Pharmacokinetic-Pharmacodynamic (PK-PD) modeling helps to better understand drug efficacy and safety and has, therefore, become a powerful tool in the learning-confirming cycles of drug-development. In translational drug research, mechanism-based PK-PD modeling has been recognized as a tool for bringing forward early insights in drug efficacy and safety into the clinical development. These models differ from descriptive PK-PD models in that they quantitatively characterize specific processes in the causal chain between drug administration and effect. This includes target site distribution, binding and activation, pharmacodynamic interactions, transduction and homeostatic feedback mechanisms. Compared to descriptive models mechanism-based PK-PD models that utilize receptor theory concepts for characterization of target binding and target activation processes have improved properties for extrapolation and prediction. In this respect, receptor theory constitutes the basis for 1) prediction of in vivo drug concentration-effect relationships and 2) characterization of target association-dissociation kinetics as determinants of hysteresis in the time course of the drug effect. This approach intrinsically distinguishes drug- and system specific parameters explicitly, allowing accurate extrapolation from in vitro to in vivo and across species. This review provides an overview of recent developments in incorporating receptor theory in PK-PD modeling with a specific focus on the identifiability of these models.
An important feature of mechanism-based pharmacokinetic/pharmacodynamic (PK/PD) models is the identification of drug- and system-specific factors that determine the intensity and time-course of pharmacological effects. This provides an opportunity to integrate information obtained from in vitro bioassays and preclinical pharmacological studies in animals to anticipate the clinical and adverse responses to drugs in humans. The fact that contemporary PK/PD modeling continues to evolve and seeks to emulate systems level properties should provide enhanced capabilities to scale-up pharmacodynamic data. Critical steps in drug discovery and development, such as lead compound and first in human dose selection, may become more efficient with the implementation and further refinement of translational PK/PD modeling. In this review, we highlight fundamental principles in pharmacodynamics and the basic expectations for in vitro bioassays and traditional allometric scaling in PK/PD modeling. Discussion of PK/PD modeling efforts for recombinant human erythropoietin is also included as a case study showing the potential for advanced systems analysis to facilitate extrapolations and improve understanding of inter-species differences in drug responses.
Growth and development are two major aspects of children not readily apparent in adults. Clearance in the paediatric population should be investigated using models that describe size, maturation and organ function influences. Size is the primary covariate and although lean body weight is argued as a better measure than total body weight, the use of different fractions of fat mass to explain how pharmacokinetic parameters vary with body composition has been proposed. Allometric scaling using an empiric power exponent of 3/4 is superior to scaling using body surface area. The sigmoid hyperbolic model has proven useful to describe maturation. An extra parameter that describes asymmetry can be incorporated into this model. These descriptors are used to illustrate creatinine, morphine and paracetamol clearance in children. Simultaneous investigation of pooled GFR, paracetamol and morphine data enabled testing for shared common features of maturation processes. Results suggest that GFR matures before paracetamol or morphine clearance, consistent with phase II conjugation processes that convert xenobiotics to water soluble forms that can subsequently be eliminated from the body through the renal system. The use of such mechanistic approaches improves understanding of paediatric pharmacokinetics; improving dosing predictions and allowing projection in exploratory drug development.
Transporters govern drug movement into and out of tissues, thereby playing an important role in drug disposition in plasma and to the site of action. The molecular cloning of such transporters has clarified the importance of members of the solute carrier family, such as OATP/SLCO, OCT/SLC22, OAT/SLC22, and MATE/SLC47, and the ATP-binding cassette transporters, such as P-glycoprotein/ABCB1, MRPs/ABCC, and BCRP/ABCG2. Elucidation of molecular characteristics of transporters has allowed the identification of transporters as mechanisms for drug-drug interactions, and of interindividual differences in drug dispositions and responses. Cumulative studies have highlighted the cooperative roles of uptake transporters and metabolic enzymes/efflux transporters. In this way, the concept of a rate-limiting process in hepatic/renal elimination across epithelial cells has developed. This review illustrates the concept of the rate-limiting step in the hepatic elimination mediated by transporters, and describes the prediction of the in vivo pharmacokinetics of drugs whose disposition is determined by transporters, based on in vitro experiments using pravastatin as an example. This review also illustrates the transporters regulating the peripheral drug concentrations.
