Population Pharmacokinetics and Exposure-Response Analysis for the CTLA-4 Inhibitor Tremelimumab in Metastatic NSCLC Patients in the Phase III POSEIDON Study

Blockade of CTLA-4 by tremelimumab combined with anti-PD-L1 durvalumab and chemotherapy provided increased antitumor activity and long-term survival benefits in first-line metastatic non-small cell lung cancer (mNSCLC) in the phase III POSEIDON study. We performed population pharmacokinetic modeling for tremelimumab using data from 1,605 patients across 6 studies (including POSEIDON) in multiple tumors (lung cancer, bladder cancer, malignant mesothelioma, and other solid tumors), and identified a 2-compartment model with linear and time-varying clearance for tremelimumab. Cox proportional hazard regression models were applied to 326 patients with mNSCLC from POSEIDON to evaluate the association between exposure metrics and efficacy end points, adjusting for baseline prognostic covariates. Improved progression-free survival (PFS) and overall survival (OS) in the tremelimumab arm (in combination with durvalumab and chemotherapy) was associated with higher tremelimumab exposure (e.g., minimum concentration at 5th dose (Cmin,dose5 ) and area under the curve at 5th dose (AUCdose5 )). However, further case-matching analyses yielded hazard ratios for the comparison of tremelimumab-treated patients in the Cmin,dose5 quartile 1 (Q1) subgroup with matched chemotherapy-treated patients of 1.04 (95% confidence interval (CI): 0.76-1.44) for OS and 0.99 (95% CI: 0.72-1.36) for PFS, suggesting that the observed apparent exposure-response relationship might be confounded. No relationship between tremelimumab exposure and safety (grade ≥3 treatment-emergent adverse events [AEs], AEs of special interest, or discontinuation due to AEs) was identified. These results support the consistent benefit observed with tremelimumab 75 mg every 3 weeks for up to 5 doses in combination with durvalumab and chemotherapy in POSEIDON as first-line therapy for mNSCLC.

Population Pharmacokinetics and Exposure-Response Analysis of Tremelimumab 300 mg Single Dose Combined with Durvalumab 1500 mg Q4W (STRIDE) in Patients with Unresectable Hepatocellular Carcinoma

A novel single-dose regimen of 300 mg tremelimumab in combination with durvalumab (STRIDE) has demonstrated a favorable benefit-risk profile in the phase 1/2 Study 22 trial (in patients with unresectable hepatocellular carcinoma, uHCC) and in the phase 3 HIMALAYA study. The current analysis evaluated the population pharmacokinetics (PopPK) of tremelimumab and durvalumab, and the exposure-response (ER) relationship for efficacy and safety of STRIDE in patients with uHCC. Previous PopPK models for tremelimumab and durvalumab were updated using data from previous studies in various cancers combined with data from Study 22 and HIMALAYA. Typical population mean parameters and associated inter- and intra-individual variability were assessed, as was the influence of covariates. Individual exposure metrics were derived from the individual empirical Bayes estimates as drivers for ER analysis related to efficacy and safety from HIMALAYA. The observed pharmacokinetics of tremelimumab in uHCC were well described by a 2-compartment model with both linear and time-dependent clearance. All identified covariates changed tremelimumab PK parameters by <25%, and thus had minimal clinical relevance; similar results were obtained from durvalumab PopPK analysis. None of tremelimumab or durvalumab exposure metrics were significantly associated with overall survival (OS), progression-free survival (PFS), or adverse events. Baseline aspartate aminotransferase and neutrophil-to-lymphocyte ratio (NLR) were associated with OS (P < .001) by the Cox proportional hazards model. No covariate was identified as a significant factor for PFS. No dose adjustment for tremelimumab or durvalumab is needed based on PopPK covariate analyses or ER analyses. Our findings support the novel STRIDE dosing regimen in patients with uHCC.

Entrectinib dose confirmation in pediatric oncology patients: pharmacokinetic considerations

PURPOSE

Entrectinib is a central nervous system-active potent inhibitor of tropomyosin receptor kinase (TRK), with anti-tumor activity against neurotrophic NTRK gene fusion-positive tumors. This study investigates the pharmacokinetics of entrectinib and its active metabolite (M5) in pediatric patients and aims to understand whether the pediatric dose of 300 mg/m² once daily (QD) provides an exposure that is consistent with the approved adult dose (600 mg QD).

METHODS

Forty-three patients aged from birth to 22 years were administered entrectinib (250-750 mg/m² QD) orally with food in 4-week cycles. Entrectinib formulations included capsules without acidulant (F1) and capsules with acidulant (F2B and F06).

RESULTS

Although there was interpatient variability with F1, entrectinib and M5 exposures increased dose dependently. Lower systemic exposures were observed in pediatric patients receiving 400 mg/m² QD entrectinib (F1) versus adults receiving either the same dose/formulation or the recommended flat dose of 600 mg QD (~ 300 mg/m² for a 70 kg adult) due to suboptimal F1 performance in the pediatric study. The observed pediatric exposures following 300 mg/m² QD entrectinib (F06) were comparable to those in adults receiving 600 mg QD.

CONCLUSIONS

Overall, the F1 formulation of entrectinib was associated with lower systemic exposure in pediatric patients compared with the commercial acidulant formulation (F06). Systemic exposures achieved in pediatric patients with the F06 recommended dose (300 mg/m²) were within the known efficacious range in adults, confirming the adequacy of the recommended dose regimen with the commercial formulation.

Population Pharmacokinetics of Monalizumab in Patients with Advanced Solid Tumors

Monalizumab is a novel, first-in-class humanized immunoglobulin G (IgG)-4 monoclonal antibody (mAb) immune checkpoint inhibitor that targets the inhibitory CD94/NKG2A receptors. The objectives of this analysis were to develop a population pharmacokinetic (PK) model of monalizumab, evaluate the impact of clinically relevant covariates on monalizumab PK, and provide dose justification for clinical trials. We developed a monalizumab population PK model to characterize the PK properties of monalizumab in patients with advanced solid tumors or head and neck squamous cell carcinoma. Data from clinical studies D419NC00001 (NCT02671435) and IPH2201-203 (NCT02643550) were pooled for the analysis, resulting in a dataset of 3066 PK samples derived from 507 subjects. The PK of monalizumab were reasonably described by a 2-compartment model with first-order elimination. Monalizumab generally exhibited linear PK over a dose range of 22.5-750 mg or 10 mg/kg every 2 weeks. The estimate of clearance was approximately 0.255 L/day and apparent volume of distribution was 6.36 L for a typical individual, consistent with previous findings for endogenous IgGs and other therapeutic mAbs. Baseline albumin and body weight were identified as significant covariates of clearance; body weight, sex, and smoking status had a significant impact on volume of distribution; and none of these covariates had impact on peripheral volume of distribution. Although these covariates were identified as statistically significant, they are considered to be not clinically meaningful, as changes in monalizumab exposure were less than 30%. Therefore, no dose adjustments of monalizumab based on patient or disease characteristics is recommended. This article is protected by copyright. All rights reserved.

