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Osimertinib is a third-generation, irreversible, oral EGFR tyrosine kinase inhibitor (TKI) recommended as first-line treatment for patients with locally advanced/metastatic EGFR mutation–positive (EGFRm) non–small cell lung cancer (NSCLC). However, MET amplification/overexpression is a common acquired osimertinib resistance mechanism. Savolitinib is an oral, potent, and highly selective MET-TKI; preliminary data suggest that combining osimertinib with savolitinib may overcome MET-driven resistance. A patient-derived xenograft (PDX) mouse model with EGFRm, MET-amplified NSCLC was tested with a fixed osimertinib dose [10 mg/kg for exposures equivalent to (≈)80 mg], combined with doses of savolitinib (0–15 mg/kg, ≈0–600 mg once daily), both with 1-aminobenzotriazole (to better match clinical half-life). After 20 days of oral dosing, samples were taken at various time points to follow the time course of drug exposure in addition to phosphorylated MET and EGFR (pMET and pEGFR) change. Population pharmacokinetics, savolitinib concentration versus percentage inhibition from baseline in pMET, and the relationship between pMET and tumor growth inhibition (TGI) were also modeled. As single agents, savolitinib (15 mg/kg) showed significant antitumor activity, reaching ∼84% TGI, and osimertinib (10 mg/kg) showed no significant antitumor activity (34% TGI, P > 0.05 vs. vehicle). Upon combination, at a fixed dose of osimertinib, significant savolitinib dose-related antitumor activity was shown, ranging from 81% TGI (0.3 mg/kg) to 84% tumor regression (15 mg/kg). Pharmacokinetic–pharmacodynamic modeling showed that the maximum inhibition of both pEGFR and pMET increased with increasing savolitinib doses. Savolitinib demonstrated exposure-related combination antitumor activity when combined with osimertinib in the EGFRm MET-amplified NSCLC PDX model.

Acalabrutinib, a selective Bruton tyrosine kinase inhibitor, is approved for the treatment of mantle cell lymphoma and chronic lymphocytic leukaemia. Many critically ill patients are unable to swallow and need oral medications to be delivered via a nasogastric (NG) tube. Furthermore, critically ill patients are typically administered proton-pump inhibitors (PPIs) to prevent stress ulcers. Concomitant administration with PPIs reduces acalabrutinib exposure and is not currently recommended. To evaluate acalabrutinib in subjects co-administered with PPIs who require NG delivery, a phase 1, open-label, randomized, crossover, single-dose study was conducted in healthy subjects.The study assessed the relative bioavailability of an acalabrutinib suspension-in regular, degassed Coca-Cola-administered via NG tube (Acala-NG) versus the pharmacokinetics (PK) of an acalabrutinib capsule administered orally with water. In addition, the PPI effect was evaluated by comparing the PK following Acala-NG in the presence or absence of rabeprazole.Exposure of acalabrutinib and its active metabolite (ACP-5862) were comparable following administration of Acala-NG versus the oral capsule (Geo mean ratio, % ref [90% confidence interval, CI]: acalabrutinib AUCAcala-NG with or without a PPI is safe and well-tolerated without impeding bioavailability.

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Osimertinib is a third-generation, irreversible, oral EGFR tyrosine kinase inhibitor (TKI) recommended as first-line treatment for patients with locally advanced/metastatic EGFR mutation–positive (EGFRm) non–small cell lung cancer (NSCLC). However, MET amplification/overexpression is a common acquired osimertinib resistance mechanism. Savolitinib is an oral, potent, and highly selective MET-TKI; preliminary data suggest that combining osimertinib with savolitinib may overcome MET-driven resistance.A patient-derived xenograft (PDX) mouse model with EGFRm, MET-amplified NSCLC was tested with a fixed osimertinib dose [10 mg/kg for exposures equivalent to (≈)80 mg], combined with doses of savolitinib (0–15 mg/kg, ≈0–600 mg once daily), both with 1-aminobenzotriazole (to better match clinical half-life). After 20 days of oral dosing, samples were taken at various time points to follow the time course of drug exposure in addition to phosphorylated MET and EGFR (pMET and pEGFR) change. Population pharmacokinetics, savolitinib concentration versus percentage inhibition from baseline in pMET, and the relationship between pMET and tumor growth inhibition (TGI) were also modeled.As single agents, savolitinib (15 mg/kg) showed significant antitumor activity, reaching ∼84% TGI, and osimertinib (10 mg/kg) showed no significant antitumor activity (34% TGI, P > 0.05 vs. vehicle). Upon combination, at a fixed dose of osimertinib, significant savolitinib dose-related antitumor activity was shown, ranging from 81% TGI (0.3 mg/kg) to 84% tumor regression (15 mg/kg). Pharmacokinetic–pharmacodynamic modeling showed that the maximum inhibition of both pEGFR and pMET increased with increasing savolitinib doses.Savolitinib demonstrated exposure-related combination antitumor activity when combined with osimertinib in the EGFRm MET-amplified NSCLC PDX model.

Aims Examine relationships between the systemic exposure of acalabrutinib, a highly selective, next-generation Bruton tyrosine kinase inhibitor, and its active metabolite (ACP-5862) vs. efficacy and safety responses in patients with B-cell malignancies who received acalabrutinib as monotherapy or in combination with obinutuzumab. Methods For exposure-efficacy analyses, patients with untreated chronic lymphocytic leukaemia were assessed for best overall response, progression-free survival and tumour regression. For exposure-safety analyses, incidences of grade ≥2 adverse events (AEs), grade ≥3 AEs and grade ≥2 events of clinical interest were assessed in patients with B-cell malignancies. Acalabrutinib and ACP-5862 pharmacokinetic (PK) parameter estimates were obtained from population PK modelling. Exposure calculations were based on study dosing regimens. Total active moieties were calculated to account for contributions of ACP-5862 to overall efficacy/safety. Results A total of 573 patients were included (exposure-efficacy analyses, n = 274; exposure-safety analyses, n = 573). Most patients (93%) received acalabrutinib 100 mg twice daily. Median total active area under the concentration-time curve (AUC24h,ss ) and total active maximal concentration at steady-state (Cmax,ss ) were similar for patients who received acalabrutinib as monotherapy or in combination with obinutuzumab, and for responders and nonresponders. No relationship was observed between AUC24h,ss /Cmax,ss and progression-free survival or tumour regression. Acalabrutinib AUC24h,ss and Cmax,ss were generally comparable across groups regardless of AE incidence. Conclusion No clinically meaningful correlations between acalabrutinib PK exposure and efficacy and safety outcomes were observed. These data support the fixed acalabrutinib dose of 100 mg twice daily in the treatment of patients with B-cell malignancies.

Selumetinib (ARRY-142886), an oral, potent and highly selective allosteric mitogen-activated protein kinase kinase 1/2 inhibitor, is approved by the US Food and Drug Administration for the treatment of pediatric patients aged ≥2 years with neurofibromatosis type 1 with symptomatic, inoperable plexiform neurofibromas. A physiologically based pharmacokinetic (PBPK) model was constructed to predict plasma concentration-time profiles of selumetinib, and to evaluate the impact of coadministering moderate cytochrome P450 (CYP) 3A4/2C19 inhibitors/inducers. The model was also used to extrapolate pharmacokinetic exposures from older children with different body surface area to guide dosing in younger children. This model was built based on physiochemical data and clinical in vivo drug-drug interaction (DDI) studies with itraconazole and fluconazole, and verified against data from an in vivo rifampicin DDI study and an absolute bioavailability study. The pediatric model was updated by changing system-specific input parameters using the Simcyp pediatric module. The model captured the observed selumetinib pharmacokinetic profiles and the interactions with CYP inhibitors/inducers. The predictions from the PBPK model showed a DDI effect of 30% to 40% increase or decrease in selumetinib exposure when coadministered with moderate CYP inhibitors or inducers, respectively, which was used to inform dose management and adjustments. The pediatric PBPK model was applied to simulate exposures in specific body surface area brackets that matched those achieved with a 25 mg/m2 dose in SPRINT clinical trials. The pediatric PBPK model was used to guide the dose for younger patients in a planned pediatric clinical study.

