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Personalized dosing | ||
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## Background | ||
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Why personalized dosing? | ||
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„Again and again, it has been shown that certain patients benefit more from individual drugs, | ||
while others suffer more heavily from side effects… | ||
…and still they are usually treated with a standard dose." | ||
Free translation of a quote from Prof. Dr. Dr. Gerd Geisslinger, Executive Director, | ||
Fraunhofer Institute for Translational Medicine and Pharmacology, Frankfurt | ||
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## Data set | ||
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A simulated dose response [data set](WWW54ExampleData.csv) | ||
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* dose: dose levels (0, 100, 200 mg) | ||
* target: continuous response variable (higher is better) | ||
* subgroup variables: | ||
+ bmi (body mass index: ‘low BMI’ or ‘high BMI’) | ||
+ age (‘<40 years’ or ‘≥40 years’) | ||
+ race (‘Black’, ‘Asian’, ‘White’) | ||
+ sex (‘Female’, ‘Male’) | ||
+ type (type of disease: ‘Acute disease’ or ‘Chronic disease’) | ||
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## The Challenge | ||
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Aim of the visualisation | ||
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* Identify subgroups with a dose response that deviates from the remaining study participants | ||
* Therewith potential subgroups for personalized dosing could be identified | ||
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