Donald E. Mager

General pharmacokinetic model for drugs exhibiting target-mediated drug disposition.

Drugs that bind with high affinity and to a significant extent (relative to dose) to a pharmacologic target such as an enzyme, receptor, or transporter may exhibit nonlinear pharmacokinetic (PK) behavior. Processes such as receptor-mediated endocytosis may result in drug elimination. A general PK model for characterizing such behavior is described and explored through computer simulations and applications to several therapeutic agents. Simulations show that model predicted plasma concentration vs. time profiles are expected to be polyexponential with steeper distribution phases for lower doses and similar terminal disposition phases. Noncompartmental parameters always show apparent Vss and CLD decreasing with dose, but apparent clearance decreases only when the binding process produces drug elimination. The proposed model well captured the time-course of drug concentrations for the aldose reductase inhibitor imirestat, the endothelin receptor antagonist bosentan, and recombinant human interferon-β 1a. This type of model has a mechanistic basis and considerable utility for fully describing the kinetics for various doses of relevant drugs.

Testosterone concentrations in diabetic and nondiabetic obese men.

OBJECTIVE To determine the prevalence of subnormal testosterone concentrations in patients with obesity and with type 2 diabetes in a primary care clinic population. RESEARCH DESIGN AND METHODS Free testosterone concentrations of 1,849 men (1,451 nondiabetic and 398 diabetic) in the Hypogonadism In Males (HIM) study were analyzed. The HIM study was a U.S.-based cross-sectional study designed to define the prevalence of hypogonadism in men aged >45 years. Free testosterone was measured by equilibrium dialysis. RESULTS The prevalence of subnormal free testosterone concentrations in lean, overweight, and obese nondiabetic men was 26% (n = 275), 29% (n = 687), and 40% (n = 489), respectively (P < 0.001 for trend), and 44% (n = 36), 44% (n = 135), and 50% (n = 227), respectively, in diabetic men (P = 0.46 for trend within group and P < 0.05 compared with nondiabetic men). The mean free testosterone concentration of diabetic men was significantly lower than that of nondiabetic men. Free testosterone concentrations were negatively and significantly (P < 0.001) related to age (r = −0.37), BMI (r = −0.18), and sex hormone–binding globulin (r = −0.11) in multiple regression analysis. The average decline of free testosterone concentrations was 7.8 pg/ml per decade in nondiabetic men and 8.4 pg/ml per decade in diabetic men. CONCLUSIONS Forty percent of obese nondiabetic men and 50% of obese diabetic men aged ≥45 years have subnormal free testosterone concentrations. In view of its high prevalence, obesity is probably the condition most frequently associated with subnormal free testosterone concentrations in males. The concomitant presence of diabetes is associated with an additional increase in the prevalence of subnormal free testosterone concentrations.

Caloric restriction and intermittent fasting alter spectral measures of heart rate and blood pressure variability in rats

Dietary restriction (DR) has been shown to increase life span, delay or prevent age‐associated diseases, and improve functional and metabolic cardiovascular risk factors in rodents and other species. To investigate the effects of DR on beat‐to‐beat heart rate and diastolic blood pressure variability (HRV and DPV) in male Sprague‐Dawley rats, we implanted telemetric transmitters and animals were maintained on either intermittent fasting (every other day feeding) or calorie‐restricted (40% caloric reduction) diets. Using power spectral analysis, we evaluated the temporal profiles of the low‐and high‐frequency oscillatory components in heart rate and diastolic blood pressure signals to assess cardiac autonomic activity. Body weight, heart rate, and systolic and diastolic blood pressure were all found to decrease in response to DR. Both methods of DR produced decreases in the low‐frequency component of DPV spectra, a marker for sympathetic tone, and the high‐frequency component of HRV spectra, a marker for parasympathetic activity, was increased. These parameters required at least 1 month to become maximal, but returned toward base‐line values rapidly once rats resumed ad libitum diets. These results suggest an additional cardiovascular benefit of DR that merits further studies of this potential effect in humans.‐Mager, D. E., Wan, R., Brown, M., Cheng, A., Wareski, P., Abernethy, D. R., Mattson, M. P. Caloric restriction and intermittent fasting alter spectral measures of heart rate and blood pressure variability in rats. FASEB J. 20, 631–637 (2006)

Merging Systems Biology with Pharmacodynamics

Enhanced pharmacodynamic models combine favorable features of systems biology and traditional models and may form the basis of precision medicine. Abstract The emerging discipline of systems pharmacology aims to combine analysis and computational modeling of cellular regulatory networks with quantitative pharmacology approaches to drive the drug discovery processes, predict rare adverse events, and catalyze the practice of personalized precision medicine. Here, we introduce the concept of enhanced pharmacodynamic (ePD) models, which synergistically combine the desirable features of systems biology and current PD models within the framework of ordinary or partial differential equations. ePD models that analyze regulatory networks involved in drug action can account for a drug’s multiple targets and for the effects of genomic, epigenomic, and posttranslational changes on the drug efficacy. This new knowledge can drive drug discovery and shape precision medicine.

