Dose schedule optimization and the pharmacokinetic driver of neutropenia

Quantitative Evaluation of Dendritic Nanoparticles in Mice: Biodistribution Dynamics and Downstream Tumor Efficacy Outcomes

A physiologically based pharmacokinetic model was developed to describe the tissue distribution kinetics of a dendritic nanoparticle and its conjugated active pharmaceutical ingredient (API) in plasma, liver, spleen, and tumors. Tumor growth data from MV-4-11 tumor-bearing mice were incorporated to investigate the exposure/efficacy relationship. The nanoparticle demonstrated improved antitumor activity compared to the conventional API formulation, owing to the extended released API concentrations at the site of action. Model simulations further enabled the identification of critical parameters that influence API exposure in tumors and downstream efficacy outcomes upon nanoparticle administration. The model was utilized to explore a range of dosing schedules and their effect on tumor growth kinetics, demonstrating the improved antitumor activity of nanoparticles with less frequent dosing compared to the same dose of naked APIs in conventional formulations.

Pharmacokinetics and Toxicities of Oral Docetaxel Formulations Co-Administered with Ritonavir in Phase I Trials

Introduction

Docetaxel is widely used as intravenous (IV) chemotherapy. Oral docetaxel is co-administered with the cytochrome P450 3A4 and P-glycoprotein inhibitor ritonavir to increase oral bioavailability. This research explores the relationship between the pharmacokinetics (PK) and toxicity of this novel oral chemotherapy.

Methods

The patients in two phase I trials were treated with different oral docetaxel formulations in combination with ritonavir in different dose levels, ranging from 20 to 80 mg docetaxel with 100 to 200 mg ritonavir a day. The patients were categorized based on the absence or occurrence of severe treatment-related toxicity (grade ≥3 or any grade leading to treatment alterations). The docetaxel area under the plasma concentration–time curve (AUC) and maximum plasma concentration (C_max) were associated with toxicity.

Results

Thirty-four out of 138 patients experienced severe toxicity, most frequently observed as mucositis, fatigue, diarrhea, nausea and vomiting. The severe toxicity group had a significantly higher docetaxel AUC (2231 ± 1405 vs 1011 ± 830 ng/mL*h, p<0.0001) and C_max (218 ± 178 vs 119 ± 77 ng/mL, p<0.0001) as compared to the patients without severe toxicity. When extrapolated from IV PK data, the patients without severe toxicity had a similar cumulative docetaxel AUC as with standard 3-weekly IV docetaxel, while the C_max was up to 10-fold lower with oral docetaxel and ritonavir.

Conclusion

Severe toxicity was observed in 25% of the patients treated with oral docetaxel and ritonavir. This toxicity seems related to the PK, as the docetaxel AUC_0-inf and C_max were up to twofold higher in the severe toxicity group as compared to the non-severe toxicity group. Future randomized trials will provide a further evaluation of the toxicity and efficacy of the new weekly oral docetaxel and ritonavir regimen in comparison to standard IV docetaxel.

Multiscale and Translational Quantitative Systems Toxicology, Pharmacokinetic-Toxicodynamic Modeling Analysis for Assessment of Doxorubicin-Induced Cardiotoxicity

Dose-dependent life-threatening doxorubicin-induced cardiotoxicity (DIC) is a major clinical challenge that needs to be addressed. Here, we developed an integrated multiscale and translational quantitative systems toxicology and pharmacokinetic-toxicodynamic (QST-PK/TD) model for optimization of doxorubicin dosing regimens for early monitoring and minimization of DIC. A QST model was established by exposing human cardiomyocytes, AC16 cells, to doxorubicin over a time course, and measuring the dynamics of intracellular signaling proteins, AC16 cell viability and released biomarkers of cardiomyocyte injury such as the B-type natriuretic peptide (BNP). Experiments were scaled up to a three-dimensional and dynamic (3DD) cell culture system to evaluate DIC under various dosing regimens. The PK determinants of doxorubicin influencing DIC were identified in vitro and then translated to the in vivo setting through hybrid physiologically based PK (PBPK)/TD models using preclinical- and clinical-level data extracted from literature. The developed cellular-level QST model captured well the observed dynamics of intracellular proteins, AC16 cell viability and BNP kinetics. In the 3DD setting, dose fractionation of doxorubicin displayed a significant reduction in cardiotoxicity compared to single intravenous doses with equal exposure, implying doxorubicin peak concentrations as the PK determinant for DIC. The in vivo hybrid PBPK/TD models captured well doxorubicin PK and DIC. Peak doxorubicin concentrations correlated well with acute DIC for dose-fractionated regimens, while maximum 48-h moving average concentrations correlated with DIC for dose-fractionated and long-term infusion regimens in vivo. The developed multiscale and translational QST-PK/TD modeling platform may serve as an in silico tool for assessment of early toxicity and/or efficacy of developmental drugs in vitro.

