Pharmacokinetic and pharmacodynamic modeling of NN703, a growth hormone secretagogue, after a single po dose to human volunteers

Bioinformatics and Computer Simulation approaches to the discovery and analysis of Bioactive Peptides

The traditional process of separating and purifying bioactive peptides is laborious and time-consuming. Using a traditional process to identify is difficult, and there is a lack of fast and accurate activity evaluation methods. How to extract bioactive peptides quickly and efficiently is still the focus of bioactive peptides research. In order to improve the present situation of the research, bioinformatics techniques and peptidome methods are widely used in this field. At the same time, bioactive peptides have their own specific pharmacokinetic characteristics, so computer simulation methods have incomparable advantages in studying the pharmacokinetics and pharmacokinetic-pharmacodynamic correlation models of bioactive peptides. The purpose of this review is to summarize the combined applications of bioinformatics and computer simulation methods in the study of bioactive peptides, with focuses on the role of bioinformatics in simulating the selection of enzymatic hydrolysis and precursor proteins, activity prediction, molecular docking, physicochemical properties, and molecular dynamics. Our review shows that new bioactive peptide molecular sequences with high activity can be obtained by computer-aided design. The significance of the pharmacokinetic-pharmacodynamic correlation model in the study of bioactive peptides is emphasized. Finally, some problems and future development potential of bioactive peptides binding new technologies are prospected.

Feedback control indirect response models

A general framework is introduced for modeling pharmacodynamic processes that are subject to autoregulation, which combines the indirect response (IDR) model approach with methods from classical feedback control of engineered systems. The canonical IDR models are modified to incorporate linear combinations of feedback control terms related to the time course of the difference (the error signal) between the pharmacodynamic response and its basal value. Following the well-established approach of traditional engineering control theory, the proposed feedback control indirect response models incorporate terms proportional to the error signal itself, the integral of the error signal, the derivative of the error signal or combinations thereof. Simulations are presented to illustrate the types of responses produced by the proposed feedback control indirect response model framework, and to illustrate comparisons with other PK/PD modeling approaches incorporating feedback. In addition, four examples from literature are used to illustrate the implementation and applicability of the proposed feedback control framework. The examples reflect each of the four mechanisms of drug action as modeled by each of the four canonical IDR models and include: selective serotonin reuptake inhibitors and extracellular serotonin; histamine H2-receptor antagonists and gastric acid; growth hormone secretagogues and circulating growth hormone; β2-selective adrenergic agonists and potassium. The proposed feedback control indirect response approach may serve as an exploratory modeling tool and may provide a bridge for development of more mechanistic systems pharmacology models.

Modeling energy intake by adding homeostatic feedback and drug intervention

Energy intake (EI) is a pivotal biomarker used in quantification approaches to metabolic disease processes such as obesity, diabetes, and growth disorders. Eating behavior is however under both short-term and long-term control. This control system manifests itself as tolerance and rebound phenomena in EI, when challenged by drug treatment or diet restriction. The paper describes a model with the capability to capture physiological counter-regulatory feedback actions triggered by energy imbalances. This feedback is general as it handles tolerance to both increases and decreases in EI, and works in both acute and chronic settings. A drug mechanism function inhibits (or stimulates) EI. The deviation of EI relative to a reference level (set-point) serves as input to a non-linear appetite control signal which in turn impacts EI in parallel to the drug intervention. Three examples demonstrate the potential usefulness of the model in both acute and chronic dosing situations. The model shifts the predicted concentration-response relationship rightwardly at lower concentrations, in contrast to models that do not handle functional adaptation. A fourth example further shows that the model may qualitatively explain differences in rate and extent of adaptation in observed EI and its concomitants in both rodents and humans.

Pharmacokinetics and pharmacokinetic-pharmacodynamic correlations of therapeutic peptides

Peptides, defined as polymers of less than 50 amino acids with a molecular weight of less than 10 kDa, represent a fast-growing class of new therapeutics which has unique pharmacokinetic characteristics compared to large proteins or small molecule drugs. Unmodified peptides usually undergo extensive proteolytic cleavage, resulting in short plasma half-lives. As a result of their low permeability and susceptibility to catabolic degradation, therapeutic peptides usually have very limited oral bioavailability and are administered either by the intravenous, subcutaneous, or intramuscular route, although other routes such as nasal delivery are utilized as well. Distribution processes are mainly driven by a combination of diffusion and to a lesser degree convective extravasation dependent on the size of the peptide, with volumes of distribution frequently not larger than the volume of the extracellular body fluid. Owing to the ubiquitous availability of proteases and peptidases throughout the body, proteolytic degradation is not limited to classic elimination organs. Since peptides are generally freely filtered by the kidneys, glomerular filtration and subsequent renal metabolism by proteolysis contribute to the elimination of many therapeutic peptides. Although small peptides have usually limited immunogenicity, formation of anti-drug antibodies with subsequent hypersensitivity reactions has been described for some peptide therapeutics. Numerous strategies have been applied to improve the pharmacokinetic properties of therapeutic peptides, especially to overcome their metabolic instability, low permeability, and limited tissue residence time. Applied techniques include amino acid substitutions, modification of the peptide terminus, inclusion of disulfide bonds, and conjugation with polymers or macromolecules such as antibody fragments or albumin. Application of model-based pharmacokinetic-pharmacodynamic correlations has been widely used for therapeutic peptides in support of drug development and dosage regimen design, especially because their targets are often well-described endogenous regulatory pathways and processes.