Strategies for clinical dose optimization of T cell-engaging therapies in oncology

Innovative approaches in the design of T cell-engaging (TCE) molecules are ushering in a new wave of promising immunotherapies for the treatment of cancer. Their mechanism of action, which generates an in trans interaction to create a synthetic immune synapse, leads to complex and interconnected relationships between the exposure, efficacy, and toxicity of these drugs. Challenges thus arise when designing optimal clinical dose regimens for TCEs with narrow therapeutic windows, with a variety of dosing strategies being evaluated to mitigate key side effects such as cytokine release syndrome, neurotoxicity, and on-target off-tumor toxicities. This review evaluates the current approaches to dose optimization throughout the preclinical and clinical development of TCEs, along with perspectives for improvement of these strategies. Quantitative approaches used to aid the understanding of dose-exposure-response relationships are highlighted, along with opportunities to guide the rational design of next-generation TCE molecules, and optimize their dose regimens in patients.

Enzymatic debridement in critically injured burn patients - Our experience in the intensive care setting and during burn resuscitation

BACKGROUND

Much of the recent literature on bromelain based enzymatic debridement of burn injury has focused on its use in smaller burn injury and specialist areas such as the hands or genitals (Krieger et al., 2012; Schulz et al., 2017a,b,c,d). This is despite the original papers describing its use in larger burn injury (Rosenberg et al., 2004, 2014). The current EMA license for Nexobrid™ advises that it should not be used for burn injuries of more than 15% TBSA and should be used with caution in patients with pulmonary burn trauma and suspected pulmonary burn trauma. The original safety and efficacy trial of NexoBrid™ limited its use to 15% TBSA aliquots with concern regarding the effect of bromelain on coagulation. In a European consensus paper of experienced burns clinicians, now on its second iteration, 100% of respondents agreed that "up to 30% BSA can be treated by enzymatic debridement based on individual decision" (Hirche et al., 2017). Hofmaenner et al.'s recent study on the safety of enzymatic debridement in extensive burns larger than 15% provides some further evidence that "bromelain based enzymatic debridement can be carried out safely in large-area burns" (Hofmaenner et al., 2020) but the literature is scant in these larger debridement areas. In our centre we have been using enzymatic debridement for resuscitation level burn injury since 2016. We have gained significant learning in this time; this article aims to describe our current protocol for enzymatic debridement in this patient population and highlight specific learning points that might aid other centres in using enzymatic debridement for larger burn injury.

METHOD

We performed a search of the IBID database to identify all adult patients who satisfied the inclusion criteria of resuscitation level burn injury (defined as total burn surface area (TBSA) ≥15% in patients aged >16 years), or level 3 admission following burn injury and who underwent Enzymatic Debridement. A case note review was completed, and details comprising patient demographics, TBSA, mechanism of burn, presence of inhalation injury, sequencing of debridement, length of ICU and hospital stay, blood product utilisation and the need for autografting were recorded. No ethical approval has been sought for this retrospective review.

RESULTS

We identified 29 patients satisfying the inclusion criteria (Table 1). Between June 2016 and June 2020 the average total burn size of patients who had at least some of their burn treated by enzymatic debridement increased from 21.4% in 2016/17 to 34.7% in 2019/20. In these patients the actual area treated by enzymatic debridement also increased from 11.9% TBSA to 20.3% TBSA. 19 patients (66%) had enzymatic debridement performed within 24 h of injury, a further 2 patients (7%) within 48 h after injury. Patients were more likely to have enzymatic debridement commenced in the first 24 h after injury if they had circumferential limb injury (39% vs 9%) or were planned for enzyme only debridement (78% vs 28%). Those who were planned for combination enzyme and surgical debridement were more likely to have enzymatic debridement commenced after the first 48 h (75%). We have performed enzymatic debridement overnight on one occasion, for a patient who presented with circumferential limb injury and was determined to undergo urgent debridement.

CONCLUSION

Much of the literature has described the use of enzymatic debridement in smaller burns, and specialist areas. However, it is our opinion that the advantages of enzymatic debridement appear to be greater in larger burns with a facility for whole burn excision on the day of admission in the ICU cubicle. We have demonstrated significantly reduced blood loss, improved dermal preservation, reduced need for autografting, and a reduction in the number of trips to theatre. We would advocate that both the team and the patient need to be as prepared as they would be for a traditional surgical excision. The early part of our learning curve for enzymatic debridement in resuscitation level injuries was steep, and we were able to build on experience from managing smaller injuries. We recommend any team wishing to using enzymatic debridement gain experience in the same way and develop robust local pathways prior to attempting use in larger burn injuries.

Physiologically-Based Pharmacokinetic Modelling of Entrectinib Parent and Active Metabolite to Support Regulatory Decision-Making

BACKGROUND AND OBJECTIVE

Entrectinib is a selective inhibitor of ROS1/TRK/ALK kinases, recently approved for oncology indications. Entrectinib is predominantly cleared by cytochrome P450 (CYP) 3A4, and modulation of CYP3A enzyme activity profoundly alters the pharmacokinetics of both entrectinib and its active metabolite M5. We describe development of a combined physiologically based pharmacokinetic (PBPK) model for entrectinib and M5 to support dosing recommendations when entrectinib is co-administered with CYP3A4 inhibitors or inducers.

METHODS

A PBPK model was established in Simcyp^® Simulator. The initial model based on in vitro-in vivo extrapolation was refined using sensitivity analysis and non-linear mixed effects modeling to optimize parameter estimates and to improve model fit to data from a clinical drug-drug interaction study with the strong CYP3A4 inhibitor, itraconazole. The model was subsequently qualified against clinical data, and the final qualified model used to simulate the effects of moderate to strong CYP3A4 inhibitors and inducers on entrectinib and M5 pharmacokinetics.

