated infections. A phase III trial of a Taiwanese vaccine (EV71vac) in Taiwan and South Vietnam showed its safety, tolerability, and efficacy in children aged 2-71 months. This B4 genotype-based vaccine, which features cross-protection against B5 and C4 genotypes, and other existing EV71 vaccines can serve as a good approach to solving the HFMD problem, which is so important for Vietnam.

Digitization and validation of a chemical synthesis literature database in the ChemPU.

Despite huge potential, automation of synthetic chemistry has only made incremental progress over the past few decades. We present an automatically executable chemical reaction database of 100 molecules representative of the range of reactions found in contemporary organic synthesis. These reactions include transition metal-catalyzed coupling reactions, heterocycle formations, functional group interconversions, and multicomponent reactions. The chemical reaction codes or χDLs for the reactions have been stored in a database for version control, validation, collaboration, and data mining. Of these syntheses, more than 50 entries from the database have been downloaded and robotically run in seven modular chemputers with yields and purities comparable to those achieved by an expert chemist. We also demonstrate the automatic purification of a range of compounds using a chromatography module seamlessly coupled to the platform and programmed with the same language.

Chemputation and the Standardization of Chemical Informatics.

The explosion in the use of machine learning for automated chemical reaction optimization is gathering pace. However, the lack of a standard architecture that connects the concept of chemical transformations universally to software and hardware provides a barrier to using the results of these optimizations and could cause the loss of relevant data and prevent reactions from being reproducible or unexpected findings verifiable or explainable. In this Perspective, we describe how the development of the field of digital chemistry or chemputation, that is the universal code-enabled control of chemical reactions using a standard language and ontology, will remove these barriers allowing users to focus on the chemistry and plug in algorithms according to the problem space to be explored or unit function to be optimized. We describe a standard hardware (the chemical processing programming architecture-the ChemPU) to encompass all chemical synthesis, an approach which unifies all chemistry automation strategies, from solid-phase peptide synthesis, to HTE flow chemistry platforms, while at the same time establishing a publication standard so that researchers can exchange chemical code (χDL) to ensure reproducibility and interoperability. Not only can a vast range of different chemistries be plugged into the hardware, but the ever-expanding developments in software and algorithms can also be accommodated. These technologies, when combined will allow chemistry, or chemputation, to follow computation-that is the running of code across many different types of capable hardware to get the same result every time with a low error rate.

A universal system for digitization and automatic execution of the chemical synthesis literature.

Robotic systems for chemical synthesis are growing in popularity but can be difficult to run and maintain because of the lack of a standard operating system or capacity for direct access to the literature through natural language processing. Here we show an extendable chemical execution architecture that can be populated by automatically reading the literature, leading to a universal autonomous workflow. The robotic synthesis code can be corrected in natural language without any programming knowledge and, because of the standard, is hardware independent. This chemical code can then be combined with a graph describing the hardware modules and compiled into platform-specific, low-level robotic instructions for execution. We showcase automated syntheses of 12 compounds from the literature, including the analgesic lidocaine, the Dess-Martin periodinane oxidation reagent, and the fluorinating agent AlkylFluor.