Organic & Biomolecular Chemistry The Application of Design of Experiments (DoE) Reaction Optimisation and Solvent Selection in the Development of New Synthetic Chemistry Journal: Organic & Biomolecular Chemistry Manuscript ID OB-REV-09-2015-001892.R1 Article Type: Review Article Date Submitted by the Author: 26-Nov-2015 Complete List of Authors: Murray, Paul; Paul Murray Catalysis Consulting Ltd, Bellany, Fiona; University College London, Department of Chemistry Benhamou, Laure; CNRS, Laboratoire de Chimie de Coordination Bucar, Dejan-Kresimir; University College London, Department of Chemistry Tabor, A; University College London, Department of Chemistry Sheppard, Tom; University College London, Department of Chemistry Page 1 of 11 OrganicPlease & Biomoleculardo not adjust margins Chemistry Organic & Biomolecular Chemistry ARTICLE The Application of Design of Experiments (DoE) Reaction Optimisation and Solvent Selection in the Development of New Received 00th January 20xx, Synthetic Chemistry Accepted 00th January 20xx a b b b b DOI: 10.1039/x0xx00000x Paul M. Murray, * Fiona Bellany, Laure Benhamou, Dejan-Krešimir Bučar, Alethea B. Tabor and Tom D. Sheppard b* www.rsc.org/ This article outlines the benefits of using ‘Design of Experiments’ (DoE) optimisation during the development of new synthetic methodology. A particularly important factor in the development of new chemical reactions is the choice of solvent which can often drastically alter the efficiency and selectivity of a process. Whilst solvent optimisation is usually done in a non-systematic way based upon a chemist’s intuition and previous laboratory experience, we illustrate how optimisation of the solvent for a reaction can be carried out by using a ‘map of solvent space’ in a DoE optimisation. A new solvent map has been developed specifically for optmisation of new chemical reactions using principle component analysis (PCA) incorporating 136 solvents with a wide range of properties. The new solvent map has been used to identify safer alternatives to toxic/hazardous solvents, and also in the optimisation of an S NAr reaction. Important factors which can facilitate uptake of a particular Introduction – Why use DOE? reaction include: readily available reagents/catalysts; a wide The development of new synthetic methodology is a key part substrate scope; good functional group compatibility; mild of academic chemistry research, focusing both on the conditions; efficiency; sustainability and a good safety profile. discovery of intrinsically novel reactions, as well as the However, such factors are rarely taken into account during the identification of improved methods for carrying out existing development of new chemistry. As noted by industrial 1 transformations. Developments made in this area can researchers, many synthetic methodology papers fail to ultimately determine which molecules are deemed to be adequately explore the substrate scope of a new reaction and ‘accessible enough’ to be suitable for a wide range of practical instead focus on reactions of largely unfunctionalised lipophilic applications, including pharmaceuticals, agrochemicals, compounds. Furthermore, despite the fact that well polymers and other functional materials, flavours/fragrances, established statistical methods for reaction optimisation are 2-3 biological probes, etc. The importance of new synthetic widely used in industry, the uptake of these methods has 4-5 methodology has been recognised by the award of several been very low in academic chemistry. Often, the Nobel prizes in recent years for the development of ‘optimisation’ process proceeds entirely via a trial and error synthetically important reactions (asymmetric catalysis; approach involving the variation of one factor at a time (e.g. metathesis; cross-coupling). These reactions have not only solvent, temperature, catalyst, concentration, etc). This type of been used extremely widely by chemists in both academia and process can lead to researchers failing to identify ‘optimal’ industry, but have even played a significant role in dictating conditions for a particular process if interactions between two 6 which molecules are employed in many of the above or more factors are present. Thus, an attempt to optimise applications. even two factors via a ‘one variable at a time’ (OVAT) approach The uptake of novel synthetic methodology by researchers can fail to find the optimum conditions if interactions between in industry and in other scientific fields is much more likely if the factors are present (in Fig. 1). For example, initial the chemistry can be demonstrated to be ‘user friendly’. optimisation of an imaginary reaction via variation of the number of equivalents of reagent and the temperature involves