Methotrexate Pharmacokinetics

Bischoff, Kenneth B.; Dedrick, Robert L.; Zaharko, Daniel S.; Longstreth, James

doi:10.1002/jps.2600600803

Cited by 458 publications

(156 citation statements)

References 11 publications

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“…During the 1960s and 1970s, Bischoff and Dedrick developed a number of PBPK models, particularly for anticancer drugs [5]. For a review of the early work on PBPK models see Himmelstein and Lutz [6].…”

Section: A Hierarchy Of Pharmacokinetic Modelsmentioning

confidence: 99%

Physiologically based pharmacokinetic modelling: a sound mechanistic basis is needed

Aarons

2005

Brit J Clinical Pharma

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Pharmacokinetics is the science of drug absorption, distribution, and elimination, or more specifically the quantification of those processes, leading to the understanding, interpretation, and prediction of blood concentration-time profiles. Occasionally, concentration-time data from other physiological fluids or tissues are available, but it is the lack of data in relevant tissues and organs that limits one's ability to get at the underlying mechanisms determining the blood profile. For example, blood concentration data are used to evaluate drug absorption for orally administered drugs, even though absorption is a multistep erratic process under the control of many factors, and measurements within the gut are not usually available.Nevertheless, blood concentration can be a useful biomarker, and sometimes a surrogate [1], to guide therapy. The idea is that pharmacokinetics accounts for some of the variability in the dose-response relationship. However, in order to transform dose into concentration, a pharmacokinetic model is required, based on an analysis of concentration-time data and preferably incorporating relevant patient characteristics, allowing it to be used for individualized therapy [2]. The complexity of a pharmacokinetic model depends on the level and quality of information available and on its purpose. A hierarchy of pharmacokinetic modelsPharmacokinetic models can be classified in order of increasing complexity. At the lowest level is the empirical model most often described by a sum of exponential terms, as in the following equation:This model adequately describes typical concentrationtime profiles and can be used to derive primary pharma- cokinetic parameters, such as clearance and half-life. It can also be used to devise a dosage regimen for a subject who has the same set of parameters [C i , λ i ]. Although useful for data description and interpolation, empirical models are very poor at extrapolation. This is because the parameters do not have a physiological interpretation, and it is difficult to predict how they change when the underlying physiology changes. For example, with a biexponential model after an intravenous bolus dose it is not obvious how the coefficients C 1 and C 2 change with age. This problem can be partly addressed by adopting a compartmental approach with a so-called physiological parameterization. A classical two-compartment model is shown in Figure 1. The concentration-time profiles that result from this model and a biexponential model are the same. However, with this model it is easier to relate the parameters to physiological processes. For example, clearance can be related to renal function, perhaps through creatinine clearance measurements, and the effect of renal impairment on the shape of the concentration-time profile can be predicted. Nevertheless, the compartments in these classical compartment models do not represent real physical spaces, and their meaning has been misrepresented by many authors. Consequently, these models should be viewed as semi-mechanistic mod...

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Section: A Hierarchy Of Pharmacokinetic Modelsmentioning

confidence: 99%

Physiologically based pharmacokinetic modelling: a sound mechanistic basis is needed

Aarons

2005

Brit J Clinical Pharma

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“…Today even very complicated PBPK/PT models can be rapidly solved using desktop personal computers with any of a variety of simulation languages. In another case of parallel development of new methods, scientists trained in chemical engineering began to develop more detailed PBPK models for the PK behavior of various drugs (Bischoff et al, 1971). Especially detailed contributions were made in the study of anti-neoplastic drugs, such as methotrexate (MTX) (Bischoff et al, 1971), 5-fluorouracil (Collins et al, 1982); and cisplatin (Farris et al, 1988).…”

