A systems pharmacology model for gene therapy in sickle cell disease.

We developed a mathematical model for autologous stem cell therapy to cure sickle cell disease (SCD). Experimental therapies using this approach seek to engraft stem cells containing a curative gene. These stem cells are expected to produce a lifelong supply of red blood cells (RBCs) containing an anti-sickling hemoglobin. This complex, multistep treatment is expensive, and there is limited patient data available from early clinical trials. Our objective was to quantify the impact of treatment parameters, such as initial stem cell dose, efficiency of lentiviral transduction, and degree of bone marrow preconditioning on engraftment efficiency, peripheral RBC numbers, and anti-sickling hemoglobin levels over time. We used ordinary differential equations to model RBC production from progenitor cells in the bone marrow, and hemoglobin assembly from its constituent globin monomers. The model recapitulates observed RBC and hemoglobin levels in healthy and SCD phenotypes. Treatment simulations predict dynamics of stem cell engraftment and RBC containing the therapeutic gene product. Post-treatment dynamics show an early phase of reconstitution due to short lived stem cells, followed by a sustained RBC production from stable engraftment of long-term stem cells. This biphasic behavior was previously reported in the literature. Sensitivity analysis of the model quantified relationships between treatment parameters and efficacy. The initial dose of transduced stem cells, and the intensity of myeloablative bone marrow preconditioning are predicted to most positively impact long-term outcomes. The quantitative systems pharmacology approach used here demonstrates the value of model-assisted therapeutic design for gene therapies in SCD.

Pharmacometric analysis linking immunoglobulin exposure to clinical efficacy outcomes in chronic inflammatory demyelinating polyneuropathy.

The two main objectives of this analysis were to (i) characterize the relationship between immunoglobulin (Ig) exposure and chronic inflammatory demyelinating polyneuropathy (CIDP) disease severity using data from 171 patients with CIDP who received either subcutaneous Ig (IgPro20; Hizentra® ) or placebo (PATH study), and to (ii) simulate and compare exposure coverage with various dosing approaches considering weekly dosing to be the reference dose. IgG pharmacokinetic (PK) parameters, including those from a previous population PK model, were used to predict individual IgG profile and exposure metrics. Treatment-related changes in Inflammatory Neuropathy Cause and Treatment (INCAT) scores were best described by a maximum effect (Emax ) model as a function of ΔIgG (total serum IgG at INCAT score assessment minus baseline IgG levels before intravenous Ig restabilization). Simulations indicate that flexible dosing from daily to biweekly (every other week) provide an exposure coverage equivalent to that of a weekly Ig dose.

Informing Development of Bispecific Antibodies Using Physiologically Based Pharmacokinetic-Pharmacodynamic Models: Current Capabilities and Future Opportunities.

Antibody therapeutics continue to represent a significant portion of the biotherapeutic pipeline, with growing promise for bispecific antibodies (BsAbs). BsAbs can target 2 different antigens at the same time, such as simultaneously binding tumor-cell receptors and recruiting cytotoxic immune cells. This simultaneous engagement of 2 targets can be potentially advantageous, as it may overcome disadvantages posed by a monotherapy approach, like the development of resistance to treatment. Combination therapy approaches that modulate 2 targets simultaneously offer similar advantages, but BsAbs are more efficient to develop. Unlike combination approaches, BsAbs can facilitate spatial proximity of targets that may be necessary to induce the desired effect. Successful development of BsAbs requires understanding antibody formatting and optimizing activity for both targets prior to clinical trials. To realize maximal efficacy, special attention is required to fully define pharmacokinetic (PK)/pharmacodynamic (PD) relationships enabling selection of dose and regimen. The application of physiologically based pharmacokinetics (PBPK) has been evolving to inform the development of novel treatment modalities such as bispecifics owing to the increase in our understanding of pharmacology, utility of multiscale models, and emerging clinical data. In this review, we discuss components of PBPK models to describe the PK characteristics of BsAbs and expand the discussion to integration of PBPK and PD models to inform development of BsAbs. A framework that can be adopted to build PBPK-PD models to inform the development of BsAbs is also proposed. We conclude with examples that highlight the application of PBPK-PD and share perspectives on future opportunities for this emerging quantitative tool.

Pharmacokinetics, Immunogenicity, and Efficacy of Etanercept in Pediatric Patients With Moderate to Severe Plaque Psoriasis.