RESULTS

The final model showed good predictive performance for entrectinib and M5, meeting commonly used predictive performance acceptance criteria in each case. The model predicted that co-administration of various moderate CYP3A4 inhibitors (verapamil, erythromycin, clarithromycin, fluconazole, and diltiazem) would result in an average increase in entrectinib exposure between 2.2- and 3.1-fold, with corresponding average increases for M5 of approximately 2-fold. Co-administration of moderate CYP3A4 inducers (efavirenz, carbamazepine, phenytoin) was predicted to result in an average decrease in entrectinib exposure between 45 and 79%, with corresponding average decreases for M5 of approximately 50%.

CONCLUSIONS

The model simulations were used to derive dosing recommendations for co-administering entrectinib with CYP3A4 inhibitors or inducers. PBPK modeling has been used in lieu of clinical studies to enable regulatory decision-making.

In vitro and clinical investigations to determine the drug-drug interaction potential of entrectinib, a small molecule inhibitor of neurotrophic tyrosine receptor kinase (NTRK)

Background Entrectinib is a CNS-active, potent inhibitor of tyrosine receptor kinases A/B/C, ROS1 and anaplastic lymphoma kinase approved for use in patients with solid tumors. We describe the in vitro and clinical studies investigating potential entrectinib drug-drug interactions. Methods In vitro studies with human biomaterials assessed the enzymes involved in entrectinib metabolism, and whether entrectinib modulates the activity of the major cytochrome P450 (CYP) enzymes or drug transporter P-glycoprotein. Clinical studies investigated the effect of a strong CYP3A4 inhibitor (itraconazole) and inducer (rifampin) on single-dose entrectinib pharmacokinetics. The effect of entrectinib on sensitive probe substrates for CYP3A4 (midazolam) and P-glycoprotein (digoxin) were also investigated. Results Entrectinib is primarily metabolized by CYP3A4. In vitro, entrectinib is a CYP3A4/5 inhibitor (IC₅₀ 2 μM) and a weak CYP3A4 inducer. Entrectinib inhibited P-glycoprotein (IC₅₀ 1.33 μM) but is a poor substrate. In healthy subjects, itraconazole increased entrectinib C_max and AUC by 73% and 504%, respectively, and rifampin decreased entrectinib C_max and AUC by 56% and 77%, respectively. Single dose entrectinib did not affect midazolam AUC, although C_max decreased by 34%. Multiple dose entrectinib increased midazolam AUC by 50% and decreased C_max by 21%. Single dose entrectinib increased digoxin AUC and C_max by 18% and 28%, respectively, but did not affect digoxin renal clearance. Conclusions Entrectinib is a CYP3A4 substrate and is sensitive to the effects of coadministered moderate/strong CYP3A4 inhibitors and strong inducers, and requires dose adjustment. Entrectinib is a weak inhibitor of CYP3A4 and P-glycoprotein and no dose adjustments are required with CYP3A4/P- glycoprotein substrates.

Registration Number (Study 2) NCT03330990 (first posted online November 6, 2017) As studies 1 and 3 are phase 1 trials in healthy subjects, they are not required to be registered.

Characterization of the pharmacokinetics of entrectinib and its active M5 metabolite in healthy volunteers and patients with solid tumors

BACKGROUND

Entrectinib is an oral, CNS-active, potent inhibitor of tyrosine receptor kinases A/B/C, tyrosine kinase ROS proto-oncogene 1, and anaplastic lymphoma kinase approved for use in patients with solid tumors. We describe 3 clinical studies, including one investigating the single/multiple dose pharmacokinetics of entrectinib in patients and two studies in healthy volunteers investigating the absorption/distribution/metabolism/excretion (ADME) of entrectinib, its relative bioavailability, and effect of food on pharmacokinetics.

METHODS

The patient study is open-label with dose-escalation and expansion phases. Volunteers received entrectinib (100-400 mg/m², and 600-800 mg) once daily with food in continuous 28-day cycles. In the ADME study, volunteers received a single oral dose of [¹⁴C]entrectinib 600 mg. In the third study, volunteers received single doses of entrectinib 600 mg as the research and marketed formulations in the fasted state (Part 1), and the marketed formulation in the fed and fasted states (Part 2). Entrectinib and its major active metabolite M5 were assessed in all studies.

RESULTS

Entrectinib was absorbed in a dose-dependent manner with maximum concentrations at ~4 h postdose and an elimination half-life of ~20 h. Entrectinib was cleared mainly through metabolism and both entrectinib and metabolites were eliminated mainly in feces (minimal renal excretion). At steady-state, the M5-to-entrectinib AUC ratio was 0.5 (with 600 mg entrectinib research formulation in patients). The research and marketed formulations were bioequivalent and food had no relevant effect on pharmacokinetics.

CONCLUSIONS

Entrectinib is well absorbed, with linear PK that is suitable for once-daily dosing, and can be taken with or without food.

PK/PD Mediated Dose Optimization of Emactuzumab, a CSF1R Inhibitor, in Patients With Advanced Solid Tumors and Diffuse-Type Tenosynovial Giant Cell Tumor

Targeted biological therapies may achieve maximal therapeutic efficacy at doses below the maximum tolerated dose (MTD); therefore, the search for the MTD in clinical studies may not be ideal for these agents. Emactuzumab is an investigational monoclonal antibody that binds to and inhibits the activation of the cell surface colony‐stimulating factor‐1 receptor. Here, we show how modeling target‐mediated drug disposition coupled with pharmacodynamic end points was used to optimize the dose of emactuzumab without defining an MTD. The model could be used to recommend doses across different disease indications. The approach recommended an optimal biological dose of emactuzumab for dosing every 2 weeks (q2w) ≥ 900 mg, approximately three‐fold lower than the highest dose tested clinically. The model predicted that emactuzumab doses ≥ 900 mg q2w would achieve target saturation in excess of 90% over the entire dosing cycle. Subsequently, a dose of 1,000 mg q2w was used in the extension phase of a phase I study of emactuzumab in patients with advanced solid tumors or diffuse‐type tenosynovial giant cell tumor. Clinical data from this study were consistent with model predictions. The model was also used to predict the optimum dose of emactuzumab for use with dosing every 3 weeks, enabling dosing flexibility with respect to comedications. In summary, this work demonstrates the value of quantitative clinical pharmacology approaches to dose selection in oncology as opposed to traditional MTD methods.

