Biomedical subjects

D Verotta

Publications and source records attributed to D Verotta.

At least 19 recordsLinked to original sources

PubMed1992

Building population pharmacokinetic--pharmacodynamic models. I. Models for covariate effects.

One major task in clinical pharmacology is to determine the pharmacokinetic-pharmacodynamic (PK-PD) parameters of a drug in a patient population. NONMEM is a program commonly used to build population PK-PD models, that is, models that characterize the relationship between a patient's PK-PD parameters and other patient specific covariates such as the patient's (patho) physiological condition, concomitant drug therapy, etc. This paper extends a previously described approach to efficiently find the relationships between the PK-PD parameters and covariates. In a first step, individual estimates of the PK-PD parameters are obtained as empirical Bayes estimates, based on a prior NONMEN fit using no covariates. In a second step, the individual PK-PD parameter estimates are regressed on the covariates using a generalized additive model. In a third and final step, NONMEM is used to optimize and finalize the population model. Four real-data examples are used to demonstrate the effectiveness of the approach. The examples show that the generalized additive model for the individual parameter estimates is a good initial guess for the NONMEM population model. In all four examples, the approach successfully selects the most important covariates and their functional representation. The great advantage of this approach is speed. The time required to derive a population model is markedly reduced because the number of necessary NONMEM runs is reduced. Furthermore, the approach provides a nice graphical representation of the relationships between the PK-PD parameters and covariates.

Adult↗

PubMed1992

Elderly, conscious patients have an accentuated hypotensive response to nitroglycerin.

There is no adequate explanation for the highly variable response of systemic blood pressure to nitroglycerin (glyceryl trinitrate [GTN]). Aging produces cardiovascular changes that should alter the effects of GTN, but elderly patients usually have been excluded from studies of GTN. Accordingly, the authors compared the effects of GTN on systemic blood pressure in elderly and younger patients. Fifty-three patients, aged 49-87 (with 30 patients older than 70), were studied. Before elective vascular surgery, 14 patients received an infusion of placebo; 26, a constant infusion of GTN; and 13, a stepwise increasing infusion of GTN. After a standardized anesthetic induction and the start of surgery, the identical infusion protocols were repeated in each group. Data on GTN infusion rate, arterial blood pressure, and GTN concentrations versus time, age, and other potentially influencing variables were pooled for analysis. Before anesthesia and surgery, GTN more commonly caused excessive hypotension in patients older than 70 yr than in younger patients, but none of the patients had complications. A repeated-measures model analysis indicated that age significantly influenced the effects of GTN on blood pressure. That is, patients who are in their 70s who receive 0.5 micrograms.kg-1.min-1 of GTN are predicted to experience a twofold greater decrease in systolic arterial pressure (approximately 33 mmHg) than patients in their 50s. However, no apparent effect of age on intraoperative GTN responsiveness was discernible nor was a predictable relationship found between the preoperative and intraoperative responsiveness or between arterial concentrations of GTN and blood pressure or age. Therefore, the authors conclude that, in the absence of the effects of anesthesia and surgery, elderly patients have a more pronounced blood pressure response to GTN than younger patients. Furthermore, the authors conclude that preoperative blood pressure responsiveness to GTN is not a reliable predictor of intraoperative responsiveness.

Aged↗

PubMed1992

Comparing responses when each response is a curve.

