Incorporating Measures of Variability and Uncertainty into the Prediction of in Vivo Hepatic Clearance from in Vitro Data

2002 ◽  
Vol 30 (3) ◽  
pp. 276-282 ◽  
Author(s):  
Ivan Nestorov ◽  
Ivelina Gueorguieva ◽  
Hannah M. Jones ◽  
Brian Houston ◽  
Malcolm Rowland
Keyword(s):  
Hepatic Clearance ◽  
Vitro Data ◽  
In Vitro Data

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

Prediction of in vivo hepatic clearance from in vitro data using cryopreserved human hepatocytes

Xenobiotica ◽  
2003 ◽  
Vol 33 (5) ◽  
pp. 475-483 ◽  
Author(s):  
K. Bachmann ◽  
J. Byers ◽  
R. Ghosh
Keyword(s):  
Hepatic Clearance ◽  
Human Hepatocytes ◽  
Vitro Data ◽  
In Vitro Data

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.

Prediction of Hepatic Clearance in Humans from Experimental Animals and In Vitro Data

2003 ◽  
pp. 453-481
Author(s):  
Masato Chiba ◽  
Yuichi Sugiyama ◽  
Yasuyuki Ishii ◽  
Hiroyuki Takahashi ◽  
Yoshihiro Shibata
Keyword(s):  
Hepatic Clearance ◽  
Experimental Animals ◽  
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

scholarly journals Functional inhibition of osteoblastic cells in an in vivo mouse model of myeloid leukemia

Blood ◽  
2012 ◽  
Vol 119 (2) ◽  
pp. 540-550 ◽  
Author(s):  
Benjamin J. Frisch ◽  
John M. Ashton ◽  
Lianping Xing ◽  
Michael W. Becker ◽  
Craig T. Jordan ◽  
...  
Keyword(s):  
Bone Loss ◽  
Myeloid Leukemia ◽  
Serum Levels ◽  
Osteoblastic Cells ◽  
Novel Approach ◽  
Vitro Data ◽  
In Vitro Data ◽  
Marrow Cells

Pancytopenia is a major cause of morbidity in acute myeloid leukemia (AML), yet its cause is unclear. Normal osteoblastic cells have been shown to support hematopoiesis. To define the effects of leukemia on osteoblastic cells, we used an immunocompetent murine model of AML. Leukemic mice had inhibition of osteoblastic cells, with decreased serum levels of the bone formation marker osteocalcin. Osteoprogenitor cells and endosteal-lining osteopontin+ cells were reduced, and osteocalcin mRNA in CD45− marrow cells was diminished. This resulted in severe loss of mineralized bone. Osteoclasts were only transiently increased without significant increases in bone resorption, and their inhibition only partially rescued leukemia-induced bone loss. In vitro data suggested that a leukemia-derived secreted factor inhibited osteoblastic cells. Because the chemokine CCL-3 was recently reported to inhibit osteoblastic function in myeloma, we tested its expression in our model and in AML patients. Consistent with its potential novel role in leukemic-dependent bone loss, CCL-3 mRNA was significantly increased in malignant marrow cells from leukemic mice and from samples from AML patients. Based on these results, we propose that therapeutic mitigation of leukemia-induced uncoupling of osteoblastic and osteoclastic cells may represent a novel approach to promote normal hematopoiesis in patients with myeloid neoplasms.

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