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Biomedical subjects

A Forrest

Publications and source records attributed to A Forrest.

At least 37 records · Page 2Linked to original sources
PubMed1998

Pharmacodynamic interactions of antibiotics alone and in combination.

Clinical trials show that the area under the inhibitory curve (AUIC) is predictive of antibacterial killing rates in patients with nosocomial pneumonia and is useful for predicting clinical or microbiological outcomes and making dosage adjustments with beta-lactams, quinolones, aminoglycosides, and vancomycin. The AUIC values of two antibiotics are additive, and since antibiotics are often given in combination, determining the AUIC for antibiotic combinations could potentially predict the microbiological outcomes for patients given these combinations. To further address this question, mathematical modeling was used to study in vitro pharmacokinetic and pharmacodynamic interactions of the antimicrobials piperacillin and ciprofloxacin. These agents were also studied in vivo in healthy volunteers. Blood samples were obtained for analysis of serum drug concentrations, and serum inhibitory titers were determined against eight common bacterial pathogens, chosen to reflect the range of MIC values to ciprofloxacin and piperacillin. Additive AUIC relationships predictive of bacterial killing rates were typical in patients given these antibiotics in combination.

Anti-Bacterial Agents↗
PubMed1998

Pharmacodynamic evaluation of factors associated with the development of bacterial resistance in acutely ill patients during therapy.

The selection of bacterial resistance was examined in relationship to antibiotic pharmacokinetics (PK) and organism MICs in the patients from four nosocomial lower respiratory tract infection clinical trials. The evaluable database included 107 acutely ill patients, 128 pathogens, and five antimicrobial regimens. Antimicrobial pharmacokinetics were characterized by using serum concentrations, and culture and sensitivity tests were performed daily on tracheal aspirates to examine resistance. Pharmacodynamic (PD) models were developed to identify factors associated with the probability of developing bacterial resistance. Overall, in 32 of 128 (25%) initially susceptible cases resistance developed during therapy. An initial univariate screen and a classification and regression tree analysis identified the ratio of the area under the concentration-time curve from 0 to 24 h to the MIC (AUC[0-24]/MIC) as a significant predictor of the development of resistance (P < 0.001). The final PK/PD model, a variant of the Hill equation, demonstrated that the probability of developing resistance during therapy increased significantly when antimicrobial exposure was at an AUC[0-24]/MIC ratio of less than 100. This relationship was observed across all treatments and within all organism groupings, with the exception of beta-lactamase-producing gram-negative organisms (consistent with type I beta-lactamase producers) treated with beta-lactam monotherapy. Combination therapy resulted in much lower rates of resistance than monotherapy, probably because all of the combination regimens examined had an AUC[0-24]/MIC ratio in excess of 100. In summary, the selection of antimicrobial resistance appears to be strongly associated with suboptimal antimicrobial exposure, defined as an AUC[0-24]MIC ratio of less than 100.

Acute Disease↗
PubMed1998

Pharmacodynamic interactions of ciprofloxacin, piperacillin, and piperacillin/tazobactam in healthy volunteers.

Mathematical modeling methods were used to study pharmacokinetic and pharmacodynamic interactions of the antimicrobial combinations piperacillin plus ciprofloxacin and piperacillin plus tazobactam. Twelve healthy volunteers received the following treatments: piperacillin (4 g), ciprofloxacin (400 mg), piperacillin (4 g) plus ciprofloxacin (400 mg), and piperacillin (4 g) plus tazobactam (0.5 g), via intravenous infusion in a four-period crossover design. Serum drug concentrations were analyzed by means of high-performance liquid chromatography (HPLC), and inhibitory titers were performed against eight organisms. The pharmacodynamic response (growth or no growth) was modeled for each of the monotherapy courses using a Hill-type model where Emax was 1 (100% probability of no growth [P(NG)]), and EC50 was the concentration associated with a 50% P(NG). For piperacillin plus ciprofloxacin, P(NG) was a function of 1) plasma concentrations for both drugs; 2) EC50 values from the monotherapy courses; and 3) theta, an interaction term that accommodates synergy, additivity, or antagonism. For piperacillin/tazobactam, the serum ultrafiltrate area under the inhibitory curve was compared with that of piperacillin alone to determine the benefit of tazobactam. The interaction between piperacillin and ciprofloxacin was additive. The addition of tazobactam to piperacillin was beneficial against certain organisms. The model developed can be used to evaluate the activity of combination regimens against representative pathogens.

