Population Pharmacokinetic Analysis Supports Initiation Treatment and Bridging from Sublingual Buprenorphine to Subcutaneous Administration of a Buprenorphine Depot (CAM2038) in the Treatment of Opioid Use Disorder.

BACKGROUND AND OBJECTIVE: In treating opioid use disorder (OUD), subcutaneous (SC) extended-release buprenorphine (BPN) depots, e.g., CAM2038, have been shown to provide smaller and less frequent fluctuations in BPN plasma concentrations and pharmacodynamic responses, improve outcomes, reduce treatment burden, and lower risks of misuse and diversion compared to daily sublingual (SL) BPN. This analysis characterized the pharmacokinetics (PK) of BPN following intravenous and SL administration, and administration of SC CAM2038 weekly and monthly. METHODS: Pharmacokinetic data from two Phase 1 and two Phase 2 trials in healthy participants and participants with OUD, respectively, were used to develop a population PK model using non-linear mixed effects modelling. The analysis included data from 252 participants and 10,658 BPN observations. RESULTS: The disposition of BPN was best described by a three-compartment model with first-order elimination, and absorption of SL BPN and SC CAM2038 weekly and monthly by dual parallel absorption pathways. Model diagnostics indicated good predictive performance of BPN concentrations. Buprenorphine plasma concentration-time profiles were simulated for treatment initiation, switching from SL BPN to CAM2038 weekly and monthly, and tapering after interrupting treatment with CAM2038. Simulations predicted CAM2038 weekly and monthly doses that provided BPN plasma maximum concentration (Cmax) and trough concentration (Ctrough) values at steady state within those observed following SL BPN administration. CONCLUSIONS: This population PK model supports the use of CAM2038 doses as individualized treatment for OUD across different treatment stages, including initiation, switching from SL BPN according to established dose conversion schedules, and tapering. TRIAL REGISTRATIONS: ISRCTN41550730 (05/19/2014), ISRCTN24987553 (07/29/2014), NCT02611752 (11/23/2015), NCT02710526 (03/16/2016).

Population Pharmacokinetics and Exposure-Response for Dapirolizumab Pegol From a Phase 2b Trial in Patients With Systemic Lupus Erythematosus.

Systemic lupus erythematosus (SLE) is a systemic, autoimmune disease characterized by chronic inflammation and organ damage. Dapirolizumab pegol inhibits CD40 ligand (CD40L) and is currently undergoing phase 3 trials for the treatment of SLE. To describe the pharmacokinetic characteristics of dapirolizumab pegol and the relationship between exposure and probability of achieving a British Isles Lupus Assessment Group-based Composite Lupus Assessment (BICLA) response, a population pharmacokinetic (popPK) model and an exposure-response model were developed, based on results of the phase 2b trial (RISE; NCT02804763) of dapirolizumab pegol in SLE. Dapirolizumab pegol pharmacokinetics were found to be dose proportional and well described by a 2-compartment model with first-order elimination from the central compartment. In the popPK model, body weight was the only significant covariate. The average concentration of dapirolizumab pegol, derived from the popPK model, was incorporated into the exposure-response model. Overall, the exposure-response model showed that treatment with dapirolizumab pegol increased the probability of transitioning from BICLA "Nonresponder" to "Responder." No significant covariates on BICLA responder status were identified. Notably, the half maximal effective concentration was greater for the transition from "Responder" to "Nonresponder" (150 µg/mL) than the transition from "Nonresponder" to "Responder" (12 µg/mL), indicating that sustained dapirolizumab pegol concentrations may be required to maintain BICLA response. In conclusion, dapirolizumab pegol pharmacokinetics were as expected for a PEGylated molecule and results from the exposure-response model indicate that a favorable dapirolizumab pegol effect was identified for both BICLA "Nonresponder" to "Responder" and "Responder" to "Nonresponder" transition probabilities.

A Population Pharmacokinetic-Pharmacodynamic Model of Pegfilgrastim.

Neutropenia and febrile neutropenia (FN) are serious side effects of cytotoxic chemotherapy which may be alleviated with the administration of recombinant granulocyte colony-stimulating factor (GCSF) derivatives, such as pegfilgrastim (PG) which increases absolute neutrophil count (ANC). In this work, a population pharmacokinetic-pharmacodynamic (PKPD) model was developed based on data obtained from healthy volunteers receiving multiple administrations of PG. The developed model was a bidirectional PKPD model, where PG stimulated the proliferation, maturation, and margination of neutrophils and where circulating neutrophils in turn increased the elimination of PG. Simulations from the developed model show disproportionate changes in response with changes in dose. A dose increase of 10% from the 6 mg therapeutic dose taken as a reference leads to area under the curve (AUC) increases of ~50 and ~5% for PK and PD, respectively. A full random effects covariate model showed that little of the parameter variability could be explained by sex, age, body size, and race. As a consequence, little of the secondary parameter variability (Cmax and AUC of PG and ANC) could be explained by these covariates.

