Deep-learning optical flow for measuring velocity fields from experimental data.

Deep learning-based optical flow (DLOF) extracts features in adjacent video frames with deep convolutional neural networks. It uses those features to estimate the inter-frame motions of objects. We evaluate the ability of optical flow to quantify the spontaneous flows of microtubule (MT)-based active nematics under different labeling conditions, and compare its performance to particle image velocimetry (PIV). We obtain flow velocity ground truths either by performing semi-automated particle tracking on samples with sparsely labeled filaments, or from passive tracer beads. DLOF produces more accurate velocity fields than PIV for densely labeled samples. PIV cannot reliably distinguish contrast variations at high densities, particularly along the nematic director. DLOF overcomes this limitation. For sparsely labeled samples, DLOF and PIV produce comparable results, but DLOF gives higher-resolution fields. Our work establishes DLOF as a versatile tool for measuring fluid flows in a broad class of active, soft, and biophysical systems.

A machine learning approach to robustly determine director fields and analyze defects in active nematics.

Active nematics are dense systems of rodlike particles that consume energy to drive motion at the level of the individual particles. They exist in natural systems like biological tissues and artificial materials such as suspensions of self-propelled colloidal particles or synthetic microswimmers. Active nematics have attracted significant attention in recent years due to their spectacular nonequilibrium collective spatiotemporal dynamics, which may enable applications in fields such as robotics, drug delivery, and materials science. The director field, which measures the direction and degree of alignment of the local nematic orientation, is a crucial characteristic of active nematics and is essential for studying topological defects. However, determining the director field is a significant challenge in many experimental systems. Although director fields can be derived from images of active nematics using traditional imaging processing methods, the accuracy of such methods is highly sensitive to the settings of the algorithms. These settings must be tuned from image to image due to experimental noise, intrinsic noise of the imaging technology, and perturbations caused by changes in experimental conditions. This sensitivity currently limits automatic analysis of active nematics. To address this, we developed a machine learning model for extracting reliable director fields from raw experimental images, which enables accurate analysis of topological defects. Application of the algorithm to experimental data demonstrates that the approach is robust and highly generalizable to experimental settings that are different from those in the training data. It could be a promising tool for investigating active nematics and may be generalized to other active matter systems.

Experimental factors that impact CaV1.2 channel pharmacology-Effects of recording temperature, charge carrier, and quantification of drug effects on the step and ramp currents elicited by the "step-step-ramp" voltage protocol.

BACKGROUND AND PURPOSE: CaV1.2 channels contribute to action potential upstroke in pacemaker cells, plateau potential in working myocytes, and initiate excitation-contraction coupling. Understanding drug action on CaV1.2 channels may inform potential impact on cardiac function. However, literature shows large degrees of variability between CaV1.2 pharmacology generated by different laboratories, casting doubt regarding the utility of these data to predict or interpret clinical outcomes. This study examined experimental factors that may impact CaV1.2 pharmacology. EXPERIMENTAL APPROACH: Whole cell recordings were made on CaV1.2 overexpression cells. Current was evoked using a "step-step-ramp" waveform that elicited a step and a ramp current. Experimental factors examined were: 1) near physiological vs. room temperature for recording, 2) drug inhibition of the step vs. the ramp current, and 3) Ca2+ vs. Ba2+ as the charge carrier. Eight drugs were studied. KEY RESULTS: CaV1.2 current exhibited prominent rundown, exquisite temperature sensitivity, and required a high degree of series resistance compensation to optimize voltage control. Temperature-dependent effects were examined for verapamil and methadone. Verapamil's block potency shifted by up to 4X between room to near physiological temperature. Methadone exhibited facilitatory and inhibitory effects at near physiological temperature, and only inhibitory effect at room temperature. Most drugs inhibited the ramp current more potently than the step current-a preference enhanced when Ba2+ was the charge carrier. The slopes of the concentration-inhibition relationships for many drugs were shallow, temperature-dependent, and differed between the step and the ramp current. CONCLUSIONS AND IMPLICATIONS: All experimental factors examined affected CaV1.2 pharmacology. In addition, whole cell CaV1.2 current characteristics-rundown, temperature sensitivity, and impact of series resistance-are also factors that can impact pharmacology. Drug effects on CaV1.2 channels appear more complex than simple pore block mechanism. Normalizing laboratory-specific approaches is key to improve inter-laboratory data reproducibility. Releasing original electrophysiology records is essential to promote transparency and enable the independent evaluation of data quality.