Adolescent↗
PubMed1997

Pharmacokinetics and pharmacodynamics of midazolam after intranasal administration.

This study aimed to characterize the pharmacokinetics and pharmacodynamics of midazolam after intranasal administration to healthy volunteers. Eight participants were given 0.25 mg/kg intranasally and 2 mg intravenously in a randomized, crossover fashion. Blood samples for determination of plasma concentrations of midazolam and measures of cognitive function (using the digit symbol substitution test) were obtained at baseline and 5, 10, 20, 30, 45, 60, 90, 120, 180, 240, and 360 minutes after administration of study medications. Plasma samples were analyzed by gas chromatography (% coefficient of variation < 10%). Pharmacokinetic data were fitted using iterative two-stage analysis to a two-compartment model. Pharmacodynamic data were fitted by a baseline subtraction Hill-type model. The mean (SD) for total clearance, distributional clearance, volume of distribution in the central compartment, volume of distribution in the peripheral compartment, absorption rate constant, bioavailability, and half-life were 0.57 (0.26) L/hr/kg, 0.31 (0.29) L/hr/kg, 0.27 (0.14) L/kg, 0.67 (0.11) L/kg, 2.46 (1.72) hr-1, 50% (13%), and 3.1 (0.84) hours, respectively. The mean (SD) for the concentration at which the effect is half maximal (EC50) and the maximal effect or the maximal change in effect measure from baseline (Emax) were 63.1 (21.2) ng/mL and 52.8 (21.1) correct substitutions, respectively. After intranasal administration, midazolam concentrations rapidly achieve values considered sufficient to induce conscious sedation and produce predictable changes in digit symbol substitution score.

Administration, Intranasal↗
PubMed1997

Population pharmacokinetics and pharmacodynamics of pegylated-liposomal doxorubicin in patients with AIDS-related Kaposi's sarcoma.

OBJECTIVE: To characterize the population pharmacokinetics of pegylated-liposomal doxorubicin in patients with acquired immunodeficiency disease (AIDS)-related Kaposi's sarcoma and to explore the relationship between response of the cutaneous Kaposi's sarcoma lesions to treatment and measures of drug exposure. METHODS: Forty-three male patients (median age, 40 years; age range, 28 to 50 years), body surface area, 1.89 m2; range, 1.5 to 2.3 m2) with AIDS and at least five biopsy-proven cutaneous Kaposi's sarcoma lesions were randomized to receive either a 10 or 20 mg/m2 dose of study drug for their first cycle and the alternate dose 3 weeks later. Patients continued to receive the study drug at a dose of 20 mg/m2 every 3 weeks. Serial blood samples were obtained after the first two doses and analyzed by HPLC for determination of total plasma doxorubicin concentration. Kaposi's sarcoma lesion response was categorized as either progressive disease, stable disease, partial response, or complete response. Classification and regression tree (CART) analysis was used to determine the relationship between drug exposure and categorical lesion response. Iterative two-stage analysis was used to characterize both the pharmacokinetics of pegylated-liposomal doxorubicin and to model the probabilities of achieving a specific lesion response. RESULTS: The pharmacokinetics of pegylated-liposomal doxorubicin were best described by a two-compartment linear structural model. Lesion response was significantly related to both the average daily maximum doxorubicin concentration (Cmax,avg) and dose intensity. CONCLUSIONS: The pharmacokinetics of pegylated-liposomal doxorubicin are strikingly different from conventional doxorubicin. Identification of both Cmax,avg and dose intensity as predictors of lesion response will provide guidelines for future dosing regimen designs.

Acquired Immunodeficiency Syndrome↗
PubMed1997

Pharmacokinetics and pharmacodynamics of oral grepafloxacin in patients with acute bacterial exacerbations of chronic bronchitis.

