Roadmap on plasticity and epigenetics in cancer.

The role of plasticity and epigenetics in shaping cancer evolution and response to therapy has taken center stage with recent technological advances including single cell sequencing. This roadmap article is focused on state-of-the-art mathematical and experimental approaches to interrogate plasticity in cancer, and addresses the following themes and questions: is there a formal overarching framework that encompasses both non-genetic plasticity and mutation-driven somatic evolution? How do we measure and model the role of the microenvironment in influencing/controlling non-genetic plasticity? How can we experimentally study non-genetic plasticity? Which mathematical techniques are required or best suited? What are the clinical and practical applications and implications of these concepts?

A physiological model of granulopoiesis to predict clinical drug induced neutropenia from in vitro bone marrow studies: with application to a cell cycle inhibitor.

Neutropenia is one of the most common dose-limiting toxocities associated with anticancer drug therapy. The ability to predict the probability and severity of neutropenia based on in vitro studies of drugs in early drug development will aid in advancing safe and efficacious compounds to human testing. Toward this end, a physiological model of granulopoiesis and its regulation is presented that includes the bone marrow progenitor cell cycle, allowing for a mechanistic representation of the action of relevant anticancer drugs based on in vitro studies. Model development used data from previously reported tracer kinetic studies of granulocyte disposition in healthy humans to characterize the dynamics of neutrophil margination in the presence of endogenous granulocyte-colony stimulating factor (G-CSF). In addition, previously published data from healthy volunteers following pegfilgrastim and filgrastim were used to quantify the regulatory effects of support G-CSF therapies on granulopoiesis. The model was evaluated for the cell cycle inhibitor palbociclib, using an in vitro system of human bone marrow mononuclear cells to quantify the action of palbociclib on proliferating progenitor cells, including its inhibitory effect on G1 to S phase transition. The in vitro results were incorporated into the physiological model of granulopoiesis and used to predict the time course of absolute neutrophil count (ANC) and the incidence of neutropenia observed in three previously reported clinical trials of palbociclib. The model was able to predict grade 3 and 4 neutropenia due to palbociclib treatment with 86% accuracy based on in vitro data.

METLIN: A Technology Platform for Identifying Knowns and Unknowns.

METLIN originated as a database to characterize known metabolites and has since expanded into a technology platform for the identification of known and unknown metabolites and other chemical entities. Through this effort it has become a comprehensive resource containing over 1 million molecules including lipids, amino acids, carbohydrates, toxins, small peptides, and natural products, among other classes. METLIN's high-resolution tandem mass spectrometry (MS/MS) database, which plays a key role in the identification process, has data generated from both reference standards and their labeled stable isotope analogues, facilitated by METLIN-guided analysis of isotope-labeled microorganisms. The MS/MS data, coupled with the fragment similarity search function, expand the tool's capabilities into the identification of unknowns. Fragment similarity search is performed independent of the precursor mass, relying solely on the fragment ions to identify similar structures within the database. Stable isotope data also facilitate characterization by coupling the similarity search output with the isotopic m/ z shifts. Examples of both are demonstrated here with the characterization of four previously unknown metabolites. METLIN also now features in silico MS/MS data, which has been made possible through the creation of algorithms trained on METLIN's MS/MS data from both standards and their isotope analogues. With these informatic and experimental data features, METLIN is being designed to address the characterization of known and unknown molecules.

Leveraging model-based study designs and serial micro-sampling techniques to understand the oral pharmacokinetics of the potent LTB4 inhibitor, CP-105696, for mouse pharmacology studies.

1. Leukotriene B4 (LTB4) is a proinflammatory mediator important in the progression of a number of inflammatory diseases. Preclinical models can explore the role of LTB4 in pathophysiology using tool compounds, such as CP-105696, that modulate its activity. To support preclinical pharmacology studies, micro-sampling techniques and mathematical modeling were used to determine the pharmacokinetics of CP-105696 in mice within the context of systemic inflammation induced by a high-fat diet (HFD). 2. Following oral administration of doses > 35 mg/kg, CP-105696 kinetics can be described by a one-compartment model with first order absorption. The compound's half-life is 44-62 h with an apparent volume of distribution of 0.51-0.72 L/kg. Exposures in animals fed an HFD are within 2-fold of those fed a normal chow diet. Daily dosing at 100 mg/kg was not tolerated and resulted in a >20% weight loss in the mice. 3. CP-105696's long half-life has the potential to support a twice weekly dosing schedule. Given that most chronic inflammatory diseases will require long-term therapies, these results are useful in determining the optimal dosing schedules for preclinical studies using CP-105696.

