Systems Engineering Approach to Modeling and Analysis of Chronic Obstructive Pulmonary Disease.

Chronic obstructive pulmonary disease (COPD) is a progressive lung disease characterized by airflow limitation. This study develops a systems engineering framework for representing important mechanistic details of COPD in a model of the cardiorespiratory system. In this model, we present the cardiorespiratory system as an integrated biological control system responsible for regulating breathing. Four engineering control system components are considered: sensor, controller, actuator, and the process itself. Knowledge of human anatomy and physiology is used to develop appropriate mechanistic mathematical models for each component. Following a systematic analysis of the computational model, we identify three physiological parameters associated with reproducing clinical manifestations of COPD: changes in the forced expiratory volume, lung volumes, and pulmonary hypertension. We quantify the changes in these parameters (airway resistance, lung elastance, and pulmonary resistance) as the ones that result in a systemic response that is diagnostic of COPD. A multivariate analysis of the simulation results reveals that the changes in airway resistance have a broad impact on the human cardiorespiratory system and that the pulmonary circuit is stressed beyond normal under hypoxic environments in most COPD patients.

Closed-loop modeling of central and intrinsic cardiac nervous system circuits underlying cardiovascular control.

The baroreflex is a multi-input, multi-output control physiological system that regulates blood pressure by modulating nerve activity between the brainstem and the heart. Existing computational models of the baroreflex do not explictly incorporate the intrinsic cardiac nervous system (ICN), which mediates central control of the heart function. We developed a computational model of closed-loop cardiovascular control by integrating a network representation of the ICN within central control reflex circuits. We examined central and local contributions to the control of heart rate, ventricular functions, and respiratory sinus arrhythmia (RSA). Our simulations match the experimentally observed relationship between RSA and lung tidal volume. Our simulations predicted the relative contributions of the sensory and the motor neuron pathways to the experimentally observed changes in the heart rate. Our closed-loop cardiovascular control model is primed for evaluating bioelectronic interventions to treat heart failure and renormalize cardiovascular physiology.

Elucidating the Mechanisms of Dynamic and Robust Control of the Liver Homeostatic Renewal Process: Cell Network Modeling and Analysis.

Recent experimental investigations of liver homeostatic renewal have identified high replication capacity hepatocyte populations as the primary maintainers of liver mass. However, the molecular and cellular processes controlling liver homeostatic renewal remain unknown. To address this problem, we developed and analyzed a mathematical model describing cellular network interactions underlying liver homeostatic renewal. Model simulation results demonstrate that without feedback control, basic homeostatic renewal is not robust to disruptions, leading to tissue loss under persistent/repetitive insults. Consequently, we extended our basic model to incorporate putative regulatory interactions and investigated how such interactions may confer robustness on the homeostatic renewal process. We utilized a Design of Experiments approach to identify the combination of feedback interactions that yields a cell network model of homeostatic renewal capable of maintaining liver mass robustly during persistent/repetitive injury. Simulations of this robust model indicate that repeated injury destabilizes liver homeostasis within several months, which differs from epidemiological observations of a much slower decay of liver function occurring over several years. To address this discrepancy, we extended the model to include feedback control by liver nonparenchymal cells. Simulations and analysis of the final multicellular feedback control network suggest that achieving robust liver homeostatic renewal requires intrinsic stability in a hepatocellular network combined with feedback control by nonparenchymal cells.

Rational Design of Hydrogel Networks with Dynamic Mechanical Properties to Mimic Matrix Remodeling.