This analysis was designed to characterize the population pharmacokinetics and pharmacodynamics of oral grepafloxacin (OPC-17,116) in patients with acute bacterial exacerbations of chronic bronchitis (ABECB). The study group included 76 patients (43 male, 33 female) between 23 and 81 years of age, who were part of a multicentre, randomized, double-blind, dose-response study. Patients were randomly assigned to receive oral regimens of grepafloxacin, 200, 400 or 600 mg, each administered once daily for 14 days. Plasma samples for drug assay (typically eight per subject; four samples on either day 3, 4 or 5, plus troughs on other clinic visit days), were obtained during treatment. Population pharmacokinetic analysis was accomplished using iterative two-stage analysis. Cultures and quantitative Gram stains from serial 24 h collections of sputum were used to determine the time (in days) taken to eradicate each bacterial strain. Population pharmacodynamic analysis was performed for three measures of antibacterial response: probability of bacteriological cure, probability of clinical cure, and time to eradication. Grepafloxacin plasma concentration profiles were best fitted by a pharmacokinetic model with first-order absorption following a lag time between administration of the dose and onset of systemic absorption. All three measures of response were strongly related to the 24 h AUIC (AUC/MIC). At an AUIC of <75, the percent probability of clinical cure was 71%; at an AUIC of 75-175, it was 80% (P < 0.05) and at an AUIC of >175, it was 98% (P < 0.01). In conclusion, antibacterial response for grepafloxacin in ABECB patients was highly related to AUIC; values of <75 appear inadequate and values of >175 were optimal.

Administration, Oral↗
PubMed1997

Pharmacodynamic modeling of the in vivo interaction between cefotaxime and ofloxacin by using serum ultrafiltrate inhibitory titers.

The pharmacokinetics (PK) and pharmacodynamics (PD) of cefotaxime and ofloxacin and of their combination were examined in a three-period randomized crossover study involving 12 healthy adults. The PK of cefotaxime and ofloxacin were modeled. PD was assessed from the predicted concentrations in serum and serum untrafiltrate inhibitory titers for 10 test organisms. An inhibitory sigmoid Emax model based on the probability of bacterial growth was used, where Emax = 1 and EC50 is the concentration resulting in a 50% probability of growth. The total body clearance (CL(T)) and volume of distribution at steady state (V(SS)) for cefotaxime were 0.236 liters/kg/h and 0.207 liters/kg, respectively, for the monotherapy and 0.231 liters/kg/h and 0.208 liters/kg for the combination therapy. Ofloxacin exhibited PK parameters of 0.143 liters/kg/h for CL(T) and 1.20 liters/kg for V(SS) following the monotherapy and of 0.141 liters/kg/h for CL(T) and 1.16 liters/kg for V(SS) following combination therapy. For the combination therapy, an interaction term, theta, defined the type and relative extent of interaction. The range of observed theta values (-0.033 to 0.067) is consistent with an additive PD interaction according to standards similar to those used for the in vitro fractional inhibitory concentration index.

Adult↗
PubMed1997

Modeling the response of pneumonia to antimicrobial therapy.

The response to antimicrobial therapy in patients with pneumonia was assessed by using a previously developed pneumonia scoring system. Patients from two different clinical trials were evaluated. The first group (n = 22) was treated with cefmenoxime. For these patients, doses were adjusted to achieve an area under the plasma concentration-versus-time curve (AUC) above the MIC of 140 microg x h/ml and pneumonia response scores were evaluated retrospectively. The second group (n = 21) were treated with either ciprofloxacin (CIP) or ceftazidime (TAZ) in a randomized clinical trial. Here, doses were adjusted to achieve AUC from 0 to 24 h/MIC values that were > 250 SIT(-1) x h (estimate of the area under the curve of inverse serum inhibitory titer versus time) and pneumonia response scoring was concurrent. In both studies eradication of the pathogen was determined by serial endotracheal cultures and clinical parameters were scored daily. A decrease in total score was indicative of an improving clinical condition. The percent change in clinical daily score was determined for each day of treatment. The rate of clinical response was determined by linear regression of the percent change in daily clinical score versus time during the course of antimicrobial therapy. Factors predictive of time to eradication were explored by interval analysis. Logistic regression was used to determine the earliest time point in therapy at which treatment scores predicted outcome. Kruskal-Wallis analysis of variance was used for statistical analysis, and significance was accepted at P < 0.05. There were no differences in baseline scores at day one for the patients treated with different antibiotics (P = 0.58). For patients with pathogen eradication, a significant difference between the two studies in time to eradication was found: 4.8 days for cefmenoxime-treated patients and 1.4 days for CIP- or TAZ-treated patients (P < 0.001). For patients experiencing bacterial eradication, the rates of clinical change for cefmenoxime and CIP or TAZ treatment were similar (P = 0.77). For patients with organisms that were not eradicated, the rates of change were similar (P = 0.14). There was a significant difference in the rate of change for patients experiencing eradication compared with that for patients in which the organism persisted (P << 0.01). Both treatment group and rate were found to be predictive of days to eradication. There was a significant difference in the percent change in clinical score on day 3 of therapy for patients with bacteria that were eradicated versus those with persistent organisms (P < 0.01). The percent change was more predictive of outcome with each subsequent day. Patients who demonstrated a > or = 10% reduction in clinical score after 72 h of treatment had an 88% probability of bacterial eradication. The clinical scoring system is a useful tool for modeling the response of pneumonia to antimicrobial therapy. The ability to predict outcome relatively early in therapy, by using a scoring system of clinical parameters which can be routinely monitored, will aid in assessing the response to antimicrobial therapy in clinical as well as in research settings.

