Population pharmacokinetic and exposure-efficacy analysis of ixekizumab in paediatric patients with moderate-to-severe plaque psoriasis (IXORA-PEDS).

AIMS: Ixekizumab is a high-affinity monoclonal antibody that selectively targets interleukin-17A used in the treatment of adult and paediatric patients with moderate-to-severe psoriasis. This analysis evaluated the pharmacokinetics (PK) of ixekizumab and the exposure-efficacy relationship in paediatric patients aged 6 to <18 years with psoriasis. METHODS: Population PK and exposure-efficacy models were developed. The models used data from paediatric patients with psoriasis participating in the Phase 3 IXORA-PEDS trial in which patients were dosed according to weight categories. The exposure-efficacy model is a Psoriasis Area and Severity Index (PASI) time course model using data up to Week 12, a co-primary efficacy endpoint. RESULTS: A 2-compartment population PK model describes the PK of ixekizumab in paediatric patients with the effect of body weight incorporated on clearance and volume terms using an allometric relationship. The weight category-based dosing ensured that ixekizumab mean trough serum concentrations in paediatric patients with psoriasis (3.20-3.33 µg/mL) were within the range of concentrations observed in adult patients with psoriasis (mean [standard deviation]: 3.48 [2.16] µg/mL) administered an efficacious dosing regimen. The observed PASI response rates at Week 12 in paediatric patients (91.9/81.8/52.5% for PASI75/90/100) are well predicted by the final exposure-efficacy model and response rates are similar or higher than those achieved in adults (86.2/66.6/35.0% for PASI75/90/100). CONCLUSION: This analysis is the first to describe the PK and exposure-efficacy relationship of ixekizumab in paediatric patients with psoriasis. The analyses support the selection of the weight category-based ixekizumab dosing regimens approved for use in paediatric patients with psoriasis.

Population Pharmacokinetics of Tadalafil in Pediatric Patients with Pulmonary Arterial Hypertension: A Combined Adult/Pediatric Model.

BACKGROUND: Tadalafil 40 mg once daily is approved for adult patients with pulmonary arterial hypertension (PAH). To investigate and potentially fulfill an unmet need in pediatric patients with PAH, pharmacokinetic (PK) data were explored in a pediatric phase Ib/II study and pooled with prior phase III (pulmonary arterial hypertension and response to tadalafil [PHIRST-1]) adult data to develop the first population PK model for tadalafil in pediatric patients with PAH. METHODS: H6D-MC-LVIG (NCT01484431) was an open-label, multicenter, multiple ascending dose study in pediatric patients with PAH, while PHIRST-1 was a phase III, multicenter, randomized, double-blind, placebo-controlled, parallel design study in adults with PAH who received one of five treatments (tadalafil 2.5, 10, 20, or 40 mg, or placebo orally, once daily). PK data from the studies were pooled to develop a pediatric population PK model for tadalafil that characterized relationships among dose, exposure, and the effects of covariates with an aim to develop a population PK model that could simulate concentration-time profiles and assess exposure-matched dosing strategies in a pediatric PAH population. RESULTS: In line with the observed data, modeling and simulation demonstrated that the doses studied in the pediatric population produced area under the concentration-time curves (AUCs) within the range of those associated with improved exercise ability in adults with PAH. The analyses included 1430 observations from 305 adult patients (PHIRST-1: 69 males and 236 females, 1102 observations) and 19 pediatric patients (LVIG: 6 males and 13 females, 328 observations) who received tadalafil once daily at different dose levels. The best-fit base model retained an effect of weight on apparent volume of distribution (V/F), fixed to the allometric scaling value of 1, and did not include an effect of weight on apparent clearance (CL/F). Other covariate effects were that bosentan increased CL/F, V/F decreased with decreasing body weight, and bioavailability (F) decreased with increasing dose and decreasing age. The PK model reliably predicted the observed concentrations and overall variability evident from the overlap of the individual observed concentrations with the distributions of simulated concentrations. CONCLUSIONS: A one-compartment model parameterized in terms of F, absorption rate constant, CL/F, and V/F described the data well. The model demonstrated that plasma tadalafil concentrations in pediatric patients aged 2 to < 18 years were similar to those in adults at similar doses, and confirmed that dosing of 40 mg once daily in pediatric patients with a bodyweight ≥ 40 kg, and a dose of 20 mg once daily in patients with a body weight < 40 kg and aged ≥ 2 years are suitable for phase III evaluation. TRIAL REGISTRATION NUMBER (DATE OF REGISTRATION): LVIG: ClinicalTrials.gov identifier: NCT01484431 (2 December 2011). PHIRST-1: ClinicalTrials.gov identifier: NCT00125918 (2 August 2005).