An increasing number of failures in clinical stages of drug development have been related to the effects of candidate drugs in a sub-group of patients rather than the ‘average’ person. Expectation of extreme effects or lack of therapeutic effects in some subgroups following administration of similar doses requires a full understanding of the issue of variability and the importance of identifying covariates that determine the exposure to the drug candidates in each individual. In any drug development program the earlier these covariates are known the better. An important component of the drive to decrease this failure rate in drug development involves attempts to use physiologically-based pharmacokinetics ‘bottom-up’ modeling and simulation to optimize molecular features with respect to the absorption, distribution, metabolism and elimination (ADME) processes. The key element of this approach is the separation of information on the system (i.e. human body) from that of the drug (e.g. physicochemical characteristics determining permeability through membranes, partitioning to tissues, binding to plasma proteins or affinities toward certain enzymes and transporter proteins) and the study design (e.g. dose, route and frequency of administration, concomitant drugs and food). In this review, the classical ‘top-down’ approach in covariate recognition is compared with the ‘bottom-up’ paradigm. The determinants and sources of inter-individual variability in different stages of drug absorption, distribution, metabolism and excretion are discussed in detail. Further, the commonly known tools for simulating ADME properties are introduced.
Despite an impressive battery of preclinical cardiac electrophysiology experimental models and the assessment of QT during clinical trials, the risk of Torsades de Pointes (TdP), a potentially lethal ventricular arrhythmia, remains among the common reasons for drug market withdrawal or lack of approval. Due to the low prevalence of TdP, development of statistical evidence that other clinical markers could be better predictors of TdP has proven challenging. Preclinical studies have provided a deeper understanding of torsadogenic mechanisms and potential pro-arrhythmic markers to assess. Translating these preclinical insights into a quantitative clinical risk assessment remains challenging because of (i) species differences in cardiac electrophysiology and drug pharmacokinetics; and (ii) the inability to measure clinically specific cardiac electrophysiology metrics, and therefore ascertain the full predictive value of earlier preclinical components of the risk assessment process. The integrative capacity of cardiac electrophysiology modeling to span time and length scales may provide a quantitative and predictive framework, to complement expert-based preclinical-to-clinical cardiac risk assessment process. In this review, we present salient elements of this risk assessment process and describe essential components of cardiac electrophysiology modeling, to propose that a progressive integration of mechanistic components into a common quantitative framework may help improve the predictability of drug-induced TdP risk.
Pairs of forward and reverse primers and TaqMan probes specific to each of 23 human solute carrier 35 (SLC35) transporters were prepared. The mRNA expression level of each target transporter was analyzed in total RNA from single and pooled specimens of adult human tissues (adipose tissue, adrenal gland, bladder, bone marrow, brain, cerebellum, colon, heart, kidney, liver, lung, mammary gland, ovary, pancreas, peripheral leukocytes, placenta, prostate, retina, salivary gland, skeletal muscle, small intestine, smooth muscle, spinal cord, spleen, stomach, testis, thymus, thyroid gland, tonsil, trachea, and uterus), from pooled specimens of fetal human tissues (brain, heart, kidney, liver, spleen, and thymus), and from three human cell lines (HeLa cell line ATCC#: CCL-2, human cell line Hep G2, and human breast carcinoma cell line MDA-435) by real-time reverse transcription PCR using an Applied Biosystems 7500 Fast Real-Time PCR System. The mRNA expression of SLC35As, SLC35Bs, SLC35Cs, SLC35D1, SLC35D2, SLC35Es, and SLC35F5 was found to be ubiquitous in both adult and fetal tissues. SLC35D3 mRNA was expressed at the highest levels in the adult retina. SLC35F1 mRNA was expressed at high levels in the adult and fetal brain. SLC35F2 mRNA was expressed at the highest levels in the adult salivary gland. Both SLC35F3 and SLC35F4 mRNAs were expressed at the highest levels in the adult cerebellum. Further, individual differences in the mRNA expression levels of human SLC35 transporters in the liver were also evaluated. Our newly determined expression profiles were used to study the gene expression in 31 adult human tissues, 6 fetal human tissues, and 3 cell lines, and tissues with high transcriptional activity for human SLC35 transporters were identified. These results are expected to be valuable for research concerning the clinical diagnosis of disease.