Selumetinib (ARRY-142886) is a potent, selective, MEK1/2 inhibitor approved in the US for the treatment of children (≥ 2 years) with neurofibromatosis type 1 (NF1) and symptomatic, inoperable plexiform neurofibromas (PN). We characterized population pharmacokinetics (PK) of selumetinib and its active N‐desmethyl metabolite, evaluated exposure–safety/efficacy relationships, and assessed the proposed therapeutic dose of 25 mg/m2 bid based on body surface area (BSA) in this patient population. Population PK modeling and covariate analysis (demographics, formulation, liver enzymes, BSA, patients/healthy volunteers) were based on pooled PK data from adult healthy volunteers (n = 391), adult oncology patients (n = 83) and pediatric patients with NF1-PN (n = 68). Longitudinal selumetinib/metabolite exposures were predicted with the final model. Exposure–safety/efficacy analyses were applied to pediatric patients (dose levels: 20, 25, 30 mg/m2 bid). Selumetinib and metabolite concentration–time courses were modeled using a joint compartmental model. Typical selumetinib plasma clearance was 11.6 L/h (95% CI 11.0–12.2 L/ h). Only BSA had a clinically relevant (> 20%) impact on exposure, supporting BSA-based administration in children. Selumetinib and metabolite exposures in responders (≥ 20% PN volume decrease from baseline) and non-responders were largely overlapping, with medians numerically higher in responders. No clear relationships between exposure and safety events were established; exposure was not associated with key adverse events (AEs) including rash acneiform, diarrhea, vomiting, and nausea. Findings support continuous selumetinib 25 mg/m2 bid in pediatric patients. Importantly, the updated dosing nomogram ensures that patients will receive a clinically active, yet tolerable, dose regardless of differences in BSA and allows dose reductions, if necessary.

Acalabrutinib is a Bruton tyrosine kinase (BTK) inhibitor approved to treat adults with chronic lymphocytic leukemia, small lymphocytic lymphoma, or previously treated mantle cell lymphoma. As the bioavailability of the acalabrutinib capsule (AC) depends on gastric pH for solubility and is impaired by acid-suppressing therapies, coadministration with proton-pump inhibitors (PPIs) is not recommended. Three studies in healthy subjects (N = 30, N = 66, N = 20) evaluated the pharmacokinetics (PKs), pharmacodynamics (PDs), safety, and tolerability of acalabrutinib maleate tablet (AT) formulated with pH-independent release. Subjects were administered AT or AC (orally, fasted state), AT in a fed state, or AT in the presence of a PPI, and AT or AC via nasogastric (NG) route. Acalabrutinib exposures (geometric mean [% coefficient of variation, CV]) were comparable for AT versus AC (AUC

Clinical development is the scientific process of exploring and confirming the product attributes and therapeutic role of potential new medical treatments. This chapter provides an overview of the clinical development of a pharmaceutical product for medical use, introducing and discussing the principles of clinical development and application of those principles on both a programmatic and a study level. While the development process is continuous, beginning during the discovery of an innovative potential pharmaceutical product and ending with the replacement of the innovative pharmaceutical by a more effective or safer alternative treatment, the process follows an orderly path of evidence-based, goal-directed development. This chapter focuses on the clinical development and registration of an innovative pharmaceutical product in the treatment of patients or of an additional indication for an existing pharmaceutical product.

Missing data is a universal problem in analysing Real-World Evidence (RWE) datasets. In RWE datasets, there is a need to understand which features best correlate with clinical outcomes. In this context, the missing status of several biomarkers may appear as gaps in the dataset that hide meaningful values for analysis. Imputation methods are general strategies that replace missing values with plausible values. Using the Flatiron NSCLC dataset, including more than 35,000 subjects, we compare the imputation performance of six such methods on missing data: predictive mean matching, expectation-maximisation, factorial analysis, random forest, generative adversarial networks and multivariate imputations with tabular networks. We also conduct extensive synthetic data experiments with structural causal models. Statistical learning from incomplete datasets should select an appropriate imputation algorithm accounting for the nature of missingness, the impact of missing data, and the distribution shift induced by the imputation algorithm. For our synthetic data experiments, tabular networks had the best overall performance. Methods using neural networks are promising for complex datasets with non-linearities. However, conventional methods such as predictive mean matching work well for the Flatiron NSCLC biomarker dataset.

Missing data is a universal problem in analysing Real-World Evidence (RWE) datasets. In RWE datasets, there is a need to understand which features best correlate with clinical outcomes. In this context, the missing status of several biomarkers may appear as gaps in the dataset that hide meaningful values for analysis. Imputation methods are general strategies that replace missing values with plausible values. Using the Flatiron NSCLC dataset, including more than 35,000 subjects, we compare the imputation performance of six such methods on missing data: predictive mean matching, expectation-maximisation, factorial analysis, random forest, generative adversarial networks and multivariate imputations with tabular networks. We also conduct extensive synthetic data experiments with structural causal models. Statistical learning from incomplete datasets should select an appropriate imputation algorithm accounting for the nature of missingness, the impact of missing data, and the distribution shift induced by the imputation algorithm. For our synthetic data experiments, tabular networks had the best overall performance. Methods using neural networks are promising for complex datasets with non-linearities. However, conventional methods such as predictive mean matching work well for the Flatiron NSCLC biomarker dataset.

AIMS Concentration-QT modelling (C-QTc) of first-in-human data has been rapidly adopted as the primary evaluation of QTc interval prolongation risk. Here, we evaluate the performance of C-QTc in early oncology settings (i.e., patients, no placebo or supratherapeutic dose, 3 + 3 designs). METHODS C-QTc performance was evaluated across three oncology scenarios using a simulation-estimation approach: (scen1) typical dose-escalation testing six dose levels (n = 21); (scen2) small dose-escalation testing two dose levels (n = 9); (scen3) expansion cohorts at one dose level (n = 6-140). True ΔΔQTc effects ranged from 3 ms ("no effect") to 20 ms ("large effect"). Performance was assessed based on the upper limit of the ΔQTc two-sided 90% CI against a threshold of 10 or 20 ms. RESULTS The performance against the 10 ms threshold was limited based on C-QTc data from typical dose escalation (scen1) and acceptable performance was observed only for relatively large expansions (n ≥ 45; scen3). Performance against the 20 ms threshold was acceptable based on C-QTc data from a typical dose escalation (scen1) or dose expansion cohort n > 10 (scen3). In general, pooling C-QTc data from dose escalation and expansion cohorts substantially improved the performance and reduced the ΔQTc 90% CI width. CONCLUSION C-QTc performance appeared limited using a 10 ms threshold, but acceptable against a 20 ms threshold. Selection of threshold may be informed by the benefit-risk balance in a specific disease area. Acceptable precision (i.e., confidence intervals) of the estimated ΔQTc, regardless of its magnitude, can be facilitated by pooling data from dose escalation and expansion cohorts.

This analysis aimed to describe the pharmacokinetics (PK) of acalabrutinib and its active metabolite, ACP-5862. A total of 8935 acalabrutinib samples from 712 subjects and 2394 ACP-5862 samples from 304 subjects from 12 clinical studies in patients with B-cell malignancies and healthy subjects were analyzed by non-linear mixed-effects modelling. Acalabrutinib PK was characterized by a two-compartment model with first-order elimination. The large variability in absorption was adequately described by transit compartment chain and first-order absorption, with between-occasion variability on the mean transit time and relative bioavailability. The PK of ACP-5862 was characterized by a two-compartment model with first-order elimination, and the formation rate was defined as the acalabrutinib clearance multiplied by the fraction metabolized. Health status, Eastern Cooperative Oncology Group performance status, and co-administration of proton pump inhibitors were significant covariates. However, none of the investigated covariates led to clinically meaningful changes in exposure, supporting a flat dosing of acalabrutinib.

The International Conference on Harmonisation (ICH) E14 guidance provides recommendations to assess the potential of a drug to delay cardiac repolarization (QT prolongation), including general guidelines for cases in which a conventional thorough QT study (TQT) might not be feasible. These guidelines have been updated through the ICH question-and-answer process, with the last revision in 2015. We conducted a comprehensive analysis of QT prolongation evaluation of small-molecule new drug applications (NDAs) approved in oncology between 2011 and 2019 to extract learning experience. The following information was analysed: (1) methods to assess QT prolongation, (2) electrocardiogram data collection, (3) QT-related label language, and (4) postmarketing requirements. Overall, every NDA included a QT assessment. The concentration-QTc modeling approach (studies in which QT was not the primary objective) was the most common approach (59%), followed by the TQT and the dedicated QT studies (20% and 21%, respectively). The quality and quantity of the QT assessments were different across NDAs, which suggested relatively large flexibility in the designs and approaches to characterizing QT liability. The QT-related label language reflected the QT results, but also the safety events and the study design limitations because of the oncology settings. There was no delay in approval because of less robust QTc studies as long as the benefit-to-risk ratio of the drug was acceptable, and the implications were reflected in the label. This work offers a structured understanding of the QT evaluation criteria by the Food and Drug Administration and can assist in planning QT prolongation assessments in oncology settings.