We describe, generalize, and demonstrate the application of a method (W. H. Lawton, A. Sylvestre, and M. S. Maggio, Technometrics 14: 513-532, 1972) that can be used to partially analyze population data. The data from each subject consist of a series of responses observed at distinct values of a predictor variable. The method assumes that all subjects' data originate from a common process but differ because the "units" of predictor and response variables differ among subjects. For example, if the predictor variable is time, time can be "faster" or "slower" from subject to subject. We deal with two different problems. In the first one the response at x for the ith subject is of the form beta 1i + beta 2iG[(x - beta 3i)/beta 4i] + epsilon, where G(x) is a mathematical "shape" function (of the predictor variable x) representing the process and epsilon is observation error. The units of observed and predictor variable are then defined by the values of beta 1i, beta 2i and beta 3i, beta 4i, respectively. In particular beta 1i and beta 3i express shifts and beta 2i, beta 4i express scales of the observed and predictor variables, respectively. In the second problem the response at x for the ith subject is of the form beta 1i + beta 2i integral of x0 G[(s - beta 3i)/beta 4i].Hi(x - s) ds + epsilon, where Hi(x) is a known function. In both problems, the method estimates the common "shape" function G(x) nonparametrically and the parameters beta 1i, beta 2i, beta 3i, and beta 4i for each subject.(ABSTRACT TRUNCATED AT 250 WORDS)

Animals↗

PubMed1992

Effects of interleukin 3 and interleukin 6 on platelet recovery in mice treated with 5-fluorouracil.

We have studied the effects of murine recombinant interleukin 3 (IL-3) and human recombinant interleukin 6 (IL-6) on platelet recovery after administration of 5-fluorouracil (5-FU) to mice. 5-FU at 250 mg/kg body weight was administered as a single i.p. injection, and treatment with IL-3 alone, IL-6 alone, or a combination of IL-3 plus IL-6 was initiated immediately following the 5-FU or after a delay of 2 days. In addition, the effects of the combination of IL-3 plus IL-6 were evaluated following delays in initiation of their administration until 4 or 6 days after 5-FU treatment. In all schedules, the IL-3 and IL-6 treatments were discontinued 8 days following 5-FU. IL-3 and IL-6 were given s.c. three times daily; each injection of IL-3 was 80,000 U, each injection of IL-6 was 5000 U, and the combination comprised separate injections of IL-3 and IL-6 at the same respective doses. The combination of IL-3 and IL-6, initiated immediately or 2 days following 5-FU, diminished the platelet nadir and increased platelet counts on individual days during the recovery phase, thus apparently decreasing the time required for recovery to a normal platelet level. However, using self-modeling nonlinear regression, in order to analyze variability in the duration of thrombocytopenia, statistically significant shortening of the period of thrombocytopenia could not be consistently demonstrated. Neither IL-3 alone nor IL-6 alone had any effect on the above parameters. Recovery of hematocrit values and white blood cell levels was unaffected by administration of either IL-3 or IL-6 alone or the combination of both cytokines. We propose that IL-3 and IL-6 can act synergistically to enhance platelet recovery following 5-FU-mediated thrombocytopenia, but their modification of the response to 5-FU is modest.

Animals↗

PubMed1991

Semiparametric analysis of non-steady-state pharmacodynamic data.

We present an approach to the analysis of pharmacodynamic (PD) data arising from non-steady-state experiments, meant to be used when only PD data, not pharmacokinetic (PK) data, are available. The approach allows estimation of the steady-state relationship between drug input and effect. The analysis is based on a model describing the time dependence of drug effect (E) on (unobserved) drug concentration (Ce) in an hypothetical effect compartment. The model consists of (i) a known model for the input rate of drug I(t), (ii) a parametric model; L(t, alpha) (a function of time t, and vector of parameters alpha), relating I to an observed variable X, (iii) a nonparametric model relating X to E. Ce is proportional to X. X (t) is given by I(t) * L(t, alpha)/AL, where L(t, alpha) = e-alpha 1t * sigma k m = 1 alpha 2k e-alpha 2k + 1t, sigma k m = 1 alpha 2k = 1, AL = integral of 0 infinity L(t) dt, and * indicates convolution. The nonparametric model relating X to E is a cubic spline, a function of X and a vector of (linear) parameters beta. The values of alpha and beta are chosen to minimize the sum of squared residuals between predicted and observed E. We also describe a similar model, generalizing a previously described one, to analyze PK/PD data. Applications of the approach to different drug-effect relationships (verapamil-PR interval, hydroxazine-wheal and flare, flecainide and/or verapamil-PR, and left ventricular ejection fraction) are reported.