Physical and Cognitive Performance and Burden of Anticholinergics, Sedatives, and ACE Inhibitors in Older Women

Polypharmacy, common in older people, confers both risk of adverse outcomes and benefits. We assessed the relationship of commonly prescribed medications with anticholinergic and sedative effects to physical and cognitive performance in older individuals. The study population comprised 932 moderately to severely disabled community‐resident women aged 65 years or older who were participants in the Womens Health and Aging Study I. A scale based on pharmacodynamic principles was developed and utilized as a measure of drug burden. This was related to measures of physical and cognitive function. After adjusting for demographics and comorbidities, anticholinergic drug burden was independently associated with greater difficulty in four physical function domains with adjusted odds ratios (95% confidence interval (CI)) of 4.9 (2.0–12.0) for balance difficulty; 3.2 (1.5–6.9) for mobility difficulty; 3.6 (1.6–8.0) for slow gait; 4.2 (2.0–8.7) for chair stands difficulty; 2.4 (1.1–5.3) for weak grip strength; 2.7 (1.3–5.4) for upper extremity limitations; 3.4 (1.7–6.9) for difficulty in activities of daily living; and 2.4 (95% CI, 1.1–5.1) for poor performance on the Mini‐Mental State Examination. Sedative burden was associated only with impaired grip strength (3.3 (1.5–7.3)) and mobility difficulty (2.4 (1.1–5.3)). The burden of multiple drugs can be quantified by incorporating the recommended dose regimen and the actual dose and frequency of drug taken. Anticholinergic drug burden is strongly associated with limitations in physical and cognitive function. Sedative burden is associated with impaired functioning in more limited domains. The risk associated with exposure of vulnerable older women to drugs with anticholinergic properties, and to a lesser extent those with sedative properties, implies that such drugs should not be used in this patient group without compelling clinical indication.

Drug Burden Index Score and Functional Decline in Older People

BACKGROUND The Drug Burden Index (DBI), a measure of exposure to anticholinergic and sedative medications, has been independently associated with physical and cognitive function in a cross-sectional analysis of community-dwelling older persons participating in the Health, Aging and Body Composition study. Here we evaluate the association between DBI and functional outcomes in Health, Aging and Body Composition study participants over 5 years. METHODS DBI was calculated at years 1 (baseline), 3, and 5, and a measure of the area under the curve for DBI (AUCDB) over the whole study period was devised and calculated. Physical performance was measured using the short physical performance battery, usual gait speed, and grip strength. The association of DBI at each time point and AUCDB with year 6 function was analyzed in data from participants with longitudinal functional measures, controlling for sociodemographics, comorbidities, and baseline function. RESULTS Higher DBI at years 1, 3, and 5 was consistently associated with poorer function at year 6. On multivariate analysis, a 1-unit increase in AUCDB predicted decreases in short physical performance battery score of .08 (P=.01), gait speed of .01 m/s (P=.004), and grip strength of .27 kg (P=.004) at year 6. CONCLUSION Increasing exposure to medication with anticholinergic and sedative effects, measured with DBI, is associated with lower objective physical function over 5 years in community-dwelling older people.

Pharmacodynamic modeling of time-dependent transduction systems

The past decade has seen a marked expansion of the development and application of mechanism-based pharmacokinetic/pharmacodynamic (PK/PD) models for quantitating the time course of drug responses. A general conceptual scheme that depicts the major processes controlling drug effects is depicted in Fig 1.1 The potential for drug distribution into a biophase as a rate-limiting step controlling some effects was pointed out by Furchgott2 and Segre,3 and the application of a linking compartment in pharmacodynamics was popularized by Sheiner et al.4 The biosensor process represents the mechanism of action of the drug whereby either receptor binding or turnover of endogenous mediators may be altered. The former can be quantitated with an array of equations reflecting reversible binding of agonist or antagonist to receptors,5 whereas the latter may require use of indirect response models.6,7 Some mechanisms involve irreversible inactivation of cells or enzymes such as those used for chemotherapeutic agents8 or drugs such as aspirin9 or omeprazole.10 Bound receptors or endogenous mediators often activate additional biochemical or physiologic steps with such transduction processes leading to the observed response.11 Further, there may occur diverse counterregulation, depletion, or tolerance mechanisms that can modify the observed response.12 A highly mechanistic characterization of pharmacologic responses in relation to dose, time, and other factors requires direct measurement of the diverse steps controlling the action of the drug. This may be feasible with invasive animal studies such as our receptor and gene-mediated models for corticosteroids13; however, the modeling of clinical drug responses has severe limitations. Most typically it is desirable and often feasible to capture a capacity constant such as the maximum induced response (Emax), a sensitivity constant such as the equilibrium dissociation constant (KD) or related biophase concentration (EC50), the Hill coefficient (γ) if necessary, and perhaps a time constant (τ) that may reflect a major rate-limiting step causing a delay in responses separate from the pharmacokinetics of the drug. Either the rate constant for biophase distribution (keo) or the constant for loss of the response variable in indirect response models (kout) is thus the fourth parameter often generally sought where relevant from clinical data. General expectations in quantitating pharmacodynamic data are that the model applied will be as mechanistically relevant as possible, it will capture the major rate-limiting step or steps in control of drug responses, and it will reflect as many doses, routes, or regimens as possible to allow maximal interpretive and predictive capability. The purpose of this report is to point out the need and feasibility of considering transduction processes and a simplified nonlinear transduction model as the third major class of PK/PD models for characterizing various drug responses with time delays.