Olaparib is a poly ADP-ribose polymerase inhibitor that induces synthetic lethality in tumors with deficient homologous recombination repair. Population exposure-response analyses were performed to evaluate the efficacy and safety of olaparib exposure in patients with cancer. Data from multiple phase I/II/III clinical studies from both capsule and tablet formulations were combined for efficacy (N = 410) and safety (N = 757) analyses. Exposure-progression-free survival (Cox proportional hazards model indicated that a 300 mg b.i.d. tablet was statistically superior to the 200 mg b.i.d. tablet dose (hazard ratio of 0.96), although the difference was small. Exposure-safety logistic regression models and hemoglobin models predicted similar probability of safety events or hemoglobin decrease with largely overlapping 95% confidence intervals at 300 mg b.i.d. tablet, 200 mg b.i.d. tablet, and 400 mg b.i.d. capsule. The analyses provided key assessments to support the approval of olaparib 300 mg tablet therapeutic dose in patients with ovarian and breast cancer, regardless of their breast cancer (BRCA) mutation status.

A prospective, multicenter, large-scale cohort with a nested case–control study (NCT00252759) was conducted to identify and quantify risk factors for interstitial lung disease (ILD) in Japanese patients with non-small-cell lung cancer who received gefitinib. This study reports the association between gefitinib exposure and the occurrence of ILD. A total of 1891 gefitinib plasma concentrations from 336 patients were measured after first dose, at steady state, and at time of ILD occurrence. Influences of demographic and pathophysiological factors on pharmacokinetics were investigated by non-linear mixed-effect modeling. The exposure to gefitinib was compared between patients without and with ILD occurrence to explore risks associated with gefitinib-induced ILD. Intra-patient comparison of exposure was also conducted between times at ILD development and normal states. In the population pharmacokinetic analysis for gefitinib, α1-acid glycoprotein (AGP), age, body weight, and concomitant use of cytochrome P450 3A4 inducers were significant covariates on oral clearance (CL/F). AGP and body weight were also identified as factors affecting the volume of distribution. CL/F was significantly lower at the time of ILD occurrence than normal states. Patients who developed ILD tended to show higher exposure to gefitinib than those without ILD; however, these differences were not statistically significant. On the other hand, exposure at the time of ILD occurrence was significantly elevated compared to the time of normal state within the same patients. Significant elevation of exposure of gefitinib was observed at the time of ILD occurrence, suggesting reduction of CL/F could be associated with ILD-induced AGP elevation. Increase in exposure of gefitinib is unlikely to be a robust predictor of ILD and does not warrant any dose modifications.

Selumetinib (AZD6244, ARRAY-142886) is a mitogen-activated protein kinase kinase inhibitor that has been tested for treatment of non-small cell lung cancer (NSCLC). Selumetinib (75 mg twice daily) plus docetaxel in patients with advanced NSCLC has been assessed in phase 2 (SELECT-2) and phase 3 (SELECT-1) clinical trials. The objective of the current analysis was to investigate the exposure-response relationship of selumetinib in these 2 clinical trials, based on the development of a population pharmacokinetic (PopPK) model for selumetinib and its active metabolite, N-desmethyl selumetinib, in patients with NSCLC. A PopPK model using data from seven phase 1 studies was first developed and served as prior information for the development of the patient PopPK model. The pharmacokinetics (PK) of selumetinib and N-desmethyl selumetinib were modeled simultaneously. A two-compartment model with zero-first order absorption and first-order elimination reasonably described the selumetinib PK. The N-desmethyl metabolite of selumetinib was described by a one-compartment model with first-order elimination. The final PK parameter estimates were similar between patients with NSCLC and patients in the phase 1 population. Selumetinib apparent clearance and central volume of distribution were 11.9 L/h and 32.1 L, respectively, in patients. Individual selumetinib exposure metrics were estimated to investigate the correlation between exposure and efficacy/safety endpoints observed in NSCLC studies. There was no significant difference in progression-free survival (the primary endpoint) among the different quartiles of exposure. Similarly, no significant correlation was observed between selumetinib exposure and other secondary efficacy or safety endpoints. The conclusions are in accordance with the reported clinical findings.

Drugs can affect the cardiovascular (CV) system either as an intended treatment or as an unwanted side effect. In both cases, drug-induced cardiotoxicities such as arrhythmia and unfavourable hemodynamic effects can occur, and be described using mathematical models; such a model informed approach can provide valuable information during drug development and can aid decision-making. However, in order to develop informative models, it is vital to understand CV physiology. The aims of this tutorial are to present (1) key background biological and medical aspects of the CV system, (2) CV electrophysiology, (3) CV safety concepts, (4) practical aspects of development of CV models and (5) regulatory expectations with a focus on using model informed and quantitative approaches to support nonclinical and clinical drug development. In addition, we share several case studies to provide practical information on project strategy (planning, key questions, assumptions setting, and experimental design) and mathematical models development that support decision-making during drug discovery and development.

Introduction: Acalabrutinib (Calquence ®), a selective Bruton tyrosine kinase (BTK) inhibitor, is approved for the treatment of mantle cell lymphoma (relapsed/refractory) and chronic lymphocytic leukemia. Patients with hematologic malignancies may require acid-reducing agents (including proton pump inhibitors [PPIs]) for the treatment of gastroesophageal reflux or peptic ulcer disease. The solubility of acalabrutinib is reduced with increasing pH; concomitant administration of acalabrutinib capsules with PPIs reduces acalabrutinib exposure and is currently not recommended. Additionally, many cancer patients are unable to swallow capsules and require alternative methods to deliver acalabrutinib, such as a suspension administered orally or via a nasogastric (NG) tube. To enable the use of acalabrutinib in patients who require co-treatment with PPIs and/or are unable to swallow capsules, a new maleate salt of acalabrutinib, formulated as an immediate-release film-coated tablet (acalabrutinib maleate tablet [AMT]), has been developed which shows fast and complete in vitro release at all physiologic pH. We evaluated the pharmacokinetics (PK), pharmacodynamics (PD), safety, and tolerability of AMT administered orally or via NG tube in the presence or absence of a PPI. In addition, the effect of food on AMT was evaluated to confirm the absence of a clinically relevant impact, consistent with acalabrutinib capsules. Methods: Three Phase 1, open-label, single-dose, cross-over studies were conducted in healthy subjects to establish PK similarity (bioequivalence) between 100-mg AMT and 100-mg acalabrutinib capsules (N=66); evaluate PPI effect by comparing PK of 100-mg AMT administered in the presence vs absence of rabeprazole (PPI; N=14); evaluate food effect by comparing PK of 100-mg AMT administered with a high-fat diet vs fasted (N=16); and assess PK following administration of 100-mg acalabrutinib maleate suspension (in 15 mL water) delivered via NG tube, in the presence vs absence of rabeprazole (N=20). PD was assessed by measuring BTK target occupancy (BTK-TO) in peripheral blood mononuclear cells across all treatment arms and studies. Results: Exposure geometric mean ratios and 90% confidence intervals (CIs) are shown in Table 1 with the PK profiles shown in Figure 1. Systemic exposures (C max and AUC) of acalabrutinib and its major pharmacologically active metabolite, ACP-5862, between AMT and acalabrutinib capsules were bioequivalent ( Conclusions: Acalabrutinib maleate, administered as a tablet or suspension, is safe and well tolerated. Based on the PK (and associated variability), BTK-TO, and established exposure-efficacy/safety relationship, AMT clinical effect is expected to be comparable to acalabrutinib capsules at the approved 100-mg BID dosing, regardless of use of PPIs and ingestion of food. Additionally, AMT improves swallowing ability given the film coating and a 50% reduced volume compared with the capsule, and can be easily suspended in a small amount of water to allow dosing in patients unable to swallow tablets. Figure 1 Figure 1. Disclosures Sharma: AstraZeneca: Current Employment, Current equity holder in publicly-traded company, Divested equity in a private or publicly-traded company in the past 24 months. Pepin: AstraZeneca: Current Employment. Burri: AstraZeneca: Current Employment, Divested equity in a private or publicly-traded company in the past 24 months. Zheng: AstraZeneca: Current Employment; Kite Pharma, a Group of Gilead: Ended employment in the past 24 months; Gilead Science Inc., AstraZeneca: Current equity holder in publicly-traded company; Gilead Science Inc.: Divested equity in a private or publicly-traded company in the past 24 months. Kuptsova-Clarkson: AstraZeneca: Current Employment, Current equity holder in publicly-traded company; AbbVie: Current holder of individual stocks in a privately-held company. de Jong: Acerta Pharma B.V. (A Member of the AstraZeneca Group): Current Employment. Yu: AstraZeneca: Current Employment; EMD Serono Research Institute: Ended employment in the past 24 months; AstraZeneca, Johnson and Johnson, AbbVie, Abbott: Current equity holder in publicly-traded company; Merck KGaA: Divested equity in a private or publicly-traded company in the past 24 months. MacArthur: AstraZeneca: Current Employment, Current holder of individual stocks in a privately-held company, Current holder of stock options in a privately-held company. Majewski: AstraZeneca: Current Employment, Current equity holder in publicly-traded company. Ware: AstraZeneca: Current equity holder in publicly-traded company; Denali (DNLI) Therapeutics: Current equity holder in publicly-traded company. Mann: AstraZeneca: Current Employment, Current equity holder in publicly-traded company. Ramies: AstraZeneca: Consultancy. Munugalavadla: AstraZeneca: Current Employment, Current equity holder in publicly-traded company. Sheridan: AstraZeneca: Current Employment, Current equity holder in publicly-traded company. Tomkinson: AstraZeneca: Current Employment, Current equity holder in publicly-traded company. OffLabel Disclosure: New Formulation

