Nonlinear Mixed-Effects Modeling of Population Pharmacokinetics Data
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Data sets involving nonlinear, sparse grouped data are common in the health sciences, especially in drug trials, where they are used to measure drug absorption, distribution, metabolism, and elimination. In this approach, patients are grouped using characteristics such as age, sex, weight, and smoking history. Given the expense of drug trials, however, it is not always possible to obtain sufficient patient data. To view a demonstration of how SimBiology can be applied to pharmacokinetics data, please complete the form below. |
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