Engineered hydrogels are increasingly used as extracellular matrix (ECM) surrogates for probing cell function in response to ECM remodeling events related to injury or disease (e.g., degradation followed by deposition/crosslinking). Inspired by these events, this work establishes an approach for pseudo-reversible mechanical property modulation in synthetic hydrogels by integrating orthogonal, enzymatically triggered crosslink degradation, and light-triggered photopolymerization stiffening. Hydrogels are formed by a photo-initiated thiol-ene reaction between multiarm polyethylene glycol and a dually enzymatically degradable peptide linker, which incorporates a thrombin-degradable sequence for triggered softening and a matrix metalloproteinase (MMP)-degradable sequence for cell-driven remodeling. Hydrogels are stiffened by photopolymerization using a flexible, MMP-degradable polymer-peptide conjugate and multiarm macromers, increasing the synthetic matrix crosslink density while retaining degradability. Integration of these tools enables sequential softening and stiffening inspired by matrix remodeling events within loose connective tissues (Young's modulus (E) ≈5 to 1.5 to 6 kPa with >3x ΔE). The cytocompatibility and utility of this approach is examined with breast cancer cells, where cell proliferation shows a dependence on the timing of triggered softening. This work provides innovative tools for 3D dynamic property modulation that are synthetically accessible and cell compatible.

A Spatial Model of Hepatic Calcium Signaling and Glucose Metabolism Under Autonomic Control Reveals Functional Consequences of Varying Liver Innervation Patterns Across Species.

Rapid breakdown of hepatic glycogen stores into glucose plays an important role during intense physical exercise to maintain systemic euglycemia. Hepatic glycogenolysis is governed by several different liver-intrinsic and systemic factors such as hepatic zonation, circulating catecholamines, hepatocellular calcium signaling, hepatic neuroanatomy, and the central nervous system (CNS). Of the factors regulating hepatic glycogenolysis, the extent of lobular innervation varies significantly between humans and rodents. While rodents display very few autonomic nerve terminals in the liver, nearly every hepatic layer in the human liver receives neural input. In the present study, we developed a multi-scale, multi-organ model of hepatic metabolism incorporating liver zonation, lobular scale calcium signaling, hepatic innervation, and direct and peripheral organ-mediated communication between the liver and the CNS. We evaluated the effect of each of these governing factors on the total hepatic glucose output and zonal glycogenolytic patterns within liver lobules during simulated physical exercise. Our simulations revealed that direct neuronal stimulation of the liver and an increase in circulating catecholamines increases hepatic glucose output mediated by mobilization of intracellular calcium stores and lobular scale calcium waves. Comparing simulated glycogenolysis between human-like and rodent-like hepatic innervation patterns (extensive vs. minimal) suggested that propagation of calcium transients across liver lobules acts as a compensatory mechanism to improve hepatic glucose output in sparsely innervated livers. Interestingly, our simulations suggested that catecholamine-driven glycogenolysis is reduced under portal hypertension. However, increased innervation coupled with strong intercellular communication can improve the total hepatic glucose output under portal hypertension. In summary, our modeling and simulation study reveals a complex interplay of intercellular and multi-organ interactions that can lead to differing calcium dynamics and spatial distributions of glycogenolysis at the lobular scale in the liver.

Low-dose aspirin for preventing intrauterine growth restriction and pre-eclampsia in sickle cell pregnancy (PIPSICKLE): a randomised controlled trial (study protocol).

INTRODUCTION: Pregnancy in sickle cell disease is fraught with many complications including pre-eclampsia (PE) and intrauterine growth restriction (IUGR). Previously, we found an abnormality in prostacyclin-thromboxane ratio in sickle cell pregnant women, a situation that is also found in non-sickle pregnancies with PE and unexplained IUGR. Low-dose aspirin (LDA) has been shown to reduce the incidence of PE and IUGR in high-risk women by reducing the vasoconstrictor thromboxane while sparing prostacyclin, in effect 'correcting' the ratio. It has been found to be safe for use in pregnancy but has not been tested in sickle cell pregnancy. We hypothesise that LDA will reduce the incidence of IUGR and PE in pregnant haemoglobin SS (HbSS) and haemoglobin SC (HbSC) women. METHODS AND ANALYSIS: This is a multisite, double blind, randomised controlled trial, comparing a daily dose of 100 mg aspirin to placebo, from 12 to 16 weeks' gestation until 36 weeks, in Lagos state, Nigeria. Four hundred and seventy-six eligible pregnant HbSS and HbSC women will be recruited consecutively, randomly assigned to either group and followed from recruitment until delivery. The primary outcome will be the incidence of birth weight below 10th centile for gestational age on INTERGROWTH 21 birth weight charts, or incidence of miscarriage or perinatal death. Secondary outcomes will include PE, maternal death, preterm delivery, perinatal death, number of crises, need for blood transfusion and complications such as infections and placental abruption. Analysis will be by intention to treat and the main treatment effects will be quantified by relative risk with 95% CI, at a 5% significance level. ETHICAL APPROVAL: Ethical approval has been granted by the Health Research and Ethics committees of the recruiting hospitals and the National Health Research and Ethics Committee. Study findings will be presented at conferences and published appropriately. TRAIL REGISTRATION NUMBER: PACTR202001787519553; Pre-results.

