RESUMEN
Non-Small Cell Lung Cancer (NSCLC) remains one of the main causes of cancer death worldwide. In the urge of finding an effective approach to treat cancer, enormous therapeutic targets and treatment combinations are explored in clinical studies, which are not only costly, suffer from a shortage of participants, but also unable to explore all prospective therapeutic solutions. Within the evolving therapeutic landscape, the combined use of radiotherapy (RT) and checkpoint inhibitors (ICIs) emerged as a promising avenue. Exploiting the power of quantitative system pharmacology (QSP), we undertook a study to anticipate the therapeutic outcomes of these interventions, aiming to address the limitations of clinical trials. After enhancing a pre-existing QSP platform and accurately replicating clinical data outcomes, we conducted an in-depth study, examining different treatment protocols with nivolumab and RT, both as monotherapy and in combination, by assessing their efficacy through clinical endpoints, namely time to progression (TTP) and duration of response (DOR). As result, the synergy of combined protocols showcased enhanced TTP and extended DOR, suggesting dual advantages of extended response and slowed disease progression with certain combined regimens. Through the lens of QSP modeling, our findings highlight the potential to fine-tune combination therapies for NSCLC, thereby providing pivotal insights for tailoring patient-centric therapeutic interventions.
Asunto(s)
Carcinoma de Pulmón de Células no Pequeñas , Neoplasias Pulmonares , Nivolumab , Carcinoma de Pulmón de Células no Pequeñas/tratamiento farmacológico , Carcinoma de Pulmón de Células no Pequeñas/radioterapia , Carcinoma de Pulmón de Células no Pequeñas/patología , Humanos , Neoplasias Pulmonares/radioterapia , Neoplasias Pulmonares/tratamiento farmacológico , Neoplasias Pulmonares/patología , Nivolumab/uso terapéutico , Nivolumab/administración & dosificación , Inhibidores de Puntos de Control Inmunológico/uso terapéutico , Inhibidores de Puntos de Control Inmunológico/administración & dosificación , Quimioradioterapia/métodos , Resultado del Tratamiento , Antineoplásicos Inmunológicos/uso terapéutico , Antineoplásicos Inmunológicos/administración & dosificación , Modelos Biológicos , Ensayos Clínicos como Asunto/métodosRESUMEN
Sophistication of mathematical models in the pharmacological context reflects the progress being made in understanding physiological, pharmacological, and disease relationships. This progress has illustrated once more the need for advanced quantitative tools able to efficiently extract information from these models. While dynamical systems theory has a long history in the analysis of systems biology models, as emphasized under the dynamical disease concept by Mackey and Glass [Science 197, 287-289 (1977)], its adoption in pharmacometrics is only at the beginning [Chae, Transl. Clin. Pharmacol. 28, 109 (2020)]. Using a quantitative systems pharmacology model of tumor immune dynamics as a case study [Kosinsky et al., J. Immunother. Cancer 6, 17 (2018)], we here adopt a dynamical systems analysis to describe, in an exhaustive way, six different statuses that refer to the response of the system to therapy, in the presence or absence of a tumor-free attractor. To evaluate the therapy success, we introduce the concept of TBA, related to the Time to enter the tumor-free Basin of Attraction, and corresponding to the earliest time at which the therapy can be stopped without jeopardizing its efficacy. TBA can determine the optimal time to stop drug administration and consequently quantify the reduction in drug exposure.
