Screening


Data points excluded


Figure 4: % Of data points generated on HTS system that are excluded


10% 15% 20% 25% 30% 35% 40% 45% 50%


0% 5%


© HTStec 2010 46% Mean % DP Excluded = 9%


It is therefore not surprising to learn that respon- dents excluded a mean of 9% of all data points generated on their system due to an unacceptable level of quality, some of which may have been a direct consequence of poor system reliability (Figure 4).


27% 12% 8% 4% 2% 0% 0% 0% 0% 0% 0% 0% 0% 0% 0% 0% 0% 0% 2% 0% 0% 5% 10% 15% 20% 25% 30% 35% 40% 45% 50% 55% 60% 65% 70% 75% 80% 85% 90% 95% 100%


Cause of greatest downtime Peripheral components hardware (eg, readers, liq- uid handlers) were ranked the cause of most fre- quent system problems and had greatest impact on downtime. This was followed by integration hard- ware (eg, robots, plate handlers and movers); inte- gration software (eg, scheduler, device drivers); and then peripheral components software (Figure 5).


Figure 5: Aspect of HTS system causing most problems and greatest downtime


Peripheral components hardware (eg readers, liquid handlers) Integration hardware (eg robots, plate handlers and movers) Integration software (eg scheduler, device drivers) Peripheral components software


1.91 1.93


2.24 2.17


Geatest Downtime Most Problematic


1.00 1.50 2.00 2.50 3.00 3.50 4.00 © HTStec 2010 MEAN RANKED ORDER 1 to 4, where 1 = least (often or downtime) and 4 = most (often or downtime)


2.69 2.70


3.21 3.29


What contributes to system failure? The introduction of a new assay readout/technolo- gy was rated as having the greatest positive effect on the successful operation of a system, while reagent characteristics (eg, viscosity, homogeneity, surface tension, etc) as having the greatest negative effect on a system, and contributing to failures (Figure 6). Weekend and holiday operation, cell- based assays, and longer incubation times (ie, extended assay duration) were broadly neutral in their effect on the system failure. Interestingly, most hardware changes and software patches or upgrades were associated with a negative effect on system operation, as were unplanned absences of key personnel.


Realistic advantage of improved reliability


Figure 6: What influences the failure of respondents HTS system


Introduction of a new assay readout/technology Weekend and holiday operation


Longer incubation times (ie extended assay duration) Cell-based assays


Miniaturised assays (ie reduced reagent volumes dispensed)


Software patches or upgrades Unplanned absence of key personnel Hardware changes


Reagent characteristics (eg viscosity, homogeneity, surface tension)


-0.41


-0.60 -0.50 -0.40 -0.30 -0.20 -0.10 0.00 0.10 0.20 0.30 Rating SCORE of -2 to +2, where -2 = negative effect, 0 = no effect, and +2 = positive effect


© HTStec 2010 -0.16


-0.18 -0.18


-0.25


0.02 0.02


-0.02 0.10


When respondents were asked what they thought would be realistic advantages if their system was more reliable they rated increased user (customer) satisfaction as the most likely outcome (Figure 7). This was followed by run screens quicker and then to repeat fewer wells (where data does not meet acceptance criteria). The least likely advantages were to identify weaker inhibitors, reduce number of false positives or to discover more lead series. The response recorded is suggestive of the fact that most respondents do not think much beyond their imme- diate task (ie, running the screen on their system for the customer group), and tend to see the advantages that might stem from improved reliability primarily in these terms, rather than how it might impact downstream or more widely on the drug discovery process. This finding was further reinforced by respondents’ answers to the question what HTS (ie, their system) has achieved in their organisation to date (Figure 8). More data points screened was rated


64 Drug Discovery World Winter 2010/11


% Responding


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