Skip to Main Content
Exposure-Response Modeling
book

Exposure-Response Modeling

by Jixian Wang
July 2015
Intermediate to advanced content levelIntermediate to advanced
351 pages
10h 2m
English
Chapman and Hall/CRC
Content preview from Exposure-Response Modeling
Dose–response relationship, dose determination, and adjustment 281
0.5824 10 = 48.24. T he refore, the optimal strategy is to take the top path
and to use a phase II tr ial first. Based on the results, we can also calculate
p
23
as
> mean(reward*res[,2]-C3>0)
[1] 0.8737
and p
35
as
> mean(res[reward*res[,2]-C3>0,2])
[1] 0.7497676
as in Figure 9.3.
For simplicity we have assumed that the reward of success is the same
with or without the phase II trial. In practice, the time delay due to running
the phase II trial makes the reward with the phase II trial much lower than
those without it. A simple approach is to use a dis count rate (e.g., 3% each
year) to adjust for the delay. Although this approach is commonly used for
public health policy making, e.g., reimbursement, ...
Become an O’Reilly member and get unlimited access to this title plus top books and audiobooks from O’Reilly and nearly 200 top publishers, thousands of courses curated by job role, 150+ live events each month,
and much more.
Start your free trial

You might also like

Computational Pharmacokinetics

Computational Pharmacokinetics

Anders Kallen
Deep Learning through Sparse and Low-Rank Modeling

Deep Learning through Sparse and Low-Rank Modeling

Zhangyang Wang, Yun Fu, Thomas S. Huang

Publisher Resources

ISBN: 9781466573215