Blocking TIM-3 in Treatment-refractory Advanced Solid Tumors: A Phase Ia/b Study of LY3321367 with or without an Anti-PD-L1 Antibody.

PURPOSE: T-cell immunoglobulin and mucin-domain-containing molecule-3 (TIM-3) blunts anticancer immunity and mediates resistance to programmed death 1 (PD-1) and PD ligand 1 (PD-L1) inhibitors. We assessed a novel, first-in-class, TIM-3 mAb, LY3321367, alone or in combination with the anti-PD-L1 antibody, LY300054 in patients with advanced solid tumor. PATIENTS AND METHODS: This open-label, multicenter, phase Ia/b study aimed to define the safety/tolerability and recommended phase II dose (RP2D) of LY3321367 with or without LY300054. Secondary objectives included pharmacokinetics/pharmacodynamics, immunogenicity, and efficacy. Biomarkers were assessed in exploratory analysis. RESULTS: No dose-limiting toxicities were observed in the monotherapy (N = 30) or combination (N = 28) dose escalation. LY3321367 treatment-related adverse events (≥2 patients) included pruritus, rash, fatigue, anorexia, and infusion-related reactions. Dose-proportional increase in LY3321367 concentrations was not affected by either LY300054 or antidrug antibodies (observed in 50%-70% of patients). Pharmacokinetic/pharmacodynamic modeling indicated 100% target engagement at doses ≥600 mg. LY3321367 RP2D was 1,200 mg biweekly for four doses followed by 600 mg every 2 weeks thereafter. In the non-small cell lung cancer monotherapy expansion cohort, outcomes varied by prior anti-PD-1 therapy response status: anti-PD-1/L1 refractory patients [N = 23, objective response rate (ORR) 0%, disease control rate (DCR) 35%, progression-free survival (PFS) 1.9 months] versus anti-PD-1/L1 responders (N = 14, ORR 7%, DCR 50%, PFS 7.3 months). In combination expansion cohorts (N = 91), ORR and DCR were 4% and 42%; CD8 infiltration in paired biopsies increased in approximately half these patients. CONCLUSIONS: LY3321367 exhibited acceptable safety profile with favorable pharmacokinetics/pharmacodynamics but only modest antitumor activity. The therapeutic relevance of TIM-3 blockade requires further investigation.

Exposure-Response Modeling to Characterize the Relationship Between Ixekizumab Serum Drug Concentrations and Efficacy Responses at Week 12 in Patients With Moderate to Severe Plaque Psoriasis.

Ixekizumab, a high-affinity monoclonal antibody, selectively targets interleukin-17A and has been shown to be efficacious in the treatment of moderate to severe psoriasis. The objective was to describe the relationship between ixekizumab concentrations and efficacy response (static Physician Global Assessment [sPGA] and the Psoriasis Activity and Severity Index [PASI) scores] after 12 weeks of ixekizumab treatment in psoriasis patients from 3 phase 3 studies. Data from 2888 psoriasis patients randomized to receive placebo or 80 mg ixekizumab every 2 weeks or every 4 weeks were analyzed. Separate logistic regression models describing the relationship between ixekizumab concentrations and sPGA or PASI scores at week 12 were used to determine the probability of patients achieving a response and to investigate the impact of various patient factors other than drug concentrations on response rates. Both dosing regimens were efficacious, with higher rates of response achieved with the higher range of observed ixekizumab concentrations after every-2-week dosing. Although higher bodyweight, palmoplantar involvement, lower baseline disease state, or high baseline C-reactive protein were associated with slightly lower response rates, the magnitude of effect of these factors on sPGA(0,1) response was small, with all subgroups able to achieve high levels of response. Other factors tested had no effect including age, sex, and antidrug antibody status. Logistic regression modeling of ixekizumab concentration and efficacy data accurately identified the proportion of responders using sPGA or PASI end points. The higher concentration ranges achieved with 80 mg every 2 weeks versus every 4 weeks were associated with higher response levels.

