0000000000142121

AUTHOR

Iñaki F. Trocóniz

The Role of Mathematical Models in Immuno-Oncology: Challenges and Future Perspectives

Immuno-oncology (IO) focuses on the ability of the immune system to detect and eliminate cancer cells. Since the approval of the first immune checkpoint inhibitor, immunotherapies have become a major player in oncology treatment and, in 2021, represented the highest number of approved drugs in the field. In spite of this, there is still a fraction of patients that do not respond to these therapies and develop resistance mechanisms. In this sense, mathematical models offer an opportunity to identify predictive biomarkers, optimal dosing schedules and rational combinations to maximize clinical response. This work aims to outline the main therapeutic targets in IO and to provide a description …

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Computer simulations for bioequivalence trials: Selection of analyte in BCS class II and IV drugs with first-pass metabolism, two metabolic pathways and intestinal efflux transporter.

A semi-physiological two compartment pharmacokinetic model with two active metabolites (primary (PM) and secondary metabolites (SM)) with saturable and non-saturable pre-systemic efflux transporter, intestinal and hepatic metabolism has been developed. The aim of this work is to explore in several scenarios which analyte (parent drug or any of the metabolites) is the most sensitive to changes in drug product performance (i.e. differences in in vivo dissolution) and to make recommendations based on the simulations outcome. A total of 128 scenarios (2 Biopharmaceutics Classification System (BCS) drug types, 2 levels of KM Pgp, in 4 metabolic scenarios at 2 dose levels in 4 quality levels of t…

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Semi-physiologic model validation and bioequivalence trials simulation to select the best analyte for acetylsalicylic acid

Abstract The objective of this paper is to apply a previously developed semi-physiologic pharmacokinetic model implemented in NONMEM to simulate bioequivalence trials (BE) of acetyl salicylic acid (ASA) in order to validate the model performance against ASA human experimental data. ASA is a drug with first-pass hepatic and intestinal metabolism following Michaelis–Menten kinetics that leads to the formation of two main metabolites in two generations (first and second generation metabolites). The first aim was to adapt the semi-physiological model for ASA in NOMMEN using ASA pharmacokinetic parameters from literature, showing its sequential metabolism. The second aim was to validate this mod…

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Towards patient stratification and treatment in the autoimmune disease lupus erythematosus using a systems pharmacology approach

Drug development in Systemic Lupus Erythematosus (SLE) has been hindered by poor translation from successful preclinical experiments to clinical efficacy. This lack of success has been attributed to the high heterogeneity of SLE patients and to the lack of understanding of disease physiopathology. Modelling approaches could be useful for supporting the identification of targets, biomarkers and patient subpopulations with differential response to drugs. However, the use of traditional quantitative models based on differential equations is not justifiable in a sparse data situation. Boolean networks models are less demanding on the required data to be implemented and can provide insights into…

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Validation of a semi-physiological model for caffeine in healthy subjects and cirrhotic patients.

The objective of this paper was to validate a previously developed semi physiological model to simulate bioequivalence trials of drug products. The aim of the model was to ascertain whether the measurement of the metabolite concentration-time profiles would provide any additional information in bioequivalence studies (Fernandez-Teruel et al., 2009a,b; Navarro-Fontestad et al., 2010). The semi-physiological model implemented in NONMEM VI was used to simulate caffeine and its main metabolite plasma levels using caffeine parameters from bibliography. Data from 3 bioequivalence studies in healthy subjects at 3 different doses (100, 175 and 400mg of caffeine) and one study in cirrhotic patients …

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Semi-Mechanistic Model for the Antitumor Response of a Combination Cocktail of Immuno-Modulators in Non-Inflamed (Cold) Tumors.

Simple Summary The clinical efficacy of immunotherapies when treating cold tumors is still low, and different treatment combinations are needed when dealing with this challenging scenario. In this work, a middle-out strategy was followed to develop a model describing the antitumor efficacy of different immune-modulator combinations, including an antigen, a toll-like receptor-3 agonist, and an immune checkpoint inhibitor in mice treated with non-inflamed tumor cells. Our results support that clinical response requires antigen-presenting cell activation and also relies on the amount of CD8 T cells and tumor resistance mechanisms present. This mathematical model is a very useful platform to ev…

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Semi-mechanistic Pharmacokinetic/Pharmacodynamic model of three pegylated rHuEPO and ior®EPOCIM in New Zealand rabbits.

Abstract Marketed formulations of erythropoietin (EPO) ior®EPOCIM, MIRCERA® and two newly developed pegylated-EPO analogues (PEG-EPO 32 and 40 kDa) formulations were intravenously administered to New Zealand rabbits. A semi-mechanistic Pharmacokinetic/Pharmacodynamic (PK/PD) model describing in a simultaneous and integrated form the time course of reticulocytes, red blood cells and hemoglobin was built to account for the time course of hematopoiesis stimulation after erythropoietin administration. Data analysis was performed based on the population approach with the software NONMEM version 7.3. Erythropoietin disposition of each of the administered formulations was best described with a two…

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Population pharmacokinetic model of lithium and drug compliance assessment.

Population pharmacokinetic analysis of lithium during therapeutic drug monitoring and drug compliance assessment was performed in 54 patients and 246 plasma concentrations levels were included in this study. Patients received several treatment cycles (1-9) and one plasma concentration measurement for each patient was obtained always before starting next cycle (pre-dose) at steady state. Data were analysed using the population approach with NONMEM version 7.2. Lithium measurements were described using a two-compartment model (CL/F=0.41Lh-1, V1/F=15.3L, Q/F=0.61Lh-1, and V2/F = 15.8L) and the most significant covariate on lithium CL was found to be creatinine clearance (reference model). Lith…

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