Bending stiffness characterization of Bacillus subtilis' flagellar filament.

The filament of a bacterial flagellum is a tube-like organelle made of a single protein-flagellin-and assembled into multiple polymorphic forms. The filament can be further discretized into four subunit domains (D0, D1, D2, and D3) along the radial direction. However, it remains unclear which subunit domain plays an important role in regulating the rigidity of the filament. In this article, we address how the absence of two outer subunit domains (D2 and D3) affects the bending stiffness of the bacterium B. subtilis' flagellar filament. We first shear off flagellar filaments from the cell body, anchor one of its ends to the wall of a microfluidic channel, and correlate the elongation of the filament with the driving background flow. A numerical model is then applied to determine the bending stiffness of the filament. We find that the bending stiffness does not change drastically when the filament transforms from normal to hyperextended forms, which is estimated to be 2-3 pN⋅µm2. Furthermore, B. subtilis' flagellar filament has similar bending stiffness to Salmonella's, although the radius of the former is almost half of that of the latter, suggesting that the rigidity comes from the inner D0 and D1 subunit domains.

Mechanisms of QT prolongation by buprenorphine cannot be explained by direct hERG channel block.

Buprenorphine is a µ-opioid receptor (MOR) partial agonist used to manage pain and addiction. QTC prolongation that crosses the 10 msec threshold of regulatory concern was observed at a supratherapeutic dose in two thorough QT studies for the transdermal buprenorphine product BUTRANS®. Because QTC prolongation can be associated with Torsades de Pointes (TdP), a rare but potentially fatal ventricular arrhythmia, these results have led to further investigation of the electrophysiological effects of buprenorphine. Drug-induced QTC prolongation and TdP are most commonly caused by acute inhibition of hERG current (IhERG) that contribute to the repolarizing phase of the ventricular action potentials (APs). Concomitant inhibition of inward late Na+ (INaL) and/or L-type Ca2+ (ICaL) current can offer some protection against proarrhythmia. Therefore, we characterized the effects of buprenorphine and its major metabolite norbuprenorphine on cardiac hERG, Ca2+, and Na+ ion channels, as well as cardiac APs. For comparison, methadone, a MOR agonist associated with QTC prolongation and high TdP risk, and naltrexone and naloxone, two opioid receptor antagonists, were also studied. Whole cell recordings were performed at 37°C on cells stably expressing hERG, CaV1.2, and NaV1.5 proteins. Microelectrode array (MEA) recordings were made on human induced pluripotent stem cell-derived cardiomyocytes (iPSC-CMs). The results showed that buprenorphine, norbuprenorphine, naltrexone, and naloxone had no effect on IhERG, ICaL, INaL, and peak Na+ current (INaP) at clinically relevant concentrations. In contrast, methadone inhibited IhERG, ICaL, and INaL. Experiments on iPSC-CMs showed a lack of effect for buprenorphine, norbuprenorphine, naltrexone, and naloxone, and delayed repolarization for methadone at clinically relevant concentrations. The mechanism of QTC prolongation is opioid moiety-specific. This remains undefined for buprenorphine, while for methadone it involves direct hERG channel block. There is no evidence that buprenorphine use is associated with TdP. Whether this lack of TdP risk can be generalized to other drugs with QTC prolongation not mediated by acute hERG channel block warrants further study.

Catheter-related right atrial thrombosis.