Asunto(s)
Neoplasias , Humanos , Neoplasias/tratamiento farmacológico , Modelos TeóricosRESUMEN
Quantitative systems pharmacology (QSP) proved to be a powerful tool to elucidate the underlying pathophysiological complexity that is intensified by the biological variability and overlapped by the level of sophistication of drug dosing regimens. Therapies combining immunotherapy with more traditional therapeutic approaches, including chemotherapy and radiation, are increasingly being used. These combinations are purposed to amplify the immune response against the tumor cells and modulate the suppressive tumor microenvironment (TME). In order to get the best performance from these combinatorial approaches and derive rational regimen strategies, a better understanding of the interaction of the tumor with the host immune system is needed. The objective of the current work is to provide new insights into the dynamics of immune-mediated TME and immune-oncology treatment. As a case study, we will use a recent QSP model by Kosinsky et al. [J. Immunother. Cancer 6, 17 (2018)] that aimed to reproduce the dynamics of interaction between tumor and immune system upon administration of radiation therapy and immunotherapy. Adopting a dynamical systems approach, we here investigate the qualitative behavior of the representative components of this QSP model around its key parameters. The ability of T cells to infiltrate tumor tissue, originally identified as responsible for individual therapeutic inter-variability [Y. Kosinsky et al., J. Immunother. Cancer 6, 17 (2018)], is shown here to be a saddle-node bifurcation point for which the dynamical system oscillates between two states: tumor-free or maximum tumor volume. By performing a bifurcation analysis of the physiological system, we identified equilibrium points and assessed their nature. We then used the traditional concept of basin of attraction to assess the performance of therapy. We showed that considering the therapy as input to the dynamical system translates into the changes of the trajectory shapes of the solutions when approaching equilibrium points and thus providing information on the issue of therapy.
Asunto(s)
Neoplasias , Humanos , Sistema Inmunológico , Inmunoterapia , Neoplasias/terapia , Análisis de Sistemas , Microambiente TumoralRESUMEN
Although smallpox has been eradicated, the United States government considers it a "material threat" and has funded the discovery and development of potential therapeutic compounds. As reported here, the human efficacious dose for one of these compounds, ST-246, was determined using efficacy studies in nonhuman primates (NHPs), together with pharmacokinetic and pharmacodynamic analysis that predicted the appropriate dose and exposure levels to provide therapeutic benefit in humans. The efficacy analysis combined the data from studies conducted at three separate facilities that evaluated treatment following infection with a closely related virus, monkeypox virus (MPXV), in a total of 96 NHPs. The effect of infection on ST-246 pharmacokinetics in NHPs was applied to humans using population pharmacokinetic models. Exposure at the selected human dose of 600 mg is more than 4-fold higher than the lowest efficacious dose in NHPs and is predicted to provide protection to more than 95% of the population.
Asunto(s)
Antivirales/uso terapéutico , Benzamidas/uso terapéutico , Isoindoles/uso terapéutico , Macaca fascicularis/virología , Monkeypox virus/efectos de los fármacos , Mpox/tratamiento farmacológico , Viruela/tratamiento farmacológico , Animales , Antivirales/farmacocinética , Antivirales/farmacología , Benzamidas/farmacocinética , Benzamidas/farmacología , Cálculo de Dosificación de Drogas , Femenino , Humanos , Isoindoles/farmacocinética , Isoindoles/farmacología , Masculino , Modelos Estadísticos , Mpox/mortalidad , Mpox/virología , Monkeypox virus/crecimiento & desarrollo , Viruela/virología , Análisis de Supervivencia , Resultado del Tratamiento , Virus de la Viruela/efectos de los fármacos , Virus de la Viruela/crecimiento & desarrolloRESUMEN
The first objective of the present study was to predict the pharmacokinetics of selected CYP3A substrates administered at a single oral dose to human. The second objective was to predict pharmacokinetics of the selected drugs in presence of inhibitors of the intestinal and/or hepatic CYP3A activity. We developed a whole-body physiologically based pharmacokinetics (WB-PBPK) model accounting for presystemic elimination of midazolam (MDZ), alprazolam (APZ), triazolam (TRZ), and simvastatin (SMV). The model also accounted for concomitant administration of the above-mentioned drugs with CYP3A inhibitors, namely ketoconazole (KTZ), itraconazole (ITZ), diltiazem (DTZ), saquinavir (SQV), and a furanocoumarin contained in grape-fruit juice (GFJ), namely 6',7'-dihydroxybergamottin (DHB). Model predictions were compared to published clinical data. An uncertainty analysis was performed to account for the variability and uncertainty of model