Age-related decrease in energy expenditure at rest parallels reductions in mass of internal organs

Repository Describing an Aging Population to Inform Physiologically Based Pharmacokinetic Models Considering Anatomical, Physiological, and Biological Age-Dependent Changes

BACKGROUND

Aging is characterized by anatomical, physiological, and biological changes that can impact drug kinetics. The elderly are often excluded from clinical trials and knowledge about drug kinetics and drug-drug interaction magnitudes is sparse. Physiologically based pharmacokinetic modeling can overcome this clinical limitation but detailed descriptions of the population characteristics are essential to adequately inform models.

OBJECTIVE

The objective of this study was to develop and verify a population database for aging Caucasians considering anatomical, physiological, and biological system parameters required to inform a physiologically based pharmacokinetic model that included population variability.

METHODS

A structured literature search was performed to analyze age-dependent changes of system parameters. All collated data were carefully analyzed, and descriptive mathematical equations were derived.

RESULTS

A total of 362 studies were found of which 318 studies were included in the analysis as they reported rich data for anthropometric parameters and specific organs (e.g., liver). Continuous functions could be derived for most system parameters describing a Caucasian population from 20 to 99 years of age with variability. Areas with sparse data were identified such as tissue composition, but knowledge gaps were filled with plausible qualified assumptions. The developed population was implemented in Matlab^® and estimated system parameters from 1000 virtual individuals were in accordance with independent observed data showing the robustness of the developed population.

CONCLUSIONS

The developed repository for aging subjects provides a singular specific source for key system parameters needed for physiologically based pharmacokinetic modeling and can in turn be used to investigate drug kinetics and drug-drug interaction magnitudes in the elderly.

Physiologically based pharmacokinetic modelling to guide drug delivery in older people

Older patients are generally not included in Phase 1 clinical trials despite being the population group who use the largest number of prescription medicines. Physiologically based pharmacokinetic (PBPK) modelling provides an understanding of the absorption and disposition of drugs in older patients. In this review, PBPK models used for the prediction of absorption and exposure of drugs after parenteral, oral and transdermal administration are discussed. Comparisons between predicted drug pharmacokinetics (PK) and observed PK are presented to illustrate the accuracy of the predictions by the PBPK models and their potential use in informing clinical trial design and dosage adjustments in older patients. In addition, a case of PBPK modelling of a bioequivalence study on two controlled release products is described, where PBPK predictions reproduced the study showing bioequivalence in healthy volunteers but not in older subjects with achlorhydria, indicating further utility in prospectively identifying challenges in bioequivalence studies.

Development of a Whole-Body Physiologically Based Pharmacokinetic Approach to Assess the Pharmacokinetics of Drugs in Elderly Individuals

Background

Because of the vulnerability and frailty of elderly adults, clinical drug development has traditionally been biased towards young and middle-aged adults. Recent efforts have begun to incorporate data from paediatric investigations. Nevertheless, the elderly often remain underrepresented in clinical trials, even though persons aged 65 years and older receive the majority of drug prescriptions. Consequently, a knowledge gap exists with regard to pharmacokinetic (PK) and pharmacodynamic (PD) responses in elderly subjects, leaving the safety and efficacy of medicines for this population unclear.

Objectives

The goal of this study was to extend a physiologically based pharmacokinetic (PBPK) model for adults to encompass the full course of healthy aging through to the age of 100 years, to support dose selection and improve pharmacotherapy for the elderly age group.

Methods

For parameterization of the PBPK model for healthy aging individuals, the literature was scanned for anthropometric and physiological data, which were consolidated and incorporated into the PBPK software PK-Sim^®. Age-related changes that occur from 65 to 100 years of age were the main focus of this work. For a sound and continuous description of an aging human, data on anatomical and physiological changes ranging from early adulthood to old age were included. The capability of the PBPK approach to predict distribution and elimination of drugs was verified using the test compounds morphine and furosemide, administered intravenously. Both are cleared by a single elimination pathway. PK parameters for the two compounds in younger adults and elderly individuals were obtained from the literature. Matching virtual populations—with regard to age, sex, anthropometric measures and dosage—were generated. Profiles of plasma drug concentrations over time, volume of distribution at steady state (V_ss) values and elimination half-life (t_½) values from the literature were compared with those predicted by PBPK simulations for both younger adults and the elderly.

