Compartmental Modeling Approach Research Articles

Identifying robustness in the regulation of collective foraging of ant colonies using an interaction-based model with backward bifurcation.

Collective behaviors in social insect societies often emerge from simple local rules. However, little is known about how these behaviors are dynamically regulated in response to environmental changes. Here, we use a compartmental modeling approach to identify factors that allow harvester ant colonies to regulate collective foraging activity in response to their environment. We propose a set of differential equations describing the dynamics of: (1) available foragers inside the nest, (2) active foragers outside the nest, and (3) successful returning foragers, to understand how colony-specific parameters, such as baseline number of foragers, interactions among foragers, food discovery rates, successful forager return rates, and foraging duration might influence collective foraging dynamics, while maintaining functional robustness to perturbations. Our analysis indicates that the model can undergo a forward (transcritical) bifurcation or a backward bifurcation depending on colony-specific parameters. In the former case, foraging activity persists when the average number of recruits per successful returning forager is larger than one. In the latter case, the backward bifurcation creates a region of bistability in which the size and fate of foraging activity depends on the distribution of the foraging workforce among the model's compartments. We validate the model with experimental data from harvester ants (Pogonomyrmex barbatus) and perform sensitivity analysis. Our model provides insights on how simple, local interactions can achieve an emergent and robust regulatory system of collective foraging activity in ant colonies.

Investigating the interactions between physical and biological heterogeneities in bioreactors using compartment, population balance and metabolic models

A generic model for the description of biological population dynamics in industrial bioreactors is detailed. Hydrodynamics, mass transfer between the cell and the surrounding fluid, population heterogeneity, metabolism and biological adaptation have to be considered with equal interest and, if possible, simultaneously. This model couples a hydrodynamic model, a population balance model for the growth rate adaptation and a metabolic model predicting the reaction rates depending on the state of the individuals. This approach dissociates the growth rate from local concentrations leading to a good understanding of the effects of a changing environment on a microbial population. Our model is applied to Escherichia coli for which experimental data exist in the literature for batch and fed-batch cultures. The considered strain is known for producing acetate when exposed to heterogeneities. When simulating a large bioreactor using a compartment model approach for hydrodynamics, our coupled model could predict that, under certain conditions, acetate is simultaneously produced and consumed in different areas of the reactor.

Modeling outdoors algal cultivation with compartmental approach

Abstract A comprehensive modeling method for the simulation of outdoors algal cultivation in bubble column photobioreactors is presented. The compartmental modeling approach presented earlier by Nauha and Alopaeus (2013) [1] is used and extended to consider changes in the directionality of light during the day. The nightly loss of biomass due to darkness is also considered. The model is capable of predicting the system hydrodynamics, mass transfer and growth of algae. Model results are verified against measurements and show good agreement. The predictive capability of the model is validated. The model is used to make suggestions for optimization of outdoors algal cultivation.

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

BackgroundClozapine 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.MethodsUnbound 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.ResultsA 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.ConclusionsA 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.Electronic supplementary materialThe online version of this article (doi:10.1186/1479-5876-12-203) contains supplementary material, which is available to authorized users.

Study of intracellular reaction and diffusion mechanism of carcinogenic PAHs: Using non-standard compartment modeling approach

Study of intracellular reaction and diffusion mechanism of carcinogenic PAHs : Using non-standard compartment modeling approach

Discretization for a spray deposition model: Criteria for temporal and spatial differencing

A spray deposition model was developed to simulate spray dispersion in open space and deposition within a citrus tree canopy. It was validated by field tests reported in earlier publications. The model is based on a compartment modeling approach where the spray cloud is spatially partitioned into several compartments, with equal thickness but increasing cross section in the direction of application. The stability of the simulation curves depends concurrently on the compartment thickness (Δx) and time step (Δt) used. Simultaneously, the needed computer memory and computational time greatly depend on Δt. In this application note, the influence of these two parameters on simulated airborne spray mass has been explored and a criterion for selecting a pair of them to optimize simulation output has been established. The criterion, Δt=Δx/ua, establishes a strong relationship of these two parameters with sprayer air velocity, ua, stressing the importance of ua in the model. The results provided critical understanding about the sensitivity of the model to the studied parameters and tend to be crucial for successful implementation of the model.