A population PK model for citalopram and its major metabolite, N-desmethyl citalopram, in rats.

A population PK model was developed in order to simultaneously describe citalopram and its major metabolite, n-desmethyl citalopram, plasma concentrations in two different strain of rats after intravenous (IV) and oral (PO) administration of citalopram. Citalopram was administered to Sprague-Dawley (SD) rats at doses: 0.3, 1, 3, and 10 mg/kg IV and 10 mg/kg PO. The compound was dosed orally to Wistar rats at doses: 0.3, 1, 3, 10, 30 and 60 mg/kg. Plasma samples were collected for citalopram and metabolite. Pharmacokinetic analyses were conducted using NONMEM 7.2. Values below the quantification limit (BLQ < 0.1 ng/mL) were included in the analyses and treated as censored information. The disposition of citalopram was best described by a 3-compartment model and its desmethyl metabolite by a 2-compartment model. Several models for the absorption rate were explored (e.g. first, zero order and combined first and zero order absorption, Michaelis-Menten, lag time) in combination with dose and/or time dependent covariate effects. Dose dependent oral bioavailability properties were also identified in this analysis. Citalopram IV clearance and metabolite formation rate were adequately described as linear processes. Metabolite clearance was adequately described using a Michaelis-Menten clearance with different parameters depending on the strain. This analysis demonstrates a very complex absorption/metabolism process explaining the highly non-linear pharmacokinetics observed across all the doses. This is the first combined parent/metabolite population PK analysis in both SD and Wistar rats over a wide range of IV and PO dosages for citalopram, a compound that exhibits highly nonlinear oral pharmacokinetics in rats.

Biomarkers for Diagnosis and Prognosis of Sinusoidal Obstruction Syndrome after Hematopoietic Cell Transplantation.

Reliable, noninvasive methods for diagnosing and prognosing sinusoidal obstruction syndrome (SOS) early after hematopoietic cell transplantation (HCT) are needed. We used a quantitative mass spectrometry-based proteomics approach to identify candidate biomarkers of SOS by comparing plasma pooled from 20 patients with and 20 patients without SOS. Of 494 proteins quantified, we selected 6 proteins (L-Ficolin, vascular cell adhesion molecule-1 [VCAM1], tissue inhibitor of metalloproteinase-1, von Willebrand factor, intercellular adhesion molecule-1, and CD97) based on a differential heavy/light isotope ratio of at least 2 fold, information from the literature, and immunoassay availability. Next, we evaluated the diagnostic potential of these 6 proteins and 5 selected from the literature (suppression of tumorigenicity-2 [ST2], angiopoietin-2 (ANG2), hyaluronic acid [HA], thrombomodulin, and plasminogen activator inhibitor-1) in samples from 80 patients. The results demonstrate that together ST2, ANG2, L-Ficolin, HA, and VCAM1 compose a biomarker panel for diagnosis of SOS. L-Ficolin, HA, and VCAM1 also stratified patients at risk for SOS as early as the day of HCT. Prognostic Bayesian modeling for SOS onset based on L-Ficolin, HA, and VCAM1 levels on the day of HCT and clinical characteristics showed >80% correct prognosis of SOS onset. These biomarkers may provide opportunities for preemptive intervention to minimize SOS incidence and/or severity.

A Compartmental Analysis for Morphine and Its Metabolites in Young Children After a Single Oral Dose.