Anti-Infective Agents↗
PubMed1997

Evaluation of a sparse sampling strategy for determining vancomycin pharmacokinetics in preterm neonates: application of optimal sampling theory.

OBJECTIVE: To use optimal sampling theory to determine the fewest vancomycin concentrations required and the appropriate sampling times to calculate vancomycin pharmacokinetic parameters in neonates. DESIGN: Unblinded evaluation in neonates with presumed sepsis. SETTING: Level 3 community-based neonatal intensive care unit. PATIENTS: Eleven neonates with presumed sepsis. INTERVENTIONS: Twelve courses of intravenous vancomycin 20 mg/kg were administered. Blood samples were collected 3 and 9 hours after initiation of a 1-hour infusion of the first dose. MEASUREMENTS AND MAIN RESULTS: A two-compartment model was fit to vancomycin concentrations using iterative two-stage analysis. Pharmacokinetic parameter estimates were used for determination of optimal sampling times for two-, three-, and four-sample strategies with subsequent generation of two-, three-, and four-sample concentration data for 100 cases. Relative performance of strategies was compared through calculation and comparison of D efficiency for the determined strategies. Bias (median percent error) and precision (median percent absolute error) of pharmacokinetic parameter estimates for each strategy in the 100 simulated cases were determined. CONCLUSIONS: For estimation of total clearance and volume in the central and peripheral compartments, all strategies performed similarly with no difference in efficiency or bias and precision of estimates. Our results suggest that for clinical evaluations two appropriately timed samples (0.5 h after a 1-h infusion, trough concentration) are adequate for estimation of vancomycin clearance in neonates.

Aminoglycosides↗
PubMed1997

In nosocomial pneumonia, optimizing antibiotics other than aminoglycosides is a more important determinant of successful clinical outcome, and a better means of avoiding resistance.

In in vitro and animal models, antibiotics show good relationships between concentration and response, when response is quantified as the rate of bacterial eradication. The strength of these in vitro relationships promises their utility for dosage regimen design and predictable cure of infections such as nosocomial pneumonia. In spite of their intuitive logic, close relationships between dosage and bacterial eradication have not been easy to show in clinical studies of nosocomial pneumonia. Presumably, a variety of patient, disease, bacterial, and pharmacokinetic variables cloud these relationships in patients, and delay their elucidation in patient trials. Patients with serious infections like nosocomial pneumonia require bactericidal antimicrobial activity. Studies in our laboratory show that the minimum effective antimicrobial action is an area under the inhibitory titer (AUIC) of 125, in which AUIC is calculated as the 24 hour serum area under the curve (AUC) divided by the minimum inhibitory concentration (MIC) of the pathogen. This target AUIC may be achieved with either a single antibiotic or it can be the sum of AUIC values of two or more antibiotics. There is considerable variability in the actual AUIC value for patients when antibiotics are administered in their usual recommended dosages. Examples of this variance will be provided using aminoglycosides, fluoroquinolones, and beta-lactams. The achievement of minimally effective antibiotic action, consisting of an AUIC of at least 125, is associated with bacterial eradication in about 7 days for beta-lactams and quinolones. Adding an aminoglycoside to beta-lactams may produce a slight increase in their rate of bacterial killing in vivo, but because of their narrow therapeutic window, and the associated low doses in relation to MIC, there are situations in which the aminoglycosides may be unable to add sufficient additional AUIC. Antibiotic activity indices allow clinicians to evaluate individualized patient regimens. Furthermore, antibiotic activity is a predictable clinical endpoint with predictable clinical outcome. This value also is highly predictive of the development of bacterial resistance. Antimicrobial regimens that do not achieve an AUIC of at least 125 cannot prevent the selective pressure that leads to overgrowth of resistant bacterial subpopulations. The methods based on the determination of AUIC have clinical applicability in routine practice, through software developed for this purpose. These indices can assist with patient management strategies in a prospective manner because they can identify patients at high risk of therapeutic failure or acquired resistance early in therapy before therapy fails. Our studies show that calculations of AUIC can be used to prospectively target regimens to improve the chances of cure with nosocomial pneumonia and other serious infections. A clinical intervention team has been organized to optimize antimicrobial regimens as early in therapy as possible, to lower the high cost events such as failure and acquired bacterial resistance.

