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Context In patients with GH deficiency (GHD) receiving GH treatment, IGF-1 concentrations are used by physicians to monitor treatment safety and efficacy and guide dosing decisions. Somatrogon is a long-acting GH approved as a once-weekly treatment for pediatric GHD. Somatrogon administration results in characteristic changes in the IGF-1 profile, with values measured at 96 hours postdose representing mean IGF-1 concentrations that best reflect overall somatrogon exposure. Objective To develop a simple method to enable physicians to predict mean IGF-1 concentrations following somatrogon dosing, based on a single IGF-1 measurement taken at any point during the 7-day dosing interval. Methods Data from phase 2 and phase 3 somatrogon studies were used to develop a 2-compartment pharmacokinetic model with delayed first-order absorption. An indirect-response pharmacokinetic/pharmacodynamic model was applied to the predicted somatrogon concentrations, and model simulations were used to predict IGF-1 and IGF-1 SD score (SDS) levels for participants in both studies. Results A total of 16,213 dosing records (from 42 and 109 participants in the phase 2 and 3 studies, respectively) were used for the simulations, generating predicted values for IGF-1 and IGF-1 SDS. Predicted values were scaled against the respective values at 96 hours (day 4). These values were used to create a table showing the adjustments required to predict mean IGF-1 and IGF-1 SDS values depending on time after dose. Conclusion We developed a simple method enabling physicians to predict mean weekly IGF-1 values using IGF-1 values measured at any point in the dosing interval. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

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, β 7-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 β 7+ 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 β 7+ effector memory T cells [placebo, 8%; PF-00547659, 84-138%] and β 7+ 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 β 7+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. [ABSTRACT FROM AUTHOR]

The article focuses on the variability of biomarkers observed in healthy subjects and inflammatory bowel disease (IBD) patients. It discusses the variability from data generation methods and in data analysis reporting. The views on the challenges faced due to variability in biomarkers when constructing and parameterizing quantitative systems pharmacology (QSP) model of immunology are also presented.

Arsenic trioxide (ATO) synergistically promotes all trans retinoic acid (ATRA)-induced differentiation of PML–RARα negative HL-60 myeloblastic leukemia cells. In PML–RARα positive myeloid leukemia cells, ATO is known to cause degradation of PML–RARα with subsequent induced myeloid differentiation. We found that ATO by itself does not cause differentiation of the PML–RARα 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 p47PHOX, 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–RARα negative leukemias. [ABSTRACT FROM AUTHOR]