Development of Copper Nanoclusters-Based Turn-Off Nanosensor for Fluorescence Detection of Two Pyrethroid Pesticides (Cypermethrin and Lambda-Cyhalothrin).

Fluorescent copper nanoclusters (Cu NCs) were synthesized by using Withania somnifera (W. somnifera) plant extract as a biotemplate. Aqueous dispersion of W. somnifera-Cu NCs displays intense emission peak at 458 nm upon excitation at 350 nm. This fluorescence emission was utilized for the detection of two pyrethroid pesticides (cypermethrin and lambda-cyhalothrin) via "turn-off" mechanism. Upon the addition of two pyrethiod pesticides independently, the fluorescence emission of W. somnifera-Cu NCs was gradually decreased with increasing concentrations of both pesticides. It was noticed that the decrease in emission intensity at 458 nm was linearly dependent on the logarithm of both pesticides concentrations in the ranges of 0.01-100 µM and of 0.05-100 µM for cypermethrin and lambda-cyhalothrin, respectively. Consequently, the limits of detection were found to be 27.06 and 23.28 nM for cypermethrin and lambda-cyhalothrin, respectively. The as-fabricated W. somnifera-Cu NCs acted as a facile sensor for the analyses of cypermethrin and lambda-cyhalothrin in vegetables (tomato and bottle gourd), which demonstrates that it could be used as portable sensing platform for assaying of two pyrethroid pesticides in food samples.

Clinical Pharmacology Applications of Real-World Data and Real-World Evidence in Drug Development and Approval-An Industry Perspective.

Since the 21st Century Cures Act was signed into law in 2016, real-world data (RWD) and real-world evidence (RWE) have attracted great interest from the healthcare ecosystem globally. The potential and capability of RWD/RWE to inform regulatory decisions and clinical drug development have been extensively reviewed and discussed in the literature. However, a comprehensive review of current applications of RWD/RWE in clinical pharmacology, particularly from an industry perspective, is needed to inspire new insights and identify potential future opportunities for clinical pharmacologists to utilize RWD/RWE to address key drug development questions. In this paper, we review the RWD/RWE applications relevant to clinical pharmacology based on recent publications from member companies in the International Consortium for Innovation and Quality in Pharmaceutical Development (IQ) RWD Working Group, and discuss the future direction of RWE utilization from a clinical pharmacology perspective. A comprehensive review of RWD/RWE use cases is provided and discussed in the following categories of application: drug-drug interaction assessments, dose recommendation for patients with organ impairment, pediatric plan development and study design, model-informed drug development (e.g., disease progression modeling), prognostic and predictive biomarkers/factors identification, regulatory decisions support (e.g., label expansion), and synthetic/external control generation for rare diseases. Additionally, we describe and discuss common sources of RWD to help guide appropriate data selection to address questions pertaining to clinical pharmacology in drug development and regulatory decision making.

Long-Term Safety and Efficacy of the Anti-Mucosal Addressin Cell Adhesion Molecule-1 Monoclonal Antibody Ontamalimab (SHP647) for the Treatment of Crohn's Disease: The OPERA II Study.