BACKGROUND AND OBJECTIVES: Currently, the majority of the surgical procedures performed in paediatric hospitals are done on a day care basis, with post-operative pain being managed by caregivers at home. Pain after discharge of these post-operative children has historically been managed with oral codeine in combination with paracetamol (acetaminophen). Codeine is an opioid, which elicits its analgesic effects via metabolism to morphine and codeine-6-glucuronide. Oral morphine is a feasible alternative for outpatient analgesia; however, the pharmacokinetics of morphine after oral administration have been previously described only sparsely, and there is little information in healthy children. METHODS: The clinical trial included 40 children from 2 to 6 years of age, with an American Society of Anaesthesiologists physical status classification of 1 or 2, who were undergoing surgical procedures requiring opioid analgesia. Morphine was orally administered prior to surgery in one of three doses: 0.1 mg/kg, 0.2 mg/kg and 0.3 mg/kg. Blood samples were collected for plasma morphine, morphine-3-glucuronide (M3G) and morphine-6-glucuronide (M6G) concentrations at 30, 60, 90, 120, 180 and 240 min after administration. All analyses were performed with the non-linear mixed-effect modelling software NONMEM version 7.2, using the first-order conditional estimation (FOCE) method. RESULTS: A pharmacokinetic model was developed to simultaneously describe the plasma profiles of morphine and its metabolites M3G and M6G after a single dose of oral morphine in young children (2-6 years of age). The disposition of morphine, M3G and M6G in plasma was best described by a one-compartment model. M3G and M6G metabolite formation was best described by a delay transit compartment, indicating a delay in the appearance of these two major metabolites. CONCLUSION: This model provides a foundation on which to further evaluate the use of oral morphine and its safety in young children. Longer follow-up time for morphine oral doses and incorporation of other important covariates, such as phenotype, will add value and will help overcome the limitations of the presented population pharmacokinetic analysis.

Nicotine and cotinine exposure from electronic cigarettes: a population approach.

BACKGROUND AND OBJECTIVES: Electronic cigarettes (e-cigarettes) are a recent technology that has gained rapid acceptance. Still, little is known about them in terms of safety and effectiveness. A basic question is how effectively they deliver nicotine; however, the literature is surprisingly unclear on this point. Here, a population pharmacokinetic model was developed for nicotine and its major metabolite cotinine with the aim to provide a reliable framework for the simulation of nicotine and cotinine concentrations over time, based solely on inhalation airflow recordings and individual covariates [i.e., weight and breath carbon monoxide (CO) levels]. METHODS: This study included ten adults self-identified as heavy smokers (at least one pack of cigarettes per day). Plasma nicotine and cotinine concentrations were measured at regular 10-min intervals for 90 min while human subjects inhaled nicotine vapor from a modified e-cigarette. Airflow measurements were recorded every 200 ms throughout the session. A population pharmacokinetic model for nicotine and cotinine was developed based on previously published pharmacokinetic parameters and the airflow recordings. All of the analyses were performed with the non-linear mixed-effect modeling software NONMEM(®) version 7.2. RESULTS: The results show that e-cigarettes deliver nicotine effectively, although the pharmacokinetic profiles are lower than those achieved with regular cigarettes. Our pharmacokinetic model effectively predicts plasma nicotine and cotinine concentrations from the inhalation volume, and initial breath CO. CONCLUSION: E-cigarettes are effective at delivering nicotine. This new pharmacokinetic model of e-cigarette usage might be used for pharmacodynamic analysis where the pharmacokinetic profiles are not available.

Prediction of brain clozapine and norclozapine concentrations in humans from a scaled pharmacokinetic model for rat brain and plasma pharmacokinetics.

BACKGROUND: Clozapine is highly effective in treatment-resistant schizophrenia, although, there remains significant variability in the response to this drug. To better understand this variability, the objective of this study was to predict brain extracellular fluid (ECF) concentrations and receptor occupancy of clozapine and norclozapine in human central nervous system by translating plasma and brain ECF pharmacokinetic (PK) relationships in the rat and coupling these with known human disposition of clozapine in the plasma. METHODS: Unbound concentrations of clozapine and norclozapine were measured in rat brain ECF using quantitative microdialysis after subcutaneous administration of a 10 mg/kg single dose of clozapine or norclozapine. These data were linked with plasma concentrations obtained in the same rats to develop a plasma-brain ECF compartmental model. Parameters describing brain ECF disposition were then allometrically scaled and linked with published human plasma PK to predict human ECF concentrations. Subsequently, prediction of human receptor occupancy at several CNS receptors was based on an effect model that related the predicted ECF concentrations to published concentration-driven receptor occupancy parameters. RESULTS: A one compartment model with first order absorption and elimination best described clozapine and norclozapine plasma concentrations in rats. A delay in the transfer of clozapine and norclozapine from plasma to the brain ECF compartment was captured using a transit compartment model approach. Human clozapine and norclozapine concentrations in brain ECF were simulated, and from these the median percentage of receptor occupancy of dopamine-2, serotonin-2A, muscarinic-1, alpha-1 adrenergic, alpha-2 adrenergic and histamine-1 for clozapine, and dopamine-2 for norclozapine were consistent with values reported in the literature. CONCLUSIONS: A PK model that relates clozapine and norclozapine disposition in rat plasma and brain, including blood-brain barrier transport, was developed. Using allometry and published human plasma PK, the model was successfully translated to predict clozapine and norclozapine concentrations and accordant receptor occupancy of both agents in human brain. These predicted exposure and occupancy measures at several receptors that bind clozapine may be employed to extend our understanding of clozapine's complex behavioral effects in humans.