Therapeutically-induced stable disease in oncology early clinical trials

RATIONALE

The RECIST guideline defines four categories of response to treatment for cancer patients according to post-baseline changes in tumor burden, hence ignoring disease history. However, if left untreated, tumors grow exponentially, implying that pretreatment changes in tumor size are key to thoroughly assess efficacy. We present a model-based approach to estimate the rates of changes in tumor mass, before and after treatment onset.

METHODS

Sixty-eight patients were eligible for the analysis of tumor size data from a Phase 1 study evaluating the effect of emactuzumab. In addition to tumor size measured at baseline and every six weeks during treatment, a pre-baseline measurement was gathered for each patient. A longitudinal regression model was used to estimate the rates of tumor size change before and after treatment onset.

RESULTS

The median pre-treatment tumor growth exponential rate was equal to 0.022 month-1, corresponding to a tumor size doubling time of 4 months, and the on-treatment median tumor shrinkage exponential rate was equal to 0.001 month-1. Among sixteen patients categorized as stable disease per RECIST, only five had similar slopes before and after treatment while nine actually improved. One patient in particular had a therapeutically induced stabilization of the disease.

CONCLUSION

Our analysis emphasizes the importance of collecting pre-baseline scans to distinguish therapeutically induced stable disease from cases where the tumor growth is not perturbed by treatment.

1006 Sleep Problems and Risk of Cancer Incidence and Mortality in the Cardiovascular Health Study (CHS)

Introduction

Even in the absence of a formal diagnosis, sleep problems (SP) are frequently indicative of an underlying sleep disorder, such as obstructive sleep apnea, which may be adversely associated with cancer risk and cancer outcomes.

Methods

We assessed the association of self-reported SP with incident cancer (N=4,997, excluding prevalent cancers) and cancer mortality (N=5849) among the participants of Cardiovascular Health Study (CHS), a population-based study of adults aged &gt;=65 years recruited from 4 US communities. Participants reported SP (daytime sleepiness, observed apnea and snoring) yearly from 1989-1994; these self-reported symptoms have been validated against objective sleep measures assessed within a subset of CHS participants (n= 1240) who received a home polysomnography as part of the Sleep Heart Health Study. Cancer incidence was ascertained through linkage with state cancer registries through 2005; cancer specific death was adjudicated through 2015. We used Cox proportional hazards regression to calculate hazard ratios (HR) and 95% confidence intervals (CI) for associations of baseline SP with subsequent cancer incidence and cancer mortality, adjusting for baseline sociodemographics, lifestyle factors, and medical history.

Results

The mean age (SD) of the study population was 73 (6) years, 56% were female, and 84% were white. The prevalence of SP was 17% for daytime sleepiness, 8% for observed apnea, and 24% for snoring; 63% reported none of the 3 SP. Overall, 1,130 first incident cancers and 1,014 cancer deaths were identified over median follow-up of 12 and 13 years, respectively. Compared to participants who reported no SP, the risk of incident cancer was inversely associated with daytime sleepiness (HR 0.86 [95% CI 0.70-1.04]), observed apnea (HR 0.74 [0.56-1.00]), and snoring (HR 0.80 [0.68-0.95]). Cancer mortality HR (95% CI) estimates were 1.00 (0.82-1.21) for daytime sleepiness, 0.77 (0.57-1.04) for observed apnea, and 0.88 (0.74, 1.04) for snoring.

Conclusion

Symptoms indicating SP reported at baseline were not associated with increased cancer incidence or cancer mortality. Ongoing analyses are focused on the impact of longitudinal SP (time dependent, cumulative average) to ensure an adequate latency period is incorporated into our analysis of the association between SP and cancer risk and mortality.

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NIHT32CA09488017

Abstract 690: Optimization of biopsy scheduling in clinical studies of T cell bispecifics through an integrated modeling and simulation, digital pathology and machine learning approach

In the context of cancer immunotherapy clinical trials, baseline and on-treatment tumor biopsies may provide important insight into whether a treatment is working as expected, and furthermore whether efficacy is anticipated. For tumor-retained antibodies that perturb the behaviour of immune cells, such as T cell bispecific antibodies (TCBs), spatial information derived from biopsy images may be particularly insightful. On-treatment biopsies in clinical trials are usually scheduled at a time point that is considered convenient for the study design and when therapeutic effects, such as T cell infiltration, are expected to be distinguishable in tumor tissue. To our knowledge, there have been no attempts to investigate optimal scheduling of on-treatment biopsy sample collection using quantitative approaches due to lack of clinical data at a sufficiently diverse range of time points.

Our integrated tissue pathology, disease modeling and machine learning workflow is designed to select the time point at which on-treatment biopsies could be most informative for making reliable predictions of response to treatment. Leveraging around 20 baseline and on-treatment digitized biopsy images from patients undergoing treatment with immune stimulating TCBs, we train a mathematical model to simulate tumor cell/T cell interactions in the tumor microenvironment. The mathematical model produces an enriched dataset of “virtual” biopsy images corresponding to predictions at intermediate time points. The virtual biopsies are evaluated based on their ability to predict treatment response.

Specific mechanisms of action of bispecific antibodies, such as upregulation of T cell activation and/or proliferation, are taken into account in the structure of the mathematical model. The model is tuned and validated using machine learning techniques, and a reserved “test” dataset comprising images that were not used to estimate model parameters is used to evaluate model performance. Our workflow has the potential to inform clinical study design by promoting a scientific basis for the selection of an on-treatment biopsy schedule. Future applications of this workflow include identification of tissue properties that may contribute to inter-individual variability, and simulations of novel doses and schedules for combinations of immune-modulating cancer therapies.

Citation Format: Lucy G. Hutchinson, Antoine Soubret, Benjamin Ribba, Jean-Eric Charoin, Alex Phipps, Richard Peck, Oliver Grimm. Optimization of biopsy scheduling in clinical studies of T cell bispecifics through an integrated modeling and simulation, digital pathology and machine learning approach [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2019; 2019 Mar 29-Apr 3; Atlanta, GA. Philadelphia (PA): AACR; Cancer Res 2019;79(13 Suppl):Abstract nr 690.