The metabolic bioactivation of a drug to a reactive metabolite (RM) and its covalent binding to cellular macromolecules is believed to be involved in clinical adverse events, including idiosyncratic drug toxicities. Therefore, it is important to assess the potential of drug candidates to generate RMs and form drug-protein covalent adducts during lead optimization processes. In this study, the RM formation of some marketed drugs were quantitatively assessed by means of a sensitive and robust detection method that we have established using 35S-glutathione (35S-GSH) as a trapping agent. Problematic drugs well-known to generate RMs exhibited a relatively high rate of 35S-GS-adducts to RM (RM-GS) formation, which contrasted with safe drugs. For practical use in lead optimization processes, a series of new chemical entities were tested and hints on the structural modifications needed in order to minimize their RM formation were provided. Furthermore, the RM-GS formation rates of a number of compounds were compared using their in vitro covalent binding yields to liver proteins determined with 14C-labeled compounds, demonstrating that the RM-GS formation rate could be a substitute for the covalent binding yield within the same series of compounds.
The injectable form of oxycodone contains hydrocotarnine that is supposed to potentiate the analgesic effect of oxycodone with unknown mechanism(s). In this study, the effects of hydrocotarnine on the cytochrome P450 (CYP) and P-glycoprotein (P-gp) were investigated. Hydrocotarnine did not induce a significant change in the metabolic activities of CYP2C9, 2C19, and 2E1 in an in vitro study using human CYP recombinants. Although weak inhibitory effects were observed on CYP3A4 and 2D6, these interactions did not seem to be clinically relevant. Hydrocotarnine also did not cause a significant change in the ATPase activity of human P-gp membranes, suggesting that it is not an inhibitor of P-gp. Furthermore, mice were intraperitoneally injected with hydrocotarnine for 14 days and the mRNA levels of major CYP isozymes and P-gp in the liver and small intestine were determined by real-time RT-PCR. As a result, none of the mRNAs investigated showed a significant change in their levels by hydrocotarnine treatment. In conclusion, it is unlikely that the potentiation of oxycodone effect by hydrocotarnine involves its effect on CYP and P-gp. The findings also demonstrate that hydrocotarnine is unlikely to cause drug interactions via CYP or P-gp.
In the present study, we identified 5 novel single nucleotide polymorphisms (SNPs) in the gene ofglycine N-acyltransferase (GlyAT) by resequencing the entire coding region and the exon-intron junctions from 95 Japanese individuals. The allelic frequencies of 5 novel SNPs were 0.016 for -695T>C, 0.021 for -260C>T, 0.005 for 290C>T, 0.005 for 19371G>A, and 0.005 for 21289G>A. Genetic variants of -979C>G and 21409A>G were in perfect linkage disequilibrium with 21364A>G and 21422C>T, respectively. The nonsynonymous SNP, 21289G>A (Arg131His) in exon 5, was also genotyped in 31 Caucasian individuals, but none of them possessed 21289A (131His) allele.
Glutathione S-transferases (GSTs) play a vital role in phase II biotransformation of many synthetic chemicals including anticancer drugs. Deletion polymorphisms in GSTT1 and GSTM1 are reportedly associated, albeit controversial, with an increased risk in cancer as well as with altered responses to chemotherapeutic drugs. In this study, to elucidate the haplotype structures of GSTT1 and GSTM1, genetic variations were identified in 194 Japanese cancer patients who received platinum-based chemotherapy. Homozygotes for deletion of GSTT1 (GSTT1*0/*0 or null) and GSTM1 (GSTM1*0/*0 or null) were found in 47.4% and 47.9% of the patients, respectively, while 23.2% of the patients had both GSTT1 null and GSTM1 null genotypes. From homozygous (+/+) and heterozygous (*0/+) patients bearing GSTT1 and GSTM1 genes, six single nucleotide polymorphisms (SNPs) for GSTT1 and 23 SNPs for GSTM1 were identified. A novel SNP in GSTT1, 226C>A (Arg76Ser), and the known SNP in GSTM1, 519C>G (Asn173Lys, *B), were found at frequencies of 0.003 and 0.077, respectively. Using the detected variations, GSTT1 and GSTM1 haplotypes were identified/inferred. Three and six common haplotypes (N≥10) in GSTT1 and GSTM1, respectively, accounted for most (>95%) inferred haplotypes. This information would be useful in pharmacogenomic studies of xenobiotics including anticancer drugs.