Resting-brain functional connectivity predicted by analytic measures of network communication.

The complex relationship between structural and functional connectivity, as measured by noninvasive imaging of the human brain, poses many unresolved challenges and open questions. Here, we apply analytic measures of network communication to the structural connectivity of the human brain and explore the capacity of these measures to predict resting-state functional connectivity across three independently acquired datasets. We focus on the layout of shortest paths across the network and on two communication measures--search information and path transitivity--which account for how these paths are embedded in the rest of the network. Search information is an existing measure of information needed to access or trace shortest paths; we introduce path transitivity to measure the density of local detours along the shortest path. We find that both search information and path transitivity predict the strength of functional connectivity among both connected and unconnected node pairs. They do so at levels that match or significantly exceed path length measures, Euclidean distance, as well as computational models of neural dynamics. This capacity suggests that dynamic couplings due to interactions among neural elements in brain networks are substantially influenced by the broader network context adjacent to the shortest communication pathways.

Modelling the sitagliptin effect on dipeptidyl peptidase-4 activity in adults with haematological malignancies after umbilical cord blood haematopoietic cell transplantation.

BACKGROUND AND OBJECTIVES: Dipeptidyl peptidase-4 (DPP4) inhibition is a potential strategy to increase the engraftment rate of haematopoietic stem/progenitor cells. A recent clinical trial using sitagliptin, a DPP4 inhibitor approved for type 2 diabetes mellitus, has been shown to be a promising approach in adults with haematological malignancies after umbilical cord blood (UCB) haematopoietic cell transplantation (HCT). On the basis of data from this clinical trial, a semi-mechanistic model was developed to simultaneously describe DPP4 activity after multiple doses of sitagliptin in subjects with haematological malignancies after a single-unit UCB HCT. METHODS: The clinical study included 24 patients who received myeloablative conditioning followed by oral sitagliptin with single-unit UCB HCT. Using a nonlinear mixed-effects approach, a semi-mechanistic pharmacokinetic-pharmacodynamic model was developed to describe DPP4 activity from these trial data, using NONMEM version 7.2 software. The model was used to drive Monte Carlo simulations to probe the various dosage schedules and the attendant DPP4 response. RESULTS: The disposition of sitagliptin in plasma was best described by a two-compartment model. The relationship between sitagliptin concentrations and DPP4 activity was best described by an indirect response model with a negative feedback loop. Simulations showed that twice daily or three times daily dosage schedules were superior to a once daily schedule for maximal DPP4 inhibition at the lowest sitagliptin exposure. CONCLUSION: This study provides the first pharmacokinetic-pharmacodynamic model of sitagliptin in the context of HCT, and provides a valuable tool for exploration of optimal dosing regimens, which are critical for improving the time to engraftment in patients after UCB HCT.

Predicting relapsing-remitting dynamics in multiple sclerosis using discrete distribution models: a population approach.

BACKGROUND: Relapsing-remitting dynamics are a hallmark of autoimmune diseases such as Multiple Sclerosis (MS). A clinical relapse in MS reflects an acute focal inflammatory event in the central nervous system that affects signal conduction by damaging myelinated axons. Those events are evident in T1-weighted post-contrast magnetic resonance imaging (MRI) as contrast enhancing lesions (CEL). CEL dynamics are considered unpredictable and are characterized by high intra- and inter-patient variability. Here, a population approach (nonlinear mixed-effects models) was applied to analyse of CEL progression, aiming to propose a model that adequately captures CEL dynamics. METHODS AND FINDINGS: We explored several discrete distribution models to CEL counts observed in nine MS patients undergoing a monthly MRI for 48 months. All patients were enrolled in the study free of immunosuppressive drugs, except for intravenous methylprednisolone or oral prednisone taper for a clinical relapse. Analyses were performed with the nonlinear mixed-effect modelling software NONMEM 7.2. Although several models were able to adequately characterize the observed CEL dynamics, the negative binomial distribution model had the best predictive ability. Significant improvements in fitting were observed when the CEL counts from previous months were incorporated to predict the current month's CEL count. The predictive capacity of the model was validated using a second cohort of fourteen patients who underwent monthly MRIs during 6-months. This analysis also identified and quantified the effect of steroids for the relapse treatment. CONCLUSIONS: The model was able to characterize the observed relapsing-remitting CEL dynamic and to quantify the inter-patient variability. Moreover, the nature of the effect of steroid treatment suggested that this therapy helps resolve older CELs yet does not affect newly appearing active lesions in that month. This model could be used for design of future longitudinal studies and clinical trials, as well as for the evaluation of new therapies.