Aminoglycosides↗
PubMed1996

Pharmacodynamic analysis of sparse data from concentration- and effect-controlled clinical trials guided by a pilot study. An investigation by simulations.

The purpose of this investigation was to explore, by computer simulation, the utility of two different clinical trial designs with sparse sampling (three concentration--effect measurements per subject) for population pharmacodynamic studies when the targeted drug concentration or effect measurements are determined by application of optimal sampling theory based on the results of a preceding, data-intensive pilot study. The two design paradigms were concentration-controlled and pharmacologic effect-controlled randomized clinical trials, respectively. The drug concentration--pharmacologic effect relationship was assumed to be describable by the Hill (sigmoid Emax) equation without hysteresis. Intersubject variability was represented by coefficients of variation of 30, 40, and 30% for Emax, EC50, and gamma, respectively. Random controller imprecision and measurement errors were included. Concentration and effect data for 100 subjects were generated by Monte Carlo simulation (ADAPT II), and pharmacodynamic parameter values were obtained by iterative two-stage analysis. These were then used to predict effect intensities over a range of drug concentrations, and the results were compared with those obtained by use of the true parameter values. Concentration- and effect-controlled trial designs were simulated in two forms: unconstrained and constrained with respect to the highest allowed targeted drug concentration or effect intensity. It was found that both types of unconstrained trials yielded good and comparable parameter estimates whereas the constrained trials (which are clinically more realistic) yielded more biased and imprecise estimates of individual pharmacodynamic parameters. Nevertheless, use of the latter to determine the effect intensities produced by different drug concentrations yielded good estimates but only in the range covered by the targeted concentration or effect measurements. For concentration-controlled trials it appears essential that the individuals in the pilot group and the clinical study group be drawn from the same population. Effect-controlled trials gave good results even when the pilot group was not representative of the population (e.g., for an aberrant subpopulation).

Clinical Trials as Topic↗
PubMed1996

Development and evaluation of a Bayesian pharmacokinetic estimator and optimal, sparse sampling strategies for ceftazidime.

Data were gathered during an activity-controlled trial in which seriously ill, elderly patients were randomized to receive intravenous ceftazidime or ciprofloxacin and for which adaptive feedback control of drug concentrations in plasma and activity profiles was prospectively performed. The adaptive feedback control algorithm for ceftazidime used an initial population model, a maximum a posteriori (MAP)-Bayesian pharmacokinetic parameter value estimator, and an optimal, sparse sampling strategy for ceftazidime that had been derived from data in the literature obtained from volunteers. Iterative two-stage population pharmacokinetic analysis was performed to develop an unbiased MAP-Bayesian estimator and updated optimal, sparse sampling strategies. The final median values of the population parameters were follows: the volume of distribution of the central compartment was equal to 0.249 liter/kg, the volume of distribution of the peripheral compartment was equal to 0.173 liter/kg, the distributional clearance between the central and peripheral compartments was equal to 0.2251 liter/h/kg, the slope of the total clearance (CL) versus the creatinine clearance (CLCR) was equal to 0.000736 liter/h/kg of CL/1 ml/min/1.73 m2 of CLCR, and nonrenal clearance was equal to + 0.00527 liter/h/kg. Optimal sampling times were dependent on CLCR; for CLCR of > or = 30 ml/min/1.73 m2, the optimal sampling times were 0.583, 3.0, 7.0, and 16.0 h and, for CLCR of < 30 ml/min/1.73 m2, optimal sampling times were 0.583, 4.15, 11.5, and 24.0 h. The study demonstrates that because pharmacokinetic information from volunteers may often not be reflective of specialty populations such as critically ill elderly individuals, iterative two-stage population pharmacokinetic analysis, MAP-Bayesian parameter estimation, and optimal, sparse sampling strategy can be important tools in characterizing their pharmacokinetics.