A diagnostic tool for population models using non-compartmental analysis: The ncappc package for R.

BACKGROUND AND OBJECTIVE: Non-compartmental analysis (NCA) calculates pharmacokinetic (PK) metrics related to the systemic exposure to a drug following administration, e.g. area under the concentration-time curve and peak concentration. We developed a new package in R, called ncappc, to perform (i) a NCA and (ii) simulation-based posterior predictive checks (ppc) for a population PK (PopPK) model using NCA metrics. METHODS: The nca feature of ncappc package estimates the NCA metrics by NCA. The ppc feature of ncappc estimates the NCA metrics from multiple sets of simulated concentration-time data and compares them with those estimated from the observed data. The diagnostic analysis is performed at the population as well as the individual level. The distribution of the simulated population means of each NCA metric is compared with the corresponding observed population mean. The individual level comparison is performed based on the deviation of the mean of any NCA metric based on simulations for an individual from the corresponding NCA metric obtained from the observed data. The ncappc package also reports the normalized prediction distribution error (NPDE) of the simulated NCA metrics for each individual and their distribution within a population. RESULTS: The ncappc produces two default outputs depending on the type of analysis performed, i.e., NCA and PopPK diagnosis. The PopPK diagnosis feature of ncappc produces 8 sets of graphical outputs to assess the ability of a population model to simulate the concentration-time profile of a drug and thereby evaluate model adequacy. In addition, tabular outputs are generated showing the values of the NCA metrics estimated from the observed and the simulated data, along with the deviation, NPDE, regression parameters used to estimate the elimination rate constant and the related population statistics. CONCLUSIONS: The ncappc package is a versatile and flexible tool-set written in R that successfully estimates NCA metrics from concentration-time data and produces a comprehensive set of graphical and tabular output to summarize the diagnostic results including the model specific outliers. The output is easy to interpret and to use in evaluation of a population PK model. ncappc is freely available on CRAN (http://cran.r-project.org/web/packages/ncappc/index.html/) and GitHub (https://github.com/cacha0227/ncappc/).

An electrostatic mechanism for Ca(2+)-mediated regulation of gap junction channels.

Gap junction channels mediate intercellular signalling that is crucial in tissue development, homeostasis and pathologic states such as cardiac arrhythmias, cancer and trauma. To explore the mechanism by which Ca(2+) blocks intercellular communication during tissue injury, we determined the X-ray crystal structures of the human Cx26 gap junction channel with and without bound Ca(2+). The two structures were nearly identical, ruling out both a large-scale structural change and a local steric constriction of the pore. Ca(2+) coordination sites reside at the interfaces between adjacent subunits, near the entrance to the extracellular gap, where local, side chain conformational rearrangements enable Ca(2+)chelation. Computational analysis revealed that Ca(2+)-binding generates a positive electrostatic barrier that substantially inhibits permeation of cations such as K(+) into the pore. Our results provide structural evidence for a unique mechanism of channel regulation: ionic conduction block via an electrostatic barrier rather than steric occlusion of the channel pore.

Pharmacokinetic Interactions for Drugs with a Long Half-Life­Evidence for the Need of Model-Based Analysis.

Pharmacokinetic drug-drug interactions (DDIs) can lead to undesired drug exposure, resulting in insufficient efficacy or aggravated toxicity. Accurate quantification of DDIs is therefore crucial but may be difficult when full concentration-time profiles are problematic to obtain. We have compared non-compartmental analysis (NCA) and model-based predictions of DDIs for long half-life drugs by conducting simulation studies and reviewing published trials, using antituberculosis drug bedaquiline (BDQ) as a model compound. Furthermore, different DDI study designs were evaluated. A sequential design mimicking conducted trials and a population pharmacokinetic (PK) model of BDQ and the M2 metabolite were utilized in the simulations where five interaction scenarios from strong inhibition (clearance fivefold decreased) to strong induction (clearance fivefold increased) were evaluated. In trial simulations, NCA systematically under-predicted the DDIs' impact. The bias in average exposure was 29­96% for BDQ and 20­677% for M2. The model-based analysis generated unbiased predictions, and simultaneous fitting of metabolite data increased precision in DDI predictions. The discrepancy between the methods was also apparent for conducted trials, e.g., lopinavir/ritonavir was predicted to increased BDQ exposure 22% by NCA and 188% by model-based methods. In the design evaluation, studies with parallel designs were considered and shown to generally be inferior to sequential/cross-over designs. However, in the case of low inter-individual variability and no informative metabolite data, a prolonged parallel design could be favored. Model-based analysis for DDI assessments is preferable over NCA for victim drugs with a long half-life and should always be used when incomplete concentration-time profiles are part of the analysis.