Therapeutic hypothermia decreases phenytoin elimination in children with traumatic brain injury.

OBJECTIVE: Preclinical and clinical studies have suggested that therapeutic hypothermia, while decreasing neurologic injury, may also lead to drug toxicity that may limit its benefit. Cooling decreases cytochrome P450 (CYP)-mediated drug metabolism, and limited clinical data suggest that drug levels are elevated. Fosphenytoin is metabolized by cytochrome P450 2C, has a narrow therapeutic range, and is a commonly used antiepileptic medication. The objective of this study was to evaluate the impact of therapeutic hypothermia on phenytoin levels and pharmacokinetics in children with severe traumatic brain injury. DESIGN: Pharmacokinetic analysis of subjects participating in a multicenter randomized phase III study of therapeutic hypothermia for severe traumatic brain injury. SETTING: ICU at the Children's Hospital of Pittsburgh. PATIENTS: Nineteen children with severe traumatic brain injury. INTERVENTIONS: None. MEASUREMENTS AND MAIN RESULTS: A sum of 121 total and 114 free phenytoin levels were evaluated retrospectively in 10 hypothermia-treated and nine normothermia-treated children who were randomized to 48 hours of cooling to 32-33°C followed by slow rewarming or controlled normothermia. Drug dosing, body temperatures, and demographics were collected during cooling, rewarming, and posttreatment periods (8 d). A trend toward elevated free phenytoin levels in the hypothermia group (p=0.051) to a median of 2.2 mg/L during rewarming was observed and was not explained by dosing differences. Nonlinear mixed-effects modeling incorporating both free and total levels demonstrated that therapeutic hypothermia specifically decreased the time-variant component of the maximum velocity of phenytoin metabolism (Vmax) 4.6-fold (11.6-2.53 mg/hr) and reduced the overall Vmax by ~50%. Simulations showed that the increased risk for drug toxicity extends many days beyond the end of the cooling period. CONCLUSIONS: Therapeutic hypothermia significantly reduces phenytoin elimination in children with severe traumatic brain injury leading to increased drug levels for an extended period of time after cooling. Pharmacokinetic interactions between hypothermia and medications should be considered when caring for children receiving this therapy.

Dynamic cross-regulation of antigen-specific effector and regulatory T cell subpopulations and microglia in brain autoimmunity.

BACKGROUND: Multiple Sclerosis (MS) is considered a T-cell-mediated autoimmune disease with a prototypical oscillatory behavior, as evidenced by the presence of clinical relapses. Understanding the dynamics of immune cells governing the course of MS, therefore, has many implications for immunotherapy. Here, we used flow cytometry to analyze the time-dependent behavior of antigen-specific effector (T(eff)) and regulatory (T(reg)) T cells and microglia in mice model of MS, Experimental Autoimmune Encephalomyelitis (EAE), and compared the observations with a mathematical cross-regulation model of T-cell dynamics in autoimmune disease. RESULTS: We found that T(eff) and T(reg) cells specific to myelin olygodendrocyte glycoprotein (MOG) developed coupled oscillatory dynamics with a 4- to 5-day period and decreasing amplitude that was always higher for the T(eff) populations, in agreement with the mathematical model. Microglia activation followed the oscillations of MOG-specific T(eff) cells in the secondary lymphoid organs, but they were activated before MOG-specific T-cell peaks in the CNS. Finally, we assessed the role of B-cell depletion induced by anti-CD20 therapy in the dynamics of T cells in an EAE model with more severe disease after therapy. We observed that B-cell depletion decreases T(eff) expansion, although its oscillatory behavior persists. However, the effect of B cell depletion was more significant in the T(reg) population within the CNS, which matched with activation of microglia and worsening of the disease. Mathematical modeling of T-cell cross-regulation after anti-CD20 therapy suggests that B-cell depletion may influence the dynamics of T cells by fine-tuning their activation. CONCLUSIONS: The oscillatory dynamics of T-cells have an intrinsic origin in the physiological regulation of the adaptive immune response, which influences both disease phenotype and response to immunotherapy.