Simulation of Bubble Columns with a Compartment Model Approach

AbstractBlasensäulenreaktoren sind zwar mechanisch einfache Apparate, die in ihnen vorherrschenden Gas‐Flüssig‐Interaktionen sind aber bedeutend komplexer. Die Auslegung anhand des axialen Dispersionsmodells hat entscheidende Nachteile in der Beschreibung der komplexen Wechselwirkungen zwischen Gas‐ und Flüssigphase. Obwohl die numerische Strömungsmechanik in den letzten Jahren, auch aufgrund steigender Rechnerkapazitäten und ‐leistungen, sehr vielversprechende Fortschritte gemacht hat, ist die Berechnung des Betriebsverhaltens industrieller Blasensäulenreaktoren nicht verifizierbar. Als Alternative bieten sich eine Unterteilung des Reaktors in Teilbilanzräume an. Diese als Kompartment‐Modellierung bekannte Beschreibungsmethode wird im Rahmen des Beitrags erläutert und diskutiert.

Kinetics of the utilization of dietary arginine for nitric oxide and urea synthesis: insight into the arginine–nitric oxide metabolic system in humans

The systemic availability of oral/dietary arginine and its utilization for nitric oxide (NO) synthesis remains unknown and may be related to a competitive hydrolysis of arginine into urea in the splanchnic area and systemic circulation. We investigated the kinetics and dose-dependency of dietary arginine utilization for NO compared with urea synthesis and studied the characteristics of the arginine-NO metabolic system in healthy humans. We traced the metabolic fate and analyzed the utilization dynamics of dietary arginine after its ingestion at 2 nutritional amounts in healthy humans (n = 9) in a crossover design by using [(15)N-(15)N-(guanido)]-arginine, isotope ratio mass spectrometry techniques, and data analysis with a compartmental modeling approach. Whatever the amount of dietary arginine, 60 ± 3% (±SEM) was converted to urea, with kinetics indicative of a first-pass splanchnic phenomenon. Despite this dramatic extraction, intact dietary arginine made a major contribution to the postprandial increase in plasma arginine. However, the model identified that the plasma compartment was a very minor (~2%) precursor for the conversion of dietary arginine into NO, which, in any case, was small (<0.1% of the dose). The whole-body and plasma kinetics of arginine metabolism were consistent with the suggested competitive metabolism by the arginase and NO synthase pathways. The conversion of oral/dietary arginine into NO is not limited by the systemic availability of arginine but by a tight metabolic compartmentation at the systemic level. We propose an organization of the arginine metabolic system that explains the daily maintenance of NO homeostasis in healthy humans.

Importance of Peptide Transporter 2 on the Cerebrospinal Fluid Efflux Kinetics of Glycylsarcosine Characterized by Nonlinear Mixed Effects Modeling

To develop a population pharmacokinetic model to quantitate the distribution kinetics of glycylsarcosine (GlySar), a substrate of peptide transporter 2 (PEPT2), in blood, CSF and kidney in wild-type and PEPT2 knockout mice. A stepwise compartment modeling approach was performed to describe the concentration profiles of GlySar in blood, CSF, and kidney simultaneously using nonlinear mixed effects modeling (NONMEM). The final model was selected based on the likelihood ratio test and graphical goodness-of-fit. The profiles of GlySar in blood, CSF, and kidney were best described by a four-compartment model. The estimated systemic elimination clearance, volume of distribution in the central and peripheral compartments were 0.236 vs 0.449ml/min, 3.79 vs 4.75ml, and 5.75 vs 9.18ml for wild-type versus knockout mice. Total CSF efflux clearance was 4.3 fold higher for wild-type compared to knockout mice. NONMEM parameter estimates indicated that 77% of CSF efflux clearance was mediated by PEPT2 and the remaining 23% was mediated by the diffusional and bulk clearances. Due to the availability of PEPT2 knockout mice, we were able to quantitatively determine the significance of PEPT2 in the efflux kinetics of GlySar at the blood-cerebrospinal fluid barrier.

