Efficiency by Design:  Optimisation in Process Research

Abstract

Experimental design (Box, G. E. P.; Hunter, W. G.; Hunter, J. S. Statistics for Experimenters; Wiley: New York, 1978 and Carlson, R. Design and Optimisation in Organic Synthesis; Elsevier: Amsterdam, 1992) is an established and proven methodology for product and process improvement in the pharmaceutical industry. This paper presents a step-by-step approach to optimisation of a synthetic transformation using a central composite experimental design, in conjunction with automated on-line HPLC. Highly predictive models for the reaction were obtained using a commercially available software package. [There are many commercially available DOE packages. The software package we used was Design-Expert 5 (DX-5) ().] These mathematical models were interrogated to examine the effect on yield and quality under a variety of reaction conditions or constraints. The synergy of experimental design and automation is also discussed.

Aryl–Aryl Bond Formation by the Fluoride‐Free Cross‐Coupling of Aryldisiloxanes with Aryl Bromides

“…[44] The preliminary study outlined above suggested that cross-coupling reactions involving aryldisiloxanes are affected by many variables; thus a traditional systematic optimisation process would be expected to be an extremely lengthy endeavour. [44] In addition, optimisation using a traditional approach is known to provide only a partial exploration of the overall "reaction space" (the full range of all the H NMR spectroscopic analysis of the isolated mixture of 17 and the corresponding homocoupled product after flash column chromatography. NA = no evidence for formation of the desired product by LCMS and 1 H NMR spectroscopic analysis of the crude reaction mixture.…”

Online quantitative mass spectrometry for the rapid adaptive optimisation of automated flow reactors

“…Traditionally, statistical experiments require full randomization to eliminate systematic errors that can create bias in the results. [11] However, we have found that waiting for heating and cooling of the reactor is the biggest contributor to the total optimization time, and that randomization did not lead to any difference in experimental results. Therefore it was decided that a higher intensification of experiments could be achieved with ascending ordering of temperature.…”

Efficient and cost‐effective experimental determination of kinetic constants and data: the success of a Bayesian systematic approach to drug transport, receptor binding, continuous culture and cell transport kinetics

“…This a three-step approach still using the Baye- The Utility values for each design are also compared. Four di¡erent kinetic systems are compared: cell transport [3], continuous culture [7], drug transport [8] and receptor binding [9].…”