INTRODUCTION: Catheter-related right atrial thrombosis is an under-recognized complication of central venous catheter placement. We performed a retrospective review, characterizing clinical aspects of catheter-related right atrial thrombosis (CRAT). METHODS: To identify cases, a literature search was conducted in PubMed and additional items selected by review of related items and bibliography review. Key clinical data were extracted and analyzed both in total and as stratified by hemodialysis versus non-hemodialysis groups. RESULTS: A total of 68 catheter-related right atrial thrombosis events were reported in 63 patients (five recurrences, of which 4 involved catheter left in place following primary treatment). Median (interquartile range) time to CRAT diagnosis was longer among hemodialysis patients - 12 (4.0-24.0) weeks compared to 5.5 (1.8-16.1) weeks among non-hemodialysis patients. The most common presentations were asymptomatic in 16/68 (23.5%), fever/sepsis in 21/68 (30.9%), pulmonary embolism in 11/68 (16.2%), catheter dysfunction in 8/68 (11.8%), dyspnea in 8/68 (11.8%), and new murmur or valvular dysfunction in 8/68 (11.8%) patients. Primary treatment selection was anticoagulation in 33/68 (48.5%), surgical thrombectomy in 17/68 (25.0%), thrombolysis in 12/68 (17.6%), or no active therapy in 6/68 (8.8%) patients. Primary treatment failure for anticoagulation and thrombolysis was 27.3% and 33.3%, respectively. The most common rescue therapy was surgical thrombectomy, ultimately resulting in an overall rate of 26/62 (41.9%). Overall, per-patient mortality was 13/63 (20.6%). Intracardiac tip position - 27/34 (79.4%) - overshadowed thrombophilia - 16/63 (25.4%) - as a risk factor for CRAT. CONCLUSION: Catheter-related right atrial thrombosis is an underdiagnosed complication of central venous catheter placement. For the hemodialysis population, a fistula-first approach is advocated. While many instances were asymptomatic, the development of unexplained fever, dyspnea, catheter dysfunction, or new murmur should trigger a search for this complication.

Drug potency on inhibiting late Na+ current is sensitive to gating modifier and current region where drug effects were measured.

INTRODUCTION: Cardiac late Na+ current (INaL) contributes to ventricular action potential duration. Pathological increase in INaL is arrhythmogenic, and inhibition of INaL offers protection against ventricular repolarization disturbance. Recently, two INaL datasets generated by different laboratories that assessed current inhibition by a panel of clinical drugs as a part of the Comprehensive in vitro Proarrhythmia Assay (CiPA) initiative were published. The results revealed a surprising degree of data variability despite of the use of a standardized voltage protocol. This study investigated whether remaining procedural differences related to experimental methods and data analysis associated with these datasets can produce differences in INaL pharmacology. METHODS: Whole cell voltage clamp recordings were performed on cells expressing NaV1.5 α- and ß1-subunits to study: 1) the impact of gating modifiers used to augment INaL (ATX-II vs. veratridine), internal solution composition (with vs. without ATP and GTP), and recording temperature (23 °C vs 37 °C) on stability of INaL measured across the duration of a patch clamp experiment; 2) mechanisms of each gating modifier on Na+ channels; and 3) effects of six drugs (lidocaine, mexiletine, chloroquine, ranolazine, ritonavir, and verapamil) on INaL induced by either gating modifier. RESULTS: Stability of INaL is affected by the choice of gating modifier, presence of nucleotides in the internal solution, and recording temperature. ATX-II and veratridine produced different changes in Na+ channel gating, inducing mechanistically distinct INaL. Drug potencies on inhibiting INaL were dependent on the choice of gating modifier and current region where drug effects were measured. DISCUSSION: INaL pharmacology can be impacted by all experimental factors examined in this study. The effect of gating modifier and current region used to quantify drug inhibition alone led to 30× difference in half inhibitory concentration (IC50) for ritonavir, demonstrating that substantial difference in drug inhibition can be produced. Drug potencies on inhibiting INaL derived from different patch clamp studies may thus not be generalizable. For INaL pharmacology to be useful for in silico modeling or interpreting drug-induced changes in cardiac action potentials or ECG, standardizing INaL experimental procedures including data analysis methods is necessary to minimize data variability.

Assessment of an In Silico Mechanistic Model for Proarrhythmia Risk Prediction Under the CiPA Initiative.

The International Council on Harmonization (ICH) S7B and E14 regulatory guidelines are sensitive but not specific for predicting which drugs are pro-arrhythmic. In response, the Comprehensive In Vitro Proarrhythmia Assay (CiPA) was proposed that integrates multi-ion channel pharmacology data in vitro into a human cardiomyocyte model in silico for proarrhythmia risk assessment. Previously, we reported the model optimization and proarrhythmia metric selection based on CiPA training drugs. In this study, we report the application of the prespecified model and metric to independent CiPA validation drugs. Over two validation datasets, the CiPA model performance meets all pre-specified measures for ranking and classifying validation drugs, and outperforms alternatives, despite some in vitro data differences between the two datasets due to different experimental conditions and quality control procedures. This suggests that the current CiPA model/metric may be fit for regulatory use, and standardization of experimental protocols and quality control criteria could increase the model prediction accuracy even further.