BACKGROUND: Patients with Crohn's disease (CD) experience intestinal inflammation. Ontamalimab (SHP647), a fully human immunoglobulin G2 monoclonal antibody against mucosal addressin cell adhesion molecule-1, is a potential novel CD treatment. OPERA II, a multicenter, open-label, phase 2 extension study, assessed the long-term safety and efficacy of ontamalimab in patients with moderate-to-severe CD. METHODS: Patients had completed 12 weeks of blinded treatment (placebo or ontamalimab at 22.5, 75, or 225 mg subcutaneously) in OPERA (NCT01276509) or had a clinical response to ontamalimab 225 mg in TOSCA (NCT01387594). Participants received ontamalimab at 75 mg every 4 weeks (weeks 0-72), then were followed up every 4 weeks for 24 weeks. One-time dose reduction to 22.5 mg or escalation to 225 mg was permitted at the investigator's discretion. The primary end points were safety and tolerability outcomes. Secondary end points included changes in serum drug and biomarker concentrations. Efficacy end points were exploratory, and used non-responder imputation methods. RESULTS: Overall, 149/268 patients completed the study. The most common adverse event leading to study discontinuation was CD flare (19.8%). Two patients died; neither death was considered to be drug related. No dose reductions occurred; 157 patients had their dose escalated. Inflammatory biomarker concentrations decreased. Serum ontamalimab levels were consistent with known pharmacokinetics. Remission rates (Harvey-Bradshaw Index [HBI] ≤ 5; baseline, 48.1%; week 72, 37.3%) and response rates (baseline [decrease in Crohn's Disease Activity Index ≥ 70 points], 63.1%; week 72 [decrease in HBI ≥ 3], 42.5%) decreased gradually. CONCLUSIONS: Ontamalimab was well tolerated; treatment responses appeared to be sustained over 72 weeks.ClinicalTrials.gov ID: NCT01298492.

Population Pharmacokinetic Analysis of Rivipansel in Healthy Subjects and Subjects with Sickle Cell Disease.

BACKGROUND: Sickle cell disease is an inherited blood disorder with reduced blood-carrying capacity. It is associated with a tendency to form microclots in blood vessels, leading to painful episodes known as a vaso-occlusive crisis. Rivipansel is a pan-selectin inhibitor being studied for the treatment of a vaso-occlusive crisis in patients with sickle cell disease. METHODS: A population pharmacokinetic model of rivipansel plasma and urine concentrations was constructed using a two-compartment model and data from nine different clinical studies. Creatinine clearance was calculated using the Schwartz formula for children and the Chronic Kidney Disease Epidemiology Collaboration formula for adults. Urine volume and concentration of the study drug in urine from subjects in five clinical studies were used to estimate renal and nonrenal clearance. RESULTS: Rivipansel drug concentrations were well described by the model. The post hoc estimates of average steady-state concentrations were predicted to be similar for the adult and pediatric cohorts of the pivotal phase III study. Parameter estimates showed almost exclusively renal excretion of rivipansel, which is consistent with the known properties of the drug. CONCLUSIONS: The pharmacokinetics of rivipansel was well characterized by a two-compartment population pharmacokinetic model. Our results illustrate the important role of simulations in optimizing a potential drug dosing regimen for patients with sickle cell disease and progressive renal impairment.

A Dynamic Quantitative Systems Pharmacology Model of Inflammatory Bowel Disease: Part 1 - Model Framework.

A mechanistic, multistate, mathematical model of inflammatory bowel disease (IBD) was developed by including key biological mechanisms in blood and gut, including cell differentiation, cytokine production, and clinical biomarkers. The model structure is consistent between healthy volunteers and IBD disease phenotype, with 24 parameters changed between diseases. Modular nature of the model allows for easy incorporation of new mechanisms or modification of existing interactions. Model simulations for steady-state levels of proteins and cells in the blood and gut using a population approach are consistent with published data. By simulating the response of two clinical biomarkers, C-reactive protein and fecal calprotectin, to parameter perturbations, the model explores hypotheses for possible treatment mechanisms. With additional experimental validation and addition of drug treatments, the model provides a platform to test hypothesis on treatment effects in IBD.

A Dynamic Quantitative Systems Pharmacology Model of Inflammatory Bowel Disease: Part 2 - Application to Current Therapies in Crohn's Disease.

Inflammatory bowel disease (IBD) is a heterogeneic disease with a variety of treatments targeting different mechanisms. A multistate, mechanistic, mathematical model of IBD was developed in part 1 of this two-part article series. In this paper, application of the model to predict response of key clinical biomarkers following different treatment options for Crohn's disease was explored. Five therapies, representing four different mechanisms of action, were simulated in the model and longitudinal profiles of key clinical markers, C-reactive protein and fecal calprotectin were compared with clinical observations. Model simulations provided an accurate match with both central tendency and variability observed in biomarker profiles. We also applied the model to predict biomarker and clinical response in an experimental, combination therapy of existing therapeutic options and provide possible mechanistic basis for the increased response. Overall, we present a validated, modular, mechanistic model construct, which can be applied to explore key biomarkers and clinical outcomes in IBD.