Model-Based Optimal AML Consolidation Treatment

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.

Optimization of clinical dosing schedule to manage neutropenia: learnings from semi-mechanistic modeling simulation approach

Neutropenia is a common side-effect of oncology drugs. We aimed to study the impact of exposure and dosing schedule on neutropenia to guide selection of dosing schedules that minimize neutropenia potential while maintaining the desired minimum concentration (C_min) required for target engagement. Dose, frequency and PK parameters were chosen for five hypothetical drugs of various half-lives to (1) achieve same exposure with continuous dosing and evaluate impact of 4 intermittent dosing schedules; and (2) achieve same nadir for continuous and intermittent dosing and evaluate impact on % time above C_min, a surrogate assumed to indicate target engagement. Absolute neutrophil count (ANC) profiles were simulated using Friberg model, a widely used semi-mechanistic myelosuppression model, assuming drug concentration directly reduce the proliferation rate of stem cells and progenitor cells in proliferation compartment. The correlations between different PK measures and neutropenia metrics were explored. In (1), when the same daily dose was used, intermittent schedules offered better management of ANC nadir. The reduced average drug exposure with intermittent dosing led to lower% time above C_min. In (2), when the dose was adjusted to achieve the same nadir, drugs with moderate half-life (8-48 h) showed similar % time above C_min regardless of schedule, while continuous dosing was better for a short half-life (4 h). Area under the concentration curve (AUC) was highly correlated with neutropenia. In summary, continuous dosing, with the dose selected correctly, is most effective to maintain % time above C_min while providing similar tolerability as intermittent dosing with a higher dose. But dose interruptions could be required to manage individual toxicities. Intermittent schedules, on the other hand, allow recovery of ANC, enabling more orderly schedules.

Chemotherapy-Induced Neutropenia as a Prognostic and Predictive Marker of Outcomes in Solid-Tumor Patients

Chemotherapy-induced neutropenia (CIN) is one of the most common side effects seen in cancer patients. As an adverse event, it is deemed undesirable since it often constitutes a dose-limiting toxicity for cytotoxic agents leading to treatment delays and/or dose reductions. It is also associated with a financial cost component from diagnostic work-up and treatment of patients with chemotherapy-induced febrile neutropenia (CIFN). Neutropenia is commonly accompanied by a decrease in other hematopoietic lineages (anemia and/or thrombocytopenia). Dosing of chemotherapeutic agents is based on the severity of adverse effects seen. Depending on the degree of neutropenia, chemotherapeutic agents may be put on hold until count recovery and growth factor support might be added to allow for dosing as scheduled. However, neutropenia appears to be more than just an adverse event. While CIFN by itself constitutes an adverse event, the appearance of just CIN is not necessarily a marker of poor outcome. In fact, it rather appears to be a surrogate marker of response and/or survival in patients treated with cytotoxic regimens. Here we present evidence in different tumor types treated with different regimens on the role CIN plays as a marker for improved outcomes. If CIN is a surrogate prognostic and/or potentially predictive marker of response, chemotherapy doses may need to be escalated to achieve neutropenia. In addition, instead of reducing treatment doses for safety concerns, the addition of growth factor support and alternative dosing schemes may be strategies to consider.

Systems Pharmacology Model of Gastrointestinal Damage Predicts Species Differences and Optimizes Clinical Dosing Schedules

Gastrointestinal (GI) adverse events (AEs) are frequently dose limiting for oncology agents, requiring extensive clinical testing of alternative schedules to identify optimal dosing regimens. Here, we develop a translational mathematical model to predict these clinical AEs starting from preclinical GI toxicity data. The model structure incorporates known biology and includes stem cells, daughter cells, and enterocytes. Published data, including cellular numbers and division times, informed the system parameters for humans and rats. The drug‐specific parameters were informed with preclinical histopathology data from rats treated with irinotecan. The model fit the rodent irinotecan‐induced pathology changes well. The predicted time course of enterocyte loss in patients treated with weekly doses matched observed AE profiles. The model also correctly predicts a lower level of AEs for every 3 weeks (Q3W), as compared to the weekly schedule.

Frequency-Domain Response Analysis for Quantitative Systems Pharmacology Models

Drug dosing regimen can significantly impact drug effect and, thus, the success of treatments. Nevertheless, trial and error is still the most commonly used method by conventional pharmacometric approaches to optimize dosing regimen. In this tutorial, we utilize four distinct classes of quantitative systems pharmacology models to introduce frequency-domain response analysis, a method widely used in electrical and control engineering that allows the analytical optimization of drug treatment regimen from the dynamics of the model.

