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Abstract Glucagon‐like peptide‐1 (GLP‐1) receptor agonists (GLP‐1RAs) and dual GLP‐1/glucagon receptor agonists improve glycaemic control and cause significant weight loss in patients with type 2 diabetes.1 These effects are driven in part by augmenting glucose‐stimulated insulin release (incretin effect), reducing caloric intake and delayed gastric emptying. We developed and externally validated a novel integrated quantitative systems pharmacology (QSP) model to gain quantitative insight into the relative contributions and mechanisms of drugs modulating glucose regulatory pathways. This model (4GI model) incorporates known feedback mechanisms among glucose, GLP‐1, glucagon, glucose‐dependent insulinotropic peptide (GIP), and insulin after glucose provocation (i.e., food intake) and drug intervention utilizing published nonpharmacological and pharmacological (liraglutide, a GLP‐1RA) data. The resulting model accurately describes the aforementioned mechanisms and independently predicts the effects of the GLP‐1RAs (dulaglutide and semaglutide) on system dynamics. Therefore, the validated 4GI model represents a quantitative decision‐making tool to support the advancement of novel therapeutics and combination strategies modulating these pathways.

Abstract Mathematical models in oncology aid in the design of drugs and understanding of their mechanisms of action by simulation of drug biodistribution, drug effects, and interaction between tumor and healthy cells. The traditional approach in pharmacometrics is to develop and validate ordinary differential equation models to quantify trends at the population level. In this approach, time‐course of biological measurements is modeled continuously, assuming a homogenous population. Another approach, agent‐based models, focuses on the behavior and fate of biological entities at the individual level, which subsequently could be summarized to reflect the population level. Heterogeneous cell populations and discrete events are simulated, and spatial distribution can be incorporated. In this tutorial, an agent‐based model is presented and compared to an ordinary differential equation model for a tumor efficacy model inhibiting the pERK pathway. We highlight strengths, weaknesses, and opportunities of each approach.

Abstract Amyloidosis is to be considered in the differential diagnosis of postoperative edema of tongue base after its ablation. It might be triggered by surgical trauma. After establishment of diagnosis, cause of secondary amyloidosis should be excluded.

Tremelimumab, an anti‐cytotoxic T‐lymphocyte antigen‐4 monoclonal antibody that enhances T‐cell activation, was evaluated in a randomized, double‐blind, placebo‐controlled, phase IIb study (NCT01843374) in patients with unresectable malignant mesothelioma. The study demonstrated no clinically meaningful differences in overall survival (OS). The objective of this analysis was to evaluate the relationship of exposure with OS. A population pharmacokinetic (PK) model adequately described the PK data. Three factors (sex, C‐reactive protein, and baseline tumor size) were identified as statistically significant PK predictors (P

The lack of standardization in the way that quantitative and systems pharmacology (QSP) models are developed, tested, and documented hinders their reproducibility, reusability, and expansion or reduction to alternative contexts. This in turn undermines the potential impact of QSP in academic, industrial, and regulatory frameworks. This article presents a minimum set of recommendations from the UK Quantitative and Systems Pharmacology Network (UK QSP Network) to guide QSP practitioners seeking to maximize their impact, and stakeholders considering the use of QSP models in their environment.

Abstract Background Variants in TTN are frequently identified in the genetic evaluation of skeletal myopathy or cardiomyopathy. However, due to the high frequency of TTN variants in the general population, incomplete penetrance, and limited understanding of the spectrum of disease, interpretation of TTN variants is often difficult for laboratories and clinicians. Currently, cardiomyopathy is associated with heterozygous A‐band TTN variants, whereas skeletal myopathy is largely associated with homozygous or compound heterozygous TTN variants. Recent reports show pathogenic variants in TTN may result in a broader phenotypic spectrum than previously recognized. Methods Here we report the results of a multisite study that characterized the phenotypes of probands with variants in TTN. We investigated TTN genotype‐phenotype correlations in probands with skeletal myopathy and/or cardiomyopathy. Probands with TTN truncating variants (TTNtv) or pathogenic missense variants were ascertained from two academic medical centers. Variants were identified via clinical genetic testing and reviewed according to the American College of Medical Genetics criteria. Clinical and family history data were documented via retrospective chart review. Family studies were performed for probands with atypical phenotypes. Results Forty‐nine probands were identified with TTNtv or pathogenic missense variants. Probands were classified by clinical presentation: cardiac (n = 30), skeletal muscle (n = 12), or both (cardioskeletal, n = 7). Within the cardioskeletal group, 5/7 probands had heterozygous TTNtv predicted to affect the distal (3’) end of the A‐band. All cardioskeletal probands had onset of proximal‐predominant muscle weakness before diagnosis of cardiovascular disease, five pedigrees support dominant transmission. Conclusion Although heterozygous TTNtv in the A‐band is known to cause dilated cardiomyopathy, we present evidence that these variants may in some cases cause a novel, dominant skeletal myopathy with a limb‐girdle pattern of weakness. These findings emphasize the importance of multidisciplinary care for patients with A‐band TTNtv who may be at risk for multisystem disease.