Etanercept has been recently approved in the United States for the treatment of moderate to severe plaque psoriasis in patients aged 4-17 years. The objective of this study was to characterize etanercept pharmacokinetics, immunogenicity, and efficacy in pediatric patients. Data from a phase 3 study and open-label extension study were analyzed. Etanercept serum concentrations in pediatric patients receiving etanercept 0.8 mg/kg (maximum, 50 mg) weekly were compared with adult psoriasis patients and pediatric patients with juvenile idiopathic arthritis (JIA) who received etanercept 0.4 mg/kg twice weekly. The developments of antietanercept antibodies and efficacy based on the Psoriasis Area and Severity Index were evaluated. Steady-state trough etanercept concentrations were similar across visits from weeks 12-48, between patients aged 4-11 and 12-17 years, between pediatric and adult psoriasis patients, and between pediatric patients with psoriasis or JIA. Etanercept serum concentrations and safety profiles were similar in patients with (15.9%) and without antietanercept antibodies. Dosing used in the study provided similar exposures and efficacy across ranges of weight and body mass index. Pharmacokinetic, immunogenicity, and efficacy data support 0.8 mg/kg (maximum, 50 mg) weekly dosing of etanercept in patients aged 4-17 years.

Modeling the intra- and extracellular cytokine signaling pathway under heat stroke in the liver.

Heat stroke (HS) is a life-threatening illness induced by prolonged exposure to a hot environment that causes central nervous system abnormalities and severe hyperthermia. Current data suggest that the pathophysiological responses to heat stroke may not only be due to the immediate effects of heat exposure per se but also the result of a systemic inflammatory response syndrome (SIRS). The observation that pro- (e.g., IL-1) and anti-inflammatory (e.g., IL-10) cytokines are elevated concomitantly during recovery suggests a complex network of interactions involved in the manifestation of heat-induced SIRS. In this study, we measured a set of circulating cytokine/soluble cytokine receptor proteins and liver cytokine and receptor mRNA accumulation in wild-type and tumor necrosis factor (TNF) receptor knockout mice to assess the effect of neutralization of TNF signaling on the SIRS following HS. Using a systems approach, we developed a computational model describing dynamic changes (intra- and extracellular events) in the cytokine signaling pathways in response to HS that was fitted to novel genomic (liver mRNA accumulation) and proteomic (circulating cytokines and receptors) data using global optimization. The model allows integration of relevant biological knowledge and formulation of new hypotheses regarding the molecular mechanisms behind the complex etiology of HS that may serve as future therapeutic targets. Moreover, using our unique modeling framework, we explored cytokine signaling pathways with three in silico experiments (e.g. by simulating different heat insult scenarios and responses in cytokine knockout strains in silico).

Decreased secretion and unfolded protein response upregulation.

Recombinant antibody fragments, for example, the classic monovalent single-chain antibody (scFv), are emerging as credible alternatives to monoclonal antibody (mAb) products. scFv fragments maintain a diverse range of potential applications in biotechnology and can be implemented as powerful therapeutic and diagnostic agents. As such, a variety of hosts have been used to produce antibody fragments resulting in varying degrees of success. Yeast, Saccharomyces cerevisiae, is an attractive host due to quality control mechanisms of the secretory pathway that ensure secreted proteins are properly folded. However, the expression of a recombinant protein in yeast is not trivial; neither are the quality control mechanisms the cell initiates to respond to overwhelming stress, such as an increased protein load, simplistic. The endoplasmic reticulum (ER) is a dynamic organelle, capable of sensing and adjusting its folding capacity in response to increased demand. When protein abundance or terminally misfolded proteins overwhelm the ER's capacity, the unfolded protein response (UPR) is activated. In the guidelines presented here, we discuss varying aspects of quality control, its modulation, and ways to design appropriate constructs for yeast recombinant protein expression. Furthermore, we have provided protocols and methods to monitor intracellular protein expression and trafficking as well as evaluation of the UPR, with essential controls. The latter part of this chapter will review considerations for the experimental design of microarray and quantitative polymerase chain reaction (q-PCR) techniques while suggesting appropriate means of data analysis.

Vulnerabilities in the tau network and the role of ultrasensitive points in tau pathophysiology.

The multifactorial nature of disease motivates the use of systems-level analyses to understand their pathology. We used a systems biology approach to study tau aggregation, one of the hallmark features of Alzheimer's disease. A mathematical model was constructed to capture the current state of knowledge concerning tau's behavior and interactions in cells. The model was implemented in silico in the form of ordinary differential equations. The identifiability of the model was assessed and parameters were estimated to generate two cellular states: a population of solutions that corresponds to normal tau homeostasis and a population of solutions that displays aggregation-prone behavior. The model of normal tau homeostasis was robust to perturbations, and disturbances in multiple processes were required to achieve an aggregation-prone state. The aggregation-prone state was ultrasensitive to perturbations in diverse subsets of networks. Tau aggregation requires that multiple cellular parameters are set coordinately to a set of values that drive pathological assembly of tau. This model provides a foundation on which to build and increase our understanding of the series of events that lead to tau aggregation and may ultimately be used to identify critical intervention points that can direct the cell away from tau aggregation to aid in the treatment of tau-mediated (or related) aggregation diseases including Alzheimer's.