Modeling and simulation of the modified Rankin Scale and National Institutes of Health Stroke Scale neurological endpoints in intracerebral hemorrhage.

Intracerebral hemorrhage (ICH) is a form of stroke characterized by uncontrolled bleeding into the parenchyma of the brain. There is no approved therapy for ICH and it is associated with very poor neurological outcomes with around half of subjects dying within 1 month and most subjects showing complete or partial disability. A key challenge is to identify subjects who could benefit from intervention using characteristics such as baseline hemorrhage volume and the increase in hemorrhage volume in the first few hours, which have been correlated with final outcomes in ICH. Combined longitudinal models were developed to describe stroke scales using categorical data (Modified Rankin Scale, mRS), continuous bounded data (National Institutes of Health Stroke Scale, NIHSS), and time to death. Covariate effects for baseline hematoma volume and maximum increase in hematoma volume were incorporated to assess the improvement in outcome when hematoma volume increase would be reduced by a potential treatment. The combined model provided an adequate description of stroke scales, with patients split into a Non-survival and a High-survival sub-population, and dropout due to death was well described by a constant hazard survival model. Models were compared indicating that the combined mRS/NIHSS model provided the most information, followed by the NIHSS-only model, and the mRS-only model, and finally the traditional statistical analysis on dichotomized response at 90 days. Simulations showed that substantial reductions in hematoma volume increase were required to increase the probability of a favorable outcome.

Evaluating the Role of Janus Kinase Pathways in Platelet Homeostasis Using a Systems Modeling Approach.

Maintaining platelet homeostasis is important to avoid spontaneous bleeding and organ damage. Thrombopoietin, the primary regulator of platelet production, is affected by and acts in part via Janus kinase (JAK)-signal transducer and activator of transcription (STAT)-mediated mechanisms. Interleukin-6 is also partly responsible for inducing thrombopoietin production via the JAK-STAT pathway. Although current understanding suggests that JAK2 is a primary mediator of platelet regulation, the emerging data show that a JAK1-specific inhibitor resulted in the modulation of platelet numbers following dosing. To gain a mechanistic understanding, a model describing platelet regulation based on known physiology and JAK-STAT pathways was built. The model provides a tool to coalesce biological understanding of platelet physiology and an in silico experimental platform to explore drug effects on platelet homeostasis. In this article, we explain the model construction and demonstrate the use of JAK-inhibitor programs as informing probes of the physiology, gaining insights on dosing paradigms that avoid platelet-related safety concerns.

Getting Innovative Therapies Faster to Patients at the Right Dose: Impact of Quantitative Pharmacology Towards First Registration and Expanding Therapeutic Use.

Quantitative pharmacology (QP) applications in translational medicine, drug-development, and therapeutic use were crowd-sourced by the ASCPT Impact and Influence initiative. Highlighted QP case studies demonstrated faster access to innovative therapies for patients through 1) rational dose selection for pivotal trials; 2) reduced trial-burden for vulnerable populations; or 3) simplified posology. Critical success factors were proactive stakeholder engagement, alignment on the value of model-informed approaches, and utilizing foundational clinical pharmacology understanding of the therapy.

Anti-MAdCAM Antibody Increases ß7+ T Cells and CCR9 Gene Expression in the Peripheral Blood of Patients With Crohn's Disease.