Modeling the Effect of Amino Acids and Copper on Monoclonal Antibody Productivity and Glycosylation: A Modular Approach.

In manufacturing monoclonal antibodies (mAbs), it is crucial to be able to predict how process conditions and supplements affect productivity and quality attributes, especially glycosylation. Supplemental inputs, such as amino acids and trace metals in the media, are reported to affect cell metabolism and glycosylation; quantifying their effects is essential for effective process development. We aim to present and validate, through a commercially relevant cell culture process, a technique for modeling such effects efficiently. While existing models can predict mAb production or glycosylation dynamics under specific process configurations, adapting them to new processes remains challenging, because it involves modifying the model structure and often requires some mechanistic understanding. Here, a modular modeling technique for adapting an existing model for a fed-batch Chinese hamster ovary (CHO) cell culture process without structural modifications or mechanistic insight is presented. Instead, data is used, obtained from designed experimental perturbations in media supplementation, to train and validate a supplemental input effect model, which is used to "patch" the existing model. The combined model can be used for model-based process development to improve productivity and to meet product quality targets more efficiently. The methodology and analysis are generally applicable to other CHO cell lines and cell types.

An Exceedingly Rare Presentation of Severe Folate Deficiency-Induced Non-Immune Hemolytic Anemia.

Macrocytic anemia is usually associated with vitamin B12 or folate deficiency. However, folate deficiency was rarely reported as a cause of hemolytic anemia. We present a case of a young man with a history of alcohol abuse who initially presented with an acute on chronic abdominal pain and was found to have jaundice and scleral icterus. His liver enzymes were unremarkable, and his abdominal imaging did not reveal any acute pathology. However, he was found to have a severe non-immune hemolytic anemia secondary to folate deficiency.

Diurnal Patterns of Gene Expression in the Dorsal Vagal Complex and the Central Nucleus of the Amygdala - Non-rhythm-generating Brain Regions.

Genes that establish the circadian clock have differential expression with respect to solar time in central and peripheral tissues. Here, we find circadian-time-induced differential expression in a large number of genes not associated with circadian rhythms in two brain regions lacking overt circadian function: the dorsal vagal complex (DVC) and the central nucleus of the amygdala (CeA). These regions primarily engage in autonomic, homeostatic, and emotional regulation. However, we find striking diurnal shifts in gene expression in these regions of male Sprague Dawley rats with no obvious patterns that could be attributed to function or region. These findings have implications for the design of gene expression studies as well as for the potential effects of xenobiotics on these regions that regulate autonomic and emotional states.

The growth of methylammonium lead iodide perovskites by close space vapor transport.