Computer Simulation↗

PubMed1991

Reversal of neuromuscular blockade in humans by neostigmine and edrophonium: a mathematical model.

Generalizations of the integrated model describing the interaction of nondepolarizing neuromuscular blocking drugs with reversible anticholinesterase drugs described in Unadkat et al. (1) are reported. The models can deal with possible incomplete reversal (irreversible block) and/or noninstantaneous anticholinesterase kinetics. Experimental data were obtained from 22 human volunteers. Different levels of steady-state vecuronium block were induced in each volunteer (in the range of 50% to 95%), and reversed by short infusions of edrophonium (10 volunteers) or neostigmine (12 volunteers). Edrophonium or neostigmine concentrations and twitch tension (measured as the force of thumb adduction) were measured. The generalized integrated models fit the data well. In the case of neostigmine we find a nondistributional delay in its action. We relate this delay to the slow decarbamylation rate of the (neostigmine-induced) carbamylated anticholinesterase observed in vitro, and are able to model such noninstantaneous anticholinesterase kinetic processes. For both edrophonium and neostigmine we detect an inverse relationship between the (induced) level of initial block and maximal percentage recovery.

Adult↗

PubMed1991

Mean time parameters for generalized physiological flow models (semihomogeneous linear systems).

This note gives expressions for recirculation mean time parameters of the disposition kinetics of particles in a semihomogeneous stationary linear system. In such a system each compartment may have an arbitrary single-pass disposition function, rather than a known parametric (usually monoexponential) one. Such systems provide a generalization of physiological flow models. Given observations of arterial blood concentrations and tissue amounts, and making the additional assumptions that (i) the fraction of total blood flow exiting each tissue that goes to each other tissue is constant and known, and (ii) the fraction of drug entering each tissue that is eliminated to the outside is constant and known, the input to each tissue can be known, and therefore both its total blood flow and its single-pass disposition function can be estimated. Recirculation mean time parameters can be computed from these estimates. Application to real thiopental data is presented as an example.

Mathematical Computing↗

PubMed1990

Comments on two recent deconvolution methods.

In a recent paper Vajda et al. presented a deconvolution method based on the assumptions that the response of a system and the input function to a system are described by first-order linear processes. The method is similar to one proposed by Veng-Pedersen, and obtains similar results. In this article a simpler, not new, and now generally available method for this special use is considered to point out potential risks associated with all three deconvolution methods.

Cimetidine↗

PubMed1990

An application of the D-optimal criterion to define the experimental design for a particular class of semi-parametric models.

An updated version of the computer program EXCAD [1] allows the user to optimize experimental design to estimate parameters of particular semi-parametric models. The semi-parametric models take the general form of a function of time (t): Y(t) = NL (c(t,alpha),beta). The function NL(C(t,alpha),beta), is, in general, a non-linear transformation of a function, C(t,alpha), that in turn is the convolution of two others. One of these two functions is expressed in a non-parametric form, and is not of direct interest to the experimenter. The other is of direct interest: it is a parametric function depending on a set of parameters alpha. This semi-parametric model applies to numerous kinds of biological experiments, such as pharmacokinetic/pharmacodynamic, physiological, circulatory flow experiments. This paper presents a new method for determining an optimal experimental design to estimate the parameters alpha and beta. The new approach adopts the D-optimal criterion, and is illustrated using real thiopental data.

Animals↗

PubMed1990

Comparative tissue concentration profiles of fentanyl and alfentanil in humans predicted from tissue/blood partition data obtained in rats.