PeptiSite: a structural database of peptide binding sites in 4D.

We developed PeptiSite, a comprehensive and reliable database of biologically and structurally characterized peptide-binding sites, in which each site is represented by an ensemble of its complexes with protein, peptide and small molecule partners. The unique features of the database include: (1) the ensemble site representation that provides a fourth dimension to the otherwise three dimensional data, (2) comprehensive characterization of the binding site architecture that may consist of a multimeric protein assembly with cofactors and metal ions and (3) analysis of consensus interaction motifs within the ensembles and identification of conserved determinants of these interactions. Currently the database contains 585 proteins with 650 peptide-binding sites. http://peptisite.ucsd.edu/ link allows searching for the sites of interest and interactive visualization of the ensembles using the ActiveICM web-browser plugin. This structural database for protein-peptide interactions enables understanding of structural principles of these interactions and may assist the development of an efficient peptide docking benchmark.

A small molecule agonist of EphA2 receptor tyrosine kinase inhibits tumor cell migration in vitro and prostate cancer metastasis in vivo.

During tumor progression, EphA2 receptor can gain ligand-independent pro-oncogenic functions due to Akt activation and reduced ephrin-A ligand engagement. The effects can be reversed by ligand stimulation, which triggers the intrinsic tumor suppressive signaling pathways of EphA2 including inhibition of PI3/Akt and Ras/ERK pathways. These observations argue for development of small molecule agonists for EphA2 as potential tumor intervention agents. Through virtual screening and cell-based assays, we report here the identification and characterization of doxazosin as a novel small molecule agonist for EphA2 and EphA4, but not for other Eph receptors tested. NMR studies revealed extensive contacts of doxazosin with EphA2/A4, recapitulating both hydrophobic and electrostatic interactions recently found in the EphA2/ephrin-A1 complex. Clinically used as an α1-adrenoreceptor antagonist (Cardura®) for treating hypertension and benign prostate hyperplasia, doxazosin activated EphA2 independent of α1-adrenoreceptor. Similar to ephrin-A1, doxazosin inhibited Akt and ERK kinase activities in an EphA2-dependent manner. Treatment with doxazosin triggered EphA2 receptor internalization, and suppressed haptotactic and chemotactic migration of prostate cancer, breast cancer, and glioma cells. Moreover, in an orthotopic xenograft model, doxazosin reduced distal metastasis of human prostate cancer cells and prolonged survival in recipient mice. To our knowledge, doxazosin is the first small molecule agonist of a receptor tyrosine kinase that is capable of inhibiting malignant behaviors in vitro and in vivo.

Identification of novel nonsteroidal compounds as substrates or inhibitors of hASBT.

A prodrug approach that employs the human apical sodium dependent bile acid transporter (hASBT) for absorption requires a recognition moiety for hASBT. Bile acids are natural ligands for hASBT, but are hormones with high molecular weight, such that a recognition moiety that is not a bile acid may be advantageous. The objective was to identify nonsteroidal small molecules that could potentially serve as promoieties in the design of prodrugs that target hASBT. Three searches for bile acid analogues were conducted and it involved molecular fingerprints as the computational tools for similarity searching, as well as traditional medicinal chemistry pattern recognition. Sixty-three compounds were tested using a hASBT-Madin-Darby canine kidney cell monolayer model. Twenty-three of these compounds were found to be hASBT inhibitors and represent novel hASBT inhibitors. Three were selected for hASBT uptake studies. Two were substrates, which represent the first reported nonsteroidal substrates of hASBT. Interestingly, each compound lacked a negative charge. These compounds promise to serve as leads to identify hASBT recognition moieties in a prodrug approach to target hASBT to increase drug absorption.

Recent advances in ligand-based drug design: relevance and utility of the conformationally sampled pharmacophore approach.