A novel in vivo model for predicting myelotoxicity of chemotherapeutic agents using IL-3/GM-CSF transgenic humanized mice

Evaluating myelotoxicity is essential for ensuring the safety of novel drugs before they are approved for clinical applications. Although in vivo prediction of the maximum tolerated doses (MTDs) of anticancer drugs is usually performed in rodents, the results are not always applicable to clinical treatment because drugs may have different effects in human and rodent cells. Previously, we generated a human IL-3 and GM-CSF transgenic humanized mouse (hu-IL-3/GM Tg), in which human granulocytes effectively differentiated after hematopoietic stem cell transplantation. In this study, we established a novel in vivo preclinical evaluation model for predicting human myelotoxicity of anticancer drugs using these hu-IL-3/GM Tg mice. The myelotoxicity was investigated by kinetic flow cytometry of human or murine granulocytes and by colony-forming unit granulocyte/macrophage (CFU-GM) assays. In both in vivo and in vitro analyses, topotecan was more myelotoxic to human than murine granulocytes. In contrast, oxaliplatin was more myelotoxic to murine granulocytes. The level of myelotoxicity of paclitaxel treatment was comparable between human and mouse cells. These results demonstrate that our humanized mouse model can simultaneously evaluate myelotoxicity against human and mouse cells in vivo, and provides an effective preclinical tool for predicting appropriate doses of anticancer agents for clinical treatment.

Fractionated Dosing Improves Preclinical Therapeutic Index of Pyrrolobenzodiazepine-Containing Antibody Drug Conjugates

Purpose: To use preclinical models to identify a dosing schedule that improves tolerability of highly potent pyrrolobenzodiazepine dimers (PBDs) antibody drug conjugates (ADCs) without compromising antitumor activity.Experimental Design: A series of dose-fractionation studies were conducted to investigate the pharmacokinetic drivers of safety and efficacy of PBD ADCs in animal models. The exposure-activity relationship was investigated in mouse xenograft models of human prostate cancer, breast cancer, and gastric cancer by comparing antitumor activity after single and fractionated dosing with tumor-targeting ADCs conjugated to SG3249, a potent PBD dimer. The exposure-tolerability relationship was similarly investigated in rat and monkey toxicology studies by comparing tolerability, as assessed by survival, body weight, and organ-specific toxicities, after single and fractionated dosing with ADCs conjugated to SG3249 (rats) or SG3400, a structurally related PBD (monkeys).Results: Observations of similar antitumor activity in mice treated with single or fractionated dosing suggests that antitumor activity of PBD ADCs is more closely related to total exposure (AUC) than peak drug concentrations (C_max). In contrast, improved survival and reduced toxicity in rats and monkeys treated with a fractionated dosing schedule suggests that tolerability of PBD ADCs is more closely associated with C_max than AUC.Conclusions: We provide the first evidence that fractionated dosing can improve preclinical tolerability of at least some PBD ADCs without compromising efficacy. These findings suggest that preclinical exploration of dosing schedule could be an important clinical strategy to improve the therapeutic window of highly potent ADCs and should be investigated further. Clin Cancer Res; 23(19); 5858-68. ©2017 AACR.

Translational Modeling of Drug-Induced Myelosuppression and Effect of Pretreatment Myelosuppression for AZD5153, a Selective BRD4 Inhibitor

In this work, we evaluate the potential risk of thrombocytopenia in man for a BRD4 inhibitor, AZD5153, based on the platelet count decreases from a Han Wistar rat study. The effects in rat were modeled and used to make clinical predictions for human populations with healthy baseline blood counts. At doses >10 mg, a dose-dependent effect on circulating platelets is expected, with similar predicted changes for both q.d. and b.i.d. dose schedules. These results suggest that at predicted efficacious doses, AZD5153 is likely to have some reductions in the clinical platelet counts, but within the normal range at projected efficacious doses. The model was then extended to incorporate preexisting myelosuppression where bone marrow function is inhibited by acute myeloid leukemia. Under these conditions, duration of platelet count recovery has the potential to be prolonged due to drug-induced myelosuppression.

Modeling and Simulation Approaches for Cardiovascular Function and Their Role in Safety Assessment

Systems pharmacology modeling and pharmacokinetic-pharmacodynamic (PK/PD) analysis of drug-induced effects on cardiovascular (CV) function plays a crucial role in understanding the safety risk of new drugs. The aim of this review is to outline the current modeling and simulation (M&S) approaches to describe and translate drug-induced CV effects, with an emphasis on how this impacts drug safety assessment. Current limitations are highlighted and recommendations are made for future effort in this vital area of drug research.