Communicating the Value of Pharmacodynamic Modelling in Drug ...
Communicating the Value of Pharmacodynamic Modelling in Drug ...
Communicating the Value of Pharmacodynamic Modelling in Drug ...
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Our purpose is to view and query model-based attributes based on<br />
simulation <strong>of</strong> mean responses.<br />
We can achieve detailed exploration <strong>of</strong> <strong>the</strong> dose-response curve for many<br />
comb<strong>in</strong>ations <strong>of</strong> endpo<strong>in</strong>ts, treatments, covariates, and compet<strong>in</strong>g products<br />
%Change from Basel<strong>in</strong>e <strong>of</strong> <strong>Drug</strong> B<br />
Response Selection<br />
Covariates, Assumptions<br />
Plots Display Trends<br />
Shaded area shows prediction<br />
<strong>in</strong>terval for expected doseresponse<br />
or response as a<br />
function <strong>of</strong> o<strong>the</strong>r explanatory<br />
variables (e.g., dose, time)<br />
Controllable Inputs<br />
(Treatments, Compet<strong>in</strong>g<br />
Therapies & Doses)<br />
Tables Display Details<br />
Dotted horizontal l<strong>in</strong>e(s) show<br />
def<strong>in</strong>ed success ranges, or “cut<br />
po<strong>in</strong>ts” based on product<br />
pr<strong>of</strong>iles<br />
Vertical l<strong>in</strong>es show explanatory<br />
variables <strong>of</strong> <strong>in</strong>terest (e.g., dose,<br />
time)<br />
Output Controls<br />
Tables display quantitative<br />
estimates <strong>of</strong> prediction <strong>in</strong>tervals<br />
or o<strong>the</strong>r <strong>in</strong>formation<br />
slide 35<br />
30 May 2008, ARCS<br />
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