Predictive Features of Persistent Activity Emergence in Regular Spiking and Intrinsic Bursting Model Neurons

Proper functioning of working memory involves the expression of stimulus-selective persistent activity in pyramidal neurons of the prefrontal cortex (PFC), which refers to neural activity that persists for seconds beyond the end of the stimulus. The mechanisms which PFC pyramidal neurons use to discriminate between preferred vs. neutral inputs at the cellular level are largely unknown. Moreover, the presence of pyramidal cell subtypes with different firing patterns, such as regular spiking and intrinsic bursting, raises the question as to what their distinct role might be in persistent firing in the PFC. Here, we use a compartmental modeling approach to search for discriminatory features in the properties of incoming stimuli to a PFC pyramidal neuron and/or its response that signal which of these stimuli will result in persistent activity emergence. Furthermore, we use our modeling approach to study cell-type specific differences in persistent activity properties, via implementing a regular spiking (RS) and an intrinsic bursting (IB) model neuron. We identify synaptic location within the basal dendrites as a feature of stimulus selectivity. Specifically, persistent activity-inducing stimuli consist of activated synapses that are located more distally from the soma compared to non-inducing stimuli, in both model cells. In addition, the action potential (AP) latency and the first few inter-spike-intervals of the neuronal response can be used to reliably detect inducing vs. non-inducing inputs, suggesting a potential mechanism by which downstream neurons can rapidly decode the upcoming emergence of persistent activity. While the two model neurons did not differ in the coding features of persistent activity emergence, the properties of persistent activity, such as the firing pattern and the duration of temporally-restricted persistent activity were distinct. Collectively, our results pinpoint to specific features of the neuronal response to a given stimulus that code for its ability to induce persistent activity and predict differential roles of RS and IB neurons in persistent activity expression.

Human biokinetic data and a new compartmental model of zirconium — A tracer study with enriched stable isotopes

Biokinetic models describing the uptake, distribution and excretion of trace elements are an essential tool in nutrition, toxicology, or internal dosimetry of radionuclides. Zirconium, especially its radioisotope 95Zr, is relevant to radiation protection due to its production in uranium fission and neutron activation of nuclear fuel cladding material. We present a comprehensive set of human data from a tracer study with stable isotopes of zirconium. The data are used to refine a biokinetic model of zirconium. Six female and seven male healthy adult volunteers participated in the study. It includes 16 complete double tracer investigations with oral ingestion and intravenous injection, and seven supplemental investigations. Tracer concentrations were measured in blood plasma and urine collected up to 100 d after tracer administration. The four data sets (two chemical tracer forms in plasma and urine) each encompass 105–240 measured concentration values above detection limits. Total fractional absorption of ingested zirconium was found to be 0.001 for zirconium in citrate-buffered drinking solution and 0.007 for zirconium oxalate solution. Biokinetic models were developed based on the linear first-order kinetic compartmental model approach used by the International Commission on Radiological Protection (ICRP). The main differences of the optimized systemic model of zirconium to the current ICRP model are (1) recycling into the transfer compartment made necessary by the observed tracer clearance from plasma, (2) different parameters related to fractional absorption for each form of the ingested tracer, and (3) a physiologically based excretion pathway to urine. The study considerably expands the knowledge on the biokinetics of zirconium, which was until now dominated by data from animal studies. The proposed systemic model improves the existing ICRP model, yet is based on the same principles and fits well into the ICRP radiation protection approach.

Tissue-Specific Compartmental Analysis for Dynamic Contrast-Enhanced MR Imaging of Complex Tumors

Dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) provides a noninvasive method for evaluating tumor vasculature patterns based on contrast accumulation and washout. However, due to limited imaging resolution and tumor tissue heterogeneity, tracer concentrations at many pixels often represent a mixture of more than one distinct compartment. This pixel-wise partial volume effect (PVE) would have profound impact on the accuracy of pharmacokinetics studies using existing compartmental modeling (CM) methods. We, therefore, propose a convex analysis of mixtures (CAM) algorithm to explicitly mitigate PVE by expressing the kinetics in each pixel as a nonnegative combination of underlying compartments and subsequently identifying pure volume pixels at the corners of the clustered pixel time series scatter plot simplex. The algorithm is supported theoretically by a well-grounded mathematical framework and practically by plug-in noise filtering and normalization preprocessing. We demonstrate the principle and feasibility of the CAM-CM approach on realistic synthetic data involving two functional tissue compartments, and compare the accuracy of parameter estimates obtained with and without PVE elimination using CAM or other relevant techniques. Experimental results show that CAM-CM achieves a significant improvement in the accuracy of kinetic parameter estimation. We apply the algorithm to real DCE-MRI breast cancer data and observe improved pharmacokinetic parameter estimation, separating tumor tissue into regions with differential tracer kinetics on a pixel-by-pixel basis and revealing biologically plausible tumor tissue heterogeneity patterns. This method combines the advantages of multivariate clustering, convex geometry analysis, and compartmental modeling approaches. The open-source MATLAB software of CAM-CM is publicly available from the Web.