From waterfall plots to spaghetti plots in early oncology clinical development

Waterfall plots are used to describe changes in tumor size observed in clinical studies. They are frequently used to illustrate the overall drug response in oncology clinical trials because of its simple representation of results. Unfortunately, this visual display suffers a number of limitations including (1) potential misguidance by masking the time dynamics of tumor size, (2) ambiguous labelling of the y-axis, and (3) low data-to-ink ratio. We offer some alternatives to address these shortcomings and recommend moving away from waterfall plots to the benefit of plots showing the individual time profiles of sum of lesion diameters (according to RECIST). The spider plot presents the individual changes in tumor measurements over time relative to baseline tumor burden. Baseline tumor size is a well-known confounding factor of drug effect which has to be accounted for when analyzing data in early clinical trials. While spider plots are conveniently correct for baseline tumor size, they cannot be presented in isolation. Indeed, percentage change from baseline has suboptimal statistical properties (including skewed distribution) and can be overly optimistic in favor of drug efficacy. We argued that plots of raw data (referred to as spaghetti plots) should always accompany spider plots to provide an equipoised illustration of the drug effect on lesion diameters.

Best Practices to Maximize the Use and Reuse of Quantitative and Systems Pharmacology Models: Recommendations From the United Kingdom Quantitative and Systems Pharmacology Network

The lack of standardization in the way that quantitative and systems pharmacology (QSP) models are developed, tested, and documented hinders their reproducibility, reusability, and expansion or reduction to alternative contexts. This in turn undermines the potential impact of QSP in academic, industrial, and regulatory frameworks. This article presents a minimum set of recommendations from the UK Quantitative and Systems Pharmacology Network (UK QSP Network) to guide QSP practitioners seeking to maximize their impact, and stakeholders considering the use of QSP models in their environment.

Models and Machines: How Deep Learning Will Take Clinical Pharmacology to the Next Level

Recent advances in machine learning (ML) have led to enthusiasm about its use throughout the biopharmaceutical industry. The ML methods can be applied to a wide range of problems and have the potential to revolutionize aspects of drug development. The incorporation of ML in modeling and simulation (M&S) has been eagerly anticipated, and in this perspective, we highlight examples in which ML and M&S approaches can be integrated as complementary parts of a clinical pharmacology workflow.

Erratum: First Dark Matter Constraints from a SuperCDMS Single-Charge Sensitive Detector [Phys. Rev. Lett. 121, 051301 (2018)]

This corrects the article DOI: 10.1103/PhysRevLett.121.051301.

First Dark Matter Constraints from a SuperCDMS Single-Charge Sensitive Detector

We present the first limits on inelastic electron-scattering dark matter and dark photon absorption using a prototype SuperCDMS detector having a charge resolution of 0.1 electron-hole pairs (CDMS HVeV, a 0.93 g CDMS high-voltage device). These electron-recoil limits significantly improve experimental constraints on dark matter particles with masses as low as 1  MeV/c^{2}. We demonstrate a sensitivity to dark photons competitive with other leading approaches but using substantially less exposure (0.49 g d). These results demonstrate the scientific potential of phonon-mediated semiconductor detectors that are sensitive to single electronic excitations.

Prediction of the Optimal Dosing Regimen Using a Mathematical Model of Tumor Uptake for Immunocytokine-Based Cancer Immunotherapy

Purpose: Optimal dosing is critical for immunocytokine-based cancer immunotherapy to maximize efficacy and minimize toxicity. Cergutuzumab amunaleukin (CEA-IL2v) is a novel CEA-targeted immunocytokine. We set out to develop a mathematical model to predict intratumoral CEA-IL2v concentrations following various systemic dosing intensities.Experimental Design: Sequential measurements of CEA-IL2v plasma concentrations in 74 patients with solid tumors were applied in a series of differential equations to devise a model that also incorporates the peripheral concentrations of IL2 receptor-positive cell populations (i.e., CD8⁺, CD4⁺, NK, and B cells), which affect tumor bioavailability of CEA-IL2v. Imaging data from a subset of 14 patients were subsequently utilized to additionally predict antibody uptake in tumor tissues.Results: We created a pharmacokinetic/pharmacodynamic mathematical model that incorporates the expansion of IL2R-positive target cells at multiple dose levels and different schedules of CEA-IL2v. Model-based prediction of drug levels correlated with the concentration of IL2R-positive cells in the peripheral blood of patients. The pharmacokinetic model was further refined and extended by adding a model of antibody uptake, which is based on drug dose and the biological properties of the tumor. In silico predictions of our model correlated with imaging data and demonstrated that a dose-dense schedule comprising escalating doses and shortened intervals of drug administration can improve intratumoral drug uptake and overcome consumption of CEA-IL2v by the expanding population of IL2R-positive cells.Conclusions: The model presented here allows simulation of individualized treatment plans for optimal dosing and scheduling of immunocytokines for anticancer immunotherapy. Clin Cancer Res; 24(14); 3325-33. ©2018 AACRSee related commentary by Ruiz-Cerdá et al., p. 3236.

Results from the Super Cryogenic Dark Matter Search Experiment at Soudan

We report the result of a blinded search for weakly interacting massive particles (WIMPs) using the majority of the SuperCDMS Soudan data set. With an exposure of 1690 kg d, a single candidate event is observed, consistent with expected backgrounds. This analysis (combined with previous Ge results) sets an upper limit on the spin-independent WIMP-nucleon cross section of 1.4×10^{-44} (1.0×10^{-44})  cm^{2} at 46  GeV/c^{2}. These results set the strongest limits for WIMP-germanium-nucleus interactions for masses >12  GeV/c^{2}.