Uncertainty Quantification Reveals the Importance of Data Variability and Experimental Design Considerations for in Silico Proarrhythmia Risk Assessment.

The Comprehensive in vitro Proarrhythmia Assay (CiPA) is a global initiative intended to improve drug proarrhythmia risk assessment using a new paradigm of mechanistic assays. Under the CiPA paradigm, the relative risk of drug-induced Torsade de Pointes (TdP) is assessed using an in silico model of the human ventricular action potential (AP) that integrates in vitro pharmacology data from multiple ion channels. Thus, modeling predictions of cardiac risk liability will depend critically on the variability in pharmacology data, and uncertainty quantification (UQ) must comprise an essential component of the in silico assay. This study explores UQ methods that may be incorporated into the CiPA framework. Recently, we proposed a promising in silico TdP risk metric (qNet), which is derived from AP simulations and allows separation of a set of CiPA training compounds into Low, Intermediate, and High TdP risk categories. The purpose of this study was to use UQ to evaluate the robustness of TdP risk separation by qNet. Uncertainty in the model parameters used to describe drug binding and ionic current block was estimated using the non-parametric bootstrap method and a Bayesian inference approach. Uncertainty was then propagated through AP simulations to quantify uncertainty in qNet for each drug. UQ revealed lower uncertainty and more accurate TdP risk stratification by qNet when simulations were run at concentrations below 5× the maximum therapeutic exposure (Cmax). However, when drug effects were extrapolated above 10× Cmax, UQ showed that qNet could no longer clearly separate drugs by TdP risk. This was because for most of the pharmacology data, the amount of current block measured was <60%, preventing reliable estimation of IC50-values. The results of this study demonstrate that the accuracy of TdP risk prediction depends both on the intrinsic variability in ion channel pharmacology data as well as on experimental design considerations that preclude an accurate determination of drug IC50-values in vitro. Thus, we demonstrate that UQ provides valuable information about in silico modeling predictions that can inform future proarrhythmic risk evaluation of drugs under the CiPA paradigm.

Corrigendum: Optimization of an In silico Cardiac Cell Model for Proarrhythmia Risk Assessment.

[This corrects the article on p. 616 in vol. 8, PMID: 28878692.].

The impact of gender, race, socioeconomic status, and treatment on outcomes in esophageal cancer: A population-based analysis.

BACKGROUND: African Americans and Hispanics are reported to have higher mortality from esophageal cancer (EC) than Caucasians. In this study, we analyzed the independent effects of race, gender, treatment, and socioeconomic status (SES) on overall survival (OS). METHODS: Data for all EC cases between 2004 and 2010 with follow-up through 2012 were obtained from the California Cancer Registry. We conducted descriptive analyses of clinical variables and survival analyses by Kaplan-Meier and Cox proportional hazards methods. RESULTS: African Americans and Hispanics were more likely to be in the lower SES strata and less likely to receive surgery than Caucasians in this cohort. The proportion of patients receiving chemotherapy and radiotherapy was similar across different racial/ethnic groups. After adjustment for stage, grade, histology, treatments, and SES in multivariate analyses, the mortality risk in African Americans (hazard ratio [HR] 0.96, 95% confidence interval [CI] 0.85-1.07) and Hispanics (HR 0.96, 95% CI 0.89-1.07) did not differ from Caucasians (HR = 1.00, referent), with histology, SES, and surgery largely accounting for unadjusted OS differences. We also observed that African American men had higher adjusted risk of death relative to Caucasian men (HR 1.24, 95% CI 1.07-1.42), but this effect was not observed for African American women compared to Caucasian women (HR 1.12, 95% CI 0.94-1.35). CONCLUSIONS: Race is not an independent risk factor for OS in our population-based analysis of EC cases. Rather, observed differences in OS by race/ethnicity result from differences in cancer histology, SES, surgery, and gender. Our findings support further health disparities research for this disease.

Physician Beware: Severe Cyanide Toxicity from Amygdalin Tablets Ingestion.

Despite the risk of cyanide toxicity and lack of efficacy, amygdalin is still used as alternative cancer treatment. Due to the highly lethal nature of cyanide toxicity, many patients die before getting medical care. Herein, we describe the case of a 73-year-old female with metastatic pancreatic cancer who developed cyanide toxicity from taking amygdalin. Detailed history and physical examination prompted rapid clinical recognition and treatment with hydroxocobalamin, leading to resolution of her cyanide toxicity. Rapid clinical diagnosis and treatment of cyanide toxicity can rapidly improve patients' clinical outcome and survival. Inquiries for any forms of ingestion should be attempted in patients with clinical signs and symptoms suggestive of poisoning.