User Influence on Indoor Aerosol Model Calibration

Calibration, or in other words ”validation”, of complex indoor aerosol models that simulate the dynamic behavior of particle number size distributions are often assumed to solely depend on the characteristics of the model and its setup. The user influence is rarely mentioned in that regard. This paper shows, with a simple exercise, the user influence on the calibration of an indoor aerosol model. It is also shown that a reasonable model simulation was achieved with a different understanding of the system modeled and several input parameter values. We utilized a single compartment and size-resolved indoor aerosol model approach to be calibrated against a model room. This kind of simple indoor aerosol models is very common in the literature and widely used in the analysis of indoor-to-outdoor relationship of aerosol particles. The input parameters for such indoor aerosol models are: outdoor particle number size distributions, indoor domain geometries, ventilation rate, penetration factor, and friction velocity (or deposition rate onto indoor surfaces). For simplicity, we considered the penetration factor and friction velocity are the only unknown input parameters to be chosen freely by the user so that the model is calibrated. We made it clear by this study that a user can influence the input parameter values significantly. Even though this suggests different sets of input parameter values can be valid for a model calibration, the model simulation differences between different calibration results remained within 1%. This implies that it is more challenging to calibrate a complex indoor aerosol model that requires many input parameters.

Network environ theory, simulation, and EcoNet® 2.0

We introduce and codify the mathematics of Ecological Network Analysis (ENA) in general and Network Environ Analysis (NEA) in particular used by the web-based simulation software EcoNet® 2.0. Where ecosystem complexity continues to drive an increasingly vast environmental modeling effort, ENA and NEA represent maturation, in part, of the compartment modeling approach. Compartment modeling mathematically represents compartment storages with both internal-connecting and external-environmental flows as ordinary differential equations. ENA and NEA expand these mathematics into complex systems analysis and corresponding network theory. EcoNet was developed to facilitate the mathematical modeling, to enhance the overall presentation, and to improve the subsequent long-term progress of ENA and NEA systems analysis. Thus, as a continuing enhancement to the overall understanding, but more importantly, to the future growth of environmental modeling associated with ENA and NEA, we derive and summarize the canonical mathematics of ENA, NEA, and EcoNet, which facilitates their future use.

Clinical Pharmacokinetics of Intravenous and Oral MLN9708, An Investigational Proteasome Inhibitor: An Analysis of Data From Four Phase 1 Monotherapy Studies

AbstractAbstract 1813 Background:Investigational agent MLN9708, a modified dipeptidyl boronic acid, is a potent, reversible and specific inhibitor of the 20S proteasome being evaluated in phase 1 trials of patients with hematologic malignancies and solid tumors. Preliminary plasma pharmacokinetic (PK) data for MLN9708 administered intravenously (IV) and orally (PO) are reported. Both routes of administration are being studied using a twice-weekly schedule (Days 1, 4, 8, and 11 of a 21-day treatment cycle) and a weekly schedule (Days 1, 8, and 15 of a 28-day treatment cycle). MLN9708 completely hydrolyzes to the pharmacologically active boronic acid MLN2238 in aqueous solutions. Methods:Preliminary PK data from four ongoing phase 1 dose-escalation studies with MLN9708 have been analyzed: two studies investigating IV administration (C16001, n=27; C16002, n=7) and two studies of the oral formulation (C16003, n=9; C16004, n=5). In all studies blood samples were collected following the first and final dose of MLN9708 administered in Cycle 1, and trough samples were collected throughout Cycle 1 and at the start of Cycle 2. MLN9708 PK samples were analyzed for MLN2238 plasma and urine concentrations using LCMS/MS with LLOQ of 0.5 ng/mL for plasma samples. Data were analyzed using noncompartmental and compartmental modeling approaches. Plasma exposure parameters (Cmax, Tmax, AUC0-t, and t1/2) were estimated using WinNonlin software v5.2. Results:Following bolus IV administration of MLN9708, MLN2238 showed multi-exponential plasma disposition, characterized by a rapid initial disposition phase (t1/2 of <0.25 hr), an intermediate disposition phase, and a terminal disposition phase with t1/2 of >4 days. For twice-weekly dosing, the Day 1 and Day 11 extrapolated immediate post-IV bolus plasma concentration of MLN2238 (C0) was roughly dose proportional over the dose range (0.125 to 2.34 mg/m2). In contrast, both the Day 1 and Day 11 dosing interval plasma concentration-time AUCs showed dose proportional increases only over the higher dose range (1 to 2.34 mg/m2). There was approximately 3–4 fold accumulation of MLN2238 by Day 11 on the twice-weekly schedule. For weekly IV dosing of MLN9708, only lower dose levels have been studied to date (0.125 to 1.4 mg/m2) but the PK behavior appears to be similar to that for twice-weekly dosing, with the exception that MLN2238 accumulates to a lesser degree (approximately 2-fold). Following oral administration of MLN9708 capsules, there was rapid absorption of MLN2238 (Tmax approximately 1 hr). At the doses studied to date (0.24 to 1.2 mg/m2) for twice-weekly and weekly dosing of MLN9708, systemic exposures achieved with oral dosing were similar to those achieved with IV dosing on the same schedule, indicating that the oral bioavailability of MLN2238 is substantial. Conclusions:MLN9708 (measured as MLN2238) shows approximately dose linear PK over the higher range of doses tested (1 to 2.34 mg/m2). Current data suggest that oral MLN9708 is rapidly absorbed and is substantially bioavailable. Acknowledgment:We thank all study investigators, study managers, and study enrollees participating in studies C16001 (advanced nonhematologic malignancies), C16002 (lymphoma), C16003 (multiple myeloma), and C16004 (multiple myeloma) for providing PK data for analysis. Disclosures:Gupta:Millennium Pharmaceuticals, Inc.: Employment. Off Label Use: Investigational agent in clinical development for the treatment of solid tumors and hematologic malignancies. Liu:Millennium Pharmaceuticals, Inc.: Employment. Berg:Millennium Pharmaceuticals, Inc.: Employment; Takeda, Inc.: Equity Ownership; Sanofi-Aventis: Equity Ownership; Pfizer: Equity Ownership. Kalebic:Millennium Pharmaceuticals, Inc.: Employment. Gomez-Navarro:Millennium Pharmaceuticals, Inc.: Employment, Equity Ownership.

