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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.

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Supplementary Figure S1: Left: CEA expression by immuno-histochemistry in the LS174T tumor mouse model: homogeneous cytoplasmic antigen distribution. Right: CEA expression in one of the treated patients (colorectal cancer): heterogeneous cytoplasmic antigen distribution with polarized apical accumulation.

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 AACR.See related commentary by Ruiz-Cerdá et al., p. 3236

Supplemental Table S2: Model parameter estimates. For model equations, refer to supplemental material.

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. 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. 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%. 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.

SummaryBackground: 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.

The spleen, a secondary lymphoid tissue (SLT), has an important role in generation of adaptive immune responses. Although splenectomy remains a common procedure, recent studies reported poor prognosis and increased risk of haematological malignancies in asplenic patients. The high baseline trafficking of T lymphocytes to splenic tissue suggests splenectomy may lead to loss of blood-borne malignant immunosurveillance that is not compensated for by the remaining SLT. To date, no quantitative analysis of the impact of splenectomy on the human T cell trafficking dynamics and tissue localisation has been reported. We developed a quantitative computational model that describes organ distribution and trafficking of human lymphocytes to explore the likely impact of splenectomy on immune cell distributions. In silico splenectomy resulted in an average reduction of T cell numbers in SLT by 35% (95%CI 0.12–0.97) and a comparatively lower, 9% (95%CI 0.17–1.43), mean decrease of T cell concentration in SLT. These results suggest that the surveillance capacity of the remaining SLT insufficiently compensates for the absence of the spleen. This may, in part, explain haematological malignancy risk in asplenic patients and raises the question of whether splenectomy has a clinically meaningful impact on patient responses to immunotherapy.

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.

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.

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.

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 AACR. See related commentary by Ruiz-Cerdá et al., p. 3236

We present the details of an autonomous power-on-demand fuel cell system for operating remote sensor packages currently being developed by the US Navy. The system is designed to extend mission lifetime six-fold by replacing non-rechargeable primary batteries with stored hydrogen and a fuel cell. This system utilizes hydrogen gas generated through a reaction between the solid chemical sodium borohydride and water. The chemical delivery mechanism utilizes feedback from the fuel cell output voltage in order to determine the amount of sodium borohydride to be metered into the reaction vessel. The fuel cell can power the load directly or indirectly through a small rechargeable battery. A boost converter is used to increase the voltage output and an integrated power path controller sets whether load power is delivered via the fuel cell or battery. Two methods for chemical delivery are currently under investigation. The deployed system will increase battlefield persistence by greatly extending the lifetime of existing sensors while reducing risk of harm to the warfighter.

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.

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.

The anaplastic lymphoma kinase (ALK) inhibitor alectinib is an effective treatment for ALK-positive non-small-cell lung cancer. This bioequivalence study evaluated the in vivo performance of test 3 formulations with the reduced wetting agent sodium lauryl sulfate (SLS) content. This randomized, 4-period, 4-sequence, crossover study compared alectinib (600 mg) as 25%, 12.5%, and 3% SLS hard capsule formulations with the reference 50% SLS clinical formulation in healthy subjects under fasted conditions (n = 49), and following a high-fat meal (n = 48). Geometric mean ratios and 90% confidence intervals (CIs) for Cmax , AUC0-last , and AUC0-∞ of alectinib, its major active metabolite, M4, and alectinib plus M4 were determined for the test formulations versus the reference formulation. Bioequivalence was concluded if the 90%CIs were within the 80% to 125% boundaries. The 25% SLS formulation demonstrated bioequivalence to the reference 50% SLS formulation for Cmax , AUC0-last , and AUC0-∞ of alectinib, M4, and alectinib plus M4 under both fasted and fed conditions. Further reductions in SLS content (12.5% and 3% SLS) did not meet the bioequivalence criteria. Cross-group comparisons showed an approximately 3-fold positive food effect. Reducing SLS to 25% resulted in a formulation that is bioequivalent to the current 50% SLS formulation used in alectinib pivotal trials.

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 Cmax and AUC0-∞ , 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.