OBJECTIVE: To define pharmacodynamic biomarkers in the peripheral blood of patients with Crohn's disease [CD] after treatment with PF-00547659, an anti-human mucosal addressin cell adhesion molecule-1 [MAdCAM-1] monoclonal antibody. METHODS: In this Phase 2, randomised, double-blind, controlled study [OPERA], blood samples were analysed from patients with moderate to severe active CD who received placebo or 22.5 mg, 75 mg, or 225 mg of PF-00547659 subcutaneously at baseline and at Weeks 4 and 8, with follow-up at Week 12. Soluble MAdCAM [sMAdCAM] was measured by mass spectrometry, ß7-expressing T cells by flow cytometry, and gene transcriptome by RNA sequencing. RESULTS: A slight increase in sMAdCAM was measured in the placebo group from baseline to Week 12 [6%], compared with significant decreases in all PF-00547659 groups [-87% to -98%]. A slight increase from baseline to Week 12 was observed in frequency and molecules of equivalent soluble fluorochrome for ß7+ central memory T cells in the placebo group [4%], versus statistically significant increases in the active treatment groups [48% to 81%]. Similar trends were seen for ß7+ effector memory T cells [placebo, 8%; PF-00547659, 84-138%] and ß7+ naïve T cells [8%; 13-50%]. CCR9 gene expression had statistically significant up-regulation [p = 1.09e-06; false discovery rate < 0.1] with PF-00547659 treatment, and was associated with an increase in ß7+ T cells. CONCLUSIONS: Results of the OPERA study demonstrate positive pharmacology and dose-dependent changes in pharmacodynamic biomarker measurements in blood, including changes in cellular composition of lymphocytes and corresponding CCR9 gene expression changes.

Phase II evaluation of anti-MAdCAM antibody PF-00547659 in the treatment of Crohn's disease: report of the OPERA study.

OBJECTIVE: This phase II, randomised, double-blind, placebo-controlled clinical trial was designed to evaluate the efficacy and safety of PF-00547659, a fully human monoclonal antibody that binds to human mucosal addressin cell adhesion molecule (MAdCAM) to selectively reduce lymphocyte homing to the intestinal tract, in patients with moderate-to-severe Crohn's disease (CD). DESIGN: Eligible adults were aged 18-75 years, with active moderate-to-severe CD (Crohn's Disease Activity Index (CDAI) 220-450), a history of failure or intolerance to antitumour necrosis factor and/or immunosuppressive agents, high-sensitivity C reactive protein >3.0 mg/L and ulcers on colonoscopy. Patients were randomised to PF-00547659 22.5 mg, 75 mg or 225 mg or placebo. The primary endpoint was CDAI 70-point decrease from baseline (CDAI-70) at week 8 or 12. RESULTS: In all, 265 patients were eligible for study entry. Although CDAI-70 response was not significantly different with placebo versus PF-00547659 treatment at weeks 8 or 12, remission rate was greater in patients with higher baseline C reactive protein (>5 mg/L vs >18.8 mg/L, respectively). Soluble MAdCAM decreased significantly from baseline to week 2 in a dose-related manner and remained low during the study in PF-00547659-treated patients. Circulating ß7+ CD4+ central memory T-lymphocytes increased at weeks 8 and 12 with PF-00547659 treatment. No safety signal was seen. CONCLUSIONS: Clinical endpoint differences between PF-00547659 and placebo did not reach statistical significance in patients with moderate-to-severe CD. PF-00547659 was pharmacologically active, as shown by a sustained dose-related decrease in soluble MAdCAM and a dose-related increase in circulating ß7+ central memory T cells. TRIAL REGISTRATION NUMBER: NCT01276509; Results.

A review of quantitative modeling of B cell responses to antigenic challenge.

A key role of B cells in the mammalian immune response is the generation of antibodies that serve to protect the organism against antigenic challenges. The same process may also be detrimental in the context of autoimmunity. Several modeling approaches have been applied to this aspect of the immune response, from predicting potential epitopes to describing B cells progress through developmental models and simulating antibody production. Here we review some of the modeling techniques, and summarize models that describe different activation mechanisms for B cells, including T cell dependent and independent models. We focus on viral infection as a prototype system, and briefly describe case studies in other disease areas such as bacterial infection and oncology. We single out aspects of the B cell response for which there are current knowledge gaps. We outline areas in need of further research in modeling applications to ultimately produce a "B cell module" for a complete immune response model.

Computational modeling and analysis of insulin induced eukaryotic translation initiation.