parameters when predicting the model outcomes. We also briefly report on the results of our efforts to develop a global sensitivity analysis and its application to the current WB-PBPK model. Considering the current criterion for a successful prediction, judged satisfied once the clinical data are captured within the 5th and 95th percentiles of the predicted concentration-time profiles, a successful prediction has been obtained for a single oral administration of MDZ and SMV. For APZ and TRZ, however, a slight deviation toward the 95th percentile was observed especially for C(max) but, overall, the in vivo profiles were well captured by the PBPK model. Moreover, the impact of DHB-mediated inhibition on the extent of intestinal pre-systemic elimination of MDZ and SMV has been accurately predicted by the proposed PBPK model. For concomitant administrations of MDZ and ITZ, APZ and KTZ, as well as SMV and DTZ, the in vivo concentration-time profiles were accurately captured by the model. A slight deviation was observed for SMV when coadministered with ITZ, whereas more important deviations have been obtained between the model predictions and in vivo concentration-time profiles of MDZ coadministered with SQV. The same observation was made for TRZ when administered with KTZ. Most of the pharmacokinetic parameters predicted by the PBPK model were successfully predicted within a two-fold error range either in the absence or presence of metabolism-based inhibition. Overall, the present study demonstrated the ability of the PBPK model to predict DDI of CYP3A substrates with promising accuracy.
Asunto(s)
Inhibidores del Citocromo P-450 CYP3A , Citocromo P-450 CYP3A/fisiología , Mucosa Intestinal/metabolismo , Hígado/metabolismo , Modelos Biológicos , Preparaciones Farmacéuticas/metabolismo , Farmacocinética , Administración Oral , Bebidas , Citrus paradisi/química , Citocromo P-450 CYP3A/metabolismo , Relación Dosis-Respuesta a Droga , Interacciones Farmacológicas , Inhibidores Enzimáticos/farmacología , Furocumarinas/aislamiento & purificación , Furocumarinas/farmacología , Humanos , Absorción Intestinal , Intestinos/fisiología , Hígado/fisiología , Microsomas Hepáticos/metabolismo , Método de Montecarlo , Especificidad de Órganos , Preparaciones Farmacéuticas/administración & dosificación , Valor Predictivo de las Pruebas , Especificidad por Sustrato , Factores de Tiempo , Distribución TisularRESUMEN
The structural complexity of a PBPK model is usually accompanied with significant uncertainty in estimating its input parameters. In the last decade, the global sensitivity analysis, which accounts for the variability of all model input parameters simultaneously as well as their correlations, has gained a wide attention as a powerful probing technique to identify and control biological model uncertainties. However, the current sensitivity analysis techniques used in PBPK modeling often neglect the correlation between these input parameters. We introduce a new strategy in the PBPK modeling field to investigate how the uncertainty and variability of correlated input parameters influence the outcomes of the drug distribution process based on a model we recently developed to explain and predict drug distribution in tissues expressing P-glycoprotein (P-gp). As direct results, we will also identify the most important input parameters having the largest contribution to the variability and uncertainty of model outcomes. We combined multivariate random sampling with a ranking procedure. Monte-Carlo simulations were performed on the PBPK model with eighteen model input parameters. Log-normal distributions were assumed for these parameters according to literature and their reported correlations were also included. A multivariate sensitivity analysis was then performed to identify the input parameters with the greatest influence on model predictions. The partial rank correlation coefficients (PRCC) were calculated to establish the input-output relationships. A moderate variability of predicted C(last) and C(max) was observed in liver, heart and brain tissues in the presence or absence of P-gp activity. The major statistical difference in model outcomes of the predicted median values has been obtained in brain tissue. PRCC calculation confirmed the importance for a better quantitative characterisation of input parameters related to the passive diffusion and active transport of the unbound drug through the blood-tissue membrane in heart and brain. This approach has also identified as important input parameters those related to the drug metabolism for the prediction of model outcomes in liver and plasma. The proposed Monte-Carlo/PRCC approach was aimed to address the effect of input parameters correlation in a PBPK model. It allowed the identification of important input parameters that require additional attention in research for strengthening the physiological knowledge of drug distribution in mammalian tissues expressing P-gp, thereby reducing the uncertainty of model predictions.