Exploring the morphospace of communication efficiency in complex networks.

Graph theoretical analysis has played a key role in characterizing global features of the topology of complex networks, describing diverse systems such as protein interactions, food webs, social relations and brain connectivity. How system elements communicate with each other depends not only on the structure of the network, but also on the nature of the system's dynamics which are constrained by the amount of knowledge and resources available for communication processes. Complementing widely used measures that capture efficiency under the assumption that communication preferentially follows shortest paths across the network ("routing"), we define analytic measures directed at characterizing network communication when signals flow in a random walk process ("diffusion"). The two dimensions of routing and diffusion efficiency define a morphospace for complex networks, with different network topologies characterized by different combinations of efficiency measures and thus occupying different regions of this space. We explore the relation of network topologies and efficiency measures by examining canonical network models, by evolving networks using a multi-objective optimization strategy, and by investigating real-world network data sets. Within the efficiency morphospace, specific aspects of network topology that differentially favor efficient communication for routing and diffusion processes are identified. Charting regions of the morphospace that are occupied by canonical, evolved or real networks allows inferences about the limits of communication efficiency imposed by connectivity and dynamics, as well as the underlying selection pressures that have shaped network topology.

Joint population pharmacokinetic/pharmacodynamic model for the heart rate effects at rest and at the end of exercise for cilobradine.

PURPOSE: To develop a semi-mechanistic population pharmacokinetic/pharmacodynamic (PKPD) model for the selective bradycardic agent cilobradine describing simultaneously the heart rate (HR) measured at rest and just after the end of exercise sharing the same set of PKPD parameters. METHODS: Healthy subjects received cilobradine orally once daily over 2 weeks at 0.25-5 mg doses or placebo. Plasma drug concentrations and HR were measured at rest and following 3 min of exercise over the entire study period. PK and HR data were analyzed using the population approach with NONMEM VII. RESULTS: Plasma disposition of cilobradine was described with a three compartment model. Cilobradine showed dose proportional and time independent pharmacokinetics. HR response was drug concentration dependent and appeared with a significant delay with respect to PK profiles, a phenomenon modeled using two transit compartments. Perturbation in HR at rest as a consequence of exercise was described assuming that physiological processes controlling cardiac frequency were constantly increased over the period of exercise only. CONCLUSIONS: The selected model provides a useful modeling tool for cases where the PD response measured is the result of a temporal experimental induced perturbation.

Semi-mechanistic modeling of the interaction between the central and peripheral effects in the antinociceptive response to lumiracoxib in rats.

The model-based approach was undertaken to characterize the interaction between the peripheral and central antinociceptive effects exerted by lumiracoxib. The effects of intraplantar and intrathecal administrations and of fixed ratio combinations of lumiracoxib simultaneously administered by these two routes were evaluated using the formalin test in rats. Pain-related behavior data, quantified as the number of flinches of the injected paw, were analyzed using a population approach with NONMEM 7. The pain response during the first phase of the formalin test, which was insensitive to lumiracoxib, was modeled using a monoexponential decay. The second phase, which was sensitive to lumiracoxib, was described incorporating synthesis and degradation processes of pain mediators that were recruited locally after tissue injury. Upregulation at the local level and in the central nervous system (CNS) was set to be proportional to the predicted levels of pain mediators in the local (injured) compartment. Results suggest a greater role of upregulated COX-2(Local) in generating the pain response compared to COX-2(CNS). Drug effects were described as inhibition of upregulated COX-2. The model adequately described the time course of nociception after formalin injection in the absence or presence of lumiracoxib administered locally and/or spinally. Data suggest that the overall response is the additive outcome of drug effects at the peripheral and central compartments, with predominance of peripheral mechanisms. Application of modeling opens new perspectives for understanding the overall mechanism of action of analgesic drugs.

Pharmacokinetic/pharmacodynamic model of the testosterone effects of triptorelin administered in sustained release formulations in patients with prostate cancer.

