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 Women's 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.

Quantitative and systems pharmacology (QSP) is increasingly being applied in pharmaceutical research and development. One factor critical to the ultimate success of QSP is the establishment of commonly accepted language, technical criteria, and workflows. We propose an integrated workflow that bridges conceptual objectives with underlying technical detail to support the execution, communication, and evaluation of QSP projects.

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. BASIC TENETS OF PHARMACODYNAMICSThe basic principles of pharmacokinetics, pharmacology, and physiology form the foundation of mechanism-based pharmacokinetic-pharmacodynamic (PK-PD) modeling. A summary of these components is shown as a diagram in Figure 1. Pharmacokinetics encompasses the factors affecting the time course of drug/metabolite concentrations in relevant biological fluids and tissues after various routes of administration and represents the driving force for pharmacological and most toxicological effects. Noncompartmental (i.e., area/moment analysis) and mammillary plasma-clearance models that quantitatively assess pharmacokinetic processes (i.e., absorption, distribution, metabolism, and excretion) are the most common methods used for PK data analysis. At the very minimum, the primary parameters of drug distribution and elimination should be identified (volume of distribution and clearance). Despite the widespread use of these assessment techniques in studies using various animal species, the relatively empirical and hybrid nature of the parameters derived from such techniques do not readily allow for extrapolation of the PK properties across species and compounds, a highly desirable feature of translational models. In contrast, physiology-based PK (PBPK) models seek to emulate physiological pathways and processes that control plasma and tissue drug concentrations, and this approach is regarded as the state-of-the-art technique in advanced PK systems analysis. 1,2 As stated by Dedrick, "Physiologic modeling enables us to examine the joint effect of a number of complex interrelated processes and assess the relative significance of each." 3 The compartments in PBPK models represent organs and tissues of interest and are arranged and connected according to anatomical and physiological relationships (Figure 1, top left). A series of mass-balance differential equations that extend from Fick's law of perfusion/diffusion describe the rate of change of drug concentrations within each tissue. Other major processes may be incorporated, including drug metabolism and/or Correspondence: DE Mager (E-mail: dmager@buffalo.edu). CONFLICT OF INTERESTThe authors declared no conflict of interest. The law of mass action and the relatively low concentration of pharmacological receptors or targets impart capacity limitation i...

Canakinumab, an anti-interleukin-1β (IL-1β) monoclonal antibody, is approved for cryopyrin-associated periodic syndromes and is under investigation for the management of other inflammatory disorders. In this study, population-based pharmacokinetic–pharmacodynamic models were developed to understand responses to canakinumab in patients with rheumatoid arthritis (RA). Total canakinumab and total IL-1β concentrations were obtained from four clinical trials (n = 472). In contrast to traditional models, free IL-1β concentrations were calculated and used to link canakinumab to changes in C-reactive protein (CRP) concentrations and American College of Rheumatology (ACR) scores of 20, 50, and 70% improvement. Temporal patterns of total canakinumab, total IL-1β, CRP, and ACR scores were all well described. Simulations confirmed that 150 mg every 4 weeks improved ACR scores in patients with RA, but no additional benefit was provided by higher doses or more frequent administration. Integrating predicted endogenous free ligand concentrations with biomarkers and clinical outcomes could be extended to new therapies of anti-inflammatory diseases.

A semimechanistic pharmacokinetic/pharmacodynamic (PK/PD) model was developed to evaluate the effects of aliskiren on the renin-angiotensin system (RAS) in humans. Mean data were extracted from a three-way crossover, placebo-controlled study. Outcome measures included the time-course of plasma renin activity (PRA) and plasma concentrations of aliskiren, active renin (AR), angiotensin I (ANG I), and angiotensin II (ANG II). The disposition of aliskiren may be best described as a two-compartment model with nonlinear elimination and distribution. The four biomarkers of RAS inhibition were co-modeled, and the AR showed a dose-dependent increase after the administration of aliskiren. This effect was described in terms of an indirect stimulatory response model in conjunction with an empirical submodel of functional adaptation. The estimated concentration of aliskiren necessary for producing 50% inhibition of PRA is 0.66 ng/ml, which is similar to in vitro estimates (0.33 ng/ml) after correction for plasma protein binding. The final and reduced models test the current hypothesis that RAS is inhibited by direct renin antagonism, and also provide suitable platforms for future clinical study design and analysis.

Hepatocellular carcinoma (HCC) is third in cancer‐related causes of death worldwide and its treatment is a significant unmet medical need. Sunitinib is a selective tyrosine kinase inhibitor of the angiogenic biomarker: soluble vascular endothelial growth factor receptor‐2 (sVEGFR2). Sunitinib failed its primary overall survival endpoint in patients with advanced HCC in a phase III trial compared to sorafenib. In the present study, pharmacokinetic‐pharmacodynamic modeling was used to link drug‐exposure to tumor‐growth‐inhibition (TGI) and time‐to‐tumor progression (TTP) through sVEGFR2 dynamics. The results suggest that 1) active drug concentration (i.e., sunitinib and its metabolite) inhibits the release of sVEGFR2 and that such inhibition is associated with TGI, and 2) daily sVEGFR2 exposure is likely a reliable predictor for the TTP in HCC patients. Moreover, the model quantitatively links the dynamics of an angiogenesis biomarker to TTP and accurately predicts observed literature‐reported results of placebo treatment.

No abstract