Informatics
research project. Each rectangle within a funnel represents an ‘event’ being tracked through the cas- cade. In this example, an ‘event’ is when a com- pound is first synthesised and registered or when an assay is completed. The width of each rectangle represents the number of compounds processed through that event. This volume is also annotated to the right of each rectangle. Hence a single fun- nel shows the attrition level by its funnel-like shape. Time is represented by the elongation of the funnel, since the distance between each rectangle and the top of the funnel represents the average number of days from compound registration to the completion of that event. These average (mean) times are also written to the left of each rectangle. It is important to note that the timescale is linear above a three-month border and that time is not scaled below the border. This change of scale is required to accommodate visualisation of short times at the top of the funnel and long timescales at the end. From Figure 1 it is evident that in October 2009, in this research project, 50 new compounds were registered. 46 of these went through Assay 1, 41 through Assay 2, 10 through Assay 3 and so forth, ending with just two of the original 50 being tested in Assay 7. It took an aver- age of four days from compound registration to get results from Assay 1 and an average of 59 days to get results from Assay 4. Note that Assays 5, 6 and 7 took more than three months to be completed and, despite being placed together at the bottom of the funnel, they differ greatly in completion time. This visualisation of new compounds made in a single month prompts us, at a glance, to ask useful and insightful process improvement questions, such as: what happened to the four compounds that were not put through the front line assay?; what is driving high attrition between Assay 2 and 3?; why is it taking so long to get results from Assays 5, 6 and 7?
Further insight into higher-level project consid- erations can be derived by examining the changes in funnels across a series of months presented in a trellis. To illustrate this, we present a six-month snapshot view of one of our lead optimisation research projects (Figure 2). Looking across the top of the funnels at their widths, we can quickly see the large increase from May to June in the number of new compounds being synthesised. In fact, we had moved additional chemistry resources on to this project in May, and so the increase in volume of new compounds is the detected conse- quence of the resource change. Notice in July, June and April the funnels fold back on themselves. This shows that the assays have been carried out
Drug Discovery World Winter 2011/12
Figure 1
A single funnel. Simple simultaneous visualisation of assay timelines and attrition rates for the test cascade of a particular project in October 2009. Each rectangle represents an event being tracked through the cascade. The width of a rectangle represents the number of compounds processed by that event (also annotated to the right of each rectangle). The distance between a rectangle and the top of the funnel represents the average number of days from compound registration to completion of that event (also annotated to the left of each rectangle)
in a different order to the stated cascade, with Assay 4 results coming out before Assay 3. Assays 1 and 2 are consistently completed within a week of compound registration, regardless of the vol- ume of requests. This suggested that this is a min- imal impact area for process improvements. However, the funnels highlight more variable timelines for Assay 3, again seemingly independ- ent of the assay’s throughput. As a result, the processes around assay three were examined dur- ing June and July.
It was discovered that a significant and variable amount of time was taken in submission of Assay 3 requests, due to the nature of decision making based on primary assay SAR information from a set of compounds (not just the compound under
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