Modelingsimulation (MS) methodologies are established quantitative tools, which have proven to be useful in supporting the research, development (RD), regulatory approval, and marketing of novel therapeutics. Applications of MS help design efficient studies and interpret their results in context of all available data and knowledge to enable effective decision-making during the RD process. In this mini-review, we focus on two sets of modeling approaches: population-based models, which are well-established within the pharmaceutical industry today, and fall under the discipline of clinical pharmacometrics (PMX); and systems dynamics models, which encompass a range of models of (patho-)physiology amenable to pharmacological intervention, of signaling pathways in biology, and of substance distribution in the body (today known as physiologically-based pharmacokinetic models) - which today may be collectively referred to as quantitative systems pharmacology models (QSP). We next describe the convergence - or rather selected integration - of PMX and QSP approaches into 'middle-out' drug-disease models, which retain selected mechanistic aspects, while remaining parsimonious, fit-for-purpose, and able to address variability and the testing of covariates. We further propose development opportunities for drug-disease systems models, to increase their utility and applicability throughout the preclinical and clinical spectrum of pharmaceutical RD.

Background Combinations of molecularly targeted agents may provide optimal anti-tumor activity and improve clinical outcomes for patients with advanced cancers. Selumetinib (AZD6244, ARRY-142886) is an oral, potent and highly selective, allosteric inhibitor of MEK1/2, a component of the RAS/RAF/MEK/ERK pathway which is constitutively activated in many cancers. We investigated the safety, tolerability, and pharmacokinetics (PK) of selumetinib in combination with molecularly targeted drugs erlotinib or temsirolimus in patients with advanced solid tumors. Methods Two-part study: dose escalation, to determine the maximum tolerated dose (MTD) of selumetinib in combination with erlotinib 100 mg once daily (QD) or temsirolimus 25 mg once weekly, followed by dose expansion at the respective combination MTDs to further investigate safety and anti-tumor effects. Results 48 patients received selumetinib plus erlotinib and 32 patients received selumetinib plus temsirolimus. The MTD with erlotinib 100 mg QD was selumetinib 100 mg QD, with diarrhea being dose limiting. The most common all grade adverse events (AEs): diarrhea, rash, nausea, and fatigue. Four (8.3%) patients had ≥12 weeks stable disease. The MTD with temsirolimus 25 mg once weekly was selumetinib 50 mg twice daily (BID), with mucositis and neutropenia being dose limiting. The most commonly reported AEs: nausea, fatigue, diarrhea, and mucositis. Ten (31.3%) patients had ≥12 weeks stable disease. The combination PK profiles were comparable to previously observed monotherapy profiles. Conclusions MTDs were established for selumetinib in combination with erlotinib or temsirolimus. Overlapping toxicities prevented the escalation of selumetinib to its recommended phase II monotherapy dose of 75 mg BID. Trial registration: ClinicalTrials.gov NCT00600496; registered 8 July 2009.

This open-label, randomized, phase 1 crossover study investigated the effect of elevated gastric pH level (>5) on the relative bioavailability and pharmacokinetic profile of the epidermal growth factor receptor tyrosine kinase inhibitor gefitinib. Healthy male volunteers (n = 26) were randomized to gefitinib 250 mg (fasted), either alone on day 1 (unmodified gastric pH) or 1 hour following the second of 2 oral doses of the H2 -receptor antagonist ranitidine 450 mg (elevated gastric pH). After a 3-week washout period, volunteers crossed to the other treatment. The geometric least-squares (GLS) mean AUC0-∞ and Cmax for gefitinib were reduced by 47% and 71%, respectively, under conditions of sustained elevated gastric pH; for both parameters, the 90%CI for the ratio of the GLS means lay below the prespecified lower limit. Median tmax was delayed from 5 to 6 hours. Mean t1/2 was similar under both gastric pH conditions. No serious adverse events were reported. The bioavailability of a single oral gefitinib 250-mg dose was reduced by approximately 50% when gefitinib was administered under conditions of sustained elevated gastric pH.

Circulating tumor DNA is released into the bloodstream from tumors and can reflect both intra-tumor heterogeneity and clonal evolution.1 As ctDNA levels are thought to reflect tumor burden, a decrease in ctDNA while on therapy may suggest treatment efficacy.2 We assessed whether longitudinal changes in ctDNA could supplement or improve RECIST-based measures for decision making during drug development. Plasma samples collected at regular intervals were analyzed to predict the risk of disease progression in patients with EGFRm (Ex19del or L858R) advanced NSCLC following initiation of first-line EGFR tyrosine kinase inhibitor (TKI) treatment in the FLAURA study (NCT02296125). Of 556 patients who received treatment (osimertinib 80 mg daily [QD] or comparator EGFR-TKI [gefitinib 250 mg QD or erlotinib 150 mg QD]), 353 (63%) had an available sample with detectable levels of ctDNA at baseline. Patients with both imaging and ctDNA samples at baseline and 3 additional timepoints (n=320, the analysis set) were divided (as implemented in caret R package)3 into training (n=259) and validation (n=61) cohorts. Clinical data from these patients (data cut-off: June 12 2017) were used to fit joint models of either ctDNA dynamics or sum of the longest tumor diameters (SLD) and progression-free survival (PFS). Longitudinal ctDNA levels were measured using droplet digital PCR (ddPCR; Biodesix®) for EGFR-TKI sensitizing mutations (Ex19del or L858R) in all available samples. Model covariates were selected based on their statistical significance for the longitudinal and hazard sub-models and were analyzed using JMbayes package as implemented in R software (3.5.1). Our analysis indicates that the joint model can independently characterize changes in ctDNA and SLD and can predict PFS in the validation cohort, using only ctDNA changes occurring within 6 weeks from the initiation of therapy. Similarly, in the training cohort, joint modelling indicates that the relationship between SLD and PFS using RECIST is consistent with the longitudinal ctDNA analysis. In the analysis set, our model estimated a PFS of 16.6 months (95% confidence interval [CI] 12.1, NC) for osimertinib (n=153) and 9.4 months (95% CI 8.0, 13.5) for comparator EGFR-TKI (n=167). Model-predicted PFS probability using either ctDNA or SLD data was similar, suggesting ctDNA dynamics may provide similar information to RECIST for clinical decision making. Based on this analysis, ctDNA dynamics could be utilized to predict RECIST-defined progression for decision making during drug development of treatments for patients with NSCLC.References: 1. Stewart CM, et al. J Pathol 2018;244(5):616-27 2. Herbreteau G, et al. J Thorac Dis 2019;11(Suppl 1):S113-26 3. R Core Team (2019). https://www.R-project.org/. Accessed Jan 27, 2020 Citation Format: Karthick Vishwanathan, James Dunyak, Philip Overend, Ryan Hartmaier, Aleksandra Markovets, Juliann Chmielecki, Ganesh Mugundu, Carl Barrett, Helen Tomkinson, Martin Johnson. Utility of longitudinal circulating tumor DNA (ctDNA) modeling to predict RECIST-defined progression in first-line patients with epidermal growth factor receptor mutation-positive (EGFRm) advanced non-small cell lung cancer (NSCLC) [abstract]. In: Proceedings of the Annual Meeting of the American Association for Cancer Research 2020; 2020 Apr 27-28 and Jun 22-24. Philadelphia (PA): AACR; Cancer Res 2020;80(16 Suppl):Abstract nr CT024.

Olaparib is a first-in-class potent oral poly(ADP-ribose) polymerase inhibitor. The aims of this analysis were to establish an integrated population pharmacokinetic (PK) model of olaparib in patients with solid tumors and to bridge the PK of olaparib between capsule and tablet formulations. The population PK model was developed using plasma concentration data from 659 patients in 11 phase I, II, and III studies of olaparib tablets/capsules monotherapy. Relative bioavailability between the tablet and capsule formulations was estimated and the relative exposure between olaparib tablet and capsule therapeutic doses was further assessed. The concentration–time profile was described using a two-compartment model with sequential zero- and first-order absorption and first-order elimination for both capsules and tablets with different absorption parameters. Multiple-dose clearance compared with single-dose clearance was reduced by approximately 15% (auto-inhibition). Disease severity had an impact on olaparib clearance, and tablet strength had an impact on Ka. The olaparib geometric mean area under the curve (AUC) and maximal concentration (Cmax) following a single 300 mg tablet were 42.1 μg h/mL and 5.8 μg/mL, respectively, and the steady-state geometric mean AUC and Cmax following a 300 mg tablet twice daily were 49.0 μg h/mL and 7.7 μg/mL, respectively. The relative exposure (AUC) of the 300 mg tablet formulation is 13% higher than the 400 mg capsule formulation. This analysis bridged the olaparib capsule and tablet formulation PK and provided key assessment to support the approval of the olaparib tablet formulation in patients with ovarian cancer, regardless of their BRCA mutation status.