Development of Translational Pharmacokinetic–Pharmacodynamic Models

Contemporary models in the field of pharmacokinetic–pharmacodynamic (PK–PD) modeling often incorporate the fundamental principles of capacity limitation and operation of turnover processes to describe the time course of pharmacological effects in mechanistic terms. This permits the identification of drug‐ and system‐specific factors that govern drug responses. There is considerable interest in utilizing mechanism‐based PK–PD models in translational pharmacology, whereby in silico, in vitro, and preclinical data may be effectively coupled with relevant models to streamline the discovery and development of new therapeutic agents. These translational PK–PD models form the subject of this review.

Dose Equivalency Evaluation of Major Corticosteroids: Pharmacokinetics and Cell Trafficking and Cortisol Dynamics

The integrity of current corticosteroid dose equivalency tables, as assessed by mechanistic models for cell trafficking and cortisol dynamics, was investigated in this study. Single, presumably equivalent, doses of intravenous hydrocortisone, methylprednisolone, dexamethasone, and oral prednisolone were given to 5 white men, according to total body weight, in a 5‐way crossover, placebo‐controlled study. Pharmacodynamic (PD) response‐time profiles for T helper cells, T suppressor cells, neutrophils, and adrenal suppression were evaluated by extended indirect response models. For adrenal suppression, prednisolone appears to be less potent than methylprednisolone or dexamethasone. A good correlation was found between the estimated in vivo EC50 values and relative receptor affinity (equilibrium dissociation constants normalized to dexamethasone). Area under the effect curves of all PD responses was calculated using a linear‐trapezoidal method. Although T helper cell trafficking and adrenal suppression achieved significant differences by repeated‐measures ANOVA (p = 0.014 and 0.022), post hoc analysis using the Bonferroni method revealed no difference between treatments. Although limited by the use of single doses and a relatively small sample size, this study applies mechanistic models for several biomarkers showing that currently used dosing tables reflect reasonable dose equivalency relationships for four corticosteroids.

Simultaneous population pharmacokinetic modelling of ketamine and three major metabolites in patients with treatment-resistant bipolar depression

AIM To construct a population pharmacokinetic (popPK) model for ketamine (Ket), norketamine (norKet), dehydronorketamine (DHNK), hydroxynorketamine (2S,6S;2R,6R)-HNK) and hydroxyketamine (HK) in patients with treatment-resistant bipolar depression. METHOD Plasma samples were collected at 40, 80, 110, 230 min on day 1, 2 and 3 in nine patients following a 40 min infusion of (R,S)-Ket (0.5 mg kg⁻¹) and analyzed for Ket, norKet and DHNK enantiomers and (2S,6S;2R,6R)-HNK, (2S,6S;2R,6R)-HK and (2S,6R;2R,6S)-HK. A compartmental popPK model was constructed that included all quantified analytes, and unknown parameters were estimated with an iterative two-stage algorithm in ADAPT5. RESULTS Ket, norKet, DHNK and (2S,6S;2R,6R)-HNK were present during the first 230 min post infusion and significant concentrations (>5 ng ml⁻¹) were observed on day 1. Plasma concentrations of (2S,6S;2R,6R)-HK and (2S,6R;2R,6S)-HK were below the limit of quantification. The average (S) : (R) plasma concentrations for Ket and DHNK were <1.0 while no significant enantioselectivity was observed for norKet. There were large inter-patient variations in terminal half-lives and relative metabolite concentrations; at 230 min (R,S)-DHNK was the major metabolite in four out of nine patients, (R,S)-norKet in three out of nine patients and (2S,6S;2R,6R)-HNK in two out of nine patients. The final PK model included three compartments for (R,S)-Ket, two compartments for (R,S)-norKet and single compartments for DHNK and HNK. All PK profiles were well described, and parameters for (R,S)-Ket and (R,S)-norKet were in agreement with prior estimates. CONCLUSION This represents the first PK analysis of (2S,6S;2R,6R)-HNK and (R,S)-DHNK. The results demonstrate that while norKet is the initial metabolite, it is not the main metabolite suggesting that future Ket studies should include the analysis of the major metabolites.