Asunto(s)
Subfamilia B de Transportador de Casetes de Unión a ATP/metabolismo , Antieméticos/farmacocinética , Encéfalo/metabolismo , Domperidona/farmacocinética , Hígado/metabolismo , Modelos Biológicos , Miocardio/metabolismo , Subfamilia B de Transportador de Casetes de Unión a ATP/deficiencia , Subfamilia B de Transportador de Casetes de Unión a ATP/genética , Animales , Antieméticos/sangre , Transporte Biológico , Simulación por Computador , Difusión , Domperidona/sangre , Ratones , Ratones Noqueados , Método de Montecarlo , Permeabilidad , Reproducibilidad de los Resultados , Distribución Tisular , Incertidumbre , Miembro 4 de la Subfamilia B de Casete de Unión a ATPRESUMEN
BACKGROUND: The expression and activity of P-glycoproteins due to genetic or environmental factors may have a significant impact on drug disposition, drug effectiveness or drug toxicity. Hence, characterization of drug disposition over a wide range of conditions of these membrane transporters activities is required to better characterize drug pharmacokinetics and pharmacodynamics. This work aims to improve our understanding of the impact of P-gp activity modulation on tissue distribution of P-gp substrate. METHODS: A PBPK model was developed in order to examine activity and expression of P-gp transporters in mouse brain and heart. Drug distribution in these tissues was first represented by a well-stirred (WS) model and then refined by a mechanistic transport-based (MTB) model that includes P-gp mediated transport of the drug. To estimate transport-related parameters, we developed an original three-step procedure that allowed extrapolation of in vitro measurements of drug permeability to the in vivo situation. The model simulations were compared to a limited set of data in order to assess the model ability to reproduce the important information of drug distributions in the considered tissues. RESULTS: This PBPK model brings insights into the mechanism of drug distribution in non eliminating tissues expressing P-gp. The MTB model accounts for the main transport mechanisms involved in drug distribution in heart and brain. It points out to the protective role of P-gp at the blood-brain barrier and represents thus a noticeable improvement over the WS model. CONCLUSION: Being built prior to in vivo data, this approach brings an interesting alternative to fitting procedures, and could be adapted to different drugs and transporters. The physiological based model is novel and unique and brought effective information on drug transporters.
Asunto(s)
Miembro 1 de la Subfamilia B de Casetes de Unión a ATP/metabolismo , Modelos Teóricos , Farmacocinética , Animales , Células CACO-2 , Humanos , Ratones , Permeabilidad , Distribución TisularRESUMEN
Expanded-bed adsorption (EBA) is a technique for primary recovery of proteins starting from unclarified broths. This process combines centrifugation, concentration, filtration, and initial capturing of the proteins in a single step. An expanded bed (EB) is comparable to a packed bed in terms of separation performance but its hydrodynamics are that of a fluidized bed. Downstream process development involving EBA is normally carried out in small columns to minimize time and costs. Our purpose here is to characterize the hydrodynamics of expanded beds of different diameters, to develop scaling parameters that can be reliably used to predict separation efficiency of larger EBA columns. A hydrodynamic model has been developed which takes into account the radial liquid velocity profile in the column. The scale-down effect can be characterized in terms of apparent axial dispersion, D(axl,app), and plate number, N(EB), adapted for expanded bed. The model is in good agreement with experimental results obtained from 1- and 5-cm column diameters with buffer solutions of different viscosities. The model and the experiments show an increase of apparent axial dispersion with an increase in column diameter. Furthermore, the apparent axial dispersion is affected by an increase in liquid velocity and viscosity. Supported by visual observations and predictions from the model, it was concluded that operating conditions (liquid viscosity and superficial velocity) resulting in a bed-void fraction between 0.7 and 0.75 would provide the optimal separation efficiency in terms of N(EB).