Evaluation of the effect of food on the pharmacokinetics of oral oncology drugs is critical to drug development, as food can mitigate or exacerbate toxicities and alter systemic exposure. Our aim is to expand on current US Food and Drug Administration (FDA) guidance and provide data-driven food-effect study design recommendations specific to the oncology therapeutic area. Data for recently approved small-molecule oncology drugs was extracted from the clinical pharmacology review in the sponsor's FDA submission package. Information on subject selection, meal types, timing of the study relative to the pivotal trial, and study outcomes was analyzed. The number of subjects enrolled ranged from 12 to 60, and the majority of studies (19 of 29) were conducted in healthy volunteers. Using AstraZeneca cost data, healthy volunteer studies were estimated to cost 10-fold less than cancer patient studies. Nine of 29 (31%) studies included meals with multiple levels of fat content. Analysis of a subset of 16 drugs revealed that final results for the food-effect study were available before the start of the pivotal trial for only 2 drugs. Conducting small food-effect studies powered to estimate effect, rather than confirm no effect, with only a standardized high-fat meal according to FDA guidance may eliminate unnecessary studies, reduce cost, and improve efficiency in oncology drug development. Starting food-effect studies as early as possible is key to inform dosing in pivotal trials.

Certain oncology compounds exhibit fundamental pharmacokinetic (PK) disparities between healthy and malignant conditions. Given the effects of tumor-associated inflammation on enzyme and transporter expression, we performed a meta-analysis of CYP- and transporter-sensitive substrate clinical PK to quantitatively compare enzyme and transporter abundances between healthy volunteers (HV) and cancer patients (CP). Hepatic and intestinal CYP1A2, CYP2C19, and CYP3A4 abundance were subsequently adjusted via Simcyp's sensitivity analysis tool. Of the 11 substrates we investigated, seven displayed marked exposure differences >1.25-fold between CP and HV. Although CP studies are limited, meta-analysis-based reduction in CYP1A2, CYP2C19, and CYP3A4 enzyme abundances in a virtual oncology population effectively captures CP-PK for caffeine, theophylline, midazolam, simvastatin, omeprazole, and a subset of oncology compounds. These changes allow extrapolation from HV to CP, enhancing predictive capability; therefore, conducting simulations in this CYP-modified oncology (MOD-CP) population provides a more relevant characterization of CP-PK.

Purpose Selumetinib (AZD6244, ARRY-142886), an oral, potent, and highly selective mitogen-activated protein kinase 1/2 inhibitor with a short half-life, has shown activity across various tumor types. Before initiation of Phase III trials, the site, scale, and color (hypromellose shell from white [Phase II] to blue [Phase III]) of the selumetinib 25 mg capsule manufacture was changed. We present 2 crossover trials evaluating Phase III capsules in healthy subjects. Methods The relative bioavailability trial was a Phase I, open-label, randomized, 3-treatment, 4-period, 6-sequence crossover trial in healthy male subjects (aged 18–55 years). Subjects received selumetinib 75 mg (3 × 25 mg) Phase II or Phase III capsules, or a 35 mg oral solution, during 4 dosing periods in 1 of 6 randomized treatment sequences. The food effect trial was a Phase I, open-label, randomized, 2-period crossover trial in healthy male subjects (aged 18–45 years). Subjects were randomized to 1 of 2 sequences to receive selumetinib 75 mg (3 × 25 mg) Phase III capsules. In sequence 1, subjects received selumetinib after 10 hours of fasting. Following a washout period, selumetinib was administered after a high-fat meal. In sequence 2, subjects received selumetinib in the fed state, before the fasted state. Pharmacokinetic parameters were determined from serial blood sampling. Findings Twenty-seven subjects were randomized to the relative bioavailability trial; 26 completed all dosing periods. Mean selumetinib AUC was unchanged (geometric least squares mean ratio [GLSMR], 90.01% [90% CI, 81.74–99.11]). Cmax was 18% lower with the Phase III capsules (GLSMR, 81.97% [90% CI, 69.01–97.36]). A post hoc exploratory statistical analysis excluding outlying observations with later Tmax showed that Phase II and III capsules produced similar exposure in terms of Cmax and AUC. High intrasubject variability for Cmax attributed to the pharmacokinetic sampling schedule was judged to have impacted on the estimated GLSMR. In the food effect trial, 34 subjects completed both study periods. A high-fat meal reduced selumetinib Cmax compared with the fasted state (GLSMR, 49.76% [90% CI, 43.82–56.51]); AUC was minimally changed (GLSMR, 84.08% [90% CI, 80.72–87.59]). Median Tmax was prolonged by 1.49 hours. No deaths or serious adverse events were reported. Implications Selumetinib 75 mg (3 × 25 mg) Phase III capsules are being used in ongoing pivotal Phase III trials and should be administered in the fasted state. Based on findings from the relative bioavailability trial, pharmacokinetic sampling frequency was increased for healthy subject trials, including the food effect trial. ClinicalTrials.gov identifiers: NCT01635023 (relative bioavailability) and NCT01974349 (food effect).

This open-label, randomized, phase 1 crossover study investigated the effect of elevated gastric pH level (5) on the relative bioavailability and pharmacokinetic profile of the epidermal growth factor receptor tyrosine kinase inhibitor gefitinib. Healthy male volunteers (n = 26) were randomized to gefitinib 250 mg (fasted), either alone on day 1 (unmodified gastric pH) or 1 hour following the second of 2 oral doses of the H

The endothelin axis and the endothelin A (ETA) receptor have been implicated in tumor development and bone metastasis. This study aimed to investigate the pharmacokinetic (PK) and safety profiles of the specific ETA receptor antagonist, zibotentan, in elderly, male Chinese patients with advanced solid tumors. The PK data generated in these Chinese patients were further compared with those previously reported in Japanese and Caucasian patient populations. In this Phase I, open-label study, patients received a single dose of zibotentan 10 mg on Day 1, followed by a 72-h washout period and 12 consecutive days of once-daily zibotentan 10 mg. Fifteen patients received at least one dose of zibotentan 10 mg. Exposure was demonstrated in all patients and the PK profiles following single dosing and multiple dosing showed relatively rapid absorption, decline in a monophasic manner, a modest amount of accumulation, and relatively low apparent clearance and volume of distribution. Zibotentan was well tolerated with no new safety concerns. Adverse events reported in >1 patient were pyrexia (n = 4), constipation (n = 3), headache (n = 3) and peripheral edema (n = 2). Comparative analysis found no evidence of significant differences in zibotentan exposure between the Chinese patients in our study, and the previous Japanese and Caucasian studies. The PK and safety profiles of zibotentan determined in this Chinese patient population are similar to those previously reported. Our findings suggest no clinically relevant inter-ethnic differences in zibotentan disposition between the patient populations analyzed.

Zibotentan (ZD4054) is an oral-specific endothelin A receptor antagonist in development for the treatment of castration-resistant prostate cancer. In a number of preclinical studies, the disposition and metabolism of zibotentan were investigated in mice, rats and dogs. Following oral and intravenous administration, zibotentan was slowly absorbed (maximal concentration at approximately 4 h) and rapidly excreted, with the majority being eliminated by 48 h. The main route of elimination was via the urine in dogs and female rats, but via the faeces in male rats and mice of both sexes. Zibotentan was moderately bound to plasma proteins of all species examined (55-95%), and widely distributed throughout all tissues with the highest concentrations seen in the organs of excretion. Zibotentan was moderately metabolised. Zibotentan was well absorbed, moderately bound to plasma proteins, widely distributed and excreted predominantly via the urine.