Vapor deposition processes have shown promise for high-quality perovskite solar cells with potential pathways for scale-up to large area manufacturing. Here, we present a sequential close space vapor transport process to deposit CH3NH3PbI3 (MAPI) perovskite thin films by depositing a layer of PbI2 then reacting it with CH3NH3I (MAI) vapor. We find that, at T = 100 °C and pressure = 9 torr, a ∼225 nm-thick PbI2 film requires ≥125 minutes in MAI vapor to form a fully-reacted MAPI film. Raising the temperature to 160 °C increases the rate of reaction, such that MAPI forms within 15 minutes, but with reduced surface coverage. The reaction kinetics can be approximated as roughly first-order with respect to PbI2, though there is evidence for a more complicated functional relation. Perovskite films reacted at 100 °C for 150 minutes were fabricated into solar cells with an SLG/ITO/CdS/MAPI/Spiro-OMeTAD/Au structure, and a device efficiency of 12.1% was achieved. These results validate the close space vapor transport process and serve as an advance toward scaled-up, vapor-phase perovskite manufacturing through continuous vapor transport deposition.

Reliable preparation of agarose phantoms for use in quantitative magnetic resonance elastography.

Agarose phantoms are one type of phantom commonly used in developing in vivo brain magnetic resonance elastography (MRE) sequences because they are inexpensive and easy to work with, store, and dispose of; however, protocols for creating agarose phantoms are non-standardized and often result in inconsistent phantoms with significant variability in mechanical properties. Many magnetic resonance imaging (MRI) and ultrasound studies use phantoms, but often these phantoms are not tailored for desired mechanical properties and as such are too stiff or not mechanically consistent enough to be used in MRE. In this work, we conducted a systematic study of agarose phantom creation parameters to identify those factors that are most conducive to producing mechanically consistent agarose phantoms for MRE research. We found that cooling rate and liquid temperature affected phantom homogeneity. Phantom stiffness is affected by agar concentration (quadratically), by final liquid temperature and salt content in phantoms, and by the interaction of these two metrics each with stir rate. We captured and quantified the implied relationships with a regression model that can be used to estimate stiffness of resulting phantoms. Additionally, we characterized repeatability, stability over time, impact on MR signal parameters, and differences in agar gel microstructure. This protocol and regression model should prove beneficial in future MRE development studies that use phantoms to determine stiffness measurement accuracy.

Causality Analysis and Cell Network Modeling of Spatial Calcium Signaling Patterns in Liver Lobules.

Dynamics as well as localization of Ca2+ transients plays a vital role in liver function under homeostatic conditions, repair, and disease. In response to circulating hormonal stimuli, hepatocytes exhibit intracellular Ca2+ responses that propagate through liver lobules in a wave-like fashion. Although intracellular processes that control cell autonomous Ca2+ spiking behavior have been studied extensively, the intra- and inter-cellular signaling factors that regulate lobular scale spatial patterns and wave-like propagation of Ca2+ remain to be determined. To address this need, we acquired images of cytosolic Ca2+ transients in 1300 hepatocytes situated across several mouse liver lobules over a period of 1600 s. We analyzed this time series data using correlation network analysis, causal network analysis, and computational modeling, to characterize the spatial distribution of heterogeneity in intracellular Ca2+ signaling components as well as intercellular interactions that control lobular scale Ca2+ waves. Our causal network analysis revealed that hepatocytes are causally linked to multiple other co-localized hepatocytes, but these influences are not necessarily aligned uni-directionally along the sinusoids. Our computational model-based analysis showed that spatial gradients of intracellular Ca2+ signaling components as well as intercellular molecular exchange are required for lobular scale propagation of Ca2+ waves. Additionally, our analysis suggested that causal influences of hepatocytes on Ca2+ responses of multiple neighbors lead to robustness of Ca2+ wave propagation through liver lobules.

Cellular network modeling and single cell gene expression analysis reveals novel hepatic stellate cell phenotypes controlling liver regeneration dynamics.