Modeling Longitudinal Preclinical Tumor Size Data to Identify Transient Dynamics in Tumor Response to Antiangiogenic Drugs

Experimental evidence suggests that antiangiogenic therapy gives rise to a transient window of vessel normalization, within which the efficacy of radiotherapy and chemotherapy may be enhanced. Preclinical experiments that measure components of vessel normalization are invasive and expensive. We have developed a mathematical model of vascular tumor growth from preclinical time‐course data in a breast cancer xenograft model. We used a mixed‐effects approach for model parameterization, leveraging tumor size data to identify a period of enhanced tumor growth that could potentially correspond to the transient window of vessel normalization. We estimated the characteristics of the window for mice treated with an anti‐VEGF antibody (bevacizumab) or with a bispecific anti‐VEGF/anti‐angiopoietin‐2 antibody (vanucizumab). We show how the mathematical model could theoretically be used to predict how to coordinate antiangiogenic therapy with radiotherapy or chemotherapy to maximize therapeutic effect, reducing the need for preclinical experiments that directly measure vessel normalization parameters.

Effect of Food and Esomeprazole on the Pharmacokinetics of Alectinib, a Highly Selective ALK Inhibitor, in Healthy Subjects

Alectinib, an anaplastic lymphoma kinase (ALK) inhibitor, is approved for treatment of patients with ALK+ non-small cell lung cancer who have progressed, on or are intolerant to, crizotinib. This study assessed the effect of a high-fat meal and the proton pump inhibitor, esomeprazole, on the pharmacokinetics (PK) of alectinib. This was an open-label, 2-group study in healthy subjects. In group 1 (n = 18), subjects were randomly assigned to a 2-treatment (A, fasted conditions; B, following a high-fat meal), 2-sequence (AB or BA) crossover assessment, separated by a 10-day washout. In group 2 (n = 24), subjects were enrolled in a 2-period, fixed-sequence crossover assessment to evaluate the effect of esomeprazole. PK parameters were evaluated for alectinib, its major similarly active metabolite, M4, and the combined exposure of alectinib and M4. Administration of alectinib following a high-fat meal substantially increased the combined exposure of alectinib and M4 to 331% (90%CI, 279%-393%) and 311% (90%CI, 273%-355%) for C_max and AUC_0-∞ , respectively, versus fasted conditions. Coadministration of esomeprazole had no clinically relevant effect on the combined exposure of alectinib and M4. Alectinib should be administered under fed conditions to maximize its bioavailability, whereas no restrictions are required with antisecretory agents.

Clinical Drug-Drug Interactions Through Cytochrome P450 3A (CYP3A) for the Selective ALK Inhibitor Alectinib

The efficacy and safety of alectinib, a central nervous system-active and selective anaplastic lymphoma kinase (ALK) inhibitor, has been demonstrated in patients with ALK-positive (ALK+) non-small cell lung cancer (NSCLC) progressing on crizotinib. Alectinib is mainly metabolized by cytochrome P450 3A (CYP3A) to a major similarly active metabolite, M4. Alectinib and M4 show evidence of weak time-dependent inhibition and small induction of CYP3A in vitro. We present results from 3 fixed-sequence studies evaluating drug-drug interactions for alectinib through CYP3A. Studies NP28990 and NP29042 enrolled 17 and 24 healthy subjects, respectively, and investigated potent CYP3A inhibition with posaconazole and potent CYP3A induction through rifampin, respectively, on the single oral dose pharmacokinetics (PK) of alectinib. A substudy of the global phase 2 NP28673 study enrolled 15 patients with ALK+ NSCLC to determine the effect of multiple doses of alectinib on the single oral dose PK of midazolam, a sensitive substrate of CYP3A. Potent CYP3A inhibition or induction resulted in only minor effects on the combined exposure of alectinib and M4. Multiple doses of alectinib did not influence midazolam exposure. These results suggest that dose adjustments may not be needed when alectinib is coadministered with CYP3A inhibitors or inducers or for coadministered CYP3A substrates.

Absorption, distribution, metabolism and excretion (ADME) of the ALK inhibitor alectinib: results from an absolute bioavailability and mass balance study in healthy subjects

1. Alectinib is a highly selective, central nervous system-active small molecule anaplastic lymphoma kinase inhibitor. 2. The absolute bioavailability, metabolism, excretion and pharmacokinetics of alectinib were studied in a two-period single-sequence crossover study. A 50 μg radiolabelled intravenous microdose of alectinib was co-administered with a single 600 mg oral dose of alectinib in the first period, and a single 600 mg/67 μCi oral dose of radiolabelled alectinib was administered in the second period to six healthy male subjects. 3. The absolute bioavailability of alectinib was moderate at 36.9%. Geometric mean clearance was 34.5 L/h, volume of distribution was 475 L and the hepatic extraction ratio was low (0.14). 4. Near-complete recovery of administered radioactivity was achieved within 168 h post-dose (98.2%) with excretion predominantly in faeces (97.8%) and negligible excretion in urine (0.456%). Alectinib and its major active metabolite, M4, were the main components in plasma, accounting for 76% of total plasma radioactivity. In faeces, 84% of dose was excreted as unchanged alectinib with metabolites M4, M1a/b and M6 contributing to 5.8%, 7.2% and 0.2% of dose, respectively. 5. This novel study design characterised the full absorption, distribution, metabolism and excretion properties in each subject, providing insight into alectinib absorption and disposition in humans.

Vascular phenotype identification and anti-angiogenic treatment recommendation: A pseudo-multiscale mathematical model of angiogenesis

The development of anti-angiogenic drugs for cancer therapy has yielded some promising candidates, but novel approaches for interventions to angiogenesis have led to disappointing results. In addition, there is a shortage of biomarkers that are predictive of response to anti-angiogenic treatments. Consequently, the complex biochemical and physiological basis for tumour angiogenesis remains incompletely understood. We have adopted a mathematical approach to address these issues, formulating a spatially averaged multiscale model that couples the dynamics of VEGF, Ang1, Ang2 and PDGF, with those of mature and immature endothelial cells and pericyte cells. The model reproduces qualitative experimental results regarding pericyte coverage of vessels after treatment by anti-Ang2, anti-VEGF and combination anti-VEGF/anti-Ang2 antibodies. We used the steady state behaviours of the model to characterise angiogenic and non-angiogenic vascular phenotypes, and used mechanistic perturbations representing hypothetical anti-angiogenic treatments to generate testable hypotheses regarding transitions to non-angiogenic phenotypes that depend on the pre-treatment vascular phenotype. Additionally, we predicted a synergistic effect between anti-VEGF and anti-Ang2 treatments when applied to an immature pre-treatment vascular phenotype, but not when applied to a normalised angiogenic pre-treatment phenotype. Based on these findings, we conclude that changes in vascular phenotype are predicted to be useful as an experimental biomarker of response to treatment. Further, our analysis illustrates the potential value of non-spatial mathematical models for generating tractable predictions regarding the action of anti-angiogenic therapies.