Pharmacokinetic analysis of pralidoxime after its intramuscular injection alone or in combination with atropine‐avizafone in healthy volunteers

Treatment of organophosphate poisoning with pralidoxime needs to be improved. Here we have studied the pharmacokinetics of pralidoxime after its intramuscular injection alone or in combination with avizafone and atropine using an auto-injector device. The study was conducted in an open, randomized, single-dose, two-way, cross-over design. At each period, each subject received either intramuscular injections of pralidoxime (700 mg), or two injections of the combination: pralidoxime (350 mg), atropine (2 mg), avizafone (20 mg). Pralidoxime concentrations were quantified using a validated LC/MS-MS method. Two approaches were used to analyse these data: (i) a non-compartmental approach; and (ii) a compartmental modelling approach. The injection of pralidoxime combination with atropine and avizafone provided a higher pralidoxime maximal concentration than that obtained after the injection of pralidoxime alone (out of bioequivalence range), while pralidoxime AUC values were equivalent. Pralidoxime concentrations reached their maximal value earlier after the injection of the combination. According to Akaike and to goodness of fit criteria, the best model describing the pharmacokinetics of pralidoxime was a two-compartment with a zero-order absorption model. When avizafone and atropine were injected with pralidoxime, the best model describing pralidoxime pharmacokinetics becomes a two-compartment with a first-order absorption model. The two approaches, non-compartmental and compartmental, showed that the administration of avizafone and atropine with pralidoxime results in a faster absorption into the general circulation and higher maximal concentrations, compared with the administration of pralidoxime alone.