BACKGROUND: Recent results from single cell gene and protein regulation studies are starting to uncover the previously underappreciated fact that individual cells within a population exhibit high variability in the expression of mRNA and proteins (i.e., molecular variability). By combining cellular network modeling, and high-throughput gene expression measurements in single cells, we seek to reconcile the high molecular variability in single cells with the relatively low variability in tissue-scale gene and protein expression and the highly coordinated functional responses of tissues to physiological challenges. In this study, we focus on relating the dynamic changes in distributions of hepatic stellate cell (HSC) functional phenotypes to the tightly regulated physiological response of liver regeneration. RESULTS: We develop a mathematical model describing contributions of HSC functional phenotype populations to liver regeneration and test model predictions through isolation and transcriptional characterization of single HSCs. We identify and characterize four HSC transcriptional states contributing to liver regeneration, two of which are described for the first time in this work. We show that HSC state populations change in vivo in response to acute challenges (in this case, 70% partial hepatectomy) and chronic challenges (chronic ethanol consumption). Our results indicate that HSCs influence the dynamics of liver regeneration through steady-state tissue preconditioning prior to an acute insult and through dynamic control of cell state balances. Furthermore, our modeling approach provides a framework to understand how balances among cell states influence tissue dynamics. CONCLUSIONS: Taken together, our combined modeling and experimental studies reveal novel HSC transcriptional states and indicate that baseline differences in HSC phenotypes as well as a dynamic balance of transitions between these phenotypes control liver regeneration responses.

Controlling the Glycosylation Profile in mAbs Using Time-Dependent Media Supplementation.

In order to meet desired drug product quality targets, the glycosylation profile of biotherapeutics such as monoclonal antibodies (mAbs) must be maintained consistently during manufacturing. Achieving consistent glycan distribution profiles requires identifying factors that influence glycosylation, and manipulating them appropriately via well-designed control strategies. Now, the cell culture media supplement, MnCl2, is known to alter the glycosylation profile in mAbs generally, but its effect, particularly when introduced at different stages during cell growth, has yet to be investigated and quantified. In this study, we evaluate the effect of time-dependent addition of MnCl2 on the glycan profile quantitatively, using factorial design experiments. Our results show that MnCl2 addition during the lag and exponential phases affects the glycan profile significantly more than stationary phase supplementation does. Also, using a novel computational technique, we identify various combinations of glycan species that are affected by this dynamic media supplementation scheme, and quantify the effects mathematically. Our experiments demonstrate the importance of taking into consideration the time of addition of these trace supplements, not just their concentrations, and our computational analysis provides insight into what supplements to add, when, and how much, in order to induce desired changes.

Single-Cell Transcriptional Analysis Reveals Novel Neuronal Phenotypes and Interaction Networks Involved in the Central Circadian Clock.

Single-cell heterogeneity confounds efforts to understand how a population of cells organizes into cellular networks that underlie tissue-level function. This complexity is prominent in the mammalian suprachiasmatic nucleus (SCN). Here, individual neurons exhibit a remarkable amount of asynchronous behavior and transcriptional heterogeneity. However, SCN neurons are able to generate precisely coordinated synaptic and molecular outputs that synchronize the body to a common circadian cycle by organizing into cellular networks. To understand this emergent cellular network property, it is important to reconcile single-neuron heterogeneity with network organization. In light of recent studies suggesting that transcriptionally heterogeneous cells organize into distinct cellular phenotypes, we characterized the transcriptional, spatial, and functional organization of 352 SCN neurons from mice experiencing phase-shifts in their circadian cycle. Using the community structure detection method and multivariate analytical techniques, we identified previously undescribed neuronal phenotypes that are likely to participate in regulatory networks with known SCN cell types. Based on the newly discovered neuronal phenotypes, we developed a data-driven neuronal network structure in which multiple cell types interact through known synaptic and paracrine signaling mechanisms. These results provide a basis from which to interpret the functional variability of SCN neurons and describe methodologies toward understanding how a population of heterogeneous single cells organizes into cellular networks that underlie tissue-level function.

Identifying a robust design space for glycosylation during monoclonal antibody production.