Objective: The present study is a review of transoral robotic surgery (TORS) for the treatment of obstructive sleep apnea-hypopnea syndrome (OSAHS). Methods: The review presents the experience of the robotic center that developed the technique with regards to patient selection, surgical method, and post-operative care. In addition, the review provides results of a systematic review and meta-analysis of the complications and clinical outcomes of TORS when applied in the management of OSAHS. Results: The rate of success, defined as 50% reduction of pre-operative AHI and an overall AHI

Therapeutic protein products (TPP) have been widely used to treat a variety of human diseases, including cancer, hemophilia, and autoimmune diseases. However, TPP can induce unwanted immune responses that can impact both drug efficacy and patient safety. The presence of aggregates is of particular concern as they have been implicated in inducing both T cell-independent and T cell-dependent immune responses. We used mathematical modeling to evaluate several mechanisms through which aggregates of TPP could contribute to the development of immunogenicity. Modeling interactions between aggregates and B cell receptors demonstrated that aggregates are unlikely to induce T cell-independent immune responses by cross-linking B cell receptors because the amount of signal transducing complex that can form under physiologically relevant conditions is limited. We systematically evaluate the role of aggregates in inducing T cell-dependent immune responses using a recently developed multiscale mechanistic mathematical model. Our analysis indicates that aggregates could contribute to T cell-dependent immune response by inducing high affinity epitopes which may not be present in the nonaggregated TPP and/or by enhancing danger signals to break tolerance. In summary, our computational analysis is suggestive of novel insights into the mechanisms underlying aggregate-induced immunogenicity, which could be used to develop mitigation strategies.

Fibrolipomas are a rare subtype of lipomas. We describe a case of a man suffering from subcutaneous penile fibrolipoma, who three months earlier has been submitted to an augmentative phalloplasty due to aesthetic dysmorphophobia. After six months from the excision of the mass, the penile elongation and penile enlargement were stable, and the patient was satisfied with his sexual intercourse and sexual life. To our knowledge, this is the first reported penile subcutaneous fibrolipoma case in the literature. The diagnostics and surgical features of this case are discussed.

Background and Purpose: Cotadutide is a dual GLP-1 and glucagon receptor agonist with balanced agonistic activity at each receptor designed to harness the advantages on promoting liver health, weight loss and glycaemic control. We characterised the effects of cotadutide on glucose, insulin, GLP-1, GIP, and glucagon over time in a quantitative manner using our glucose dynamics systems model (4GI systems model), in combination with clinical data from a multiple ascending dose/Phase 2a (MAD/Ph2a) study in overweight and obese subjects with a history of Type 2 diabetes mellitus (NCT02548585)., Experimental Approach: The cotadutide PK-4GI systems model was calibrated to clinical data by re-estimating only food related parameters. In vivo cotadutide efficacy was scaled based on in vitro potency. The model was used to explore the effect of weight loss on insulin sensitivity and predict the relative contribution of the GLP-1 and glucagon receptor agonistic effects on glucose., Key Results: Cotadutide MAD/Ph2a clinical endpoints were successfully predicted. The 4GI model captured a positive effect of weight loss on insulin sensitivity and showed that the stimulating effect of glucagon on glucose production counteracts the GLP-1 receptor-mediated decrease in glucose, resulting in a plateau for glucose decrease around a 200-μg cotadutide dose., Conclusion and Implications: The 4GI quantitative systems pharmacology model was able to predict the clinical effects of cotadutide on glucose, insulin, GLP-1, glucagon and GIP given known in vitro potency. The analyses demonstrated that the quantitative systems pharmacology model, and its successive refinements, will be a valuable tool to support the clinical development of cotadutide and related compounds., (© 2024 The Authors. British Journal of Pharmacology published by John Wiley & Sons Ltd on behalf of British Pharmacological Society.)

