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L B Sheiner

Publications and source records attributed to L B Sheiner.

At least 109 records · Page 6Linked to original sources
PubMed1982

Clearance of serum creatine kinase activity.

There is confusion regarding the calculation of serum creatine kinase (CK) activity clearance from an elimination rate constant and a distribution volume derived from one- and two-compartment serum enzyme elimination models. We measured serum CK activity clearance from hepatic enzyme extraction and compared this direct measurement with clearance calculated assuming one- and two-compartment elimination models after bolus and constant infusions of a purified preparation of the MM isoenzyme of CK (MM-CK) activity. Although serum CK activity appears to confer on the body the characteristics of first-order disposition from two compartments, clearance is estimated equally well by one-, two-, and noncompartmental models of disposition and is essentially identical to the hepatic clearance of CK activity. As long as the rate constant and distribution volume are compatible and appropriate for a given elimination model, clearance, the product of the two, will be properly estimated regardless of the model chosen.

Animals↗
PubMed1982

A noninvasive in vivo method of assessing the kinetics of halothane metabolism in humans.

The authors describe a noninvasive method of estimating the kinetic constants that characterize metabolism of inhaled anesthetics in humans. Ten healthy male volunteers breathed subanesthetic concentrations of halothane and isoflurane in a fixed inspired ratio of 20:1. Isoflurane served as a marker that identified changes in uptake in nonmetabolizing depots. Each study progressed through nine 30-min levels (numbered 0-8). At each level, inspired concentrations of both halothane and isoflurane were doubled, and alveolar concentrations and uptakes were determined. Clearance (uptake/alveolar concentration) of isoflurane remained constant over a range of concentrations of 0.00006 to 0.008%. In contrast, clearance of halothane decreased as the alveolar concentration increased from 0.0007 to 0.13%. On this basis, the authors assumed that the clearance of halothane was a combination of linear clearance to depots and saturable metabolism, the former proportional to the clearance of isoflurane, and the latter attributable to a Michaelis-Menten process. Applying such a model to halothane, they estimated the mean (+/- SE) Vmax (the composite maximum rate of metabolism) to be 0.79 +/- 0.09 ml . min-1 . individual-1, and the Km (the composite concentration at which half-saturation of enzymes occurs) to be 0.029 +/- 0.003%. This model provides a significantly better data fit than that provided by two simpler submodels, one of which assumes that all clearance is linear, and the other of which allows a part of clearance to be saturable but ignores the isoflurane marker data. The value of 0.029% for Km indicates that a wide range of clinical anesthetic concentrations will produce similar rates of metabolism; that metabolism will proceed at near maximum rates during the first several minutes of recovery; and that most metabolism probably occurs after, rather than during, anesthesia.

Adult↗
PubMed1982

Estimating population kinetics.

This paper will review the methods that have been advanced for the estimation of parameters of models quantifying the population characteristics of the kinetic behavior of endogenous and exogenous substances in individuals of the population. Such methods are used frequently, for example, in pharmacokinetic studies. In certain populations, especially biological ones, considerable kinetic variability between population members is present. The models with which we are concerned describe this variability. Some interindividual kinetic variability may be explainable on the basis of measureable concomitant variables, but much of it may remain unexplainable on such a basis. We give this matter particular attention. The assumptions underlying the models are critically discussed.

Analysis of Variance↗
PubMed1981

A standard approach to compiling clinical pharmacokinetic data.

A standard format for a Clinical Pharmacokinetic Summary is proposed. It consists of a heading, tables, notes, and references for each drug reviewed. The table presents a unified and logical set of clinically useful population pharmacokinetic parameters. They concern four major areas: absorption, distribution, elimination, and the relationship of concentration to effect. Within each major group, parameters dealing with extents and rates of processes are given. Each such parameter is really two: a population mea value (for example, average volume of distribution) and the standard deviation of individual values about this mean. The first value allows individual predictions of dosage or drug level to be made; the second allows computation of the likely proximity of subsequently observed quantities to those predictions. The table presents single consensus values for each population parameter, rather than a list of values. A procedure for computing these consensus values, and for revising them in the light of new data, or reinterpreted old data, is given. Examples of Summaries are given. The method appears applicable to a variety of drugs. We suggest our approach as a standard one for preparing Clinical Pharmacokinetic Summaries, and urge our colleagues to consider it for that purpose.