Determining conserved metabolic biomarkers from a million database queries.

MOTIVATION: Metabolite databases provide a unique window into metabolome research allowing the most commonly searched biomarkers to be catalogued. Omic scale metabolite profiling, or metabolomics, is finding increased utility in biomarker discovery largely driven by improvements in analytical technologies and the concurrent developments in bioinformatics. However, the successful translation of biomarkers into clinical or biologically relevant indicators is limited. RESULTS: With the aim of improving the discovery of translatable metabolite biomarkers, we present search analytics for over one million METLIN metabolite database queries. The most common metabolites found in METLIN were cross-correlated against XCMS Online, the widely used cloud-based data processing and pathway analysis platform. Analysis of the METLIN and XCMS common metabolite data has two primary implications: these metabolites, might indicate a conserved metabolic response to stressors and, this data may be used to gauge the relative uniqueness of potential biomarkers. AVAILABILITY AND IMPLEMENTATION: METLIN can be accessed by logging on to: https://metlin.scripps.edu CONTACT: siuzdak@scripps.edu SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Volumetric imaging of optically cleared and fluorescently labeled animal tissue (VIOLA) for quantifying the 3D biodistribution of nanoparticles at cellular resolution in tumor tissue.

Nanoparticle (NP) technology holds significant promise to mediate targeted drug delivery to specific organs in the body. Understanding the 3D biodistribution of NPs in heterogeneous environments such as the tumor tissue can provide crucial information on efficacy, safety and potential clinical outcomes. Here we present a novel end-to-end workflow, VIOLA, which makes use of tissue clearing methodology in conjunction with high resolution imaging and advanced 3D image processing to quantify the spatiotemporal 3D biodistribution of fluorescently labeled ACCURIN® NPs. Specifically, we investigate the spatiotemporal biodistribution of NPs in three different murine tumor models (CT26, EMT6, and KPC-GEM) of increasing complexity and translational relevance. We have developed new endpoints to characterize NP biodistribution at multiple length scales. Our observations reveal that the macroscale NP biodistribution is spatially heterogeneous and exhibits a gradient with relatively high accumulation at the tumor periphery that progressively decreases towards the tumor core in all the tumor models. Microscale analysis revealed that NP extravasation from blood vessels increases in a time dependent manner and plateaus at 72 h post injection. Volumetric analysis and pharmacokinetic modeling of NP biodistribution in the vicinity of the blood vessels revealed that the local NP density exhibits a distance dependent spatiotemporal biodistribution which provide insights into the dynamics of NP extravasation in the tumor tissue. Our data represents a comprehensive analysis of NP biodistribution at multiple length scales in different tumor models providing unique insights into their spatiotemporal dynamics. Specifically, our results show that NPs exhibit a dynamic equilibrium with macroscale heterogeneity combined with microscale homogeneity.

A whole-body circulatory neutrophil model with application to predicting clinical neutropenia from in vitro studies.