Section: A Historical Perspectivementioning

confidence: 99%

“…In another case of parallel development of new methods, scientists trained in chemical engineering began to develop more detailed PBPK models for the PK behavior of various drugs (Bischoff et al, 1971). Especially detailed contributions were made in the study of anti-neoplastic drugs, such as methotrexate (MTX) (Bischoff et al, 1971), 5-fluorouracil (Collins et al, 1982); and cisplatin (Farris et al, 1988). These studies showed the ease with which realistic descriptions of physiology and of the relevant pathways of metabolism could be combined into PBPK descriptions of chemical disposition and paved the way for more extensive use of physiological modeling of tissue dosimetry, both in toxicology and in extrapolating tissue dosimetry from test animals to humans.…”

Section: A Historical Perspectivementioning

confidence: 99%

“…With this drug, tissue dosimetry is related to the extent of MTX binding to DHFR and binding is a measure both of chemotherapeutic efficacy and of expected cellular toxicity. Elegant physiological modeling of tissue dosimetry has been conducted with MTX (Bischoff et al, 1971;Morrison and Allegra, 1987). The earlier body of work with MTX formed a starting point for developing physiological models that included tissue binding for dioxin.…”

Section: A Pbpk Model For Dioxin */Early Approachesmentioning

confidence: 99%

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Toxicokinetic modeling and its applications in chemical risk assessment

Andersen

2003

Toxicology Letters

157

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“…Such a model ofdrug distribution could be termed 'physiological'; it would necessarily be complex and it would call for a considerable amount of information not readily available. Nevertheless, several models possessing some of these features have been described (Bischoff, Dedrick, Zaharko & Longstreth, 1971;Harrison & Gibaldi, 1977;Luecke & Wosilait, 1978) in order to improve upon more standard pharmacokinetic approaches to drugs such as digoxin and methotrexate.…”

Section: Introductionmentioning

confidence: 99%

'MacDope': a simulation of drug disposition in the human body: applications in clinical pharmacokinetics.

Bloch¹,

Sweeney²,

Ahmed³

et al. 1980

Brit J Clinical Pharma

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1 We have described a novel approach to absorption, distribution, metabolism and elimination of drugs in which the patient is described using 23 Patient Factors and drugs by up to 50 Drug Factors. Kinetic behaviour of a drug results from the interaction of patient and drug factors according to equations describing an eight compartment model. In this model non-linear processes (protein binding, hepatic drug metabolism and renal tubular transport) are handled by derivations of the law of mass action which have been generalised to permit the consequences of multiple drugs interacting at single macromolecular sites to be correctly calculated. 2 The mathematical description of this model is provided in a companion paper and solution of the equations is only possible using a digital computer. The computer programme is provided with an interactional format which makes operation independent of mathematical skills. Patients are defined by age, sex, height and weight with, or without, organ dysfunction; the programme then generates appropriate factors. Drug enters the system when a prescription is typed on the keyboard and required Drug Factors are then retrieved from the disc files. Drug concentrations in plaVma or body fluids are given as simple graphs as a function of time, or in tabular form. 3 Any of the Patient or Drug Factors may be altered before, or during a run and up to three drugs may be simulated at one time thus permitting certain kinetic interactions to be examined. The scope of the simulator is illustrated using aspirin: pH dependent gastric absorption, first-order conversion of aspirin to salicylate, partly first order and partly saturable hepatic metabolism of salicylate, and the complex renal handling of this drug are all represented. Interaction of phenytoin with salicylate has been examined quantitatively to suggest limited clinical relevance for the observed displacement of phenytoin from serum albumin. The use of the simulator in a short course of pharmacokinetics is briefly described.

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Methotrexate Pharmacokinetics

Cited by 458 publications

References 11 publications

Physiologically based pharmacokinetic modelling: a sound mechanistic basis is needed

Physiologically based pharmacokinetic modelling: a sound mechanistic basis is needed

Toxicokinetic modeling and its applications in chemical risk assessment

'MacDope': a simulation of drug disposition in the human body: applications in clinical pharmacokinetics.

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