Optimal Design for Estimating Parameters of the 4-Parameter Hill Model

Khinkis, Leonid; Levasseur, Laurence M.; Faessel, Hélène M.; Greco, William R.

doi:10.1080/15401420390249925

Cited by 35 publications

(31 citation statements)

References 17 publications

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“…Estimates of treatment effects were based on these models, and 95% confidence intervals of these estimates were reported. Four-parameter logistic regression models were used to calculate and compare IC 50 values of drug treatments (22). All analyses were performed using SAS/STAT software, v9.2 (SAS Institute, Inc., Cary, NC).…”

Section: Methodsmentioning

confidence: 99%

Resistance to the Translation Initiation Inhibitor Silvestrol is Mediated by ABCB1/P-Glycoprotein Overexpression in Acute Lymphoblastic Leukemia Cells

Gupta

Sass

Davis

et al. 2011

AAPS J

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Abstract. Protein synthesis is a powerful therapeutic target in leukemias and other cancers, but few pharmacologically viable agents are available that affect this process directly. The plant-derived agent silvestrol specifically inhibits translation initiation by interfering with eIF4A/mRNA assembly with eIF4F. Silvestrol has potent in vitro and in vivo activity in multiple cancer models including acute lymphoblastic leukemia (ALL) and is under pre-clinical development by the US National Cancer Institute, but no information is available about potential mechanisms of resistance. In a separate report, we showed that intraperitoneal silvestrol is approximately 100% bioavailable systemically, although oral doses were only 1% bioavailable despite an apparent lack of metabolism. To explore mechanisms of silvestrol resistance and the possible role of efflux transporters in silvestrol disposition, we characterized multi-drug resistance transporter expression and function in a silvestrol-resistant ALL cell line generated via culture of the 697 ALL cell line in gradually increasing silvestrol concentrations. This resistant cell line, 697-R, shows significant upregulation of ABCB1 mRNA and P-glycoprotein (Pgp) as well as cross-resistance to known Pgp substrates vincristine and romidepsin. Furthermore, 697-R cells readily efflux the fluorescent Pgp substrate rhodamine 123. This effect is prevented by Pgp inhibitors verapamil and cyclosporin A, as well as siRNA to ABCB1, with concomitant re-sensitization to silvestrol. Together, these data indicate that silvestrol is a substrate of Pgp, a potential obstacle that must be considered in the development of silvestrol for oral delivery or targeting to tumors protected by Pgp overexpression.

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Section: Methodsmentioning

confidence: 99%

Resistance to the Translation Initiation Inhibitor Silvestrol is Mediated by ABCB1/P-Glycoprotein Overexpression in Acute Lymphoblastic Leukemia Cells

Gupta

Sass

Davis

et al. 2011

AAPS J

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“…The four and five parameter Hill model has been widely used to study sigmoidal dose effect relationships in biochemical, physiological, and pharmacological contexts (Holford and Sheiner 1981;Khinkis et al 2003). The Hill equation was introduced by Hill (1910) to describe the relationship between oxygen tension and the saturation of haemoglobin (Goutelle et al 2008) as described by Barcroft and Camis (1909).…”

Section: Model Backgroundmentioning

confidence: 99%

Kinetic model selection and the Hill model in geochemistry

Turner

Henley

Sleap

et al. 2014

Int. J. Environ. Sci. Technol.

