Reduce & Repeat Non-Clinical Statistics Conference 2014, Brugge October 2014 More Precise XC50s Using Fewer Wells (in vitro) and Fewer Animals (in vivo)

Raw Conc-Response Data 2 Jonathan Bright | September 2014Innovative Medicines | Discovery Sciences

Only Half of the Concs 3 Jonathan Bright | September 2014Innovative Medicines | Discovery Sciences

Only Half of the Replicates 4 Jonathan Bright | September 2014Innovative Medicines | Discovery Sciences

Only Half of the Concs and Half of the Replicates 5 Jonathan Bright | September 2014Innovative Medicines | Discovery Sciences

Only Half of the Concs and Half of the Replicates and Half of the Controls 6 Jonathan Bright | September 2014Innovative Medicines | Discovery Sciences

IC50 and 95% Confidence Interval 7 Jonathan Bright | September 2014Innovative Medicines | Discovery Sciences

Findings #1 For a “well-behaved” assay, the resource (wells) may be dramatically reduced with little impact on either the estimate of the XC50 or its confidence interval “Well-behaved” -Max and min controls that safely position the curve top and bottom -Conc-response data that have the right sort of sigmoid shape -Acceptable to overlook details such as biphasic and partial inhibition May be exploited -Throughput -Cost -Compound use 8 Jonathan Bright | September 2014Innovative Medicines | Discovery Sciences

Second Set of Raw Conc-Response Data 9 Jonathan Bright | September 2014Innovative Medicines | Discovery Sciences

IC50 and 95% Confidence Interval 10 Jonathan Bright | September 2014Innovative Medicines | Discovery Sciences

IC50 and 95% Confidence Interval 11 Jonathan Bright | September 2014Innovative Medicines | Discovery Sciences

Findings #2 Run-to-run differences in XC50 are massive compared to the small changes in XC50 that occur as a result of reducing the resource (wells) on any given run Put in terms of components of variation -Between run variation dominates within-run variation -Within-run variation changes hardly at all as the number of concs and number of replicates changes May be exploited -Reduce the resource per run -Repeat -Average 12 Jonathan Bright | September 2014Innovative Medicines | Discovery Sciences

IC50 vs Run 13 Jonathan Bright | September 2014Innovative Medicines | Discovery Sciences

IC50 vs Run 14 Jonathan Bright | September 2014Innovative Medicines | Discovery Sciences

IC50 vs Run 15 Jonathan Bright | September 2014Innovative Medicines | Discovery Sciences

IC50 vs Run 16 Jonathan Bright | September 2014Innovative Medicines | Discovery Sciences

IC50 vs Run 17 Jonathan Bright | September 2014Innovative Medicines | Discovery Sciences

IC50 vs Run 18 Jonathan Bright | September 2014Innovative Medicines | Discovery Sciences

In Vivo A situation similar to the in vitro case has been observed, whereby study-to-study differences are the main component of variation -Was it a “good day” or a “bad day” for compound X 2 Start Strategy (Brian Middleton) -Start half the planned animals (reduce) -Independently run the second half (repeat) -Average Gives a superior estimate of the e.g. XC50 or XD50 Provides in some cases a chance to change doses for the second start 19 Jonathan Bright | September 2014Innovative Medicines | Discovery Sciences

Summary In both in vitro and in vivo settings there are large run-to-run or study-to-study differences when a compound is retested -Root cause analysis Exploit by -reducing the resource (wells or animals) on a given occasion -repeating the experiment -averaging across the experiments Reduce -Throughput, cost and compound benefits Reduce and Repeat -Precision benefit + 20 Jonathan Bright | September 2014Innovative Medicines | Discovery Sciences

Acknowledgement and Reference Siller H, Taylor JD, Middleton B. Two-start design within a Sephadex inflammatory model – A means to generate reliable ED 50 data whilst significantly reducing the number of animals used. Pulm Pharmacol Ther 2012; 25: Jonathan Bright | September 2014Innovative Medicines | Discovery Sciences

Extra Slide 22 Jonathan Bright | September 2014Innovative Medicines | Discovery Sciences

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