Bibliographies as Topic↗
PubMed1981

Some suggestions for measuring predictive performance.

The performance of a prediction or measurement model is often evaluated by computing the correlation coefficient and/or the regression of predictions on true (reference) values. These provide, however, only a poor description of predictive performance. The mean square prediction error (precision) and the mean prediction error (bias) provide better descriptions of predictive performance. These quantities are easily computed, and can be used to compare prediction methods to absolute standards or to one another. The measures, however, are unreliable when the reference method is imprecise. The use of these measures is discussed and illustrated.

Kinetics↗
PubMed1981

Evaluation of methods for estimating population pharmacokinetic parameters. II. Biexponential model and experimental pharmacokinetic data.

Individual pharmacokinetic parameters quantify the pharmacokinetics of an individual, while population pharmacokinetic parameters quantify population mean-kinetics, interindividual variability, and residual variability, including intraindividual variability and measurement error. Individual pharmacokinetics are estimated by fitting individual data to a pharmacokinetic model. Population pharmacokinetic parameters have been estimated either by fitting all individuals' data together as though there were no individual kinetic difference, the naive pooled data (NPD) approach, or by fitting each individuals' data separately and then combining the individual parameter estimates, the two stage (TS) approach. A third approach, NONMEM, takes a middle course between these. This study provides further evidence of NONMEM's validity by comparing, using simulation, the three approaches on three types of data sets corresponding to three typical types of pharmacokinetic studies. The estimates of population parameters provided by the NPD method are poorer than those provided by either of the other methods. The estimates provided by the TS method are adequate for mean values and for residual variability, but not for interindividual kinetic variability. NONMEM's estimates are as good as those of the TS method for mean parameters and for residual variability, and considerably better for interindividual variability. The latter estimates are still not acceptable in an absolute sense. This is probably due, not to an intrinsic fault of the method (as it is in the case of the TS approach), but to an insufficient number of individuals being studied.

Biopharmaceutics↗
PubMed1981

Predicting individual phenytoin dosage.

Most previously suggested methods for predicting phenytoin dosage from steady-state drug levels (Cpss) measured in the clinical setting fail to fully exploit all relevant (population) information. A bayesian prediction method, applicable to any drug, is available. It appropriately combines all types of information. In this paper, we compare the Bayesian method as applied to phenytoin to two other prediction methods (and a baseline, nonfeedback one). Actual doses are compared to predictions in 49 patients. Each method is optimized, as far as possible, for the test data. The comparison favors the Bayesian method. Since each of the other prediction methods for phenytoin can be shown to be a theoretically suboptimal special case of the Bayesian one, the superiority of the latter may be a general phenomenon. Because the pharmacokinetic model linking steady-state phenytoin levels and dosage is so simple, a good approximation of the general Bayesian method can be implemented as a graphical device, or as a program for a programmable calculator. We present and describe both of these approximations.

Feedback↗
PubMed1981

The effect of quinidine and its metabolites on the electrocardiogram and systolic time intervals: concentration--effect relationships.

1 A combined pharmacokinetic and pharmacodynamic model has been used to analyze the relationship between electrocardiographic (ECG) and systolic time intervals (STI) and changes in plasma concentration of quinidine after oral and i.v. doses in ten normal subjects. 2 The major effects of quinidine were on cardiac repolarization. Contrary to previous descriptions, we found no important change in the U wave, but the T wave was split into two peaks. The amplitude of these two peaks (T and T') was reduced, and the QT' peak and QT intervals were prolonged. The QT peak interval and systolic intervals did not change appreciably. There were small increases in the PQ and QRS intervals. 3 The effect of quinidine on the QT interval could be explained by a linear pharmacodynamic model. The equilibration between plasma and effect site had a half-time of 8 min. The slope of the pharmacodynamic model was 20.3 ms . mg 1(-1) after i.v. dosing and 33.5 ms . mg 1(-1) after oral dosing. 4 The difference in effect model slopes suggests pharmacologically active metabolites of quinidine are formed during absorption from the gut. 5 The total effect of a single oral dose of quinidine appears to be the same as the same dose given intravenously, even though only 70% of the oral dose reaches the systemic circulation as quinidine.