Insulin, the primary hormone regulating the level of glucose in the bloodstream, modulates a variety of cellular and enzymatic processes in normal and diseased cells. Insulin signals are processed by a complex network of biochemical interactions which ultimately induce gene expression programs or other processes such as translation initiation. Surprisingly, despite the wealth of literature on insulin signaling, the relative importance of the components linking insulin with translation initiation remains unclear. We addressed this question by developing and interrogating a family of mathematical models of insulin induced translation initiation. The insulin network was modeled using mass-action kinetics within an ordinary differential equation (ODE) framework. A family of model parameters was estimated, starting from an initial best fit parameter set, using 24 experimental data sets taken from literature. The residual between model simulations and each of the experimental constraints were simultaneously minimized using multiobjective optimization. Interrogation of the model population, using sensitivity and robustness analysis, identified an insulin-dependent switch that controlled translation initiation. Our analysis suggested that without insulin, a balance between the pro-initiation activity of the GTP-binding protein Rheb and anti-initiation activity of PTEN controlled basal initiation. On the other hand, in the presence of insulin a combination of PI3K and Rheb activity controlled inducible initiation, where PI3K was only critical in the presence of insulin. Other well known regulatory mechanisms governing insulin action, for example IRS-1 negative feedback, modulated the relative importance of PI3K and Rheb but did not fundamentally change the signal flow.

Modeling and analysis of retinoic acid induced differentiation of uncommitted precursor cells.

Manipulation of differentiation programs has therapeutic potential in a spectrum of human cancers and neurodegenerative disorders. In this study, we integrated computational and experimental methods to unravel the response of a lineage uncommitted precursor cell-line, HL-60, to Retinoic Acid (RA). HL-60 is a human myeloblastic leukemia cell-line used extensively to study human differentiation programs. Initially, we focused on the role of the BLR1 receptor in RA-induced differentiation and G1/0-arrest in HL-60. BLR1, a putative G protein-coupled receptor expressed following RA exposure, is required for RA-induced cell-cycle arrest and differentiation and causes persistent MAPK signaling. A mathematical model of RA-induced cell-cycle arrest and differentiation was formulated and tested against BLR1 wild-type (wt) knock-out and knock-in HL-60 cell-lines with and without RA. The current model described the dynamics of 729 proteins and protein complexes interconnected by 1356 interactions. An ensemble strategy was used to compensate for uncertain model parameters. The ensemble of HL-60 models recapitulated the positive feedback between BLR1 and MAPK signaling. The ensemble of models also correctly predicted Rb and p47phox regulation and the correlation between p21-CDK4-cyclin D formation and G1/0-arrest following exposure to RA. Finally, we investigated the robustness of the HL-60 network architecture to structural perturbations and generated experimentally testable hypotheses for future study. Taken together, the model presented here was a first step toward a systematic framework for analysis of programmed differentiation. These studies also demonstrated that mechanistic network modeling can help prioritize experimental directions by generating falsifiable hypotheses despite uncertainty.

Arsenic trioxide cooperates with all trans retinoic acid to enhance mitogen-activated protein kinase activation and differentiation in PML-RARalpha negative human myeloblastic leukemia cells.

Arsenic trioxide (ATO) synergistically promotes all trans retinoic acid (ATRA)-induced differentiation of PML-RARalpha negative HL-60 myeloblastic leukemia cells. In PML-RARalpha positive myeloid leukemia cells, ATO is known to cause degradation of PML-RARalpha with subsequent induced myeloid differentiation. We found that ATO by itself does not cause differentiation of the PML-RARalpha negative HL-60 cells, but enhances ATRA's capability to cause differentiation. ATO augmented ATRA-induced RAF/MEK/ERK axis signaling, expression of CD11b and p47(PHOX), and inducible oxidative metabolism. ATO enhanced ATRA-induced population growth retardation without evidence of apoptosis or enhanced G1/G0 growth arrest. Compared to ATRA-treated cells, the ATRA plus ATO-treated cells progressed more slowly through the cell cycle as detected by a slower rate of accumulation in G2/M following nocodazole treatment. Hoechst/PI staining showed that low-dose ATO did not induce apoptosis. In summary, our results indicate that ATO in conjunction with ATRA is of potential chemotherapeutic use in PML-RARalpha negative leukemias.