A flexible nonlinear feedback system that captures diverse patterns of adaptation and rebound

An important approach to modeling tolerance and adaptation employs feedback mechanisms in which the response to the drug generates a counter-regulating action which affects the response. In this paper we analyze a family of nonlinear feedback models which has recently proved effective in modeling tolerance phenomena such as have been observed with SSRI's. We use dynamical systems methods to exhibit typical properties of the response-time course of these nonlinear models, such as overshoot and rebound, establish quantitive bounds and explore how these properties depend on the system and drug parameters. Our analysis is anchored in three specific in vivo data sets which involve different levels of pharmacokinetic complexity. Initial estimates for system (k(in), k(out), k(tol)) and drug (EC(50)/IC(50), E(max)/I(max), n) parameters are obtained on the basis of specific properties of the response-time course, identified in the context of exploratory (graphical) data analysis. Our analysis and the application of its results to the three concrete examples demonstrates the flexibility and potential of this family of feedback models.

A nonlinear feedback model capturing different patterns of tolerance and rebound

The objectives of the present analysis are to disect a class of turnover feedback models that have proven to be flexible from a mechanistic and empirical point of view, for the characterization of the onset, intensity and duration of response. Specifically, this class of models is designed so that it has the following properties: (I) Stimulation of the production term, which raises the steady state R(ss), causes an overshoot and a rebound upon return to baseline. (II) Stimulation of the loss term, which lowers the steady state R(ss), causes an overshoot which is negligible vis-a-vis the rebound upon the return to baseline. (III) Inhibition of the loss term, which raises the steady state R(ss), causes an overshoot which is larger than the rebound upon the return to the baseline. These models are then anchored in three datasets corresponding to the cases (I), (II) and (III). The objectives of this paper are to analyze the behavior of these turnover models from a mathematical/analytical point of view and to make simulations with different parameter settings and dosing regimens in order to highlight the intrinsic behavior of these models and draw some general conclusions. We also expand the analysis with two different extensions of the basic feedback model: one with a transduction step in the moderator and one which captures nonlinear phenomena (triggering mechanisms) caused by different drug input rates. A related objective is to come up with recommendations about experimental design and model building techniques in situations of feedback systems from a drug discovery point of view.

Pharmacokinetics and pharmacodynamics of a new formulation of recombinant human growth hormone administered by ZomaJet 2 Vision, a new needle-free device, compared to subcutaneous administration using a conventional syringe

The objective of the present study was to investigate the applicability of a new human growth hormone (Zomacton) formulation, administered both by a conventional syringe and by a new needle-free device (ZomaJet 2 Vision). The study was performed according to a randomized, controlled, three-period crossover design. On 3 separate days, all subjects received in a random order a single subcutaneous injection of 1.67 mg hGH as follows: Zomacton 4 mg/ml conventional syringe administration (Treatment A), Zomacton 10 mg/ml conventional syringe administration (Treatment B), or Zomacton 10 mg/ml ZomaJet 2 Vision administration (Treatment C). The pharmacokinetic parameters were assessed for the individual subjects in each group by noncompartmental methods. Bioequivalence was assessed based on log-transformed AUC and C(max) values. To investigate the effectiveness of two formulations and the different administration methods, the pharmacodynamic parameters (insulin-like growth factor-1 [IGF-1] and free fatty acids [FFA]) were also evaluated. No subjects were withdrawn due to adverse events. The local tolerance assessment (assessed by inspection)revealed no differences between ZomaJet2 Vision application and conventional injections by syringe. Administration of the new hGH formulation by syringe was found to be bioequivalent with the reference treatment, both based on AUC and C(max) values; the new formulation administered by use of ZomaJet 2 Vision was found to be bioequivalent based on AUC values only. When using the ZomaJet 2 Vision, the absorption of hGH was faster, resulting in higher C(max) values. The maximum hGH serum concentration of around 20 ng/ml was observed 3.5 to 4 hours after drug administration. The terminal half-life was found to be around 2.5 hours. Comparison of the pharmacodynamic profiles (both IGF-1 and FFA) demonstrated bioequieffectiveness. These results support the use of jet injectors as a viable alternative to the traditional injection pens.