The steady-state tissue/blood partition coefficients of fentanyl and alfentanil were determined in 13 organs and tissues in the rat. A 6-h infusion of both drugs was used in order to achieve steady-state. Blood and tissue concentrations of drugs were measured by gas-liquid chromatography. The partition coefficients of fentanyl were two- to 30-fold higher than those of alfentanil. These data were then used in a physiologic pharmacokinetic model describing the disposition of the two opioids in humans. The model predicted the plasma pharmacokinetics of these drugs in humans reasonably well. However, simulation beyond 24 h after a bolus administration showed a terminal half-life of 20 h for fentanyl, i.e., an elimination phase that has not yet been described in actual pharmacokinetic studies. In keeping with this, the volume of distribution of fentanyl in the model was also larger than expected. The simulated tissue concentration curves of fentanyl and alfentanil in humans could be used to explain the propensity of fentanyl to give secondary peaks in plasma concentration curves and the difference in effect kinetics between the two opioids. Physiologic pharmacokinetic modeling, based on measured data in small animals, can generate information that is not obtainable by empirical methods in humans.

Alfentanil↗

PubMed1989

An inequality-constrained least-squares deconvolution method.

The output-function (Y) of a linear system is the convolution of the input function (I) to the system with the disposition-function (H) of the system. Given Y and H deconvolution yields I. A non-parametric method for numerical deconvolution is described. The method is based on an inequality-constrained least-squares criterion and approximates I by a discontinuous function. No assumptions are made about the form of H or Y. Numerical stability and physical realism are obtained by constraining the estimated I to be nonnegative and piecewise-monotonic (nonincreasing, nondecreasing, or alternating segments of both). When I is constrained to be monotonic, the deconvolution yields a staircase function. The method can be used to calculate drug input rates. It is compared to previously published deconvolution methods for this purpose, using simulated data and real theophylline and pentobarbital data.

Models, Theoretical↗

PubMed1989

A semiparametric approach to physiological flow models.

By regarding sampled tissues in a physiological model as linear subsystems, the usual advantages of flow models are preserved while mitigating two of their disadvantages, (i) the need for assumptions regarding intratissue kinetics, and (ii) the need to simultaneously fit data from several tissues. To apply the linear systems approach, both arterial blood and (interesting) tissue drug concentrations must be measured. The body is modeled as having an arterial compartment (A) distributing drug to different linear subsystems (tissues), connected in a specific way by blood flow. The response (CA, with dimensions of concentration) of A is measured. Tissues receive input from A (and optionally from other tissues), and send output to the outside or to other parts of the body. The response (CT, total amount of drug in the tissue (T) divided by the volume of T) from the T-th one, for example, of such tissues is also observed. From linear systems theory, CT can be expressed as the convolution of CA with a disposition function, F(t) (with dimensions 1/time). The function F(t) depends on the (unknown) structure of T, but has certain other constant properties: The integral integral infinity0 F(t) dt is the steady state ratio of CT to CA, and the point F(0) is the clearance rate of drug from A to T divided by the volume of T. A formula for the clearance rate of drug from T to outside T can be derived. To estimate F(t) empirically, and thus mitigate disadvantage (i), we suggest that, first, a nonparametric (or parametric) function be fitted to CA data yielding predicted values, CA, and, second, the convolution integral of CA with F(t) be fitted to CT data using a deconvolution method. By so doing, each tissue's data are analyzed separately, thus mitigating disadvantage (ii). A method for system simulation is also proposed. The results of applying the approach to simulated data and to real thiopental data are reported.

Models, Biological↗

PubMed1989

The pharmacokinetics and pharmacodynamics of diltiazem and its metabolites in healthy adults after a single oral dose.