A circulatory model of granulopoiesis and its regulation is presented that includes neutrophil trafficking in the lungs, liver, spleen, bone marrow, lymph nodes, and blood. In each organ, neutrophils undergo transendothelial migration from vascular to interstitial space, clearance due to apoptosis, and recycling via the lymphatic flow. The model includes cell cycling of progenitor cells in the bone marrow, granulocyte colony-stimulating factor (G-CSF) kinetics and its neutrophil regulatory action, as well as neutrophil margination in the blood. From previously reported studies, 111 In-labeled neutrophil kinetic data in the blood and sampled organs were used to estimate the organ trafficking parameters in the model. The model was further developed and evaluated using absolute neutrophil count (ANC), band cell, and segmented neutrophil time course data from healthy volunteers following four dose levels of pegfilgrastim (r2  = 0.77-0.99), along with ANC time course responses following filgrastim (r2  = 0.96). The baseline values of various cell types in bone marrow and blood, as well as G-CSF concentration in the blood, predicted by the model are consistent with available literature reports. After incorporating the mechanism of action of both paclitaxel and carboplatin, as determined from an in vitro bone marrow studies, the model reliably predicted the observed ANC time course following paclitaxel plus carboplatin observed in a phase I trial of 46 patients (r2  = 0.70). The circulatory neutrophil model may provide a mechanistic framework for predicting multi-organ neutrophil homeostasis and dynamics in response to therapeutic agents that target neutrophil dynamics and trafficking in different organs.

Structure-Based Drug Design and Synthesis of PI3Kα-Selective Inhibitor (PF-06843195).

The phosphoinositide 3-kinase (PI3K)/mammalian target of rapamycin (mTOR) signaling pathway is a frequently dysregulated pathway in human cancer, and PI3Kα is one of the most frequently mutated kinases in human cancer. A PI3Kα-selective inhibitor may provide the opportunity to spare patients the side effects associated with broader inhibition of the class I PI3K family. Here, we describe our efforts to discover a PI3Kα-selective inhibitor by applying structure-based drug design (SBDD) and computational analysis. A novel series of compounds, exemplified by 2,2-difluoroethyl (3S)-3-{[2'-amino-5-fluoro-2-(morpholin-4-yl)-4,5'-bipyrimidin-6-yl]amino}-3-(hydroxymethyl)pyrrolidine-1-carboxylate (1) (PF-06843195), with high PI3Kα potency and unique PI3K isoform and mTOR selectivity were discovered. We describe here the details of the design and synthesis program that lead to the discovery of 1.

Predicting Chemotherapy-Induced Neutropenia and Granulocyte Colony-Stimulating Factor Response Using Model-Based In Vitro to Clinical Translation.

The ability to predict the incidence of chemotherapy-induced neutropenia in early drug development can inform risk monitoring and mitigation strategies, as well as decisions on advancing compounds to clinical trials. In this report, a physiological model of granulopoiesis that incorporates the drug's mechanism of action on cell cycle proliferation of bone marrow progenitor cells was extended to include the action of the cytotoxic agents paclitaxel, carboplatin, doxorubicin, and gemcitabine. In vitro bone marrow studies were conducted with each compound, and results were used to determine the model's drug effect parameters. Population simulations were performed to predict the absolute neutrophil count (ANC) and incidence of neutropenia for each compound, which were compared to results reported in the literature. In addition, using the single agent in vitro study results, the model was able to predict ANC time course in response to paclitaxel plus carboplatin in combination, which compared favorably to the results reported in a phase 1 clinical trial of 46 patients (r2 = 0.70). Model simulations were used to compare the relative risk (RR) of neutropenia in patients with high baseline ANCs for five chemotherapeutic regimens: doxorubicin (RR = 0.59), paclitaxel plus carboplatin combination (RR = 0.079), carboplatin (RR = 0.047), paclitaxel (RR = 0.031), and gemcitabine (RR = 0.013). Finally, the model was applied to quantify the reduced incidence of neutropenia with coadministration of pegfilgrastim or filgrastim, for both paclitaxel and the combination of paclitaxel plus carboplatin. The model provides a framework for predicting clinical neutropenia using in vitro bone marrow studies of anticancer agents that may guide drug development decisions.

A Microfluidic Perfusion Platform for In Vitro Analysis of Drug Pharmacokinetic-Pharmacodynamic (PK-PD) Relationships.