Objectives: Tumor size dynamics and survival are traditionally analyzed in a 2-stage approach, without consideration of joint dependencies. The objective of this analysis was to develop a joint model which associates tumor size dynamics and progression-free survival (PFS), to predict time-to-progression. Methods: Phase 2 trial data from selumetinib (AZD6244; ARRY-142886, MEK inhibitor), in NSCLC patients (SELECT-2; NCT01750281) were used to develop a joint model for tumor size dynamics and PFS. The analysis was performed using JM package in R. Treatment arm, KRAS mutation and WHO performance status were evaluated as covariates. Model was evaluated by survival estimation based on early time (e.g., first 3 months) tumor size data. The final joint model based on SELECT-2 data was then used to predict PFS of selumetinib in SELECT-1 (NCT01933932) phase 3 trial. Results: The joint model developed on SELECT-2 data identified a significant association (p value Citation Format: Xiao Tong, James Dunyak, Diansong Zhou, David Carlile, Helen Tomkinson, Gabriel Helmlinger, Nidal Al-Huniti, Hongmei Xu. Joint modeling of longitudinal tumor dynamics and survival in non-small cell lung cancer (NSCLC) patients [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2018; 2018 Apr 14-18; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2018;78(13 Suppl):Abstract nr 4760.

Background: AZD0156 is a highly selective first oral ATM inhibitor in the clinic. Coordinating DNA single and double strand break repair, AZD0156 enhances the preclinical activity of olaparib, leading to its development as an antitumor agent in combination. We report here results from an ongoing phase 1 adaptive dose escalation study of AZD0156 in combination with olaparib. Methods: This phase I study is to assess the safety, tolerability, pharmacokinetics (PK) and preliminary efficacy of escalating doses of AZD0156 in combination with olaparib in patients with advanced malignancies. AZD0156 is mainly metabolized by CYP3A and FMO, which undergo genetic polymorphism. The flexible language incorporated in the protocol also allow rapid dose escalation beyond subtherapeutic doses. Results: PK data from the first 2 dose cohorts were lower than predicted and the AZD0156 dose was increased 4 X and dosing changed from QD (daily) to BD (twice daily). The mean terminal half-life of AZD0156 was 9-12 hours and PK was dose proportional. No significant drug-drug interactions (DDI) were observed with olaparib. Minor toxicities included nausea, vomiting and anemia in about 40% of patients in all cohorts. Grade 3 and 4 hematologic toxicities were observed in AZD0156 120mg BD with olaparib 200mg BD, and this dose level was considered intolerable. At doses of AZD0156 of 30 and 60mg BD, active target engagement was demonstrated. PK profile was similar across FMO genotype. Conclusion: Hematologic toxicities, consistent with the mode of action, emerged as dose-limiting toxicities of AZD0156 in combination with olaparib. Pharmacologically active doses of AZD0156 with olaparib were achieved more quickly in patients by using real-time PK, real-time genotyping, safety, DDI assessment, and PK/PD modelling. Citation Format: Yingxue Chen, Martin Pass, Nuria Bui Bruna, Christine Stephens, Andrew Pierce, Wouter Hanekom, Hani Gabra, Helen Tomkinson, Nidal Al-Huniti. Adaptive oncology phase 1 study of first-in-class inhibitor of ataxia telangiectasia mutated protein kinase (ATM), in combination with olaparib [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2018; 2018 Apr 14-18; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2018;78(13 Suppl):Abstract nr 4909.

Summary Background Combinations of molecularly targeted agents may provide optimal anti-tumor activity and improve clinical outcomes for patients with advanced cancers. Selumetinib (AZD6244, ARRY-142886) is an oral, potent and highly selective, allosteric inhibitor of MEK1/2, a component of the RAS/RAF/MEK/ERK pathway which is constitutively activated in many cancers. We investigated the safety, tolerability, and pharmacokinetics (PK) of selumetinib in combination with molecularly targeted drugs erlotinib or temsirolimus in patients with advanced solid tumors. Methods Two-part study: dose escalation, to determine the maximum tolerated dose (MTD) of selumetinib in combination with erlotinib 100 mg once daily (QD) or temsirolimus 25 mg once weekly, followed by dose expansion at the respective combination MTDs to further investigate safety and anti-tumor effects. Results 48 patients received selumetinib plus erlotinib and 32 patients received selumetinib plus temsirolimus. The MTD with erlotinib 100 mg QD was selumetinib 100 mg QD, with diarrhea being dose limiting. The most common all grade adverse events (AEs): diarrhea, rash, nausea, and fatigue. Four (8.3%) patients had ≥12 weeks stable disease. The MTD with temsirolimus 25 mg once weekly was selumetinib 50 mg twice daily (BID), with mucositis and neutropenia being dose limiting. The most commonly reported AEs: nausea, fatigue, diarrhea, and mucositis. Ten (31.3%) patients had ≥12 weeks stable disease. The combination PK profiles were comparable to previously observed monotherapy profiles. Conclusions MTDs were established for selumetinib in combination with erlotinib or temsirolimus. Overlapping toxicities prevented the escalation of selumetinib to its recommended phase II monotherapy dose of 75 mg BID. Trial registration: ClinicalTrials.gov NCT00600496; registered 8 July 2009. Electronic supplementary material The online version of this article (doi:10.1007/s10637-017-0459-7) contains supplementary material, which is available to authorized users.

e20606 Background: Tumor burden has long been used for the clinical diagnosis, staging, prognosis and treatment of non-small cell lung cancer (NSCLC), as described, for example, in the 7th edition of the AJCC/UICC NSCLC staging guidelines. Previous longitudinal tumor size approaches have used fixed tumor kinetic parameters or tumor shrinkage at a given timepoint, to correlate PFS and OS in a stepwise fashion. Here we describe a joint modeling approach which allows for individual, patient-level predictions of survival during NSCLC treatment. Joint modeling simultaneously fits OS and tumor size dynamics, converting full information from individual tumor assessments into a personalized prediction of survival - thereby avoiding dichotomization of response measure in a patient. Methods: Clinical data from IPASS Phase 3 study of Iressa (gefitinib) in NSCLC were used to fit a joint model of OS and tumor size. The data from a follow-up study (IFUM, Phase 4) for the same drug in a narrower population were used to validate the model on an independent set of subjects. This part included simulating clinical trials from the model and comparing the simulated survival with the observed data. The survival estimation method for individual patients followed from a Bayesian formulation and was implemented in R packages JM and JMbayes. Results: A joint model for overall survival and tumor size was developed and validated using clinical trial simulations. Individual survival estimates were obtained for subjects in a subsequent study based on early data cut-off for tumor assessments. Patient-level predictions were shown to be accurate as well as study-level survival estimates. The model was able to update individual survival predictions in real time. Conclusions: Joint tumor size / survival modeling provides a promising area of investigation for prediction of survival in individual patients. It can be used as a quantitative tool for estimating time-evolving risk of death based on early tumor size measurements. A clinically validated version of such a tool may allow physicians to better choose between treatment continuation and change, following tumor size measurements from standard clinical care.

e20040 Background: Longitudinal tumor burden has long been used for the clinical diagnosis, staging, prognosis and treatment of non-small cell lung cancer (NSCLC). Tumor burden and growth rate correlate directly with survival and RECIST (measurement of tumor) is widely used as a surrogate endpoint. RECIST doesn’t take into account the impact of the therapy on the speed of growth over time, and poorly correlates with survival, especially in IO therapies. Surrogate endpoints such as progression-free survival (PFS) or dichotomous RECIST-based overall response rate (ORR) allow early assessment of efficacy based on reduced study population size. Unfortunately, ORR and PFS are poorly predictive of OS in NSCLC. This well-known loss of information during categorization emphasizes the potential benefits of continuous tumor load modeling. Methods: This research provides a statistically valid basis for modeling and interpretation of longitudinal response dynamics, in the context of time-to-event (survival) censoring, through development of a joint longitudinal/event model. Using clinical data from the Phase 3 IPASS study of Iressa (gefitinib), we build a generalizable model relating tumor load dynamics to a time-evolving hazard of progression. Results: Using longitudinal data from other smaller and shorter studies, we identify the time-progression of patient’s risk, including post-treatment time of minimum hazard of progression and the time when hazard rapidly increases. This is applied at both the population strata and individual patient level to assess different treatment paradigms. The model shows that EGFR-mutated patients on gefitinib have stable hazard of progression for about 8 months, as which point hazard increases rapidly. EGFR-mutated patients treated with carboplatin/paclitaxel started with a 72% higher initial progression hazard which then increased rapidly after 4 months. Conclusions: Because of their continuous-in-time nature, joint longitudinal/event models provide a basis for exploring the complex timing issues in oncology treatment sequencing, treatment staging strategies for combinations, and dosing regimes.

