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Mouse and human data implicate the NOD1 and NOD2 sensors of the intestinal microbiome and the associated signal transduction via the receptor interacting protein kinase 2 (RIPK2) as a potential key signaling node for the development of inflammatory bowel disease (IBD) and an attractive target for pharmacological intervention. The TRUC mouse model of IBD was strongly indicated for evaluating RIPK2 antagonism for its effect on intestinal inflammation based on previous knockout studies with NOD1, NOD2, and RIPK2. We identified and profiled the BI 706039 molecule as a potent and specific functional inhibitor of both human and mouse RIPK2 and with favorable pharmacokinetic properties. We dosed BI 706039 in the spontaneous TRUC mouse model from age 28 to 56 days. Oral, daily administration of BI 706039 caused dose-responsive and significant improvement in colonic histopathological inflammation, colon weight, and terminal levels of protein-normalized fecal lipocalin (all P values <0.001). These observations correlated with dose responsively increasing systemic levels of the BI 706039 compound, splenic molecular target engagement of RIPK2, and modulation of inflammatory genes in the colon. This demonstrates that a relatively low oral dose of a potent and selective RIPK2 inhibitor can modulate signaling in the intestinal immune system and significantly improve disease associated intestinal inflammation.NEW & NOTEWORTHY The RIPK2 kinase at the apex of microbiome immunosensing is an attractive target for pharmacological intervention. A low oral dose of a RIPK2 inhibitor leads to significantly improved intestinal inflammation in the murine TRUC model of colitis. A selective and potent inhibitor of the RIPK2 kinase may represent a new class of therapeutics that target microbiome-driven signaling for the treatment of IBD.
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Colitis Ulcerosa/tratamiento farmacológico , Colon/efectos de los fármacos , Inhibidores de Proteínas Quinasas/farmacología , Proteína Serina-Treonina Quinasa 2 de Interacción con Receptor/antagonistas & inhibidores , Animales , Disponibilidad Biológica , Células Cultivadas , Colitis Ulcerosa/enzimología , Colitis Ulcerosa/genética , Colitis Ulcerosa/patología , Colon/enzimología , Colon/patología , Enfermedad de Crohn/enzimología , Enfermedad de Crohn/patología , Citocinas/genética , Citocinas/metabolismo , Proteínas de Unión al ADN/genética , Modelos Animales de Enfermedad , Heces/química , Humanos , Mediadores de Inflamación/metabolismo , Lipocalinas/metabolismo , Ratones Endogámicos BALB C , Ratones Noqueados , Modelos Biológicos , Monocitos/efectos de los fármacos , Monocitos/metabolismo , Inhibidores de Proteínas Quinasas/farmacocinética , Proteína Serina-Treonina Quinasa 2 de Interacción con Receptor/genética , Proteína Serina-Treonina Quinasa 2 de Interacción con Receptor/metabolismo , Proteínas de Dominio T Box/genéticaRESUMEN
PURPOSE: Infections due to severe neutropenia are the most common therapy-associated causes of mortality in patients with acute myeloid leukemia (AML). New strategies to lessen the severity and duration of neutropenia are needed. METHODS: Cytarabine is commonly used for AML consolidation therapy; we compared high- and intermediate-dose cytarabine administration on days 1, 2, and 3 (AC-123) versus days 1, 3, and 5 (AC-135) in consolidation therapy of AML. Recently, clinical trials demonstrated that high-dose AC-123 resulted in a shortened white blood cell (WBC) recovery time compared with high-dose AC-135. Our main hypothesis is that this is also the case for different cytarabine dosage, granulocyte colony-stimulating factor (G-CSF) administration, and cycle lengths. We analyzed 334 treatment schedules on virtual cohorts of digital twins. RESULTS: Comparison of 32,565 simulated consolidation cycles resulted in a reduction in the WBC recovery time for AC-123 in 99.6% of the considered cycles (median reduction 3.5 days) without an increase in the number of leukemic blasts (lower value in 94.2% of all cycles), compared to AC-135. CONCLUSION: Our numerical study supports the use of AC-123 plus G-CSF as standard conventional AML consolidation therapy to reduce the risk for life-threatening infectious complications.
