Annual Review of Pharmacology and Toxicology - Volume 53, 2013

Two selective inhibitors of the hepatitis C virus (HCV) protease nearly double the cure rates for this infection when combined with peginterferon alfa and ribavirin. These drugs, boceprevir and telaprevir, received regulatory approval in 2011 and are the first direct-acting antiviral agents (DAAs) that selectively target HCV. During 2012, at least 30 additional DAAs were in various stages of clinical development. HCV protease inhibitors, polymerase inhibitors, and NS5A inhibitors (among others) can achieve high cure rates when combined with peginterferon alfa and ribavirin and demonstrate promise when used in combination with one another. Current research is attempting to improve the pharmacokinetics and tolerability of these agents, define the best regimens, and determine treatment strategies that produce the best outcomes. Several DAAs will reach the market simultaneously, and resources will be needed to guide the use of these drugs. We review the clinical pharmacology, trial results, and remaining challenges of DAAs for the treatment of HCV.

To achieve sensitive and specific mechanism-based prediction of drug toxicity, the tools of systems pharmacology will be integrated using structured ontological approaches, analytics, mathematics, and statistics. Success of this effort is based on the assumption that a systems network that consists of drug-induced perturbations of physiological functions can be characterized. This network spans the hierarchy of biological organization, from gene to mRNA to protein to intracellular organelle to cell to organ to organism. It is populated with data from each of these levels of biological organization. These data, from disparate sources, include the published literature, drug development archives of all approved drugs and drug candidates that did not complete development, and various toxicity databases and adverse event reporting systems. The network contains interrelated genomics, transcriptomics, and metabolomics data, as well as organ and physiological functional data that are derived from the universe of information that describes and analyzes drug toxicity. Here we describe advances in bioinformatics, computer sciences, next-generation sequencing, and systems biology that create the opportunity for integrated systems pharmacology–based prediction of drug safety.

A new generation of technologies commonly named omics permits assessment of the entirety of the components of biological systems and produces an explosion of data and a major shift in our concepts of disease. These technologies will likely shape the future of health care. One aspect of these advances is that the data generated document the uniqueness of each human being in regard to disease risk and treatment response. These developments have reemphasized the concept of personalized medicine. Here we review the impact of omics technologies on one key aspect of personalized medicine: the individual drug response. We describe how knowledge of different omics may affect treatment decisions, namely drug choice and drug dose, and how it can be used to improve clinical outcomes.

The kidney plays a vital role in the body's defense against potentially toxic xenobiotics and metabolic waste products through elimination pathways. In particular, secretory transporters in the proximal tubule are major determinants of the disposition of xenobiotics, including many prescription drugs. In the past decade, considerable progress has been made in understanding the impact of renal transporters on the disposition of many clinically used drugs. In addition, renal transporters have been implicated as sites for numerous clinically important drug-drug interactions. This review begins with a description of renal drug handling and presents relevant equations for the calculation of renal clearance, including filtration and secretory clearance. In addition, data on the localization, expression, substrates, and inhibitors of renal drug transporters are tabulated. The recent US Food and Drug Administration drug-drug interaction draft guidance as it pertains to the study of renal drug transporters is presented. Renal drug elimination in special populations and transporter splicing variants are also described.

During the past few years, crystallography of G protein–coupled receptors (GPCRs) has experienced exponential growth, resulting in the determination of the structures of 16 distinct receptors—9 of them in 2012 alone. Including closely related subtype homology models, this coverage amounts to approximately 12% of the human GPCR superfamily. The adrenergic, rhodopsin, and adenosine receptor systems are also described by agonist-bound active-state structures, including a structure of the receptor–G protein complex for the β2-adrenergic receptor. Biochemical and biophysical techniques, such as nuclear magnetic resonance and hydrogen-deuterium exchange coupled with mass spectrometry, are providing complementary insights into ligand-dependent dynamic equilibrium between different functional states. Additional details revealed by high-resolution structures illustrate the receptors as allosteric machines that are controlled not only by ligands but also by ions, lipids, cholesterol, and water. This wealth of data is helping redefine our knowledge of how GPCRs recognize such a diverse array of ligands and how they transmit signals 30 angstroms across the cell membrane; it also is shedding light on a structural basis of GPCR allosteric modulation and biased signaling.

Peptide hormones and neurotransmitters are of central importance in most aspects of intercellular communication and are involved in virtually all degenerative diseases. In this review, we discuss physicochemical approaches to the design of novel peptide and peptidomimetic agonists, antagonists, inverse agonists, and related compounds that have unique biological activity profiles, reduced toxic side effects, and, if desired, the ability to cross the blood-brain barrier. Designing ligands for specific biological and medical needs is emphasized, as is the close collaboration of chemists and biologists to maximize the chances for success. Special emphasis is placed on the use of conformational (ϕ-ψ space) and topographical (χ space) considerations in design.

Recent studies of membrane transporters have revealed their importance in determining the pharmacokinetics of transporter substrates. When drug-drug interactions (DDIs) or genetic polymorphisms (i.e., pharmacogenetics) affect the activities of transporters, the pharmacokinetics of transporter substrate drugs is altered; this alteration influences the substrate drugs' subsequent pharmacological or toxicological effects. In predicting these effects quantitatively from in vitro experimental results, we must first determine the contribution of each transporter to the overall elimination process. Furthermore, the accurate estimation of effective inhibitor concentrations at the site of interaction (e.g., intestinal lumen, extracellular and intracellular space of hepatocytes) is challenging. In predicting pharmacogenetic effects, the extrapolation from in vitro observations to in vivo outcomes (e.g., changes in intrinsic activities and/or expression levels) is still evolving. In this review, we describe the current status of, and difficulties inherent in, the accurate prediction of the altered pharmacokinetics caused by transporter-mediated DDIs and pharmacogenetics.