Pharmacometric Models for Improved Prediction of Myelosuppression and Treatment Response in Oncology

Chemotherapy plays an important role in the treatment of cancer. However, these drugs also cause death of non-malignant cells, resulting in severe side-effects. In addition, drug resistance may exist. Predictive tools for dose and drug selection are therefore warranted. In this thesis predictive pharmacometric models were developed for the main dose-limiting side-effect, neutropenia, and for treatment response following chemotherapy. Neutropenia is associated with a high risk for life-threatening infections and leads frequently to reduced dose delivery and thereby suboptimal treatment of the tumor. A better characterization of the dynamics of docetaxel induced neutropenia was obtained by simultaneous analysis of neutrophils and leukocytes. The fraction of neutrophils was shown to change over the time-course, hence leukocytes and neutrophil counts are not interchangeable biomarkers. Sometimes neutrophil count is reported as categorical severity of neutropenia (Grade 0-4). A method was developed that allowed analysis of these data closer to its true continuous nature. The main regulatory hormone of neutrophils is granulocyte colony stimulating factor (G-CSF). Although recombinant G-CSF is used as supportive therapy to prevent neutropenia, little is known of how the endogenous G-CSF concentrations vary in patients following chemotherapy. A prospective study was carried out and simultaneous analysis of endogenous G-CSF and neutrophils following chemotherapy enabled a more mechanistic model to be developed that also could verify the self-regulatory properties of the physiological system. Patient characteristics were investigated using a pharmacokinetic-myelosuppression model for docetaxel in patients with normal and impaired liver function. The model was a useful tool in evaluating different dosing strategies and a reduced dosing scheme was suggested in patients with poor liver function, thereby enabling docetaxel treatment in this patient population which has previously been excluded. Treatment of acute myeloid leukemia with daunorubicin and cytarabine is associated with drug resistance and high variability in pharmacokinetics, which was partly explained for daunorubicin by peripheral leukocyte count. An integrated model of the in vitro drug sensitivity and treatment response showed that in vitro drug sensitivity was predictive for treatment outcome in this patient population and may therefore be used for choice of drug. The developed pharmacometric models in this thesis may be useful in the optimization of treatments schedules for existing and new drugs as well as to assist in drug and dose selection to improve therapy in an individual patient. The models and methods presented may also facilitate pooled analysis of data and demonstrate principles which could be useful for the pharmacometric community

Tumor growth inhibition modeling of individual lesion dynamics and interorgan variability in HER2-negative breast cancer patients treated with docetaxel

Information on individual lesion dynamics and organ location are often ignored in pharmacometric modeling analyses of tumor response. Typically, the sum of their longest diameters is utilized. Herein, a tumor growth inhibition model was developed for describing the individual lesion time-course data from 183 patients with metastatic HER2-negative breast cancer receiving docetaxel. The interindividual variability (IIV), interlesion variability (ILV), and interorgan variability of parameters describing the lesion time-courses were evaluated. Additionally, a model describing the probability of new lesion appearance and a time-to-event model for overall survival (OS), were developed. Before treatment initiation, the lesions were largest in the soft tissues and smallest in the lungs, and associated with a significant IIV and ILV. The tumor growth rate was 2.6 times higher in the breasts and liver, compared with other metastatic sites. The docetaxel drug effect in the liver, breasts, and soft tissues was greater than or equal to 1.2 times higher compared with other organs. The time-course of the largest lesion, the presence of at least 3 liver lesions, and the time since study enrollment, increased the probability of new lesion appearance. New lesion appearance, along with the time to growth and time-course of the largest lesion at baseline, were identified as the best predictors of OS. This tumor modeling approach, incorporating individual lesion dynamics, provided a more complete understanding of heterogeneity in tumor growth and drug effect in different organs. Thus, there may be potential to tailor treatments based on lesion location, lesion size, and early lesion response to provide better clinical outcomes

Lectin‐Like Oxidized Low‐Density Lipoprotein Receptor 1 Inhibition in Type 2 Diabetes: Phase 1 Results

