Biomarker exposure-response relationships as the basis for rational dose selection: Lessons from a simulation exercise using a selective COX-2 inhibitor

2015 ◽  
Vol 56 (5) ◽  
pp. 609-621 ◽  
Author(s):  
Amit Taneja ◽  
Sean P. Oosterholt ◽  
Meindert Danhof ◽  
Oscar Della Pasqua
Keyword(s):  
Dose Selection ◽  
Simulation Exercise ◽  
Exposure Response ◽  
Rational Dose ◽  
Cox 2

scholarly journals Exposure–Response Analyses for Therapeutic Dose Selection of Belantamab Mafodotin in Patients with Relapsed/Refractory Multiple Myeloma

2021 ◽  
Author(s):  
Geraldine Ferron‐Brady ◽  
Chetan Rathi ◽  
Jon Collins ◽  
Herbert Struemper ◽  
Joanna Opalinska ◽  
...  
Keyword(s):  
Multiple Myeloma ◽  
Therapeutic Dose ◽  
Dose Selection ◽  
Refractory Multiple Myeloma ◽  
Exposure Response ◽  
Selection Of

scholarly journals Exposure–response relationship of AMG 386 in combination with weekly paclitaxel in recurrent ovarian cancer and its implication for dose selection

2012 ◽  
Vol 69 (5) ◽  
pp. 1135-1144 ◽  
Author(s):  
Jian-Feng Lu ◽  
Erik Rasmussen ◽  
Beth Y. Karlan ◽  
Ignace B. Vergote ◽  
Lynn Navale ◽  
...  
Keyword(s):  
Ovarian Cancer ◽  
Recurrent Ovarian Cancer ◽  
Weekly Paclitaxel ◽  
Response Relationship ◽  
Dose Selection ◽  
Exposure Response ◽  
Amg 386 ◽  
Relationship Of

A comprehensive evaluation of exposure–response relationships in clinical trials: application to support guselkumab dose selection for patients with psoriasis

2018 ◽  
Vol 45 (4) ◽  
pp. 523-535 ◽  
Author(s):  
Chuanpu Hu ◽  
Zhenling Yao ◽  
Yang Chen ◽  
Bruce Randazzo ◽  
Liping Zhang ◽  
...  
Keyword(s):  
Clinical Trials ◽  
Comprehensive Evaluation ◽  
Dose Selection ◽  
Exposure Response ◽  
Selection For

scholarly journals Translation of Pharmacodynamic Biomarkers of Antibiotic Efficacy in Specific Populations to Optimize Doses

Antibiotics ◽  
2021 ◽  
Vol 10 (11) ◽  
pp. 1368
Author(s):  
Manjunath P. Pai ◽  
Ryan L. Crass
Keyword(s):  
Drug Exposure ◽  
Current Approach ◽  
Dose Selection ◽  
Underlying Assumption ◽  
Exposure Response ◽  
Liver And Kidney ◽  
Trial Endpoints ◽  
Pharmacodynamic Biomarkers ◽  
Antibiotic Efficacy ◽  
Efficacy Studies

Antibiotic efficacy determination in clinical trials often relies on non-inferiority designs because they afford smaller study sample sizes. These efficacy studies tend to exclude patients within specific populations or include too few patients to discern potential differences in their clinical outcomes. As a result, dosing guidance in patients with abnormal liver and kidney function, age across the lifespan, and other specific populations relies on drug exposure-matching. The underlying assumption for exposure-matching is that the disease course and the response to the antibiotic are similar in patients with and without the specific condition. While this may not be the case, clinical efficacy studies are underpowered to ensure this is true. The current paper provides an integrative review of the current approach to dose selection in specific populations. We review existing clinical trial endpoints that could be measured on a more continuous rather than a discrete scale to better inform exposure–response relationships. The inclusion of newer systemic biomarkers of efficacy can help overcome the current limitations. We use a modeling and simulation exercise to illustrate how an efficacy biomarker can inform dose selection better. Studies that inform response-matching rather than exposure-matching only are needed to improve dose selection in specific populations.

Use of dose–exposure–response relationships in Phase 2 and Phase 3 guselkumab studies to optimize dose selection in psoriasis

2019 ◽  
Vol 33 (11) ◽  
pp. 2082-2086 ◽  
Author(s):  
M. Lebwohl ◽  
R.G. Langley ◽  
Y. Zhu ◽  
H. Zhou ◽  
M. Song ◽  
...  
Keyword(s):  
Phase 2 ◽  
Dose Selection ◽  
Phase 3 ◽  
Exposure Response
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