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      Calculation of a First-In-Man Dose of 7- O-Succinyl Macrolactin A Based on Allometric Scaling of Data from Mice, Rats, and Dogs

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          Abstract

          7- O-Succinyl macrolactin A (SMA) exerts several pharmacological effects including anti-bacterial, anti-inflammation, and anti-cancer activities. Recently, SMA has been extensively evaluated as an anti-cancer drug. Thus, the objectives of the present study were to characterise the pharmacokinetics of SMA via both non-compartmental and compartmental analysis in mice, rats, and dogs, and to derive an appropriate first-in-man dose based on allometric scaling of the animal data. The time courses of plasma SMA concentrations after intravenous administration to rats and dogs were analysed retrospectively, as were data collected after intraperitoneal SMA injection in mice. Pharmacokinetic parameters were estimated via both noncompartmental and compartmental analysis, and were correlated with body weight and/or the potential maximum life-span. The clearance and distribution volume of SMA in humans were predicted, and a first-in-man dose proposed. A two-compartment model best described the time courses of SMA plasma concentrations after a saturation elimination process was applied to fit the dataset obtained from rats. Incorporation of the maximum potential life-span during allometric scaling was required to improve the estimation of human clearance. The SMA clearance and the distribution volume in the steady state, in a 70-kg adult male, were estimated to be 30.6 L/h and 19.5 L, respectively. To meet the area under the curve (AUC) required for anti-tumour activity, a dose of 100 mg (∼1.5 mg/kg) was finally proposed as the first dose for a 70-kg human. Although toxicological profiles derived from non-clinical studies must be considered before any final decision is made, our work will facilitate clinical studies on SMA.

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          Prediction-corrected visual predictive checks for diagnosing nonlinear mixed-effects models.

          Informative diagnostic tools are vital to the development of useful mixed-effects models. The Visual Predictive Check (VPC) is a popular tool for evaluating the performance of population PK and PKPD models. Ideally, a VPC will diagnose both the fixed and random effects in a mixed-effects model. In many cases, this can be done by comparing different percentiles of the observed data to percentiles of simulated data, generally grouped together within bins of an independent variable. However, the diagnostic value of a VPC can be hampered by binning across a large variability in dose and/or influential covariates. VPCs can also be misleading if applied to data following adaptive designs such as dose adjustments. The prediction-corrected VPC (pcVPC) offers a solution to these problems while retaining the visual interpretation of the traditional VPC. In a pcVPC, the variability coming from binning across independent variables is removed by normalizing the observed and simulated dependent variable based on the typical population prediction for the median independent variable in the bin. The principal benefit with the pcVPC has been explored by application to both simulated and real examples of PK and PKPD models. The investigated examples demonstrate that pcVPCs have an enhanced ability to diagnose model misspecification especially with respect to random effects models in a range of situations. The pcVPC was in contrast to traditional VPCs shown to be readily applicable to data from studies with a priori and/or a posteriori dose adaptations.
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            Physiological parameters in laboratory animals and humans.

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                Author and article information

                Journal
                Biomol Ther (Seoul)
                Biomol Ther (Seoul)
                Biomol Ther (Seoul)
                ksp
                Biomolecules & Therapeutics
                The Korean Society of Applied Pharmacology
                1976-9148
                2005-4483
                November 2017
                10 March 2017
                : 25
                : 6
                : 648-658
                Affiliations
                [1 ]College of Pharmacy, Yeungnam University, Gyeongsan 38541, Republic of Korea
                [2 ]College of Pharmacy, Chung-Ang University, Seoul 06974, Republic of Korea
                Author notes
                [* ]Corresponding Author: E-mail: wkang@ 123456cau.ac.kr , Tel: +82-2-820-5601, Fax: +82-2-816-7338
                [ψ]

                Present Address

                Department of Pharmaceutical Sciences, Leslie Dan Faculty of Pharmacy, University of Toronto, 144 College Street, Toronto M5S 3M2, Canada

                Article
                bt-25-648
                10.4062/biomolther.2016.192
                5685435
                28274094
                907caecd-28cd-4a9d-868a-84b895948eec
                Copyright © 2017 The Korean Society of Applied Pharmacology

                This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License ( http://creativecommons.org/licenses/by-nc/4.0/) which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.

                History
                : 24 August 2016
                : 08 December 2016
                : 09 January 2017
                Categories
                Original Article

                7-o-succinyl macrolactin a,pharmacokinetics,first-in-man dose,allometric scaling,dienetichron plot

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