Results

For most organs, the age-dependent information gathered in the extensive literature analysis was dense. In contrast, with respect to blood flow, the literature study produced only sparse data for several tissues, and in these cases, linear regression was required to capture the entire elderly age range. On the basis of age-informed physiology, the predicted PK profiles described age-associated trends well. The root mean squared prediction error for the prediction of plasma concentrations of furosemide and morphine in the elderly were improved by 32 and 49 %, respectively, by use of age-informed physiology. The majority of the individual V_ss and t_½ values for the two model compounds, furosemide and morphine, were well predicted in the elderly population, except for long furosemide half-lifes.

Conclusion

The results of this study support the feasibility of using a knowledge-driven PBPK aging model that includes the elderly to predict PK alterations throughout the entire course of aging, and thus to optimize drug therapy in elderly individuals. These results indicate that pharmacotherapy and safety-related control of geriatric drug therapy regimens may be greatly facilitated by the information gained from PBPK predictions.

Electronic supplementary material

The online version of this article (doi:10.1007/s40262-016-0422-3) contains supplementary material, which is available to authorized users.

The influence of shc proteins and aging on whole body energy expenditure and substrate utilization in mice

While it has been proposed that Shc family of adaptor proteins may influence aging by regulating insulin signaling and energy metabolism, the overall impact of Shc proteins on whole body energy metabolism has yet to be elucidated. Thus, the purpose of this study was to determine the influence of Shc proteins and aging on whole body energy metabolism in a mouse model under ambient conditions (22°C) and acute cold exposure (12°C for 24 hours). Using indirect respiration calorimetry, we investigated the impact of Shc proteins and aging on EE and substrate utilization (RQ) in p66 Shc−/− (ShcKO) and wild-type (WT) mice. Calorimetry measurements were completed in 3, 15, and 27 mo mice at 22°C and 12°C. At both temperatures and when analyzed across all age groups, ShcKO mice demonstrated lower 24 h total EE values than that of WT mice when EE data was expressed as either kJ per mouse, or adjusted by body weight or crude organ mass (ORGAN) (P≤0.01 for all). The ShcKO mice also had higher (P<0.05) fed state RQ values than WT animals at 22°C, consistent with an increase in glucose utilization. However, Shc proteins did not influence age-related changes in energy expenditure or RQ. Age had a significant impact on EE at 22°C, regardless of how EE data was expressed (P<0.05), demonstrating a pattern of increase in EE from age 3 to 15 mo, followed by a decrease in EE at 27 mo. These results indicate a decline in whole body EE with advanced age in mice, independent of changes in body weight (BW) or fat free mass (FFM). The results of this study indicate that both Shc proteins and aging should be considered as factors that influence energy expenditure in mice.

Smaller organ mass with greater age, except for heart

Autopsy/cadaver data indicate that many organs and tissues are smaller in the elderly compared with young adults; however, in vivo data are lacking. The aim of this study was to determine whether the mass of specific high-metabolic-rate organs is different with increasing age, using MRI. Seventy-five healthy women (41 African-Americans and 34 Caucasians, age range 19-88 yr) and 36 men (8 African-Americans and 28 Caucasians, age range 19-84 yr) were studied. MRI-derived in vivo measures of brain, heart, kidneys, liver, and spleen were acquired. Left ventricular mass (LVM) was measured by either echocardiography or cardiac gated MRI. Total body fat mass and fat-free mass (FFM) were measured with a whole body dual-energy X-ray absorptiometry (DXA) scanner. Multiple regression analysis was used to investigate the association between the organ mass and age after adjustment for weight and height (or DXA measures of FFM), race, sex, and interactions among these variable. No statistically significant interaction was found among age, sex, and race in any regression model. Significant negative relationships between organ mass and age were found for brain (P < 0.0001), kidneys (P = 0.01), liver (P = 0.001), and spleen (P < 0.0001). A positive relationship between LVM and age was found after adjustment for FFM (P = 0.037). These findings demonstrate that age has a significant effect on brain, kidneys, liver, spleen, and heart mass. The age effect was independent of race and sex.

