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Ethically Attractive Dose‐Finding Designs for Drugs With a Narrow Therapeutic Index
Author(s) -
LledóGarcía Rocío,
Hennig Stefanie,
Nyberg Joakim,
Hooker Andrew C.,
Karlsson Mats O.
Publication year - 2012
Publication title -
the journal of clinical pharmacology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.92
H-Index - 116
eISSN - 1552-4604
pISSN - 0091-2700
DOI - 10.1177/0091270010390041
Subject(s) - clinical trial , clinical study design , index (typography) , medicine , therapeutic index , computer science , baseline (sea) , risk analysis (engineering) , statistics , drug , pharmacology , mathematics , world wide web , oceanography , geology
A simulation‐based comparison study on the relative merits of dose‐control trials (DCTs) with exposure—response analysis versus concentration‐control trials (CCTs) for drugs with narrow therapeutic index showed that DCT designs are more informative about the exposure—response relationship. The authors revisit the question employing optimal design methodology and propose strategies for designing ethically attractive trials for these drugs, balancing between individual—collective risk and informativeness. An optimal study was performed considering a hypothetical immunosuppressant agent with 2 clinical end points. Different scenarios were optimized applying cost‐based designs (unwanted events vs number of subjects/trial or maximal individual risk). Dose/exposure targets and number of subjects per trial/arm were optimized. Prior information inclusion on baseline risks was evaluated. DCTs were more informative, needing smaller studies to provide the same information as CCTs. Using the number of unwanted events—rather than subjects—as cost resulted in ethically more attractive designs. Including prior baseline risk information reduced the number of subject/events and allowed the use of targets closer to the optimal. Designing dose‐finding trials for some narrow therapeutic index drugs may be improved by using DCTs with exposure—response analysis, cost‐based designs, prior information, and optimal design analysis providing information on the ethical trade‐off between individual risk and information gain.