Biological Availability↗
PubMed1981

Pharmacokinetic and pharmacodynamic modeling in vivo.

A rational goal of clinical pharmacology is to described and predict the relationship between drug dose and drug effect. The processes involved in the dose-effect relationship can be described in two main categories - pharmacokinetics, which is concerned with factors affecting the dose-active site concentration process, and pharmacodynamics, which describes the active site concentration-effect process. The development of models of the dose-effect relationship will be described starting with dose-effect models which do not distinguish between pharmacokinetics and pharmacodynamics, progressing to models based upon pharmacokinetic predictions of the active site concentration, and finally describing models which combine both pharmacokinetic and pharmacodynamic models to predict both active site concentrations and the drug effect.

Body Fluid Compartments↗
PubMed1981

A clinical evaluation of various delta check methods.

To evaluate the performance of delta check techniques, we analyzed 707 unselected pairs of continuous-flow test results, using three different delta check methods. If any of the test results (plus the urea nitrogen/creatinine ratio and the anion gap) failed one of the checks, the reason for the failure was sought by examining subsequent test results, retesting specimens, and (or) reviewing te patient's chart. Each delta check failure was accordingly classified as a true or false positive. The percentage of positives we judged to be true positives ranged from 5 to 29%. Each of the three methods had test types with low and high percentages of true positives. We conclude that with the delta check methods one can detect errors otherwise overlooked, but at the cost of investigating many false positives, because, in the population we studied, disease processes or therapy often caused large changes in a series of test results for a patient.

Chemistry, Clinical↗
PubMed1980

Evaluation of methods for estimating population pharmacokinetics parameters. I. Michaelis-Menten model: routine clinical pharmacokinetic data.

Individual pharmacokinetic par parameters quantify the pharmacokinetics of an individual, while population pharmacokinetic parameters quantify population mean kinetics, interindividual variability, and residual intraindividual variability plus measurement error. Individual pharmacokinetics are estimated by fitting individual data to a pharmacokinetic model. Population pharmacokinetic parameters are estimated either by fitting all individual's data together as though there was no individual kinetic differences (the naive pooled data approach), or by fitting each individual's data separately, and then combining the individual parameter estimates (the two-stage approach). A third approach, NONMEM, takes a middle course between these, and avoids shortcomings of each of them. A data set consisting of 124 steady-state phenytoin concentration-dosage pairs from 49 patients, obtained in the routine course of their therapy, was analyzed by each method. The resulting population parameter estimates differ considerably (population mean Km, for example, is estimated as 1.57, 5.36, and 4.44 micrograms/ml by the naive pooled data, two-stage, and NONMEN approaches, respectively). Simulations of the data were analyzed to investigate these differences. The simulations indicate that the pooled data approach fails to estimate variabilities and produces imprecise estimates of mean kinetics. The two-stage approach produces good estimates of mean kinetics, but biased and imprecise estimates of interindividual variability. NONMEN produces accurate and precise estimates of all parameters, and also reasonable confidence intervals for them. This performance is exactly what is expected from theoretical considerations and provides empirical support for the use of NONMEM when estimating population pharmacokinetics from routine type patient data.

Adult↗
PubMed1980

Pyridostigmine kinetics with and without renal function.

Pyridostigmine kinetics were examined under conditions of clinical use as an antagonist of nondepolarizing neuromuscular blockade in anesthetized patients with and without renal function. Pyridostigmine serum levels were assayed by gas-liquid chromatography, and data were fitted to a 2-compartment kinetic model. Pyridostigmine kinetics following renal transplantation (n = 5) were not different from those in patients with normal renal function. Renal function (n = 5) elimination half-life increased from 112 +/- 12 min (mean +/- SD) to 379 +/- 162 min, and serum clearance decreased from 9 +/- 2 ml/kg/min to 2 +/- 0.6 ml/kg/min in anephric patients (n = 4). We conclude that renal function accounts for 75% of pyridostigmine clearance.

Adult↗
PubMed1980

Quantitative analysis of the disopyramide concentration-effect relationship.