Glycan distribution has been identified as a "critical quality attribute" for many biopharmaceutical products, including monoclonal antibodies. Consequently, determining quantitatively how process variables affect glycan distribution is important during process development to control antibody glycosylation. In this work, we assess the effect of six bioreactor process variables on the glycan distribution of an IgG1 produced in CHO cells. Our analysis established that glucose and glutamine media concentration, temperature, pH, agitation rate, and dissolved oxygen (DO) had small but significant effects on the relative percentage of various glycans. In addition, we assessed glycosylation enzyme transcript levels and intracellular sugar nucleotide concentrations within the CHO cells to provide a biological explanation for the observed effects on glycan distributions. From these results we identified a robust operating region, or design space, in which the IgG1 could be produced with a consistent glycan distribution. Since our results indicate that perturbations to bioreactor process variables will cause only small (even if significant) changes to the relative percentage of various glycans (<±1.5%)-changes that are too small to affect the bioactivity and efficacy of this IgG1 significantly-it follows that the glycan distribution obtained will be consistent even with relatively large variations in bioreactor process variables. However, for therapeutic proteins where bioactivity and efficacy are affected by small changes to the relative percentage of glycans, the same analysis would identify the manipulated variables capable of changing glycan distribution, and hence can be used to implement a glycosylation control strategy. © 2016 American Institute of Chemical Engineers Biotechnol. Prog., 32:1149-1162, 2016.

Computational Modeling of Spatiotemporal Ca(2+) Signal Propagation Along Hepatocyte Cords.

OBJECTIVE: The purpose of this study is to model the dynamics of lobular Ca(2+) wave propagation induced by an extracellular stimulus, and to analyze the effect of spatially systematic variations in cell-intrinsic signaling parameters on sinusoidal Ca(2+) response. METHODS: We developed a computational model of lobular scale Ca(2+) signaling that accounts for receptor- mediated initiation of cell-intrinsic Ca(2+) signal in hepatocytes and its propagation to neighboring hepatocytes through gap junction-mediated molecular exchange. RESULTS: Analysis of the simulations showed that a pericentral-to-periportal spatial gradient in hormone sensitivity and/or rates of IP3 synthesis underlies the Ca(2+) wave propagation. We simulated specific cases corresponding to localized disruptions in the graded pattern of these parameters along a hepatic sinusoid. Simulations incorporating locally altered parameters exhibited Ca(2+) waves that do not propagate throughout the hepatic plate. Increased gap junction coupling restored normal Ca(2+) wave propagation when hepatocytes with low Ca(2+) signaling ability were localized in the midlobular or the pericentral region. CONCLUSION: Multiple spatial patterns in intracellular signaling parameters can lead to Ca(2+) wave propagation that is consistent with the experimentally observed spatial patterns of Ca(2+) dynamics. Based on simulations and analysis, we predict that increased gap junction-mediated intercellular coupling can induce robust Ca(2+) signals in otherwise poorly responsive hepatocytes, at least partly restoring the sinusoidally oriented Ca (2+) waves. SIGNIFICANCE: Our bottom-up model of agonist-evoked spatial Ca(2+) patterns can be integrated with detailed descriptions of liver histology to study Ca(2+) regulation at the tissue level.

Systems analysis of non-parenchymal cell modulation of liver repair across multiple regeneration modes.

BACKGROUND: A hallmark of chronic liver disease is the impairment of the liver's innate regenerative ability. In this work we use a computational approach to unravel the principles underlying control of liver repair following an acute physiological challenge. METHODS: We used a mathematical model of inter- and intra-cellular interactions during liver regeneration to infer key molecular factors underlying the dysregulation of multiple regeneration modes, including delayed, suppressed, and enhanced regeneration. We used model analysis techniques to identify organizational principles governing the cellular regulation of liver regeneration. We fit our model to several published data sets of deficient regeneration in rats and healthy regeneration in humans, rats, and mice to predict differences in molecular regulation in disease states and across species. RESULTS: Analysis of the computational model pointed to an important balance involving inflammatory signals and growth factors, largely produced by Kupffer cells and hepatic stellate cells, respectively. Our model analysis results also indicated an organizational principle of molecular regulation whereby production rate of molecules acted to induce coarse-grained control of signaling levels while degradation rate acted to induce fine-tuning control. We used this computational framework to investigate hypotheses concerning molecular regulation of regeneration across species and in several chronic disease states in rats, including fructose-induced steatohepatitis, alcoholic steatohepatitis, toxin-induced cirrhosis, and toxin-induced diabetes. Our results indicate that altered non-parenchymal cell activation is sufficient to explain deficient regeneration caused by multiple disease states. We also investigated liver regeneration across mammalian species. Our results suggest that non-invasive measures of liver regeneration taken at 30 days following resection could differentiate between several hypotheses about how human liver regeneration differs from rat regeneration. CONCLUSIONS: Overall, our results provide a new computational platform integrating a wide range of experimental information, with broader utility in exploring the dynamic patterns of liver regeneration across species and over multiple chronic diseases.