New Results from the Search for Low-Mass Weakly Interacting Massive Particles with the CDMS Low Ionization Threshold Experiment

The CDMS low ionization threshold experiment (CDMSlite) uses cryogenic germanium detectors operated at a relatively high bias voltage to amplify the phonon signal in the search for weakly interacting massive particles (WIMPs). Results are presented from the second CDMSlite run with an exposure of 70 kg day, which reached an energy threshold for electron recoils as low as 56 eV. A fiducialization cut reduces backgrounds below those previously reported by CDMSlite. New parameter space for the WIMP-nucleon spin-independent cross section is excluded for WIMP masses between 1.6 and 5.5  GeV/c^{2}.

Challenges and Opportunities for Quantitative Clinical Pharmacology in Cancer Immunotherapy: Something Old, Something New, Something Borrowed, and Something Blue

Cancer immunotherapy (CIT) initiates or enhances the host immune response against cancer. Following decades of development, patients with previously few therapeutic options may now benefit from CIT. Although the quantitative clinical pharmacology (qCP) of previous classes of anticancer drugs has matured during this time, application to CIT may not be straightforward since CIT acts via the immune system. Here we discuss where qCP approaches might best borrow or start anew for CIT.

First direct limits on lightly ionizing particles with electric charge less than e/6

While the standard model of particle physics does not include free particles with fractional charge, experimental searches have not ruled out their existence. We report results from the Cryogenic Dark Matter Search (CDMS II) experiment that give the first direct-detection limits for cosmogenically produced relativistic particles with electric charge lower than e/6. A search for tracks in the six stacked detectors of each of two of the CDMS II towers finds no candidates, thereby excluding new parameter space for particles with electric charges between e/6 and e/200.

Search for low-mass weakly interacting massive particles with SuperCDMS

We report a first search for weakly interacting massive particles (WIMPs) using the background rejection capabilities of SuperCDMS. An exposure of 577 kg days was analyzed for WIMPs with mass <30  GeV/c(2), with the signal region blinded. Eleven events were observed after unblinding. We set an upper limit on the spin-independent WIMP-nucleon cross section of 1.2×10(-42)  cm(2) at 8  GeV/c(2). This result is in tension with WIMP interpretations of recent experiments and probes new parameter space for WIMP-nucleon scattering for WIMP masses <6  GeV/c(2).

Search for low-mass weakly interacting massive particles using voltage-assisted calorimetric ionization detection in the SuperCDMS experiment

SuperCDMS is an experiment designed to directly detect weakly interacting massive particles (WIMPs), a favored candidate for dark matter ubiquitous in the Universe. In this Letter, we present WIMP-search results using a calorimetric technique we call CDMSlite, which relies on voltage-assisted Luke-Neganov amplification of the ionization energy deposited by particle interactions. The data were collected with a single 0.6 kg germanium detector running for ten live days at the Soudan Underground Laboratory. A low energy threshold of 170  eVee (electron equivalent) was obtained, which allows us to constrain new WIMP-nucleon spin-independent parameter space for WIMP masses below 6  GeV/c2.

Silicon detector dark matter results from the final exposure of CDMS II

We report results of a search for weakly interacting massive particles (WIMPS) with the silicon detectors of the CDMS II experiment. This blind analysis of 140.2 kg day of data taken between July 2007 and September 2008 revealed three WIMP-candidate events with a surface-event background estimate of 0.41(-0.08)(+0.20)(stat)(-0.24)(+0.28)(syst). Other known backgrounds from neutrons and 206Pb are limited to <0.13 and <0.08 events at the 90% confidence level, respectively. The exposure of this analysis is equivalent to 23.4 kg day for a recoil energy range of 7-100 keV for a WIMP of mass 10  GeV/c2. The probability that the known backgrounds would produce three or more events in the signal region is 5.4%. A profile likelihood ratio test of the three events that includes the measured recoil energies gives a 0.19% probability for the known-background-only hypothesis when tested against the alternative WIMP+background hypothesis. The highest likelihood occurs for a WIMP mass of 8.6  GeV/c2 and WIMP-nucleon cross section of 1.9×10(-41)  cm2.

A model-based approach to optimize detection of treatment effects in early oncology trials

e13508

Background: Tumor size change from baseline (RECIST) is often used to assess antitumor activity of investigational agents in phase 1 trials, but this measure does not take into account the tumor growth rate (TGR) prior to treatment. TGR could be highly variable in a phase 1 ‘all-comers’ patient population, with a high TGR potentially masking a meaningful treatment effect (TE). Assessing the change in TGR (Mehrara et al, BJC 2011) using historical tumor burden assessments (Gomez-Roca et al, Eur J Cancer 2011) may provide higher sensitivity to true TE (TTE). The objectives of the current study are to formalize a Growth Rate Based Method (GRBM) and to compare, using simulated patients, the ability of GRBM and RECIST assessments to detect and quantify TTE. Methods: The exponential tumor growth model (Claret et al, J Clin Oncol. 2009) was used to simulate the sum of the longest diameters (SLD) individual time courses of 2000 virtual patients under different TGR scenarios: slow, medium, fast and ‘all comers’ (highly variable TGR as often encountered in phase 1). Different sampling designs were simulated wherein tumor assessments with measurement errors were obtained, ranging from 16 to 4 weeks prior to treatment initiation (TI), immediately before TI, and 8 and 16 weeks after TI. TTE was defined as the difference between the simulated SLDs at 16 weeks with and without treatment. GRBM response was defined as the model-predicted difference between the SLDs with and without treatment, as estimated from the simulated samples. Sensitivity (Se) of RECIST or GRBM was defined as the probability of classifying a patient as a RECIST or GRBM >30% reduction when the TTE >30%, and specificity (Sp) as the probability of RECIST or GRBM reduction <30% when TTE <30%. Results: RECIST Se was consistently inferior to GRBM, notably in the all-comers TGR (37% vs 74-89%) scenario. GRBM maintained Se (71-89%) irrespective of TGR whereas RECIST Se degraded significantly with increasing TGR. RECIST Sp was high (97-100%) while GRBM Sp was lower (55-80%) depending on sampling design and TGR. Conclusions: Incorporation of an additional pretreatment tumor assessment by GRBM may augment RECIST by increasing sensitivity to TTE, particularly in a heterogeneous TGR phase 1 setting.