Optimization of an In silico Cardiac Cell Model for Proarrhythmia Risk Assessment.

Drug-induced Torsade-de-Pointes (TdP) has been responsible for the withdrawal of many drugs from the market and is therefore of major concern to global regulatory agencies and the pharmaceutical industry. The Comprehensive in vitro Proarrhythmia Assay (CiPA) was proposed to improve prediction of TdP risk, using in silico models and in vitro multi-channel pharmacology data as integral parts of this initiative. Previously, we reported that combining dynamic interactions between drugs and the rapid delayed rectifier potassium current (IKr) with multi-channel pharmacology is important for TdP risk classification, and we modified the original O'Hara Rudy ventricular cell mathematical model to include a Markov model of IKr to represent dynamic drug-IKr interactions (IKr-dynamic ORd model). We also developed a novel metric that could separate drugs with different TdP liabilities at high concentrations based on total electronic charge carried by the major inward ionic currents during the action potential. In this study, we further optimized the IKr-dynamic ORd model by refining model parameters using published human cardiomyocyte experimental data under control and drug block conditions. Using this optimized model and manual patch clamp data, we developed an updated version of the metric that quantifies the net electronic charge carried by major inward and outward ionic currents during the steady state action potential, which could classify the level of drug-induced TdP risk across a wide range of concentrations and pacing rates. We also established a framework to quantitatively evaluate a system's robustness against the induction of early afterdepolarizations (EADs), and demonstrated that the new metric is correlated with the cell's robustness to the pro-EAD perturbation of IKr conductance reduction. In summary, in this work we present an optimized model that is more consistent with experimental data, an improved metric that can classify drugs at concentrations both near and higher than clinical exposure, and a physiological framework to check the relationship between a metric and EAD. These findings provide a solid foundation for using in silico models for the regulatory assessment of TdP risk under the CiPA paradigm.

Characterization of loperamide-mediated block of hERG channels at physiological temperature and its proarrhythmia propensity.

BACKGROUND: Loperamide (Immodium®) is indicated for symptomatic control of diarrhea. It is a µ-opioid receptor agonist, and recently has been associated with misuse and abuse. At therapeutic doses loperamide has not been associated with cardiotoxicity. However, loperamide overdose is associated with proarrhythmia and death - two effects that are likely attributable to its block of cardiac ion channels that are critical for generating action potentials. In this study, we defined loperamide-hERG channel interaction characteristics, and used a ventricular myocyte action potential model to compare loperamide's proarrhythmia propensity to twelve drugs with defined levels of clinical risk. METHODS AND RESULTS: Whole-cell voltage-clamp recordings were performed at 37°C on a HEK293 cell line stably expressing the hERG channel proteins, and loperamide was bath-applied to assess its effects on hERG current. Loperamide suppressed hERG current in a use- and voltage-dependent but frequency-independent manner, with a half-maximal inhibitory concentration <90nM. The onset of current suppression was concentration-dependent and appeared to follow a first-order reaction. Loperamide also altered the voltage-dependence of steady state hERG current properties. Electrophysiological data were integrated into a myocyte model that simulated dynamic drug-hERG channel interaction to estimate Torsade de Pointes risk through comparisons with reference drugs with defined clinical risk. In the context of overdose that would result in loperamide levels far exceeding those produced by therapeutic doses, loperamide is placed in the high risk category, alongside quinidine, bepridil, dofetilide, and sotalol. CONCLUSIONS: The combined in vitro and in silico approach provides mechanistic insight regarding the potential for loperamide to generate cardiotoxicity in overdose situations. This strategy holds promise for improving cardiac safety assessment.

PD-1 and PD-L1 as emerging therapeutic targets in gastric cancer: current evidence.