1. A combined pharmacokinetic-pharmacodynamic model has been used to analyse the relationship between QT prolongation and changes in plasma concentration which occurred after disopyramide was given intravenously and orally to eight healthy subjects. 2. The pharmacokinetic models appropriate to intravenous and oral disopyramide have been extended by an 'effect compartment' which has no influence on the predetermined mass of drug in the body. 3. The model incorporates an adjustment for lag of effect behind any rapid changes in plasma concentration such as occur in the early distributive phase following intravenous administration. This permits calculation of the proportionality constant relating plasma concentration to effect. 4. Irrespective of the route of administration the mean (+/- s.d.) prolongation of the QT interval was 14.5 +/- 6.5 ms/micrograms ml-1. 5. There was no evidence that metabolite produced during first pass after oral administration made any significant contribution to effect. 6. This modelling technique should be applicable to the study of the concentration-effect relationship of a number of other drugs, both in health and in disease.

Administration, Oral↗
PubMed1979

Simultaneous modeling of pharmacokinetics and pharmacodynamics: application to d-tubocurarine.

We propose a model of drug pharmacodynamic response that when integrated with a pharmacokinetic model allows characterization of the temporal aspects of pharmacodynamics as well as the time-independent sensitivity component. The total model can accommodate extremes of effect. It allows fitting of simultaneous plasma concentration (Cp) and effect data from the initial distribution phase of drug administration, or from any non-equilibrium phase. The model postulates a hypothetical effect compartment, the dynamics of which are adjusted to reflect the temporal dynamics of drug effect. The effect compartment is modeled as an additional compartment linked to the plasma compartment by a first-order process, but whose exponential does not enter into the pharmacokinetic solution for the mass of drug in the body. The hypothetical amount of drug in the effect compartment is then related to the observed effect by the Hill equation, a nonlinear sigmoid form. Nonlinear least-squares data fitting is used for parameter estimation. The model is demonstrated on two different sets of Cp and effect data for the drug d-tubocurarine (dTC). In 7 normal subjects, the (mean +/- SD) rate constant for equilibration of dTC effect (paralysis) and Cp is 0.13 +/- 0.04 min-1 and the (mean +/- SD) steady-state Cp required to produce 50% paralysis is 0.37 +/- 0.05 microgram/ml.

Adult↗
PubMed1979

Forecasting individual pharmacokinetics.

Often drug dosage may be chosen rationally by use of plasma concentration (CP) as the "therapeutic" end point. The ability to accurately forecast the CP resulting from a dosage regimen is central to choosing that regimen. Tradionally forecasting has been attempted only by accounting for known influences on pharmacokinetics, such as sex, age, and renal disease. One must also adjust for previously observed CPs. Herein, we discuss and explain an approach to both of these tasks, mainly focusing on the latter. The approach balances observed outcomes against prior expectations taking account of observation CP error. For digoxin, use of 1 measured CP, as opposed to none, improves forecast precision for future CPs by 40% (decrement in variance of forecast error), and 2 CPs improve it by 67%. There is also an increase in forecast accuracy (decrement in mean of forecast error) as the number of CPs used increases. After only 2, forecast accuracy and precision are as good as theoretically possible. Moreover, information from CPs is far more valuable for forecasting than that from observable patient features-sex, age, and the like; use of all the latter information does not improve accuracy and precision as much as only 1 CP.

Adult↗
PubMed1979

Clinical estimation of creatinine clearance.

One hundred fifty-four 24-hour urine collections from 16 patients with stable renal function from whom careful urine collections were made were used to compare the "error" in determining renal function (creatinine clearance) when it is estimated using measured 24-hour creatinine excretion versus when creatinine excretion is predicted from serum creatinine, sex, age, and weight, using a simple estimation scheme. These "errors" were comparable (the coefficients of variation were 10% and 13%, respectively). Thus, the prediction scheme is as acceptable as direct measurement of creatinine excretion for purposes of estimating creatinine clearance in stable patients, and is simpler to perform. Two hundred twenty-two 24-hour urine collections from 86 patients having urine collections performed in a routine fashion were also analyzed in this manner. The routinely assessed patients demonstrated markedly greater intraindividual variability (coefficient of variation, 27%) in measured creatinine excretion than did the carefully studied patients (10%). The authors suspect that the excess variability was due to inaccurate urine collection. If so, the prediction scheme may also be acceptable in the routine clinical setting.

Adult↗