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OBJECTIVE: Neutropenia is an adverse event commonly arising during intensive chemotherapy of acute myeloid leukemia (AML). It is often associated with infectious complications. Mathematical modeling, simulation, and optimization of the treatment process would be a valuable tool to support clinical decision making, potentially resulting in less severe side effects and deeper remissions. However, until now, there has been no validated mathematical model available to simulate the effect of chemotherapy treatment on white blood cell (WBC) counts and leukemic cells simultaneously. METHODS: We developed a population pharmacokinetic/pharmacodynamic (PK/PD) model combining a myelosuppression model considering endogenous granulocyte-colony stimulating factor (G-CSF), a PK model for cytarabine (Ara-C), a subcutaneous absorption model for exogenous G-CSF, and a two-compartment model for leukemic blasts. This model was fitted to data of 44 AML patients during consolidation therapy with a novel Ara-C plus G-CSF schedule from a phase II controlled clinical trial. Additionally, we were able to optimize treatment schedules with respect to disease progression, WBC nadirs, and the amount of Ara-C and G-CSF. RESULTS: The developed PK/PD model provided good prediction accuracies and an interpretation of the interaction between WBCs, G-CSF, and blasts. For 14 patients (those with available bone marrow blast counts), we achieved a median 4.2-fold higher WBC count at nadir, which is the most critical time during consolidation therapy. The simulation results showed that relative bone marrow blast counts remained below the clinically important threshold of 5%, with a median of 60% reduction in Ara-C. CONCLUSION: These in silico findings demonstrate the benefits of optimized treatment schedules for AML patients. SIGNIFICANCE: Until 2017, no new drug had been approved for the treatment of AML, fostering the optimal use of currently available drugs.
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Factor Estimulante de Colonias de Granulocitos y Macrófagos , Leucemia Mieloide Aguda , Médula Ósea , Citarabina/efectos adversos , Factor Estimulante de Colonias de Granulocitos , Humanos , Leucemia Mieloide Aguda/tratamiento farmacológicoRESUMEN
Acute lymphoblastic leukemia is the most common malignancy in childhood. Successful treatment requires initial high-intensity chemotherapy, followed by low-intensity oral maintenance therapy with oral 6-mercaptopurine (6MP) and methotrexate (MTX) until 2-3 years after disease onset. However, intra- and inter-individual variability in the pharmacokinetics (PK) and pharmacodynamics (PD) of 6MP and MTX make it challenging to balance the desired antileukemic effects with undesired excessive myelosuppression during maintenance therapy. A model to simulate the dynamics of different cell types, especially neutrophils, would be a valuable contribution to improving treatment protocols (6MP and MTX dosing regimens) and a further step to understanding the heterogeneity in treatment efficacy and toxicity. We applied and modified a recently developed semi-mechanistic PK/PD model to neutrophils and analyzed their behavior using a non-linear mixed-effects modeling approach and clinical data obtained from 116 patients. The PK model of 6MP influenced the accuracy of absolute neutrophil count (ANC) predictions, whereas the PD effect of MTX did not. Predictions based on ANC were more accurate than those based on white blood cell counts. Using the new cross-validated mathematical model, simulations of different treatment protocols showed a linear dose-effect relationship and reduced ANC variability for constant dosages. Advanced modeling allows the identification of optimized control criteria and the weighting of specific influencing factors for protocol design and individually adapted therapy to exploit the optimal effect of maintenance therapy on survival.
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We investigate the personalisation and prediction accuracy of mathematical models for white blood cell (WBC) count dynamics during consolidation treatment using intermediate or high-dose cytarabine (Ara-C) in acute myeloid leukaemia (AML). Ara-C is the clinically most relevant cytotoxic agent for AML treatment. We extend a mathematical model of myelosuppression and a pharmacokinetic model of Ara-C with different hypotheses of Ara-C's pharmacodynamic effects. We cross-validate the 12 model variations using dense WBC count measurements from 23 AML patients. Surprisingly, the prediction accuracy remains satisfactory in each of the models despite different modelling hypotheses. Therefore, we compare average clinical and calculated WBC recovery times for different Ara-C schedules as a successful methodology for model discrimination. As a result, a new hypothesis of a secondary pharmacodynamic effect on the proliferation rate seems plausible. Furthermore, we demonstrate the impact of treatment timing on subsequent nadir values based on personalised predictions as a possibility for influencing/controlling myelosuppression.
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Proliferación Celular/efectos de los fármacos , Citarabina , Leucemia Mieloide Aguda , Modelos Biológicos , Citarabina/farmacocinética , Citarabina/farmacología , Humanos , Leucemia Mieloide Aguda/tratamiento farmacológico , Leucemia Mieloide Aguda/metabolismo , Leucemia Mieloide Aguda/patologíaRESUMEN
Acute lymphoblastic leukemia is the most common malignancy in childhood and requires prolonged oral maintenance chemotherapy to prevent disease relapse after remission induction with intensive intravenous chemotherapy. In maintenance therapy, drug doses of 6-mercaptopurine (6-MP) and methotrexate (MTX) are adjusted to achieve sustained antileukemic activity without excessive myelosuppression. However, uncertainty exists regarding timing and extent of drug dose responses and optimal dose adaptation strategies. We propose a novel comprehensive mathematical model for 6-MP and MTX pharmacokinetics, pharmacodynamics and myelosuppression in acute lymphoblastic maintenance therapy. We personalize and cross-validate the mathematical model using clinical data and propose a real-time algorithm to predict chemotherapy responses with a clinical decision support system as a potential future application.