e18130 Background: Understanding the clinical pharmacology properties of new drugs is essential, enabling correct prescribing with respect to dose, interactions and organ impairment. In the era of targeted therapy and resurgence in oncology R&D there is a need to consider how and when to define clinical pharmacology, since many drugs are given accelerated reviews, limiting the development time. This assessment was undertaken to understand how FDA review the clinical pharmacology components of NDAs. Methods: The Clinical Pharmacology and Biopharmaceutics Review documents of small molecule approvals in oncology by FDA from 2011 -2016 were analysed. Information regarding clinical pharmacology studies, in addition to post marketing requirements (PMR) was analysed. Results: Of 42 small molecules identified, 35 had clinical pharmacology review information. There were 16 accelerated approvals and in only 3 approvals were there no PMRs issued. A particular issue concerns the dose, 14 NDAs had identifiable issues in review, resulting in a 10 PMRs which include conducting a further pivotal study with additional doses. The majority of submissions (33) included clinical assessment of drug effect on the QTc interval. 7 PMRs were issued, 4 requesting completion of ongoing studies. A number of PMRs (24) were issued to assess organ impairment and DDI assessment (12). In all orally administered drugs a food interaction study was conducted with 1 PMR issued. In 32 submissions an excretion balance study was conducted, only 1 of the remaining 3 drugs was issued a PMR. Conclusions: Whilst a number of PMRs for clinical pharmacology studies were issued it is encouraging that these did not limit approval, ensuring patient access. For accelerated approvals, there will be insufficient time to complete many studies prior to filing. However, there were a significant number of PMRs regarding dose, reflecting FDA concerns that there is inadequate characterisation of the dose. Clinical pharmacology characterisation of NMEs is still required, but could be conducted through PMRs to enable early patient access. A major focus for sponsors should be a clearer understanding of the dose response relationship.

e20536 Background: Osimertinib is an oral, potent, irreversible, CNS active EGFR-TKI, selective for sensitizing (EGFRm) and T790M resistance mutations, indicated for the treatment of patients with T790M positive advanced non-small cell lung cancer who have progressed on or after EGFR-TKI therapy. Osimertinib pharmacokinetics (PK) were evaluated using a population approach and pharmacodynamic (PD) relationships using appropriate modeling approaches. Methods: To understand the impact of covariates on osimertinib PK, a population PK analysis was performed using data from patients who received osimertinib (20–240 mg) during the AURA studies. Exposure metrics were derived from a PK model and used to assess the exposure-response (safety/efficacy) relationship. Efficacy analysis included patients who were T790M positive (n = 710) and safety analysis included all dosed patients (n = 1088). The impact of covariates on exposure-response was assessed. Models accounting for rare safety events were applied to quantify the association between events and exposure. Results: Population PK analyses supported dose- and time-independent PK of osimertinib with no clinically meaningful covariates identified. Patients in the highest exposure quartile (Q4) had a numerically shorter median progression-free survival (8.3 months [95% CI 6.9, 10.5]) compared with patients in Q1, Q2 and Q3 (all 11.2 months [95% CIs 9.7, 12.7; 8.5, 15.6 and 8.7, 13.7, respectively]). A model-based analysis indicated that this effect is likely due to a larger number of patients in Q4 with poor prognostic features, i.e. worse performance status (WHO 1 or 2) and lower baseline serum albumin compared with Q1, Q2 and Q3, rather than to osimertinib exposure. Model-predicted probability of a relationship between osimertinib exposure and LVEF changes was not evident. Model-based analysis predicted that, compared with the median probability (0.03), the probability of a patient experiencing interstitial lung disease may increase with increasing osimertinib exposure (Q1 probability 0.01 [steady-state AUC 6361 nM*h] vs Q4 0.06 [24460 nM*h]) at the 80 mg dose. Conclusions: Population PK and PK-PD analysis is supportive of 80 mg as an appropriate dose for osimertinib. Clinical trial information: NCT01802632; NCT01802632; NCT02094261; NCT02151981.

2535 Background: Evaluation of the effect of food on the pharmacokinetics of orally administered oncology drugs is a critical aspect of drug development, as food can mitigate or exacerbate toxicities and can change and influence variability in systemic exposure. Our aim in this review of approved oncology products is to describe the approaches used by sponsors to assess food effect and decide on the final dosing recommendations. Methods: Data for small molecule oncology drugs approved between 2003-2016 was extracted from the clinical pharmacology review in the sponsor’s FDA submission package. Information on food-effect study design, outcomes, intersubject variability, exposure-response relationships for safety, and the label dosing recommendation regarding food was analyzed. Results: Of the 29 drugs analyzed, 19 food effect studies were conducted in healthy volunteers, and 10 were conducted in cancer patients. The ratio of population geometric means between fed and fasted treatments fell outside the 80-125 percent equivalence limit in 55% of compounds for AUC and in 69% of compounds for Cmax. 6 drugs (21%) are recommended to be given with food, 11 drugs (38%) in the fasted state, and 12 drugs (41%) can be dosed regardless of food. Label recommendations appeared to be driven by the exposure-response analysis. 80% of drugs with a fasted label recommendation despite an increase in bioavailability with food had an exposure-response relationship for safety. Conclusions: Optimizing study design by conducting early food effect studies designed to estimate food effect rather than confirming no food effect, and learning the impact of food early may eliminate unnecessary study arms and save sponsors money and time. Furthermore, understanding the potential of food to mitigate or exacerbate toxicities may improve patients’ experience with treatments and has been shown here to be a major driver of the final dosing recommendation regarding food.

This paper presents an overview of a cross-species investigation of the metabolic fate of [14C]-zibotentan (ZD4054), with particular focus on the main analytical challenges encountered during the study. A combination of detection methods were used including HPLC coupled to UV, RAD and/or MS(MS), and 1H NMR spectroscopy. The objective was to characterise and identify the major metabolites found in the circulation and excreta of rat and dog for comparison with those produced in human. Initial investigations in rat, using [14C]-labelled zibotentan positioned on the oxadiazole ring and HPLC–UV–RAD analysis, revealed seven labelled resolved metabolite peaks. Parallel analysis by HPLC–UV–MS (with in-source fragmentation) uncovered two additional metabolites, indicating loss of the radiolabel during biotransformation. Hence, in subsequent studies in rat, dog and human, dual-radiolabelled zibotentan was employed with the 14C-label positioned on the pyridine ring, which was shown to be less prone to metabolism. A total of 12 metabolites were found in the excreta and plasma in all species. One of these metabolites was found in the circulation in humans, which warranted further investigations. Characterisation of the isolated human circulating metabolite by 1H NMR was complicated by the co-extraction of a matrix component with a similar UV-chromophore to zibotentan, which was identified as daidzein, an isoflavone derived from the animal feed.

Background: Zibotentan (ZD4054) is an oral, specific endothelin A receptor antagonist presently under investigation for the treatment of hormone-resistant prostate cancer. Preclinical in vitro studies suggest that zibotentan has the potential to act as a time-dependent inhibitor of the cytochrome P450 isozyme 3A4 (CYP3A4) metabolic pathway. In clinical practice, it is likely that zibotentan will be coadministered with drugs metabolized by this pathway; the potential exists, therefore, that zibotentan-induced drug interactions could occur. Objectives: The primary objective of this study was to evaluate the effect of zibotentan on the pharmaco-kinetics of a clinically relevant dose of midazolam in healthy volunteers. Secondary objectives were to evaluate exposure to zibotentan, ensure the safety of the healthy volunteers dosed, and investigate the effect of zibotentan on the pharmacokinetics of the midazolam metabolites 1-hydroxy midazolam and 4-hydroxy midazolam. The potency of zibotentan as a CYP3A4 inhibitor was also assessed. Methods: This was an open-label, randomized, singlecenter, 2-period, Phase I, crossover study. Volunteers were randomized in a 1:1 ratio to 1 of 2 cohorts. In cohort 1, volunteers received a single dose of midazolam 7.5 mg on day 1 (treatment A) of a 2-day study period. After a minimum 7-day washout period, volunteers received zibotentan 10 mg once daily on days 1 through 7, plus a single dose of midazolam 7.5 mg on day 6 (treatment B) of a 7-day study period. In cohort 2, volunteers received treatment B followed by treatment A, with a minimum 7-day washout period between treatments. AUC 0−∞ and C max data were expressed as geometric least squares mean ratios and 90% CIs for midazolam + zibotentan:midazolam. A moderate interaction between midazolam and zibotentan was predefined to have occurred if the upper 90% CI of the ratio was >1.5. Adverse events (AEs) were assessed according to the National Cancer Institute's Common Terminology Criteria for Adverse Events version 3. AE data were assessed based on information provided by the volunteer, through open-ended and nonleading verbal questions to the volunteer at each visit, and through observation by the investigational team, other care providers, or relatives. Results: Six volunteers (all white) were included in each cohort (cohort 1, mean [SD] age, 48 [7] years; mean weight, 74 [6] kg; cohort 2, mean age, 51 [11] years; mean weight, 75 [13] kg). Steady-state levels of zibotentan, achieved over 7 days, increased the midazolam AUC 0−∞ by 1.2-fold compared with midazolam alone. The upper limits of the 90% CIs for the AUC 0−∞ and C max ratios were below the predefined level of 1.5 (1.37 and 1.32, respectively). Zibotentan had no apparent effect on the pharmacokinetics of 1-hydroxy midazolam and 4-hydroxy midazolam. Fatigue was reported in 11 volunteers (92%) receiving midazolam monotherapy and 10 (83%) receiving midazolam combined with zibotentan. Headache was reported in all 12 volunteers after zibotentan monotherapy. Conclusions: In this population of healthy male volunteers, once-daily zibotentan 10 mg increased the AUC 0−∞ of midazolam 1.2-fold; however, the treatment ratio was below the predefined limit for clinical significance. Zibotentan was well tolerated when given alone or in combination with midazolam. The results indicate that once-daily zibotentan 10 mg acted as a weak inhibitor of the CYP3A4 pathway. ClinicalTrials. gov identifier: NCT00709553.