In the absence of three-dimensional (3D) structures of potential drug targets, ligand-based drug design is one of the popular approaches for drug discovery and lead optimization. 3D structure-activity relationships (3D QSAR) and pharmacophore modeling are the most important and widely used tools in ligand-based drug design that can provide crucial insights into the nature of the interactions between drug target and ligand molecule and provide predictive models suitable for lead compound optimization. This review article will briefly discuss the features and potential application of recent advances in ligand-based drug design, with emphasis on a detailed description of a novel 3D QSAR method based on the conformationally sample pharmacophore (CSP) approach (denoted CSP-SAR). In addition, data from a published study are used to compare the CSP-SAR approach to the Catalyst method, emphasizing the utility of the CSP approach for ligand-based model development.

Structural requirements of the ASBT by 3D-QSAR analysis using aminopyridine conjugates of chenodeoxycholic acid.

The human apical sodium-dependent bile acid transporter (ASBT) is a validated drug target and can be employed to increase oral bioavailability of various drug conjugates. The aim of the present study was to investigate the chemical space around the 24-position of bile acids that influences both inhibition and uptake by the transporter. A series of 27 aminopyridine and aminophenol conjugates of glutamyl-chenodeoxycholate were synthesized and their ASBT inhibition and transport kinetics (parametrized as K(i), K(t), and J(max)) measured using stably transfected ASBT-MDCK cells. All conjugates were potent ASBT inhibitors. Monoanionic conjugates exhibited higher inhibition potency than neutral conjugates. However, neutral conjugates and chloro-substituted monoanionic conjugates were not substrates, or at least not apparent substrates. Kinetic analysis of substrates indicated that similar values for K(i) and K(t) implicate substrate binding to ASBT as the rate-limiting step. Using 3D-QSAR, four inhibition models and one transport efficiency model were developed. Steric fields dominated in CoMFA models, whereas hydrophobic fields dominated CoMSIA models. The inhibition models showed that a hydrophobic or bulky substitute on the 2 or 6 position of a 3-aminopyridine ring enhanced activity, while a hydrophobic group on the 5 position was detrimental. Overall, steric and hydrophobic features around the 24 position of the sterol nucleus strongly influenced bile acid conjugate interaction with ASBT. The relative location of the pyridine nitrogen and substituent groups also modulated binding.

Structural determinants for transport across the intestinal bile acid transporter using C-24 bile acid conjugates.

The human apical sodium dependent bile acid transporter (hASBT) reabsorbs gram quantities of bile acid daily and is a potential prodrug target to increase oral drug absorption. In the absence of a high resolution hASBT crystal structure, 3D-QSAR modeling may prove beneficial in designing prodrug targets to hASBT. The objective was to derive a conformationally sampled pharmacophore 3D-QSAR (CSP-SAR) model for the uptake of bile acid conjugates by hASBT. A series of bile acid conjugates of glutamyl chenodeoxycholate were evaluated in terms of K(m) and normalized V(max) (normV(max)) using hASBT-MDCK cells. All monoanionic conjugates were potent substrates. Dianions, cations and zwitterions, which bound with a high affinity, were not substrates. CSP-SAR models were derived using structural and physicochemical descriptors, and evaluated via cross validation. The best CSP-SAR model for K(m) included two structural and two physiochemical descriptors, where substrate hydrophobicity enhanced affinity. A best CSP-SAR model for K(m)/normV(max) employed one structural and three physicochemical descriptors, also indicating hydrophobicity enhanced efficiency. Overall, the bile acid C-24 region accommodated a range of substituted anilines, provided a single negative charge was present near C-24. In comparing uptake findings to prior inhibition results, increased hydrophobicity enhanced activity, with dianions and zwitterions hindering activity.

Molecular switch controlling the binding of anionic bile acid conjugates to human apical sodium-dependent bile acid transporter.

The human apical sodium-dependent bile acid transporter (hASBT) may serve as a prodrug target for oral drug absorption. Synthetic, biological, NMR, and computational approaches identified the structure-activity relationships of mono- and dianionic bile acid conjugates for hASBT binding. Experimental data combined with a conformationally sampled pharmacophore/QSAR modeling approach (CSP-SAR) predicted that dianionic substituents with intramolecular hydrogen bonding between hydroxyls on the cholane skeleton and the acid group on the conjugate's aromatic ring increased conjugate hydrophobicity and improved binding affinity. Notably, the model predicted the presence of a conformational molecular switch, where shifting the carboxylate substituent on an aromatic ring by a single position controlled binding affinity. Model validation was performed by effectively shifting the spatial location of the carboxylate by inserting a methylene adjacent to the aromatic ring, resulting in the predicted alteration in binding affinity. This work illustrates conformation as a determinant of ligand physiochemical properties and ligand binding affinity to a biological transporter.

