Competitive Workflow: novel software architecture for automating drug design

As industrialization of laboratory processes for drug discovery continues to gather momentum, the bottleneck has moved toward exploitation of this tide of information to enable better quality decisions. The development of information-management systems to automate data and materials management can have a positive impact on productivity, as can increasingly sophisticated computer-aided molecular design approaches. However, as long as key decisions can only be taken by a small number of expert individuals working in a complex social environment, the impact of such innovations will be limited. This review describes Competitive Workflow, a distributed multi-agent system explicitly designed for the automation of decision making, currently the preserve of the expert. The approach builds on workflow architectures that capture best practice in information processing, but aims to extend these to model the tacit knowledge of the expert in the selection of alternative pathways through the workflow. The review also discusses recent developments in related workflow-management systems, particularly for information management and processing services front multiple sources, as well as distributed multi-agent approaches. A specific implementation of Competitive workflow--the Discovery Bus--and its application to meta-quantitative structure-activity relationship analysis is also described.