RESUMEN
In this study, we present the translational modeling used in the discovery of AZD1979, a melanin-concentrating hormone receptor 1 (MCHr1) antagonist aimed for treatment of obesity. The model quantitatively connects the relevant biomarkers and thereby closes the scaling path from rodent to man, as well as from dose to effect level. The complexity of individual modeling steps depends on the quality and quantity of data as well as the prior information; from semimechanistic body-composition models to standard linear regression. Key predictions are obtained by standard forward simulation (e.g., predicting effect from exposure), as well as non-parametric input estimation (e.g., predicting energy intake from longitudinal body-weight data), across species. The work illustrates how modeling integrates data from several species, fills critical gaps between biomarkers, and supports experimental design and human dose-prediction. We believe this approach can be of general interest for translation in the obesity field, and might inspire translational reasoning more broadly.
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Fármacos Antiobesidad/administración & dosificación , Azetidinas/administración & dosificación , Modelos Biológicos , Obesidad/tratamiento farmacológico , Oxadiazoles/administración & dosificación , Receptores de la Hormona Hipofisaria/antagonistas & inhibidores , Investigación Biomédica Traslacional , Animales , Fármacos Antiobesidad/farmacocinética , Fármacos Antiobesidad/farmacología , Fármacos Antiobesidad/uso terapéutico , Azetidinas/farmacocinética , Azetidinas/farmacología , Azetidinas/uso terapéutico , Biomarcadores/metabolismo , Peso Corporal/efectos de los fármacos , Relación Dosis-Respuesta a Droga , Descubrimiento de Drogas , Ingestión de Energía/efectos de los fármacos , Femenino , Humanos , Masculino , Ratones , Obesidad/metabolismo , Oxadiazoles/farmacocinética , Oxadiazoles/farmacología , Oxadiazoles/uso terapéutico , Ratas , Receptores de la Hormona Hipofisaria/metabolismo , Proyectos de InvestigaciónRESUMEN
Essentials MEDI2452 is a specific antidote of the platelet P2Y12 receptor antagonist ticagrelor. Hemostatic effects of MEDI2452 were evaluated in pigs treated with ticagrelor and aspirin. MEDI2452 eliminated free ticagrelor within 5 min and gradually normalized platelet aggregation. Improvements in blood pressure (significant) and in blood-loss and survival (non-significant) were observed. SUMMARY: Background Ticagrelor, a P2Y12 antagonist, is approved for the prevention of thromboembolic events. However, antiplatelet therapies carry a risk of bleeding. Objective To explore the hemostatic effects of MEDI2452, an antidote for ticagrelor. Methods Pigs, pre-treated with aspirin, were given an intravenous infusion of ticagrelor or vehicle. At the end of the infusion, a piece of a liver lobe was cut off and a bolus of MEDI2452 or vehicle was administered intravenously. Blood was collected to monitor blood loss, mean arterial blood pressure (MAP) was recorded and survival time was observed over 4 h. Blood samples for drug plasma exposures and platelet aggregation were collected. Results MEDI2452 eliminated the free concentrations of ticagrelor and its active metabolite AR-C124910XX within 5 min. ADP-induced platelet aggregation was close to normal at 60 min, which was not significantly different from aspirin alone. MEDI2452 numerically reduced ticagrelor-mediated effects: body-weight-adjusted blood loss in the 15- to 90-min interval, 12 (confidence interval [CI] 95% 7-28] vs. 17 (CI 95% 5-31) (ticagrelor and aspirin) vs. 5 (CI 95% 3-9) mL kg-1 (aspirin alone), survival 70% (CI 95% 47-100) vs. 45% (CI 95% 21-92) (ticagrelor and aspirin) vs. 100% (CI 95% 100-100) (aspirin alone), and median survival time, 240 (CI 95% 180-240) vs. 169 (CI 95% 64-240) (ticagrelor and aspirin) vs. 240 (CI 95% 240-240) min (aspirin alone). Finally, MEDI2452 significantly attenuated the decline in MAP, 0.08 (CI 95% 0.07-0.09) vs. 0.141 (CI 95% 0.135-0.148) (ticagrelor and aspirin) vs. 0.04 (CI 95% 0.03-0.05) mmHg per min (aspirin alone) and maintained MAP at a significantly higher level, 73 (CI 95% 51-95) vs. 48 (CI 95% 25-70) (ticagrelor and aspirin) vs. 115 (CI 95% 94-136) mmHg (aspirin alone). Conclusion MEDI2452 eliminated free ticagrelor and AR-C124910XX within 5 min. This translated into a gradual normalization of ADP-induced platelet aggregation and significant improvement in blood pressure and numerical but non-significant improvements in blood-loss and survival.