variation of the first variable whilst keeping T=40. This suggests that 2 equivalents of reagent give the ‘best yield’. a. Paul Murray Catalysis Consulting ltd; 67 Hudson Close, Yate,BS37 4NP, UK. E-mail: [email protected] . Subsequent variation of the temperature whilst keeping eq=2 b. Department of Chemistry, University College London, 20 Gordon St, London, suggests that the optimum conditions are T=55, Eq=2. WC1H 0AJ, UK.; Tel: +44 20 7679 2467; E-mail: [email protected] Electronic Supplementary Information (ESI) available: Principle component values However, due to interaction between the factors this fails to for the new PCA solvent map, experimental procedures, spectroscopic data and 1H identify the true optimum conditions where a higher yield of and 13 C NMR spectra. See DOI: 10.1039/x0xx00000x This journal is © The Royal Society of Chemistry 20xx J. Name ., 2013, 00 , 1-3 | 1 Please do not adjust margins OrganicPlease & Biomoleculardo not adjust margins Chemistry Page 2 of 11 ARTICLE Organic & Biomolecular Chemistry product can be obtained using smaller quantities of reagent the use of DoE for reaction optimisation in projects carried out (T=105, Eq=1.25). This is a consequence of the fact that the full in collaboration with industrial partners. 5 reaction space has not been explored and at no-point was the This pitfall shown in Figure 1 can readily be avoided using a combination of high T/low eq considered. true DoE approach in which each vertex of reaction space is explored. In combination with a ‘centre point’ experiment this 3.5 is then used to evaluate the full multi-dimensional reaction space in order to determine where the highest yield can be 3 Optimum obtained (Fig. 2). This provides a great deal more information 2.5 about the behaviour of the reaction from a similar (or Best at T=40 2 potentially smaller) number of experiments than the traditional approach. The DoE study uses standard statistical 1.5 T=40 techniques to model the effect of each variable (and potential 1 interactions between variables) on the reaction outcome. A further benefit of the statistical approach, is that it can provide 0.5 Eq=2 Reagent Equivalents (eq) a built-in ‘cross-check’ of each of the individual screening 0 reactions, enabling any anomalous results to be readily -45 5 55 105 "False identified. In the traditional OVAT approach, repetition of each Optimum" Temperature (T) experiment is advisable to ensure reproducibility, or the entire ‘optimisation’ could be led astray by a single anomalous result. Fig. 1 The pitfalls of traditional ‘one variable at a time’ (OVAT) optimisation Optimisation of New Synthetic Methodology 4.5 Most new synthetic methodology development projects 4 begin with an initial discovery (by design or by serendipity) of 3.5 Optimum reaction conditions which provide the desired product in 3 moderate yield (Table 1). This is then usually followed by an 2.5 Expt 1 optimisation phase in which the yield of a single reaction is 2 Expt 2 improved by variation of a variety of parameters. This is often 1.5 extremely time consuming, as many different factors may Expt 3 1 need to be explored in order to provide good yields of the Expt 4 desired product from a representative substrate. Assuming Reagent Equivalents (eq) 0.5 experiments are performed only at high/medium/low values 0 Expt 5 of each factor, this requires three experiments for each factor -20 30 80 130 investigated. Once ‘optimised’ conditions are identified, they Temperature (T) are then applied to a selection of substrates. This makes the assumption, however, that the optimised conditions for one Fig. 2 A DoE study covering the entire reaction space will not miss substrate will also be the best conditions for other compounds the optimum conditions provided it lies within the space covered. studied. This inherently leads to the selection of substrates The technique of ‘Design of Experiments’ is a statistical which are ‘similar’ to the initial one, frequently meaning that 1 approach to reaction optimisation that allows the variation of largely unfunctionalised/lipophilic molecules are explored. multiple factors simultaneously in order to screen ‘reaction More ‘difficult’ examples (functional groups, polar molecules, space’ for a particular process. Importantly, this enables the sterically hindered compounds) are avoided as they do not evaluation of a large number of reaction parameters in a work well under the ‘optimised conditions’, though in fact they relatively small number of experiments. Whilst this technique may simply require modification of the conditions in order to is routinely applied by process chemists in a wide range of give a good yield of the product. industries, and also by academics working in engineering By switching