In rural areas, networkable environmental monitoring equipment is often used to provide continuous, real-time information without the need for a dedicated operator for maintenance or monitoring. However, power and energy availability are often controlling factors for operational lifetime when these systems are put on location. In these situations, batteries are often used as the main energy storage medium and require servicing or replacement when exhausted. This can lead high costs related to man-power and logistics to return and maintain the equipment at those locations. Sodium borohydride hydrolysis was once looked at as a promising way to store hydrogen for use in PEM fuel cells. Concerns regarding hydrogen storage capacity and recyclability of reaction products have prevented its use in larger transportation or energy storage applications. However, the energy density of sodium borohydride still makes the reaction suitable for specific applications where reuse is not needed. As such, present here a system utilizing solid sodium borohydride as a storage medium to meet on demand power needs of these types of systems. The system utilizes a PEM fuel cell integrated with an electro-mechanical system to control chemical metering and power management. We have previously shown results from our initial testing with solid sodium borohydride using commercial-off-the-shelf tablets for generating hydrogen when added to a reaction vessel containing water. Conceptually, a tablet would be introduced to the reaction vessel whenever additional hydrogen gas would be required. Operating in this manner would require good stability and reproducibility over multiple tablet reaction events. Initial testing showed good reaction rates when a cobalt catalyst was employed, either pre-doped into the solid tablet mixture or when the catalyst was pre-mixed with the water in the reaction vessel. Analysis of the gas mixture showed high quality hydrogen gas flows could be produced and sent to the PEM fuel cell for power production. However, concerns with the stability, safety, and handling of the catalyst have led to a need to identify a more green chemistry approach. We present here an alternative approach using common mineral and organic acids as hydrolysis accelerators that could be considered a greener approach to hydrogen generation for remote power applications. These include hydrochloric acid, phosphoric acid, citric acid, and acetic acid. Initial testing shows good reproducibility over multiple hydrogen generation events and reasonable reaction control. A comparison of hydrogen yield and gas composition is also shown. Finally, cost comparison between these accelerators is performed in order to assess their suitability in practical application.

The emergence of genetic data linking Nav1.7 sodium channel over- and under- expression to human pain signalling has led to an interest in the treatment of chronic pain through inhibition of Nav1.7 channels. We describe the pharmacokinetic (PK) results of a clinical microdose study performed with four potent and selective Nav1.7 inhibitors and the subsequent modelling resulting in the selection of a single compound to explore Nav1.7 pharmacology at higher doses. A clinical microdose study to investigate the intravenous and oral PK of four compounds (PF-05089771, PF-05150122, PF-05186462 and PF-05241328) was performed in healthy volunteers. PK parameters were derived via noncompartmental analysis. A physiologically-based PK (PBPK) model was used to predict exposure and multiples of Nav1.7 50 % inhibitory concentration (IC50) for each compound at higher doses. Plasma clearance, volume of distribution and bioavailability ranged from 45 to 392 mL/min/kg, 13 to 36 L/kg and 38 to 110 %, respectively. The PBPK model for PF-05089771 predicted a 1 g oral dose would be required to achieve exposures of approximately 12× Nav1.7 IC50 at maximum concentration (C max), and approximately 3× IC50 after 12 h (minimum concentration [C min] for a twice-daily regimen). Lower multiples of Nav1.7 IC50 were predicted with the same oral doses of PF-05150122, PF-05186462, and PF-05241328. In a subsequent single ascending oral dose clinical study, the predictions for PF-05089771 compared well with observed data. Based on the human PK data obtained from the microdose study and subsequent modelling, PF-05089771 provided the best opportunity to explore Nav1.7 blockade for the treatment of acute or chronic pain conditions.

Alectinib is a selective anaplastic lymphoma kinase (ALK) inhibitor approved for the treatment of ALK-positive non-small cell lung cancer. Alectinib and its major active metabolite M4 exhibited drug-drug interaction (DDI) potential through cytochrome P450 (CYP) enzymes CYP3A4 and CYP2C8 in vitro. Clinical relevance of the DDI risk was investigated as part of a rapid development program to fulfill the breakthrough therapy designation. Therefore, a strategy with a combination of physiologically based pharmacokinetic (PBPK) modeling and limited clinical trials focused on generating informative data for modeling was made to ensure extrapolation ability of DDI risk. The PBPK modeling has provided mechanistic insight into the low victim DDI risk of alectinib through CYP3A4 by a novel two-dimensional analysis for fmCYP3A4 and FG , and demonstrated negligible CYPs 2C8 and 3A4 enzyme-modulating effects at clinically relevant exposure. This work supports that alectinib can be prescribed without dose adjustment for CYP-mediated DDI liabilities.

Unmanned and autonomous systems are used extensively for Navy missions. While most of these systems are able to operate without human interaction, limitations in power capacity place a fundamental limit on overall system autonomy. Inductive wireless power transfer provides an effective way to enhance unmanned systems (vehicles, sensors, etc.). This report examines different methods for efficiently controlling power modulation and determining which side, transmitter or receiver, commands power needs. The need for charging a wide array of systems and bidirectional power capabilities are considered, which point toward a need of underwater wireless power standards, a framework of which is proposed.

The capability of bi-directional, underwater power transfer (both sending and receiving power) increases the functionality of underwater vehicles by allowing them to be charged and provide charge wirelessly to other systems without leaving the water. To minimize the footprint of the charging circuitry, a single transistor-based full-bridge circuit can be used to either send or receive power. This work focuses on the operation of the circuit in power receive mode, as an active rectifier. An algorithm common for active rectification is presented, and the effects of non-idealities on the timing control and efficiency is presented through experimental results.

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.

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.

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

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.

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.

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.