Proceedings: AACR 101st Annual Meeting 2010‐‐ Apr 17‐21, 2010; Washington, DC Zibotentan (ZD4054) is a small-molecule, specific endothelin A (ETA) receptor antagonist being investigated for the treatment of hormone-resistant prostate cancer. Zibotentan is eliminated by both renal (58%) and metabolic clearance. The current study investigated whether hepatic impairment has a clinically relevant effect on exposure to zibotentan. This open-label, two-centre study investigated the PK and tolerability of zibotentan in subjects with hepatic impairment, compared with subjects with normal hepatic function. Subjects were divided into four categories using the Child-Pugh (CP) classification: mild hepatic impairment (CP A), moderate hepatic impairment (CP B), severe hepatic impairment (CP C) and normal hepatic function. Each subject received a single oral dose of zibotentan 10 mg. AUC and Cmax are expressed as the ratio (R) of geometric means and 90% confidence intervals (CI) for each hepatic impairment group compared with the normal function group. The possibility that hepatic impairment had a clinically relevant effect on exposure of zibotentan was considered if the upper 90% CI for the ratio exceeded two. Thirty-seven subjects were enrolled and 32 subjects (eight per group) received zibotentan and completed the study. Compared with the normal function group, zibotentan Cmax was 7% (R 0.93; 90% CI 0.75-1.15), 11% (R 0.89; 90% CI 0.72-1.1) and 5% (R 0.95; 90% CI 0.77-1.17) lower in subjects with CP A, CP B and CP C hepatic impairment, respectively. Zibotentan AUC was 40% (R 1.40; 90% CI 0.91-2.17), 45% (R 1.45; 90% CI 0.94-2.24) and 190% (R 2.90; 90% CI 1.88-4.49) higher in subjects with CP A, CP B and CP C hepatic impairment, respectively, compared with those with normal function. Mean t½ was 9.28 h, 13.0 h, 14.6 h and 24.8 h for the normal function, CP A, CP B and CP C hepatic impairment groups, respectively. Compared with the normal function group, CL/F was approximately 25%, 29% and 64% lower, respectively, in the CP A, CP B and CP C hepatic impairment groups. Zibotentan was well tolerated by all subjects, with headache (CTC Grade 1-2) being the most common adverse event in each group. Despite increased exposure to zibotentan with increased hepatic impairment, there were no differences in the type or severity of adverse events. In conclusion, following a single oral dose of zibotentan 10 mg, there was no significant difference in Cmax with degree of hepatic impairment, indicating that hepatic impairment did not affect the absorption of zibotentan. AUC was higher and t½ longer in subjects with hepatic impairment than in those with normal function due to the slower clearance of zibotentan, with the extent of the difference being related to the degree of impairment. Trial sponsored by AstraZeneca ([NCT00672581][1]; AZ code D4320C00025). Citation Format: {Authors}. {Abstract title} [abstract]. In: Proceedings of the 101st Annual Meeting of the American Association for Cancer Research; 2010 Apr 17-21; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2010;70(8 Suppl):Abstract nr 2770. [1]: /lookup/external-ref?link_type=CLINTRIALGOV&access_num=NCT00672581&atom=%2Fcanres%2F70%2F8_Supplement%2F2770.atom

The pharmacokinetic (PK) profile of zibotentan (ZD4054), a small-molecule, specific endothelin A (ETA) receptor antagonist, was evaluated under fed and fasting conditions in two Phase I studies in healthy male subjects. These two studies were open-label crossover studies in which half the subjects received a single zibotentan dose following a high fat meal and again after a 7-day washout in a fasted state. The other half received a single zibotentan dose in a fasted state initially and again 7 days later following a high fat meal. Study 1 (AstraZeneca study 4045IL/013) included nine subjects aged >65 years who received single-dose zibotentan 25 mg and study 2 (AstraZeneca study D4320C00028) included 30 male subjects aged ≤65 years who received single-dose zibotentan 10 mg. AUC and Cmax were log-transformed prior to analysis using an analysis of variance model fitting for the effects of sequence, subject, period and treatment. In subjects aged >65 years who received zibotentan 25 mg, there was no difference in AUC values between the fed (GLS mean 15041 ng.h/ml) and fasted groups (GLS mean 14740 ng.h/ml; treatment ratio of fed/fasted [90% CI], 1.02 [0.8-1.30]). However Cmax was lower for fed (GLS mean 1005 ng/ml) than fasted subjects (GLS mean 1262 ng/ml; treatment ratio of fed/fasted [90% CI], 0.8 [0.58-1.08]). In subjects aged ≤65 years who received zibotentan 10 mg, there was a statistically significant decrease in AUC for fed subjects (GLS mean 4031 ng.h/ml) compared with fasted subjects (GLS mean 4711 ng.h/ml; treatment ratio of fed/fasted [90% CI], 0.86 [0.80-0.91]), and Cmax for fed subjects (GLS mean 357 ng/ml) compared with fasted subjects (GLS mean 470 ng/ml; treatment ratio of fed/fasted [90% CI], 0.76 [0.71-0.81]). In both studies, median tmax was 4 hours in the fed group versus 2 hours in the fasted group. In study 2, a food effect on AUC was excluded because the corresponding 90% CIs were within the predefined limits of 0.8-1.25. However, a food effect could not be excluded for Cmax, because the lower limit of the 90% CI was below the predefined margin. The reduction in Cmax under fed conditions was consistent with a slower rate of absorption indicated by median tmax being delayed by 2 hours under fed conditions. The reduction in Cmax is not considered to be clinically relevant as efficacy is likely to be driven by AUC or time above a particular concentration, therefore future studies are being conducted without any food restrictions. Citation Format: {Authors}. {Abstract title} [abstract]. In: Proceedings of the 101st Annual Meeting of the American Association for Cancer Research; 2010 Apr 17-21; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2010;70(8 Suppl):Abstract nr 2755.

Background The RAS/RAF/MEK/ERK pathway is constitutively activated in many cancers. Selumetinib (AZD6244, ARRY-142886) is an oral, potent and highly selective, allosteric MEK1/2 inhibitor with a short half-life that has shown clinical activity as monotherapy in phase I and II studies of advanced cancer. Preclinical data suggest that selumetinib may enhance the activity of chemotherapeutic agents. We assessed the safety, tolerability, and pharmacokinetics (PK) of selumetinib (AZD6244, ARRY-142886) in combination with docetaxel or dacarbazine in patients with advanced solid tumors. Methods This study was a phase I, open-label, multicenter study in patients aged ≥18 years with advanced solid tumors who were candidates for docetaxel or dacarbazine treatment. Part A of the study (dose escalation) evaluated safety, tolerability, PK, and maximum tolerated dose (MTD) of selumetinib twice daily (BID) with docetaxel 75 mg/m2 or dacarbazine 1000 mg/m2 administered every 21 days. Patients receiving docetaxel could be administered primary prophylactic granulocyte-colony stimulating factor according to standard guidelines. Part B of the study (dose expansion) further evaluated safety, tolerability, and PK in 12 additional patients at the MTD combinations determined in part A. Results A total of 35 patients received selumetinib plus docetaxel, and 25 received selumetinib plus dacarbazine. The MTD of selumetinib was 75 mg BID in combination with either docetaxel (two dose-limiting toxicity [DLT] events: neutropenia with fever, and thrombocytopenia) or dacarbazine (one DLT event: thrombocytopenia). Common adverse events occurring with each treatment combination were diarrhea, peripheral/periorbital edema, fatigue, and nausea. PK parameters for selumetinib and docetaxel or dacarbazine were similar when administered alone or in combination. Partial responses were reported in 6/35 patients receiving selumetinib plus docetaxel and 4/25 patients receiving selumetinib plus dacarbazine. Conclusions The combinations of selumetinib plus docetaxel and selumetinib plus dacarbazine demonstrated manageable safety and tolerability profiles and preliminary signs of clinical activity in patients with advanced solid tumors. Trial registration ClinicalTrials.gov NCT00600496; registered 8 July 2009. Electronic supplementary material The online version of this article (doi:10.1186/s12885-017-3143-6) contains supplementary material, which is available to authorized users.