A control engineering model of calcium regulation.

CONTEXT: A control engineering perspective provides a framework for representing important mechanistic details of the calcium (Ca) regulatory system efficiently. The resulting model facilitates the testing of hypotheses about mechanisms underlying the emergence of known Ca-related pathologies. OBJECTIVE: The objective of this work is to develop a comprehensive computational model that will enable quantitative understanding of plasma Ca regulation under normal and pathological conditions. DESIGN: Ca regulation is represented as an engineering control system where physiological subprocesses are mapped onto corresponding block components (sensor, controller, actuator, and process), and underlying mechanisms are represented by differential equations. The resulting model is validated with clinical observations of induced hypo- or hypercalcemia in healthy subjects, and its applicability is demonstrated by comparing model predictions of Ca-related pathologies to corresponding clinical data. RESULTS: Our model accurately predicts clinical responses to induced hypo- and hypercalcemia in healthy subjects within a framework that facilitates the representation of Ca-related pathologies in terms of control system component defects. The model also enables a deeper understanding of the emergence of pathologies and the testing of hypotheses about related features of Ca regulation-for example, why primary hyperparathyroidism and hypoparathyroidism arise from "controller defects." CONCLUSIONS: The control engineering framework provides an efficient means of organizing the subprocesses constituting Ca regulation, thereby facilitating a fundamental understanding of this complex process. The resulting validated model's predictions are consistent with clinically observed short- and long-term dynamic characteristics of the Ca regulatory system in both healthy and diseased patients. The model also enables simulation of currently infeasible clinical tests and generates predictions of physiological variables that are currently not measurable.

Identification of manipulated variables for a glycosylation control strategy.

N-linked glycan distribution affects important end-use characteristics such as the bioactivity and efficacy of many therapeutic proteins, (including monoclonal antibodies), in vivo. Yet, obtaining desired glycan distributions consistently during batch-to-batch production can be challenging for biopharmaceutical manufacturers. While an appropriately implemented on-line glycosylation control strategy during production can help to ensure a consistent glycan distribution, to date no such strategies have been reported. Our goal is to develop and validate a comprehensive strategy for effective on-line control of glycosylation, the successful achievement of which requires first identifying appropriate manipulated variables that can be used to direct the glycan distribution to a desired state. While various culture conditions such as bioreactor process variables, media type, and media supplements have been shown to affect the glycan distribution, in this study we focus on the latter. Specifically, we implemented a statistically designed series of experiments to determine the significant main effects (as well as interaction effects) of media supplementation with manganese, galactose, ammonia and found that each had significant effects on certain glycans. We also include data indicating the glycosylation enzyme gene transcript levels as well as the intracellular nucleotide sugar concentrations in the presence of the media supplements to provide insight into the intracellular conditions that may be contributing to the changes in glycan distribution. The acquired experimental data sets were then used to identify which glycans can be controlled by the media supplements and to what degree. We determined that MnCl2 can be used as a manipulated variable to increase the relative abundance of M51 and decrease FA2 simultaneously, and galactose can be used as a manipulated variable to increase the relative abundance of FA2G1 and decrease FA2 and A2 simultaneously.