The objectives of the current work were to develop a predictive population pharmacokinetic (PK)/pharmacodynamic (PD) model for the testosterone (TST) effects of triptorelin (TRP) administered in sustained-release (SR) formulations to patients with prostate cancer and determine the minimal required triptorelin serum concentration (C(TRP_min)) to keep the testosterone levels of the patients below or equal to the level of castration (TST ≤ 0.5 ng/ml). A total of eight healthy male volunteers and 74 patients with prostate cancer received one or two doses of triptorelin injected subcutaneously or intramuscularly. Five different triptorelin formulations were tested. Pharmacokinetic (serum concentration of triptorelin) and pharmacodynamic (TST levels in serum) data were analyzed by using the population approach with NONMEM software (http://www.iconplc.com/technology/products/nonmem/). The PK/PD model was constructed by assembling the agonist nature of triptorelin with the competitive reversible receptor binding interaction with the endogenous agonist, a process responsible for the initial and transient TST flare-up, and triggering down-regulation mechanisms described as a decrease in receptor synthesis. The typical population values of K(D), the receptor equilibrium dissociation constant of triptorelin, and C(TRP_min) to keep 95% of the patients castrated were 0.931 and 0.0609 ng/ml, respectively. The semimechanistic nature of the model renders the predictions of the effect of triptorelin on TST possible regardless the type of SR formulation administered, while exploring different designs during the development of new delivery systems.

Modeling the effector - regulatory T cell cross-regulation reveals the intrinsic character of relapses in Multiple Sclerosis.

BACKGROUND: The relapsing-remitting dynamics is a hallmark of autoimmune diseases such as Multiple Sclerosis (MS). Although current understanding of both cellular and molecular mechanisms involved in the pathogenesis of autoimmune diseases is significant, how their activity generates this prototypical dynamics is not understood yet. In order to gain insight about the mechanisms that drive these relapsing-remitting dynamics, we developed a computational model using such biological knowledge. We hypothesized that the relapsing dynamics in autoimmunity can arise through the failure in the mechanisms controlling cross-regulation between regulatory and effector T cells with the interplay of stochastic events (e.g. failure in central tolerance, activation by pathogens) that are able to trigger the immune system. RESULTS: The model represents five concepts: central tolerance (T-cell generation by the thymus), T-cell activation, T-cell memory, cross-regulation (negative feedback) between regulatory and effector T-cells and tissue damage. We enriched the model with reversible and irreversible tissue damage, which aims to provide a comprehensible link between autoimmune activity and clinical relapses and active lesions in the magnetic resonances studies in patients with Multiple Sclerosis. Our analysis shows that the weakness in this negative feedback between effector and regulatory T-cells, allows the immune system to generate the characteristic relapsing-remitting dynamics of autoimmune diseases, without the need of additional environmental triggers. The simulations show that the timing at which relapses appear is highly unpredictable. We also introduced targeted perturbations into the model that mimicked immunotherapies that modulate effector and regulatory populations. The effects of such therapies happened to be highly dependent on the timing and/or dose, and on the underlying dynamic of the immune system. CONCLUSION: The relapsing dynamic in MS derives from the emergent properties of the immune system operating in a pathological state, a fact that has implications for predicting disease course and developing new therapies for MS.

The semantic organization of the animal category: evidence from semantic verbal fluency and network theory.

Semantic memory is the subsystem of human memory that stores knowledge of concepts or meanings, as opposed to life-specific experiences. How humans organize semantic information remains poorly understood. In an effort to better understand this issue, we conducted a verbal fluency experiment on 200 participants with the aim of inferring and representing the conceptual storage structure of the natural category of animals as a network. This was done by formulating a statistical framework for co-occurring concepts that aims to infer significant concept-concept associations and represent them as a graph. The resulting network was analyzed and enriched by means of a missing links recovery criterion based on modularity. Both network models were compared to a thresholded co-occurrence approach. They were evaluated using a random subset of verbal fluency tests and comparing the network outcomes (linked pairs are clustering transitions and disconnected pairs are switching transitions) to the outcomes of two expert human raters. Results show that the network models proposed in this study overcome a thresholded co-occurrence approach, and their outcomes are in high agreement with human evaluations. Finally, the interplay between conceptual structure and retrieval mechanisms is discussed.