Scaling Factors for the Extrapolation of In Vivo Metabolic Drug Clearance From In Vitro Data: Reaching a Consensus on Values of Human Micro-somal Protein and Hepatocellularity Per Gram of Liver

2007 ◽  
Vol 8 (1) ◽  
pp. 33-45 ◽  
Author(s):  
Zoe Barter ◽  
Martin Bayliss ◽  
Philip Beaune ◽  
Alan Boobis ◽  
David Carlile ◽  
...  
Keyword(s):  
Drug Clearance ◽  
Scaling Factors ◽  
Metabolic Drug ◽  
Vitro Data ◽  
In Vitro Data

Hepatic Scaling Factors for In Vitro-In Vivo Extrapolation (IVIVE) of Metabolic Drug Clearance in Patients with Colorectal Cancer with Liver Metastasis

2021 ◽  
pp. DMD-AR-2021-000359
Author(s):  
Areti-Maria Vasilogianni ◽  
Brahim Achour ◽  
Daniel Scotcher ◽  
Sheila Annie Peters ◽  
Zubida M. Al-Majdoub ◽  
...  
Keyword(s):  
Colorectal Cancer ◽  
Liver Metastasis ◽  
Drug Clearance ◽  
Scaling Factors ◽  
Metabolic Drug ◽  
In Vivo Extrapolation

Use of Toxicokinetics in Risk Assessment Based on In Vitro Data

1993 ◽  
Vol 21 (2) ◽  
pp. 173-180
Author(s):  
Gunnar Johanson
Keyword(s):  
Risk Assessment ◽  
Whole Body ◽  
External Exposure ◽  
Target Dose ◽  
Toxic Response ◽  
Route Of Exposure ◽  
Vitro Data ◽  
In Vitro Data

This presentation addresses some aspects of the methodology, advantages and problems associated with toxicokinetic modelling based on in vitro data. By using toxicokinetic models, particularly physiologically-based ones, it is possible, in principle, to describe whole body toxicokinetics, target doses and toxic effects from in vitro data. Modelling can be divided into three major steps: 1) to relate external exposure (applied dose) of xenobiotic to target dose; 2) to establish the relationship between target dose and effect (in vitro data, e.g. metabolism in microsomes, partitioning in tissue homogenates, and toxicity in cell cultures, are useful in both steps); and 3) to relate external exposure to toxic effect by combining the first two steps. Extrapolations from in vitro to in vivo, between animal and man, and between high and low doses, can easily be carried out by toxicokinetic simulations. In addition, several factors that may affect the toxic response by changing the target dose, such as route of exposure and physical activity, can be studied. New insights concerning the processes involved in toxicity often emerge during the design, refinement and validation of the model. The modelling approach is illustrated by two examples: 1) the carcinogenicity of 1,3-butadiene; and 2) the haematotoxicity of 2-butoxyethanol. Toxicokinetic modelling is an important tool in toxicological risk assessment based on in vitro data. Many factors, some of which can, and should be, studied in vitro, are involved in the expression of toxicity. Successful modelling depends on the identification and quantification of these factors.

scholarly journals MATURATION OF HEMOLYSIN-PRODUCING CELL CLONES

1970 ◽  
Vol 131 (6) ◽  
pp. 1261-1270 ◽  
Author(s):  
George C. Saunders ◽  
Douglas Swartzendruber
Keyword(s):  
Bone Marrow ◽  
Doubling Time ◽  
Sheep Erythrocyte ◽  
Mature Animal ◽  
Cell Clones ◽  
Initial Appearance ◽  
Vitro Data ◽  
In Vitro Data

Cells capable of reacting with sheep erythrocyte (SRBC) antigen to maturate and produce hemolysin appear simultaneously in the bone marrow and spleen of 1-day old Swiss-Webster mice. However, hemolysin-producing cell clones (HPCC) do not result. Complete functional precursor units generally appear in the spleens of mice older than 3 days. In vivo and in vitro data correlate well in this regard. Complete precursor units are not seen in the bone marrow and only very rarely in the thymus. The efficiency of precursor units of neonatal mice when they become functional approximates that of the mature animal when based on the doubling time of plaque-forming cells (PFC). Possible explanations of the initial appearance of incomplete precursor units have been discussed.

Identification of human cytochrome P 450 s that metabolise anti-parasitic drugs and predictions of in vivo drug hepatic clearance from in vitro data

2003 ◽  
Vol 59 (5-6) ◽  
pp. 429-442 ◽  
Author(s):  
Xue-Qing Li ◽  
Anders Bj�rkman ◽  
Tommy B. Andersson ◽  
Lars L. Gustafsson ◽  
Collen M. Masimirembwa
Keyword(s):  
Hepatic Clearance ◽  
Human Cytochrome ◽  
Cytochrome P 450 ◽  
Vitro Data ◽  
In Vitro Data

scholarly journals In Vitro Interaction of Caspofungin Acetate with Voriconazole against Clinical Isolates of Aspergillus spp

2002 ◽  
Vol 46 (9) ◽  
pp. 3039-3041 ◽  
Author(s):  
Sofia Perea ◽  
Gloria Gonzalez ◽  
Annette W. Fothergill ◽  
William R. Kirkpatrick ◽  
Michael G. Rinaldi ◽  
...  
Keyword(s):  
Inhibitory Concentration ◽  
Fractional Inhibitory Concentration ◽  
Broth Microdilution ◽  
Microdilution Method ◽  
Broth Microdilution Method ◽  
In Vitro Interaction ◽  
Vitro Data ◽  
In Vitro Data

ABSTRACT The interaction between caspofungin acetate and voriconazole was studied in vitro by using 48 clinical Aspergillus spp. isolates obtained from patients with invasive aspergillosis. MICs were determined by the NCCLS broth microdilution method. Synergy, defined as a fractional inhibitory concentration (FIC) index of <1, was detected in 87.5% of the interactions; an additive effect, defined as an FIC index of 1.0, was observed in 4.2% of the interactions; and a subadditive effect, defined as an FIC index of 1.0 to 2.0, was found in 8.3% of the interactions. No antagonism was observed. Animal models are required to validate the in vivo significance of these in vitro data presented for the combination of caspofungin and voriconazole.

scholarly journals How well can in vitro data predict in vivo effects of chemicals? Rodent carcinogenicity as a case study

2016 ◽  
Vol 77 ◽  
pp. 54-64 ◽  
Author(s):  
Louis Anthony (Tony) Cox ◽  
Douglas A. Popken ◽  
A. Michael Kaplan ◽  
Laura M. Plunkett ◽  
Richard A. Becker
Keyword(s):  
In Vivo Effects ◽  
Vitro Data ◽  
In Vitro Data ◽  
Rodent Carcinogenicity
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