Glucagon-like peptide-1 (GLP-1) receptor agonists (GLP-1RAs) and dual GLP-1/glucagon receptor agonists improve glycaemic control and cause significant weight loss in patients with type 2 diabetes. 1 These effects are driven in part by augmenting glucose-stimulated insulin release (incretin effect), reducing caloric intake and delayed gastric emptying. We developed and externally validated a novel integrated quantitative systems pharmacology (QSP) model to gain quantitative insight into the relative contributions and mechanisms of drugs modulating glucose regulatory pathways. This model (4GI model) incorporates known feedback mechanisms among glucose, GLP-1, glucagon, glucose-dependent insulinotropic peptide (GIP), and insulin after glucose provocation (i.e., food intake) and drug intervention utilizing published nonpharmacological and pharmacological (liraglutide, a GLP-1RA) data. The resulting model accurately describes the aforementioned mechanisms and independently predicts the effects of the GLP-1RAs (dulaglutide and semaglutide) on system dynamics. Therefore, the validated 4GI model represents a quantitative decision-making tool to support the advancement of novel therapeutics and combination strategies modulating these pathways., (© 2021 The Authors. CPT: Pharmacometrics & Systems Pharmacology published by Wiley Periodicals LLC on behalf of American Society for Clinical Pharmacology and Therapeutics.)

Mathematical models in oncology aid in the design of drugs and understanding of their mechanisms of action by simulation of drug biodistribution, drug effects, and interaction between tumor and healthy cells. The traditional approach in pharmacometrics is to develop and validate ordinary differential equation models to quantify trends at the population level. In this approach, time-course of biological measurements is modeled continuously, assuming a homogenous population. Another approach, agent-based models, focuses on the behavior and fate of biological entities at the individual level, which subsequently could be summarized to reflect the population level. Heterogeneous cell populations and discrete events are simulated, and spatial distribution can be incorporated. In this tutorial, an agent-based model is presented and compared to an ordinary differential equation model for a tumor efficacy model inhibiting the pERK pathway. We highlight strengths, weaknesses, and opportunities of each approach., (© 2022 The Authors. CPT: Pharmacometrics & Systems Pharmacology published by Wiley Periodicals LLC on behalf of American Society for Clinical Pharmacology and Therapeutics.)

Linear models are generally reliable methods for analyzing tumor growth in vivo, with drug effectiveness being represented by the steepness of the regression slope. With immunotherapy, however, not all tumor growth follows a linear pattern, even after log transformation. Tumor kinetics models are mechanistic models that describe tumor proliferation and tumor killing macroscopically, through a set of differential equations. In drug combination studies, although an additional drug-drug interaction term can be added to such models, however, the drug interactions suggested by tumor kinetics models cannot be translated directly into synergistic effects. We have developed a novel statistical approach that simultaneously models tumor growth in control, monotherapy, and combination therapy groups. This approach makes it possible to test for synergistic effects directly and to compare such effects among different studies., (© 2019 John Wiley & Sons, Ltd.)

Precision medicine aims to use patient genomic, epigenomic, specific drug dose, and other data to define disease patterns that may potentially lead to an improved treatment outcome. Personalized dosing regimens based on tumor drug penetration can play a critical role in this approach. State-of-the-art techniques to measure tumor drug penetration focus on systemic exposure, tissue penetration, cellular or molecular engagement, and expression of pharmacological activity. Using in silico methods, this information can be integrated to bridge the gap between the therapeutic regimen and the pharmacological link with clinical outcome. These methodologies are described, and challenges ahead are discussed. Supported by many examples, this review shows how the combination of these techniques provides enhanced patient-specific information on drug accessibility at the tumor tissue level, target binding, and downstream pharmacology. Our vision of how to apply tumor drug penetration measurements offers a roadmap for the clinical implementation of precision dosing., (© 2018 The Authors Clinical Pharmacology & Therapeutics published by Wiley Periodicals, Inc. on behalf of American Society for Clinical Pharmacology and Therapeutics.)

The lack of standardization in the way that quantitative and systems pharmacology (QSP) models are developed, tested, and documented hinders their reproducibility, reusability, and expansion or reduction to alternative contexts. This in turn undermines the potential impact of QSP in academic, industrial, and regulatory frameworks. This article presents a minimum set of recommendations from the UK Quantitative and Systems Pharmacology Network (UK QSP Network) to guide QSP practitioners seeking to maximize their impact, and stakeholders considering the use of QSP models in their environment., (© 2019 The Authors CPT: Pharmacometrics & Systems Pharmacology published by Wiley Periodicals, Inc. on behalf of the American Society for Clinical Pharmacology and Therapeutics.)