Synthesis and Characterization of a Novel Diels - Alder Adduct of Codeine.

The Diels - Alder reaction was applied to 4,5-epoxymorphinan opioids to generate a novel aromatic cycloadduct at C(7) - C(8): Thermolytic cleavage of sultine 8 produced the reactive diene o-quinodimethane 7 which condensed favorably with codeine (11), but not with codeinone (9) or 14- hydroxycodeinone (10), producing the desired tetrahydronaphtho adduct 12 with (7R,8R) geometry (Scheme). The configuration of the cycloadduct was determined by 1D- and 2D-NMR experiments. The unanticipated reactivity of these codeine derivatives was investigated by quantum-mechanical calculations, and it was determined that steric effects of the 6-keto and 14-hydroxy group likely precluded condensation by raising the molecular energy of their respective transition states.

Inhibition requirements of the human apical sodium-dependent bile acid transporter (hASBT) using aminopiperidine conjugates of glutamyl-bile acids.

PURPOSE: Synthesize aminopiperidine conjugates of glutamyl-bile acids (glu-BAs) and develop a hASBT inhibition model using the conformationally sampled pharmacophore (CSP) approach. METHODS: glu-BAs aminopiperidine conjugates were synthesized. hASBT inhibition was measured as K(i). A CSP-SAR model was built using structural and physico-chemical descriptors and evaluated via cross-validation. RESULTS: Twenty-nine aminopiperidine conjugates were synthesized. All inhibited hASBT, with K(i) ranging from 0.95 to 31.8 muM. Amidation of the piperidine nitrogen slightly decreased activity, while replacement by a carbon increased potency. Esterification of the glutamic acid linker had a minor impact, suggesting that a negative charge around C-24 is not required for binding. Three quantitative CSP-SAR models were developed. The best model (r (2) = 0.813, Q (2) = 0.726) included two descriptors: angle between 7-OH, alpha-substituent and centroid of rings B and C, and electrostatic contribution to the solvation free-energy. The model successfully distinguished between compounds with K(i) < 16muM and K(i) > 16muM. Models indicated that hydrophobicity, alpha substituent orientation, and partially compacted side chain conformation promote inhibitory potency. Qualitative CSP-SAR analysis indicated that the presence of an internal salt bridge, resulting in a locked conformation of the side chain, yielded weaker inhibitors. CONCLUSIONS: Aminopiperidine conjugates of glu-BAs were potent hASBT inhibitors. A predictive and robust CSP-SAR model was developed.

Computational model for predicting chemical substituent effects on passive drug permeability across parallel artificial membranes.

Drug permeability is often a limiting step in drug action, requiring chemical optimization of a drug candidate to improve this property. Such optimization is typically performed in the context of a congeneric series, where substituents are varied to optimize the target property. Motivated by this need the present work examines the influence of chemical substituents on passive permeability (log P pass) across parallel artificial membranes (PAMPA) undertaken for three congeneric series of compounds; benzoic acids, pyridines and quinolines. PAMPA showed pyridine and quinoline to have high permeability and chemical substituents to typically reduce the permeability. On the contrary, benzoic acid showed poor permeability and chemical substituents typically increased the permeability. To quantitate these effects with respect to physical properties, models were built to explain and predict the permeability of these classes of compounds based on computed molecular descriptors. Models for the benzoic acid series in the ionized state indicated the solvent accessible surface area, cavity dispersion and the free energy of solvation in hexane as well as in water to dominate permeability. However, when the acid group is treated as neutral, the free energy of solvation in water, the fraction polar surface area, the polar surface area and difference in the free energy of solvation between hexane and water were important; these terms, among others, were also important for the neutral pyridine-quinoline series. Considering that the permeability of the benzoic acid series is about 2 orders of magnitude lower than the pyridines and quinolines and that a shift of approximately two pH units in the p K a of the acid group of benzoic acid will allow for the neutral species of the molecule to dominate under experimental conditions (pH = 6.5), these results suggest that the additional energy barrier associated with permeation of the benzoic acid series is associated with the need to protonate the acidic group, thereby forming the neutral species which may then cross the hydrophobic region of the membrane.