Quantitative PET imaging of radioligands with slow kinetics in human brain

Dear Sir, We read with interest the commentary by Hirvonen et al. [1] on the quantification of radioligands with slow kinetics. Their critique of our work on the quantification of the type 1 cannabinoid receptor (CB1R) ligand [F] MK-9470 in the human brain [2] was of particular interest and triggered our response to support the methods that were used in the analysis of the behavior of this novel radioligand. Here we specifically address the vulnerabilities and pitfalls highlighted by Hirvonen et al. and argue that our assumptions can be reasonably justified even in the absence of a “gold standard” for radioligands with slow tissue kinetics. The general approach for analyzing neuroreceptor PET studies is based on compartmental modeling approaches formulated by Mintun et al. [3]. Even though the mathematical formulation of this model relies on several assumptions (e.g., rate constants are not changing during the PET study and the tracer concentration in the compartments is homogeneous), brain PET imaging analyzed with this approach has been a powerful tool that has enabled the study of neuroreceptor systems in normal and pathological conditions as well as supporting drug development. The compartmental model formulation is such that the parameters (K1; k2; k3 1⁄4 fNDkon Bavail CS ð Þ and k4=koff, where CS is the tracer concentration bound to the receptors and fND is the tracer free fraction in tissue [4]) could be related to the biochemical and physiological characteristics of the tracer and the receptor system. The estimation of all five parameters (rate constants and Bavail) is however only possible when using multiple injection protocols [5–8]. Another approach is to perform a series of studies at different specific activities [9–11] and use an in vivo Scatchard analysis to estimate Bavail and Kd. It should be noted that very often, when performing single bolus or bolus plus constant infusion (B/I) tracer administration experiments, the individual model parameters cannot be identified (even when the number of parameters is reduced by using high specific activity tracer, so that kon Bavail CS ð Þ ! HighSA konBavail). The reason that it is not possible to find a unique solution to the individual rate constants is because of the large correlation between parameters and the large coefficients of variation of the estimates. In general, the macro parameters (volume of distribution, binding potential, irreversible uptake rate constant) obtained from the combination of individual rate constants are more stable. As a consequence caution is required when interpreting any estimates of individual rate constants particularly when derived from single tracer injection experiments. Hirvonen et al. [1] asserted that our assumption that k4 is uniform across brain regions is invalid and that k4 differs across brain regions in correlation with receptor density. In support of their argument they discussed [I]iomazenil, a SPECT ligand for benzodiazepine receptors that are widely distributed at high density throughout the brain. In nonhuman primates for [I]iomazenil, the in vivo kon and koff (estimated using a combination of parameters from in vivo Scatchard analysis [11] and from single bolus tracer studies [12]) were much slower than the in vitro measurements, whereas the ratio of the in vivo rates kon/koff was similar to the in vitro measured Kd values. S. M. Sanabria-Bohorquez (*) Imaging, Merck Research Laboratories, Sumneytown Pike WP44D-2, West Point, PA 19486, USA e-mail: sandra_sanabria@merck.com

A software supported compartmental modeling approach for Paenibacillus polymyxa

This paper shows the derivation, selection and validation of a six-compartment model for P. polymyxa fed-batch fermentations on minimal media. P. polymyxa is known to produce a highly potent antibiotic, namely macrolactin. While biological insight is exploited to set up a basic model structure, a modeling tool is used to automatically select between possible reaction rates to describe individual steps. Experiments are used to identify the model parameters, and the most promising model candidate is validated with another experiment.

Pharmacokinetic evaluation and modeling of formulated levodopa intranasal delivery systems

Levodopa ( l-dopa), the metabolic precursor of dopamine, has primarily been used for the treatment of Parkinson's disease (PD) in combination with carbidopa (C-dopa). This study aims to investigate the feasibility of l-dopa nasal delivery systems prepared using maleic acid solution containing 2-hydroxypropyl-β-cyclodextrin, and to develop pharmacokinetic models. Following oral or intravenous administration of l-dopa plus C-dopa and intranasal dosing of l-dopa in the presence and absence of C-dopa to the rat, the concentrations of l-dopa in plasma and brain were determined using HPLC. The pharmacokinetic profiles were analyzed using non-compartmental and compartmental modeling approaches. Simultaneous nonlinear regression was performed to improve the identifiability of model parameters. l-Dopa was rapidly absorbed into blood and brain. The absolute bioavailabilities of oral and nasal preparations containing C-dopa were 17.7 and 45.4%, respectively. C-dopa caused a 1.2-fold decrease in the elimination rate of l-dopa, indicating decreased metabolism. Although the half-life after nasal administration was relatively short (less than 30 min) in both blood and brain regardless of C-dopa addition, the systemic exposure was promising due to rapid absorption. In conclusion, the l-dopa nasal delivery system could be used as a good rescue therapy for PD patients who experience symptom fluctuation with oral l-dopa administration.

Compartmental Modeling of an Industrial Column

The industrial production of refined sodium bicarbonate is realized in large-scale bubble columns, called the BIR columns. Several complex phenomena exist in these columns, such as three-phase flow, gas-liquid mass transfer of CO2, and crystallization. This work deals with the development of an operational BIR column model using the compartmental modeling approach. It is fed by previous works and current studies. A parametric sensitivity analysis is realized to identify the more important modeling parameters and to point the future research that have to be performed. Some simulations results are presented for typical operating conditions of an industrial column.