Analysis of the molecular networks in androgen dependent and independent prostate cancer revealed fragile and robust subsystems.

Androgen ablation therapy is currently the primary treatment for metastatic prostate cancer. Unfortunately, in nearly all cases, androgen ablation fails to permanently arrest cancer progression. As androgens like testosterone are withdrawn, prostate cancer cells lose their androgen sensitivity and begin to proliferate without hormone growth factors. In this study, we constructed and analyzed a mathematical model of the integration between hormone growth factor signaling, androgen receptor activation, and the expression of cyclin D and Prostate-Specific Antigen in human LNCaP prostate adenocarcinoma cells. The objective of the study was to investigate which signaling systems were important in the loss of androgen dependence. The model was formulated as a set of ordinary differential equations which described 212 species and 384 interactions, including both the mRNA and protein levels for key species. An ensemble approach was chosen to constrain model parameters and to estimate the impact of parametric uncertainty on model predictions. Model parameters were identified using 14 steady-state and dynamic LNCaP data sets taken from literature sources. Alterations in the rate of Prostatic Acid Phosphatase expression was sufficient to capture varying levels of androgen dependence. Analysis of the model provided insight into the importance of network components as a function of androgen dependence. The importance of androgen receptor availability and the MAPK/Akt signaling axes was independent of androgen status. Interestingly, androgen receptor availability was important even in androgen-independent LNCaP cells. Translation became progressively more important in androgen-independent LNCaP cells. Further analysis suggested a positive synergy between the MAPK and Akt signaling axes and the translation of key proliferative markers like cyclin D in androgen-independent cells. Taken together, the results support the targeting of both the Akt and MAPK pathways. Moreover, the analysis suggested that direct targeting of the translational machinery, specifically eIF4E, could be efficacious in androgen-independent prostate cancers.

A test of highly optimized tolerance reveals fragile cell-cycle mechanisms are molecular targets in clinical cancer trials.

Robustness, a long-recognized property of living systems, allows function in the face of uncertainty while fragility, i.e., extreme sensitivity, can potentially lead to catastrophic failure following seemingly innocuous perturbations. Carlson and Doyle hypothesized that highly-evolved networks, e.g., those involved in cell-cycle regulation, can be resistant to some perturbations while highly sensitive to others. The "robust yet fragile" duality of networks has been termed Highly Optimized Tolerance (HOT) and has been the basis of new lines of inquiry in computational and experimental biology. In this study, we tested the working hypothesis that cell-cycle control architectures obey the HOT paradigm. Three cell-cycle models were analyzed using monte-carlo sensitivity analysis. Overall state sensitivity coefficients, which quantify the robustness or fragility of a given mechanism, were calculated using a monte-carlo strategy with three different numerical techniques along with multiple parameter perturbation strategies to control for possible numerical and sampling artifacts. Approximately 65% of the mechanisms in the G1/S restriction point were responsible for 95% of the sensitivity, conversely, the G2-DNA damage checkpoint showed a much stronger dependence on a few mechanisms; approximately 32% or 13 of 40 mechanisms accounted for 95% of the sensitivity. Our analysis predicted that CDC25 and cyclin E mechanisms were strongly implicated in G1/S malfunctions, while fragility in the G2/M checkpoint was predicted to be associated with the regulation of the cyclin B-CDK1 complex. Analysis of a third model containing both G1/S and G2/M checkpoint logic, predicted in addition to mechanisms already mentioned, that translation and programmed proteolysis were also key fragile subsystems. Comparison of the predicted fragile mechanisms with literature and current preclinical and clinical trials suggested a strong correlation between efficacy and fragility. Thus, when taken together, these results support the working hypothesis that cell-cycle control architectures are HOT networks and establish the mathematical estimation and subsequent therapeutic exploitation of fragile mechanisms as a novel strategy for anti-cancer lead generation.