Gastric adenocarcinoma is a leading cause of global cancer-related morbidity and mortality, and new therapeutic approaches are needed. Despite the improved outcomes with monoclonal antibodies targeting human epidermal growth factor receptor 2 and vascular endothelial growth factor receptor 2, durable responses are uncommon. Targeting immune checkpoints including PD-1, PD-L1 and CTLA-4 have led to improved survival across several tumor types, frequently characterized by prolonged benefit in responding patients. Tumoral and lymphocyte-derived immunohistochemical staining for PD-1, PD-L1, and tumor mutational burden have shown potential as predictive response biomarkers in several tumor types. Optimal incorporation of immune-mediated therapies into gastric cancer (GC) is an area of intense ongoing investigation and benefit has been demonstrated in smaller studies of advanced patients. Important questions of biomarker selection, roles for molecular characterization, optimal combinatorial approaches, and therapeutic sequencing remain. In this study, current data are reviewed for immune checkpoint inhibitors in GC, and putative biomarkers, ongoing trials, and future considerations are discussed.

The safety of Bruton's tyrosine kinase inhibitors for the treatment of chronic lymphocytic leukemia.

INTRODUCTION: The approval of ibrutinib has revolutionized the therapeutic landscape of chronic lymphocytic leukemia (CLL). Currently ibrutinib is indicated for patients that are both treatment naïve as well as those with relapsed CLL. Ibrutinib is generally well-tolerated with durable responses that improve over time in most patients. Important toxicities include atrial fibrillation and bleeding. Areas cover: This review covers the pharmacokinetics, pharmacodynamics, safety and efficacy of ibrutinib in the treatment of CLL. We also compare ibrutinib with other kinase inhibitors and chemoimmunotherapy regimens using data from clinical trials. A literature search utilized the PubMed database. Expert opinion: Despite the efficacy and tolerability of ibrutinib, important questions remain, which include selection of patients receiving ibrutinib in the first and subsequent lines of treatment, optimal dosing, sequential use of ibrutinib versus other kinase inhibitors and combination therapy. Prospective studies should incorporate minimal residual disease (MRD) status as a clinical endpoint to determine whether patients can be taken off kinase inhibitors.

Improving the In Silico Assessment of Proarrhythmia Risk by Combining hERG (Human Ether-à-go-go-Related Gene) Channel-Drug Binding Kinetics and Multichannel Pharmacology.

BACKGROUND: The current proarrhythmia safety testing paradigm, although highly efficient in preventing new torsadogenic drugs from entering the market, has important limitations that can restrict the development and use of valuable new therapeutics. The CiPA (Comprehensive in vitro Proarrhythmia Assay) proposes to overcome these limitations by evaluating drug effects on multiple cardiac ion channels in vitro and using these data in a predictive in silico model of the adult human ventricular myocyte. A set of drugs with known clinical torsade de pointes risk was selected to develop and calibrate the in silico model. METHODS AND RESULTS: Manual patch-clamp data assessing drug effects on expressed cardiac ion channels were integrated into the O'Hara-Rudy myocyte model modified to include dynamic drug-hERG channel (human Ether-à-go-go-Related Gene) interactions. Together with multichannel pharmacology data, this model predicts that compounds with high torsadogenic risk are more likely to be trapped within the hERG channel and show stronger reverse use dependency of action potential prolongation. Furthermore, drug-induced changes in the amount of electronic charge carried by the late sodium and L-type calcium currents was evaluated as a potential metric for assigning torsadogenic risk. CONCLUSIONS: Modeling dynamic drug-hERG channel interactions and multi-ion channel pharmacology improves the prediction of torsadogenic risk. With further development, these methods have the potential to improve the regulatory assessment of drug safety models under the CiPA paradigm.

Focus on Alectinib and Competitor Compounds for Second-Line Therapy in ALK-Rearranged NSCLC.

The management of anaplastic lymphoma kinase rearranged (ALK+) non-small cell lung cancer (NSCLC) exemplifies the potential of a precision medicine approach to cancer care. The ALK inhibitor crizotinib has led to improved outcomes in the first- and second-line setting; however, toxicities, intracranial activity, and acquired resistance necessitated the advent of later generation ALK inhibitors. A large portion of acquired resistance to ALK inhibitors is caused by secondary mutations in the ALK kinase domain. Alectinib is a second-generation ALK inhibitor capable of overcoming multiple crizotinib-resistant ALK mutations and has demonstrated improved outcomes after crizotinib failure. Favorable toxicity profile and improved intracranial activity have spurred ongoing front-line trials and comparisons to other ALK inhibitors. However, important questions regarding comparability to competitor compounds, acquired alectinib resistance, and ALK inhibitor sequencing remain. Here, we review the key clinical data supporting alectinib in the second-line therapy of ALK+ NSCLC and provide context in comparison to other ALK inhibitors in development.