Adult↗
PubMed1995

Effect of aging on atenolol pharmacokinetics and pharmacodynamics.

A study was conducted to characterize and compare the pharmacodynamics and pharmacokinetics of atenolol in young and elderly men. Six young (mean +/- SD, 25.0 +/- 3.0 years) and six elderly (63.0 +/- 3.2 years) healthy men took atenolol 100 mg orally once daily for 6 days. Heart rate response to submaximal exercise was measured at selected times for 48 hours, and plasma and urine samples were collected over the same time interval. The Sigmoid Emax model was fit to percent reductions in exercise heart rate and atenolol plasma concentrations. The younger men had significantly lower values for area under the steady-state plasma concentration-time curve and higher values for systemic clearance/F and renal clearance. EC50 values showed a trend toward greater sensitivity to the negative chronotropic effects of atenolol among the elderly men. Model-derived percent reductions in heart rate were greater at all concentrations among the elderly men. These data suggest that group differences in atenolol pharmacokinetics were likely a result of age-related decline in renal function, and that the elderly subjects were at least as sensitive as, and maybe even more sensitive than, the younger subjects to the negative chronotropic effects of atenolol.

Adrenergic beta-Antagonists↗
PubMed1995

Population pharmacokinetics and renal function-sparing effects of amphotericin B colloidal dispersion in patients receiving bone marrow transplants.

The purpose of this study was to evaluate the pharmacokinetics of amphotericin B colloidal dispersion and its effect on creatinine clearance in bone marrow transplant patients with systemic fungal infections. Seventy-five patients (42 females and 33 males) with a median age of 34.5 years and a median weight of 70.0 kg were enrolled in the study. Patients received 1 of 15 dose levels (range, 0.5 to 8.0 mg/kg of body weight) daily for a mean duration of 28 days and a mean cumulative dose amount of 8 g. Plasma samples for amphotericin B determination (median number, 4; range, 2 to 30) and daily serum creatinine values were obtained for each patient. Iterative two-stage analysis, one of several approaches to population pharmacokinetic and pharmacodynamic modelling, was employed for the pharmacokinetic analysis. The plasma data were available for 51 of 75 patients and were best described by a two-compartment model. Both plasma clearance and volume of distribution increased with escalating doses; the overall average terminal elimination half-life was 29 h. Of the covariates studied, only body weight and dose size were significant. Serum creatinine values over the duration of therapy were available for 59 of 75 patients. Overall, there was no net change in renal function over the duration of therapy; 12 patients had > 30% increases in creatinine clearance, whereas 13 had > 30% decreases. No measure of amphotericin B colloidal dispersion exposure, demographic values, or concomitant treatment with other medications was related to changes in the creatinine clearance.

Adolescent↗
PubMed1994

Optimal sampling theory: effect of error in a nominal parameter value on bias and precision of parameter estimation.

The authors examined the robustness of optimal sampling theory in estimating the parameter values of two different populations of patients receiving a constant rate, half-hour intravenous infusion of theophylline. One population consisted of smokers; the other included nonsmokers. The smoking population was predicted to have a serum clearance approximately 50% greater than the nonsmokers because of an induction of the cytochrome P450 system. After an initial study to provide both patient-specific and population mean parameter values, optimal sampling strategies that were derived from each population (seven sample split designs) and the patient's seven sample and four sample design were determined. A second study was performed with an overall sampling strategy that was superset of all the above strategies. The analysis of all samples served as the reference for the parameter values. Bias and precision of the values determined with each of the optimal sampling sets (seven sample sets based on the "correct" and "wrong" populations, the patient's seven and four sample sets) were determined relative to these reference values. Irrespective of the sample set used for analysis, unbiased and precise parameter estimates, particularly of hybrid parameters were provided. With the patient's four sample set, Vss was significantly biased, but the value of (2.2%) was clinically insignificant. The authors conclude that optimal sampling theory, as implemented in this study, provides robust estimates of important pharmacokinetic parameter values, even when errors of 50% are present in the clearance of the population used to calculate the optimal sampling design.

Adolescent↗