Case studies addressing human pharmacokinetic uncertainty using a combination of pharmacokinetic simulation and alternative first in human paradigms

PF-184298 ((S)-2,3-dichloro-N-isobutyl-N-pyrrolidin-3-ylbenzamide) and PF-4776548 ((3-(4-fluoro-2-methoxy-benzyl)-7-hydroxy-8,9-dihydro-3H,7H-pyrrolo[2,3-c][1,7]naphthyridin-6-one)) are novel compounds which were selected to progress to human studies. Discordant human pharmacokinetic predictions arose from pre-clinical in vivo studies in rat and dog, and from human in vitro studies, resulting in a clearance prediction range of 3 to >20 mL min⁻¹ kg⁻¹ for PF-184298, and 5 to >20 mL min⁻¹ kg⁻¹ for PF-4776548. A package of work to investigate the discordance for PF-184298 is described. Although ultimately complementary to the human pharmacokinetic data in characterising the disposition of PF-184298 in humans, these data did not provide any further confidence in pharmacokinetic prediction. A fit for purpose human pharmacokinetic study was conducted for each compound, with an oral pharmacologically active dose for PF-184298, and an intravenous and oral microdose for PF-4776548. This provided a relatively low cost, clear decision making approach, resulting in the termination of PF-4776548 and further progression of PF-184298. A retrospective analysis of the data showed that, if the tools had been available at the time, the pharmacokinetics of PF-184298 in human could have been predicted from a population based simulation tool in combination with physicochemical properties and in vitro human intrinsic clearance.

Results from a low-energy analysis of the CDMS II germanium data

We report results from a reanalysis of data from the Cryogenic Dark Matter Search (CDMS II) experiment at the Soudan Underground Laboratory. Data taken between October 2006 and September 2008 using eight germanium detectors are reanalyzed with a lowered, 2 keV recoil-energy threshold, to give increased sensitivity to interactions from weakly interacting massive particles (WIMPs) with masses below ∼10  GeV/c(2). This analysis provides stronger constraints than previous CDMS II results for WIMP masses below 9  GeV/c(2) and excludes parameter space associated with possible low-mass WIMP signals from the DAMA/LIBRA and CoGeNT experiments.

Sigmoidoscopy and Colonoscopy are Inversely Associated with Both Left- and Right-sided Advanced Adenomas

Background: The U.S. Preventive Services Task Force recommends routine colorectal cancer screening starting at age 50; however, evidence is insufficient to recommend one screening method over the other methods. Common colorectal cancer screening methods include fecal occult blood tests (FOBT), sigmoidoscopy, and colonoscopy.

Objective: We examined the association between advanced adenomas, known precursors to colorectal cancer, and history of screening by FOBT, sigmoidoscopy, and colonoscopy.

Methods: We conducted a case-control study of advanced colorectal adenomatous polyps, which included 306 advanced adenoma cases and 2,287 controls without advanced adenomas, aged 24 to 79, who received an index colonoscopy from 1998 to 2007. All participants completed a questionnaire covering screening history and other colorectal cancer risk factors. Participants with polyps underwent a standard pathology review; adenomas ≥10 mm or at with at least 20% villous components were considered advanced adenomas. We used separate logistic regression models to estimate adjusted odds ratios (ORs) and 95% CIs for the associations between advanced adenomas and previous FOBT, sigmoidoscopy, and colonoscopy at least 2 years before the index colonoscopy.

Results: Each screening method was associated with decreased odds of advanced adenomas; however, only associations for sigmoidoscopy and colonoscopy were statistically significant. The OR for advanced adenomas, comparing participants with at least one previous FOBT to those who had never had FOBT, was 0.82 (95% CI: 0.63–1.06); for sigmoidoscopy, OR = 0.59 (95% CI: 0.46–0.77); and for colonoscopy, OR = 0.53 (95% CI: 0.39–0.72). These associations were similar with respect to left- and right-sided advanced adenomas.

Discussion: Our findings suggest colonoscopy and sigmoidoscopy have similar inverse associations with advanced adenomas in both left and right sides of the colon. This is in contrast to studies of colorectal cancer that suggest endoscopy is associated with a decreased risk for tumors of the left but not right side. The discrepancy between our findings and these studies may be explained if right-sided colorectal cancers are more likely to have nonadenoma precursors that are overlooked by screening.

Evaluation of ventricular arrhythmias in early clinical pharmacology trials and potential consequences for later development

This white paper, prepared by members of the Cardiac Safety Research Consortium, discusses several important issues regarding the evaluation of ventricular arrhythmias in early clinical pharmacology trials and their potential consequences for later clinical drug development. Ventricular arrhythmias are infrequent but potentially important medical events whose occurrence in early clinical pharmacology trials can dramatically increase safety concerns. Given the increasing concern with all potential safety signals and the resultant more extensive electrocardiographic monitoring of subjects participating in early phase trials, an important question must be addressed: Are relatively more frequent observations of ventricular arrhythmias related simply to more extensive monitoring, or are they genuinely related to the drug under development? The discussions in this paper provide current thinking and suggestions for addressing this question.

Demonstration of a wireless, self-powered, electroacoustic liner system

This paper demonstrates the system operation of a self-powered active liner for the suppression of aircraft engine noise. The fundamental element of the active liner system is an electromechanical Helmholtz resonator (EMHR), which consists of a Helmholtz resonator with one of its rigid walls replaced with a circular piezoceramic composite plate. For this system demonstration, two EMHR elements are used, one for acoustic impedance tuning and one for energy harvesting. The EMHR used for acoustic impedance tuning is shunted with a variable resistive load, while the EMHR used for energy harvesting is shunted to a flyback power converter and storage element. The desired acoustic impedance conditions are determined externally, and wirelessly transmitted to the liner system. The power for the receiver and the impedance tuning circuitry in the liner are supplied by the harvested energy. Tuning of the active liner is demonstrated at three different sound pressure levels (148, 151, and 153 dB) in order to show the robustness of the energy harvesting and storage system. An acoustic tuning range of approximately 200 Hz is demonstrated for each of the three available power levels.