Background Blockade of the lectin‐like oxidized low‐density lipoprotein receptor‐1 (LOX‐1) is a potentially attractive mechanism for lowering inflammatory and lipid risk in patients with atherosclerosis. This study aims to assess the safety, tolerability, and target engagement of MEDI6570, a high‐affinity monoclonal blocking antibody to LOX‐1. Methods and Results This phase 1, first‐in‐human, placebo‐controlled study (NCT03654313) randomized 88 patients with type 2 diabetes to receive single ascending doses (10, 30, 90, 250, or 500 mg) or multiple ascending doses (90, 150, or 250 mg once monthly for 3 months) of MEDI6570 or placebo. Primary end point was safety; secondary and exploratory end points included pharmacokinetics, immunogenicity, free soluble LOX‐1 levels, and change in coronary plaque volume. Mean age was 57.6/58.1 years in the single ascending doses/multiple ascending doses groups, 31.3%/62.5% were female, and mean type 2 diabetes duration was 9.7/8.7 years. Incidence of adverse events was similar among cohorts. MEDI6570 exhibited nonlinear pharmacokinetics, with terminal half‐life increasing from 4.6 days (30 mg) to 11.2 days (500 mg), consistent with target‐mediated drug disposition. Dose‐dependent reductions in mean soluble LOX‐1 levels from baseline were observed (>66% at 4 weeks and 71.61–82.96% at 10 weeks in the single ascending doses and multiple ascending doses groups, respectively). After 3 doses, MEDI6570 was associated with nonsignificant regression of noncalcified plaque volume versus placebo (−13.45 mm3 versus −8.25 mm3). Conclusions MEDI6570 was well tolerated and demonstrated dose‐dependent soluble LOX‐1 suppression and a pharmacokinetic profile consistent with once‐monthly dosing. Registration URL: https://clinicaltrials.gov/; Unique identifier: NCT03654313

Prediction and Modeling of Effects on the QTc Interval for Clinical Safety Margin Assessment, Based on Single-Ascending-Dose Study Data with AZD3839

Corrected QT interval (QTc) prolongation in humans is usually predictable based on results from preclinical findings. This study confirms the signal from preclinical cardiac repolarization models (human ether-a-go-go-related gene, guinea pig mono-phasic action potential, and dog telemetry) on the clinical effects on the QTc interval. A thorough QT/QTc study is generally required for bioavailable pharmaceutical compounds to de-termine whether or not a drug shows a QTc effect above a threshold of regulatory interest. However, as demonstrated in this AZD3839 [(S)-1-(2-(difluoromethyl)pyridin-4-yl)-4-fluoro-1-(3-(pyrimidin-5-yl)phenyl)-1H-isoindol-3-amine hemifumarate] single-ascending-dose (SAD) study, high-resolution digital electrocardiogram data, in combination with adequate efficacy biomarker and pharmacokinetic data and nonlinear mixe

A pharmacometric analysis of patient-reported outcomes in breast cancer patients through item response theory

Purpose An item response theory (IRT) pharmacometric framework is presented to characterize Functional Assessment of Cancer Therapy-Breast (FACT-B) data in locally-advanced or metastatic breast cancer patients treated with ado-trastuzumab emtansine (T-DM1) or capecitabine-plus-lapatinib. Methods In the IRT model, four latent well-being variables, based on FACT-B general subscales, were used to describe the physical, social/family, emotional and functional well-being. Each breast cancer subscale item was reassigned to one of the other subscales. Longitudinal changes in FACT-B responses and covariate effects were investigated. Results The IRT model could describe both item-level and subscale-level FACT-B data. Non-Asian patients showed better baseline social/family and functional well-being than Asian patients. Moreover, patients with Eastern Cooperative Oncology Group performance status of 0 had better baseline physical and functional well-being. Well-being was described as initially increasing or decreasing before reaching a steady-state, which varied substantially between patients and subscales. T-DM1 exposure was not related to any of the latent variables. Physical well-being worsening was identified in capecitabine-plus-lapatinib-treated patients, whereas T-DM1-treated patients typically stayed stable. Conclusion The developed framework provides a thorough description of FACT-B longitudinal data. It acknowledges the multi-dimensional nature of the questionnaire and allows covariate and exposure effects to be evaluated on responses