Database for physiologically based pharmacokinetic (PBPK) modeling: physiological data for healthy and health-impaired elderly

Physiologically based pharmacokinetic (PBPK) models have increasingly been employed in chemical health risk assessments. By incorporating individual variability conferred by genetic polymorphisms, health conditions, and physiological changes during development and aging, PBPK models are ideal for predicting chemical disposition in various subpopulations of interest. In order to improve the parameterization of PBPK models for healthy and health-impaired elderly (herein defined as those aged 65 yr and older), physiological parameter values were obtained from the peer-reviewed literature, evaluated, and entered into a Microsoft ACCESS database. Database records include values for key age-specific model inputs such as ventilation rates, organ volumes and blood flows, glomerular filtration rates, and other clearance-related processes. In total, 528 publications were screened for relevant data, resulting in the inclusion of 155 publications comprising 1051 data records for healthy elderly adults and 115 data records for elderly with conditions such as diabetes, chronic obstructive pulmonary disease (COPD), obesity, heart disease, and renal disease. There are no consistent trends across parameters or their associated variance with age; the gross variance in body weight decreased with advancing age, whereas there was no change in variance for brain weight. The database contains some information to inform ethnic and gender differences in parameters; however, the majority of the published data pertain to Asian (mostly Japanese) and Caucasian males. As expected, the number of records tends to decrease with advancing age. In addition to a general lack of data for parameters in the elderly with various health conditions, there is also a dearth of information on blood and tissue composition in all elderly groups. Importantly, there are relatively few records for alveolar ventilation rate; therefore, the relationship between this parameter and cardiac output (usually assumed to be 1:1) in the elderly is not well informed by the database. Despite these limitations, the database represents a potentially useful resource for parameterizing PBPK models for the elderly to facilitate the prediction of dose metrics in older populations for application in risk assessment.

A cellular-level approach to predicting resting energy expenditure across the adult years

BACKGROUND

We previously derived a whole-body resting energy expenditure (REE) prediction model by using organ and tissue mass measured by magnetic resonance imaging combined with assumed stable, specific resting metabolic rates of individual organs and tissues. Although the model predicted REE well in young persons, it overpredicted REE by approximately 11% in elderly adults. This overprediction may occur because of a decline in the fraction of organs and tissues as cell mass with aging.

OBJECTIVE

The aim of the present study was to develop a cellular-level REE prediction model that would be applicable across the adult age span. Specifically, we tested the hypothesis that REE can be predicted from a combination of organ and tissue mass, the specific resting metabolic rates of individual organs and tissues, and the cellular fraction of fat-free mass.

DESIGN

Fifty-four healthy subjects aged 23-88 y had REE, organ and tissue mass, body cell mass, and fat-free mass measured by indirect calorimetry, magnetic resonance imaging, whole-body (40)K counting, and dual-energy X-ray absoptiometry, respectively.

RESULTS

REE predicted by the cellular-level model was highly correlated with measured REE (r = 0.92, P < 0.001). The mean difference between measured REE (x+/- SD: 1487 +/- 294 kcal/d) and predicted REE (1501 +/- 300 kcal/d) for the whole group was not significant, and the difference between predicted and measured REE was not associated with age (r = 0.009, NS).

CONCLUSION

The present approach establishes an REE-body composition link with the use of a model at the cellular level. The combination of 2 aging-related factors (ie, decline in both the mass and the cellular fraction of organs and tissues) may account for the lower REE observed in elderly adults.