For piezoelectric-based, vibration energy harvesting systems, a simplified resonant model is typically used to represent the piezoelectric transducer. Furthermore, the total amount of harvested power is calculated assuming an ideal and lossless power converter. A coupled, system-level model is developed that includes parasitic losses in the power converter for a system comprised of a cantilevered transducer beam and pulsed resonant converter. The accuracy of the system-level model is validated with experimental data, and it is shown that the simplified resonant model underpredicts the total harvested power by approximately 30% for the implemented system. In addition to capturing the electrical domain behavior of the system, the system-level model is also shown to accurately predict the effect of energy harvesting on the beam mechanics.

Objective. The aim of this study was to determine the pharmacokinetics of pregabalin in a patient with malabsorption secondary to celiac disease and compare the findings with the data available from pre-existing studies in healthy volunteer controls. Methods. A 39-year-old man consented to a 24-hour pregabalin assay with sequential pre and post-dose blood sampling. Results. The blood levels measured in this subject were no different to healthy male volunteers enrolled in previous studies. Conclusion. Although the results obtained are encouraging, the wide spectrum of effects and interactions of various drugs in malabsorption would suggest that therapy of any kind should be considered at individual level and monitored with blood assays. Wiley Periodicals, Inc.

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.

Cytochrome P450 3A4 (CYP3A4) is the most important enzyme in drug metabolism and because it is the most frequent target for pharmacokinetic drug-drug interactions (DDIs) it is highly desirable to be able to predict CYP3A4-based DDIs from in vitro data. In this study, the prediction of clinical DDIs for 30 drugs on the pharmacokinetics of midazolam, a probe substrate for CYP3A4, was done using in vitro inhibition, inactivation, and induction data. Two DDI prediction approaches were used, which account for effects at both the liver and intestine. The first was a model that simultaneously combines reversible inhibition, time-dependent inactivation, and induction data with static estimates of relevant in vivo concentrations of the precipitant drug to provide point estimates of the average magnitude of change in midazolam exposure. This model yielded a success rate of 88% in discerning DDIs with a mean -fold error of 1.74. The second model was a computational physiologically based pharmacokinetic model that uses dynamic estimates of in vivo concentrations of the precipitant drug and accounts for interindividual variability among the population (Simcyp). This model yielded success rates of 88 and 90% (for "steady-state" and "time-based" approaches, respectively) and mean -fold errors of 1.59 and 1.47. From these findings it can be concluded that in vivo DDIs for CYP3A4 can be predicted from in vitro data, even when more than one biochemical phenomenon occurs simultaneously.

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.

A self-powered wireless hydrogen sensor node has been designed and developed from a system level approach. By using multi-source energy harvesting circuitry such as scavenged or “reclaimed” energy from light emitting and vibrational sources as the source of power for commercial low power microcontrollers, amplifiers, and RF transmitters, the sensor node is capable of conditioning and deciphering the output of hydrogen sensitive ZnO nanorods sensors. Upon the detection of a discernible amount of hydrogen, the system will ‘wake’ from an idle state to create a wireless data communication link to relay the detection of hydrogen to a central monitoring station. Two modes of operation were designed for the use of hydrogen detection. The first mode would sense for the presence of hydrogen above a set threshold, and alert a central monitoring station of the detection of significant levels of hydrogen. In the second mode of operation, actual hydrogen concentrations starting as low as 10 ppm are relayed to the receiver to track the amount of hydrogen present.

This paper presents a characterization of the thermal effects and marine fouling on an undersea wireless power transfer system. The coils used in wireless power transfer experience elevated temperatures due to the resistive losses in the wire. Several different coating strategies to both protect the coils against seawater and dissipate the generated heat are investigated. In addition, the rise in temperature can increase the likelihood of marine bio-fouling on the exposed surfaces of the coils. A study of bio-fouling on the wireless power transfer coils and whether there might be increased microbial growth as a result of the power transfer is also explored.

This paper presents the development and implementation of an inductive, underwater wireless power transfer system for use with unmanned underwater vehicles (UUVs). Specifically, the design and fabrication of power transfer coils and power electronics is provided for a system capable of providing 75W to a load. At small standoff distances (

This report describes the thermal effects and marine fouling on an undersea wireless power transfer system. The coils used in this wireless power transfer (WPT) experience elevated temperatures because of the resistive losses in the wire. Urethane and epoxy prevent water intrusion, but are thermal insulators and can lead to coil failure. Several different coating strategies to both protect the coils against seawater and dissipate the generated heat are investigated. In addition, the rise in temperature can increase the likelihood of marine biofouling on the exposed coil surfaces. A biofouling study on the wireless power transfer coils and whether there might be increased microbial growth as a result of the power transfer is also explored. The main benefit to the study provided here is to begin to gain an understanding of the effects thermal and marine fouling would have on WPT efficiency. The analysis will show that handling the heat should be a priority when implementing a high-power WPT system for unmanned underwater vehicles (UUVs). Coils must be carefully designed to dissipate the heat buildup but still maintain good transfer efficiency. Fortunately, the analysis will also show that the elevated temperatures on the coils is at a biocidal level, effectively killing off any marine microbes.