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This study introduces the Hill model for modelling sorption kinetics and illustrates its efficacy using formal model selection procedures. Although the coefficient of determination (R 2 ) value can be used to ensure goodness-of-fit of a particular model to a set of data, a measure that incorporates the number of model parameters, such as the Bayesian information criterion, law of iterated logarithm criterion, Akaike information criterion, and the extra sum-of-squares F-test is necessary to undertake reliable model selection. This study undertook a formal model selection procedure based on these criteria, in combination with the coefficient of determination, for a range of candidate kinetics sorption models [the pseudo-second order (PSO), the intra-particle diffusion (IPD), Power, Elovich, and the four and five parameter Hill models]. It was found that the model order that statistically best described the data was Hill 5 [ Hill 4 [ pseudo-second order [ Elovich [ Power [ IPD as given by the evidence ratios, information criterion weights and Bayes factors. The extra sum-of-squares F-test, only applicable to nested models, confirms the best fit order as Hill 5 [ Hill 4 [ PSO models. Two new parameters (T and k Hill ) have also been defined that give the Hill models a mechanistic meaning directly comparable to the well-defined parameters of the pseudo-second-order model, namely, the pseudo-secondorder rate constant k pso and the instantaneous sorption coefficient h pso . In the field of geochemistry the use of the four and five parameter Hill models for describing sorption kinetics has been overlooked with many studies favouring the PSO model. It is strongly recommended that the Hill model be considered more widely as a general predictive tool in geochemistry.

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“…Khinkis et al [4] conducted a cell growth inhibition study in a laboratory to investigate the effectiveness of 7 anticancer drugs to shrink the tumor using the 4-parameter Hill model. Nominal parameter values for these drugs used in the study are displayed in Table 1.…”

Section: Objectives Models and Algorithms For Finding Optimal Desimentioning

confidence: 99%

“…Nominal parameter values for these drugs used in the study are displayed in Table 1. Figure 1 shows the mean response shapes of (2) for the 7 different sets of values of the parameters in Khinkis et al [4], suggesting that the characteristics of the drugs are quite different.…”

Section: Objectives Models and Algorithms For Finding Optimal Desimentioning

confidence: 99%

“…In Section 3, we discuss optimality criteria for dose response studies in the context of the popular Hill model and its relationship with the 4-parameter logistic model. In Section 4, we revisit a dose response study with 7 anti-cancer drugs from Khinkis et al [4], report the single-objective optimal designs for estimating all parameters in the mean function, the ED 50 and the MED , and how they compared with the multiple-objective optimal design that accounts for these objectives simultaneously at the onset. Additionally, we show how an Equivalence Theorem can be used to confirm the optimality of a multiple-objective optimal design and study sensitivities of such an optimal design to mis-specification in the nominal values, changes in the design criteria and relative interests in the multiple objectives.…”

Section: Introductionmentioning

confidence: 99%

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Multiple-Objective Optimal Designs for Studying the Dose Response Function and Interesting Dose Levels

Hyun

Wong

2015

The International Journal of Biostatistics

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We construct an optimal design to simultaneously estimate three common interesting features in a dose-finding trial with possibly different emphasis on each feature. These features are (1) the shape of the dose-response curve, (2) the median effective dose and (3) the minimum effective dose level. A main difficulty of this task is that an optimal design for a single objective may not perform well for other objectives. There are optimal designs for dual objectives in the literature but we were unable to find optimal designs for 3 or more objectives to date with a concrete application. A reason for this is that the approach for finding a dual-objective optimal design does not work well for a 3 or more multiple-objective design problem. We propose a method for finding multiple-objective optimal designs that estimate the three features with user-specified higher efficiencies for the more important objectives. We use the flexible 4-parameter logistic model to illustrate the methodology but our approach is applicable to find multiple-objective optimal designs for other types of objectives and models. We also investigate robustness properties of multiple-objective optimal designs to mis-specification in the nominal parameter values and to a variation in the optimality criterion. We also provide computer code for generating tailor made multiple-objective optimal designs.

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Optimal Design for Estimating Parameters of the 4-Parameter Hill Model

Cited by 35 publications

References 17 publications

Resistance to the Translation Initiation Inhibitor Silvestrol is Mediated by ABCB1/P-Glycoprotein Overexpression in Acute Lymphoblastic Leukemia Cells

Resistance to the Translation Initiation Inhibitor Silvestrol is Mediated by ABCB1/P-Glycoprotein Overexpression in Acute Lymphoblastic Leukemia Cells

Kinetic model selection and the Hill model in geochemistry

Multiple-Objective Optimal Designs for Studying the Dose Response Function and Interesting Dose Levels

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