ArticleCPT: pharmacometrics & systems pharmacology2016
Systems Pharmacology Modeling of Prostate-Specific Antigen in Patients With Prostate Cancer Treated With an Androgen Receptor Antagonist and Down-Regulator.
Article in CPT: pharmacometrics & systems pharmacology, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
1 citing paper in PubMed, 3 citations in OpenAlex.
Corrections and comments
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Authors and funding
5 authors at 3 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
First-in-human (FIH) studies with AZD3514, a selective androgen receptor (AR) down-regulator, showed decreases of >30% in the prostate-specific antigen (PSA) in some patients. A modeling approach was adopted to understand these observations and define the optimum clinical use hypothesis for AZD3514 for clinical testing. Initial empirical modeling showed that only baseline PSA correlated significantly with this biological response, whereas drug concentration did not. To identify the mechanistic cause of this observation, a mechanism-based model was first developed, which described the effects of AZD3514 on AR protein and PSA mRNA levels in LNCaP cells with and without dihydrotestosterone (DHT). Second, the mechanism-based model was linked to a population pharmacokinetic (PK) model; PSA effects of clinical doses were subsequently simulated under different clinical conditions. This model was used to adjust the design of the ongoing clinical FIH study and direct the backup program.
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