Interleukin (IL)-13 is involved in the pathogenesis of some types of asthma. Tralokinumab is a human immunoglobulin G 4 monoclonal antibody that specifically binds to IL-13. Two placebo-controlled phase II studies (phase IIa, NCT00873860 and phase IIb, NCT01402986) have been conducted in which tralokinumab was administered subcutaneously. This investigation aimed to characterize tralokinumab's dose-exposure-response (forced expiratory volume in 1 s (FEV 1 )) relationship in patients with asthma and to predict the most appropriate dose for phase III. An integrated population pharmacokinetic-pharmacodynamic (PK/PD) modeling analysis was required for phase III dose selection, due to differing phase II patient populations, designs, and regimens. Analysis of combined datasets enabled the identification of tralokinumab's dose-exposure-FEV 1 response relationship in patients with asthma. Near-maximal FEV 1 increase was predicted at a dose of 300 mg SC once every 2 weeks (Q2W). This dose was chosen for tralokinumab in the phase III clinical development program for treatment of severe, uncontrolled asthma., (© 2017 American Society for Clinical Pharmacology and Therapeutics.)

The objectives of this analysis were to develop a population pharmacokinetics (PK) model of durvalumab, an anti-PD-L1 antibody, and quantify the impact of baseline and time-varying patient/disease characteristics on PK. Pooled data from two studies (1,409 patients providing 7,407 PK samples) were analyzed with nonlinear mixed effects modeling. Durvalumab PK was best described by a two-compartment model with both linear and nonlinear clearances. Three candidate models were evaluated: a time-invariant clearance (CL) model, an empirical time-varying CL model, and a semimechanistic time-varying CL model incorporating longitudinal covariates related to disease status (tumor shrinkage and albumin). The data supported a slight decrease in durvalumab clearance with time and suggested that it may be associated with a decrease in nonspecific protein catabolic rate among cancer patients who benefit from therapy. No covariates were clinically relevant, indicating no need for dose adjustment. Simulations indicated similar overall PK exposures following weight-based and flat-dosing regimens., (© 2018, The Authors. Clinical Pharmacology & Therapeutics published by Wiley Periodicals, Inc. on behalf of American Society for Clinical Pharmacology and Therapeutics.)

Drug development is a lengthy, costly process with low probability of success. Biopharmaceuticals are highly specific molecules, with efficacy and safety closely tied to target biology and pharmacology. The "learning-predicting-confirming" continuum by translational and clinical modeling and simulation (M&S) was implemented at every decision point for mavrilimumab, a human monoclonal antibody in development for rheumatoid arthritis (RA). This tutorial uses mavrilimumab as an example to demonstrate rational discovery, preclinical development, clinical study design, and dose selection of biotherapeutics by M&S., (© 2017 The Authors CPT: Pharmacometrics & Systems Pharmacology published by Wiley Periodicals, Inc. on behalf of American Society for Clinical Pharmacology and Therapeutics.)

The purpose of this commentary is to place probability of trial success, or assurance, in the context of decision making in drug development, and to illustrate its properties in an intuitive manner for the readers of Clinical Pharmacology and Therapeutics. The hope is that this will stimulate a dialog on how assurance should be incorporated into a quantitative decision approach for clinical development and trial design that uses all available information., (© 2015 ASCPT.)

High throughput molecular and functional profiling of patients is a key driver of precision medicine. DNA and RNA characterization has been enabled at unprecedented cost and scale through rapid, disruptive progress in sequencing technology, but challenges persist in data management and interpretation. We analyze the state-of-the-art of large-scale unbiased sequencing in drug discovery and development, including technology, application, ethical, regulatory, policy and commercial considerations, and discuss issues of LUS implementation in clinical and regulatory practice., (© 2015 American Society for Clinical Pharmacology and Therapeutics.)

The theme of this month's issue of Clinical Pharmacology & Therapeutics is pharmacometrics. When looking back at the early days of pharmacometrics, current contributions to the drug development process look impressive. The questions are whether the original promise is being kept and how the impact can become even greater.

Systems pharmacology is an emerging approach that sets out to use quantitative concepts rooted in the synergy between modeling and simulation on one hand and large-scale data collection and analysis on the other to investigate biological systems and design therapeutic interventions. Interest in this field has recently increased substantially, but so have perceived challenges and misunderstandings, especially related to implementation. This Commentary explores the opportunities and challenges in the rapidly evolving area of systems pharmacology from a drug discovery and development perspective.