A potential complicating factor in the characterization of the pharmacokinetics and pharmacodynamics of diltiazem after an oral dose in the presence of two metabolites, N-demethyldiltiazem and desacetyldiltiazem, in plasma. Both N-demethyldiltiazem and desacetylditiazem have been shown to have pharmacologic activity in animal tissues. It is therefore possible that these metabolites contribute to the pharmacologic effect of diltiazem, but this possibility has not been explored. The purpose of this study was to investigate the pharmacokinetics and pharmacodynamics of diltiazem, N-demethyldiltiazem, and desacetyldiltiazem. Particular attention was paid to the effect of diltiazem on atrioventricular conduction. Six healthy men received a 120 mg oral dose of diltiazem. Concentrations of diltiazem, N-demethyldiltiazem, and desacetyldiltiazem in plasma and urine were measured by a sensitive HPLC method. Measures of pharmacologic response (heart rate, blood pressure, and PR interval) were obtained at each blood sampling time. Mean (+/- SD) peak plasma concentrations of diltiazem, N-demethyldiltiazem, and desacetyldiltiazem were 174.3 +/- 72.7, 42.6 +/- 10.0, and 14.9 +/- 3.3 ng/ml, respectively. The apparent half-lives of diltiazem, N-demethyldiltiazem, and desacetyldiltiazem were 6.5 +/- 1.4 hours, 9.4 +/- 2.2 hours, and 18 +/- 6.2 hours, respectively. Both N-demethyldiltiazem and diltiazem were eliminated by net secretion, whereas the renal clearance of desacetyldiltiazem did not exceed clearance by filtration. Both N-demethyldiltiazem and desacetyldiltiazem are bound to plasma proteins, with unbound fractions of 0.323 +/- 0.035 and 0.230 +/- 0.021. These values are similar to the unbound fraction of diltiazem (0.254 +/- 0.027). No significant effect of diltiazem on blood pressure or heart rate was noted. However, a prolongation of the PR interval was observed in all six subjects. Furthermore, an apparent clockwise hysteresis in the concentration-effect relationship was found in four of the six subjects. These findings suggest that some form of acute tolerance to the electrophysiologic effect of diltiazem develops, but the results of pharmacodynamic modeling suggest that this is not caused by the antagonistic effects the metabolites.

Administration, Oral↗

PubMed1989

Semiparametric approach to pharmacokinetic-pharmacodynamic data.

A semiparametric model for analysis of pharmacokinetic (PK) and pharmacodynamic (PD) data arising from non-steady-state experiments is presented. The model describes time lag between drug concentration in a sampling compartment, e.g., venous blood (Cv), and drug effect (E). If drug concentration at the effect site (Ce) equilibrates with arterial blood concentration (Ca) slower than with Cv, a non-steady-state experiment yields E vs. Cv data describing a counterclockwise hysteresis loop. If Ce equilibrates with Ca faster than with Cv, clockwise hysteresis is observed. To model hysteresis, a parametric model is proposed linking (unobserved) Ca to Cv with elimination rate constant kappa ov and also linking Ca to Ce with elimination rate constant kappa oe. When kappa oe is greater than (or less than) kappa ov clockwise (or counterclockwise) hysteresis occurs. Given kappa oe and kappa ov, numerical (constrained) deconvolution is used to obtain the disposition function of the arterial compartment (Ha), and convolution is used to calculate Ce given Ha. The values of kappa oe and kappa ov are chosen to collapse the hysteresis loops to single curves representing the Ce-E (steady-state) concentration-response curve. Simulations, and an application to real data, are reported.

Humans↗

PubMed1989

Pharmacodynamic modeling of verapamil effects under steady-state and nonsteady-state conditions.

Pharmacodynamic models relating the plasma concentration (Cp) of verapamil to the drug's effect (E) on the P-R interval were investigated after single dose infusions of (0.15-0.22 mg/kg) verapamil in 22 normal subjects. Model predictions of the steady-state Cp-E relationship were then compared to results from actual steady-state drug infusions in the same subjects. Two methods of estimating the steady-state concentration response relationship from the single dose data were examined: 1) the relationship of descending limb Cp vs. E and 2) the relationship of estimated effect site concentrations (Ce) vs. E. When compared to experimental steady-state measurements, the absolute errors of predictions from the Ce vs. E method were less than those from the Cp vs. E predictions (6.8 +/- 4.4 vs. 9.6 +/- 6.6, mean +/- S.D.). Similarly, the slope of the linear regression of E on Cp differed more from the observed steady-state slope than the slope of E on Ce. Sigmoid Emax models fit to Cp vs. E. data gave false Emax values even when data immediately following drug infusion were disregarded whereas Ce vs. E plots demonstrated that Emax was not reached (and Ce much less than Cp). Neither the postinfusion (descending limb) Cp vs. E nor Ce vs. E plots allowed analysis of higher concentration vs. effect relationships after usual (0.15-0.22 mg/kg) doses of verapamil. In summary, we have demonstrated that nonsteady-state postdrug infusion effect vs. plasma concentration data for verapamil does not reflect the true steady-state relationship and that use of a model to estimate effect site concentration provides a closer estimate of the true steady-state relationship.

