ArticleClinical pharmacokinetics2017
Translational Modeling and Simulation in Supporting Early-Phase Clinical Development of New Drug: A Learn-Research-Confirm Process.
Article in Clinical pharmacokinetics, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
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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.
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Who cites it
3 citing papers in PubMed, 10 citations in OpenAlex.
- Effect of renal impairment on the pharmacokinetics and safety of dorzagliatin, a novel dual-acting glucokinase activator.Clinical and translational science · 2022Article
- Comparison of Precision and Accuracy of Five Methods to Analyse Total Score Data.The AAPS journal · 2020Article
- Comparison of Power, Prognosis, and Extrapolation Properties of Four Population Pharmacodynamic Models of HbA1c for Type 2 Diabetes.CPT: pharmacometrics & systems pharmacology · 2018Article
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Authors and funding
11 authors at 8 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
BACKGROUND AND
objectivePharmacokinetic/pharmacodynamic modeling and simulation can aid clinical drug development by dynamically integrating key system- and drug-specific information into predictive profiles. In this study, we propose a methodology to predict pharmacokinetic/pharmacodynamic profiles of sinogliatin (HMS-5552, RO-5305552), a novel glucokinase activator to treat diabetes mellitus, for first-in-patient (FIP) studies. METHODS AND
resultsInitially, pharmacokinetic/pharmacodynamic profiles of sinogliatin and another glucokinase activator (US2) previously acquired from healthy subjects were fitted using Model A incorporating an indirect response mechanism. The pharmacokinetic/pharmacodynamic profiles of US2 in patients with type 2 diabetes mellitus (T2DM) were then fitted using Model B incorporating circadian rhythm and food effects after thoughtful research on the difference between healthy subjects and T2DM patients. The differences in results between the two US2 modeling populations were used to scale the values of the pharmacodynamic parameters and refine the pharmacodynamic model of sinogliatin, which was then utilized to project pharmacokinetic/pharmacodynamic profiles of sinogliatin in T2DM patients after an 8-day simulated treatment. Results showed that the projected pharmacokinetic/pharmacodynamic values of five parameters were within 70-130% of values fitted from observed clinical data while the other two remaining projected parameters were within a twofold error. Population pharmacokinetic/pharmacodynamic analysis conducted for sinogliatin also suggested that age and sex were significantly correlated to pharmacokinetic/pharmacodynamic characteristics. Additionally, Model B was combined with a glycosylated hemoglobin (HbA
conclusionsModel-based drug development methods utilizing a learn-research-confirm cycle may accurately project pharmacokinetic/pharmacodynamic profiles of new drugs in FIP studies.
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