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This paper explores how changes in genetics, database, high-throughput screening and bioinformatics technologies have allowed pharmaceutical firms to exploit economies of scale in experimentation. Traditional craft-based, sequential experimentation in chemistry and biology has been complemented by firstly, the automated, mass-production analysis of populations and secondly, by 'in silico' experimentation using simulations and databases. The changes are analysed within a Chandlerian framework that highlights how increases in the 'throughput' of R&D are dependent on organizational and managerial responses to systemic uncertainty.