Adult↗

PubMed1988

A new criterion for selection of pharmacokinetic multiexponential equations.

In linear pharmacokinetics, the time course of the plasma concentration of a drug, Ct, is expressed by the sum of exponential terms, (formula; see text) This article proposes a new statistical criterion for discriminating between alternate polyexponential models. According to this new criterion, the model that best interprets a set of experimental data points is that which minimizes the area between the approximate confidence limits of Ct.

Doxorubicin↗

PubMed1988

D-optimal design applied to binding saturation curves of an enkephalin analog in rat brain.

The D-optimal design, a minimal sample design that minimizes the volume of the joint confidence region for the parameters, was used to evaluate binding parameters in a saturation curve with a view to reducing the number of experimental points without loosing accuracy in binding parameter estimates. Binding saturation experiments were performed in rat brain crude membrane preparations with the opioid mu-selective ligand [3H]-[D-Ala2,MePhe4,Gly-ol5]enkephalin (DAGO), using a sequential procedure. The first experiment consisted of a wide-range saturation curve, which confirmed that [3H]-DAGO binds only one class of specific sites and non-specific sites, and gave information on the experimental range and a first estimate of binding affinity (Ka), capacity (Bmax) and non-specific constant (k). On this basis the D-optimal design was computed and sequential experiments were performed each covering a wide-range traditional saturation curve, the D-optimal design and a splitting of the D-optimal design with the addition of 2 points (+/- 15% of the central point). No appreciable differences were obtained with these designs in parameter estimates and their accuracy. Thus sequential experiments based on D-optimal design seem a valid method for accurate determination of binding parameters, using far fewer points with no loss in parameter estimation accuracy.

Animals↗

PubMed1987

Pharmacodynamic modeling of the EEG effects of ketamine and its enantiomers in man.

The pharmacodynamics of a racemic mixture of ketamine R,S(+/-)-ketamine and of each enantiomer, S(+)-ketamine and R(-)-ketamine, were studied in five volunteers. The median frequency of the electroencephalogram (EEG) power spectrum, a continuous noninvasive measure of the degree of central nervous system (CNS) depression (pharmacodynamics), was related to measured serum concentrations of drug (pharmacokinetics). The concentration-effect relationship was described by an inhibitory sigmoid Emax pharmacodynamic model, yielding estimates of both maximal effect (Emax) and sensitivity (IC50) to the racemic and enantiomeric forms of ketamine. R(-)-ketamine was not as effective as R,S(+/-)-ketamine or S(+)-ketamine in causing EEG slowing. The maximal decrease (mean +/- SD) of the median frequency (Emax) for R(-)-ketamine was 4.4 +/- 0.5 Hz and was significantly different from R,S(+/-)-ketamine (7.6 +/- 1.7 Hz) and S(+)-ketamine (8.3 +/- 1.9 Hz). The ketamine serum concentration that caused one-half of the maximal median frequency decrease (IC50) was 1.8 +/- 0.5 micrograms/mL for R(-)-ketamine; 2.0 +/- 0.5 micrograms/mL for R,S(+/-)-ketamine; and 0.8 +/- 0.4 microgram/mL for S(+)-ketamine. Because the maximal effect (Emax) of the R(-)-ketamine was different from that of S(+)-ketamine and R,S(+/-)-ketamine, it was not possible to directly compare the potency (i.e., IC50) of these compounds. Accordingly, a classical agonist/partial-agonist interaction model was examined, using the separate enantiomer results to predict racemate results. Although the model did not predict racemate results well, its failure was not so great as to provide clear evidence of synergism (or excess antagonism) of the enantiomers.

Adult↗