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Adenosina/análogos & derivados , Anticuerpos Neutralizantes/administración & dosificación , Antídotos/administración & dosificación , Aspirina/administración & dosificación , Adenosina/efectos adversos , Adenosina/química , Adenosina Difosfato/química , Animales , Biotinilación , Presión Sanguínea/efectos de los fármacos , Anticuerpos ampliamente neutralizantes , Hemorragia/inducido químicamente , Hemostasis , Humanos , Agregación Plaquetaria/efectos de los fármacos , Inhibidores de Agregación Plaquetaria/uso terapéutico , Pruebas de Función Plaquetaria , Porcinos , Ticagrelor , Factores de TiempoRESUMEN
The investigational ticagrelor-neutralizing antibody fragment, MEDI2452, is developed to rapidly and specifically reverse the antiplatelet effects of ticagrelor. However, the dynamic interaction of ticagrelor, the ticagrelor active metabolite (TAM), and MEDI2452, makes pharmacokinetic (PK) analysis nontrivial and mathematical modeling becomes essential to unravel the complex behavior of this system. We propose a mechanistic PK model, including a special observation model for post-sampling equilibration, which is validated and refined using mouse in vivo data from four studies of combined ticagrelor-MEDI2452 treatment. Model predictions of free ticagrelor and TAM plasma concentrations are subsequently used to drive a pharmacodynamic (PD) model that successfully describes platelet aggregation data. Furthermore, the model indicates that MEDI2452-bound ticagrelor is primarily eliminated together with MEDI2452 in the kidneys, and not recycled to the plasma, thereby providing a possible scenario for the extrapolation to humans. We anticipate the modeling work to improve PK and PD understanding, experimental design, and translational confidence.
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Adenosina/análogos & derivados , Anticuerpos Neutralizantes/administración & dosificación , Antídotos/administración & dosificación , Modelos Teóricos , Adenosina/administración & dosificación , Adenosina/farmacocinética , Adenosina/farmacología , Animales , Anticuerpos Neutralizantes/farmacología , Antídotos/farmacocinética , Antídotos/farmacología , Anticuerpos ampliamente neutralizantes , Interacciones Farmacológicas , Masculino , Ratones , Ratones Endogámicos C57BL , Agregación Plaquetaria/efectos de los fármacos , Antagonistas del Receptor Purinérgico P2Y/administración & dosificación , Antagonistas del Receptor Purinérgico P2Y/farmacocinética , Antagonistas del Receptor Purinérgico P2Y/farmacología , Ratas , Ratas Sprague-Dawley , Especificidad de la Especie , TicagrelorRESUMEN
Human dose-prediction is fundamental for ranking lead-optimization compounds in drug discovery and to inform design of early clinical trials. This tutorial describes how uncertainty in such predictions can be quantified and efficiently communicated to facilitate decision-making. Using three drug-discovery case studies, we show how several uncertain pieces of input information can be integrated into one single uncomplicated plot with key predictions, including their uncertainties, for many compounds or for many scenarios, or both.
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Algorithms for parameter estimation and model selection that identify both the structure and the parameters of an ordinary differential equation model from experimental data are presented. The work presented here focuses on the case of an unknown structure and some time course information available for every variable to be analysed, and this is exploited to make the algorithms as efficient as possible. The algorithms are designed to handle problems of realistic size, where reactions can be nonlinear in the parameters and where data can be sparse and noisy. To achieve computational efficiency, parameters are mostly estimated for one equation at a time, giving a fast and accurate parameter estimation algorithm compared with other algorithms in the literature. The model selection is done with an efficient heuristic search algorithm, where the structure is built incrementally. Two test systems are used that have previously been used to evaluate identification algorithms, a metabolic pathway and a genetic network. Both test systems were successfully identified by using a reasonable amount of simulated data. Besides, measurement noise of realistic levels can be handled. In comparison to other methods that were used for these test systems, the main strengths of the presented algorithms are that a fully specified model, and not only a structure, is identified, and that they are considerably faster compared with other identification algorithms.