Static in vitro cell culture studies cannot capture the dynamic concentration profiles of drugs, nutrients, and other factors that cells experience in physiological systems. This limits the confidence in the translational relevance of in vitro experiments and increases the reliance on empirical testing of exposure-response relationships and dose optimization in animal models during preclinical drug development, introducing additional challenges owing to species-specific differences in drug pharmacokinetics (PK) and pharmacodynamics (PD). Here, we describe the development of a microfluidic cell culture device that enables perfusion of cells under 2D or 3D culture conditions with temporally programmable concentration profiles. Proof-of-concept studies using doxorubicin and gemcitabine demonstrated the ability of the microfluidic PK-PD device to examine dose- and time-dependent effects of doxorubicin as well as schedule-dependent effects of doxorubicin and gemcitabine combination therapy on cell viability using both step-wise drug concentration profiles and species-specific (i.e., mouse, human) drug PK profiles. The results demonstrate the importance of including physiologically relevant dynamic drug exposure profiles during in vitro drug testing to more accurately mimic in vivo drug effects, thereby improving translatability across nonclinical studies and reducing the reliance on animal models during drug development.

Kinetic modelling of [11C]flumazenil using data-driven methods.

PURPOSE: [(11)C]Flumazenil (FMZ) is a benzodiazepine receptor antagonist that binds reversibly to central-type gamma-aminobutyric acid (GABA-A) sites. A validated approach for analysis of [(11)C]FMZ is the invasive one-tissue (1T) compartmental model. However, it would be advantageous to analyse FMZ binding with whole-brain pixel-based methods that do not require a-priori hypotheses regarding preselected regions. Therefore, in this study we compared invasive and noninvasive data-driven methods (Logan graphical analysis, LGA; multilinear reference tissue model, MRTM2; spectral analysis, SA; basis pursuit denoising, BPD) with the 1T model. METHODS: We focused on two aspects: (1) replacing the arterial input function analyses with a reference tissue method using the pons as the reference tissue, and (2) shortening the scan protocol from 90 min to 60 min. Dynamic PET scans were conducted in seven healthy volunteers with arterial blood sampling. Distribution volume ratios (DVRs) were selected as the common outcome measure. RESULTS: The SA, LGA with and without arterial input, and MRTM2 agreed best with the 1T model DVR values. The invasive and noninvasive BPD were slightly less well correlated. The full protocol of a 90-min emission data performed better than the 60-min protocol, but the 60-min protocol still delivered useful data, as assessed by the coefficient of variation, and the correlation and bias analyses. CONCLUSION: This study showed that the SA, LGA and MRTM2 are valid methods for the quantification of benzodiazepine receptor binding with [(11)C]FMZ using an invasive or noninvasive protocol, and therefore have the potential to reduce the invasiveness of the procedure.

The runner's high: opioidergic mechanisms in the human brain.

The runner's high describes a euphoric state resulting from long-distance running. The cerebral neurochemical correlates of exercise-induced mood changes have been barely investigated so far. We aimed to unravel the opioidergic mechanisms of the runner's high in the human brain and to identify the relationship to perceived euphoria. We performed a positron emission tomography "ligand activation" study with the nonselective opioidergic ligand 6-O-(2-[(18)F]fluoroethyl)-6-O-desmethyldiprenorphine ([(18)F]FDPN). Ten athletes were scanned at 2 separate occasions in random order, at rest and after 2 h of endurance running (21.5 +/- 4.7 km). Binding kinetics of [(18)F]FDPN were quantified by basis pursuit denoising (DEPICT software). Statistical parametric mapping (SPM2) was used for voxelwise analyses to determine relative changes in ligand binding after running and correlations of opioid binding with euphoria ratings. Reductions in opioid receptor availability were identified preferentially in prefrontal and limbic/paralimbic brain structures. The level of euphoria was significantly increased after running and was inversely correlated with opioid binding in prefrontal/orbitofrontal cortices, the anterior cingulate cortex, bilateral insula, parainsular cortex, and temporoparietal regions. These findings support the "opioid theory" of the runner's high and suggest region-specific effects in frontolimbic brain areas that are involved in the processing of affective states and mood.

Applications of Quantitative Systems Pharmacology in Model-Informed Drug Discovery: Perspective on Impact and Opportunities.

Quantitative systems pharmacology (QSP) approaches have been increasingly applied in the pharmaceutical since the landmark white paper published in 2011 by a National Institutes of Health working group brought attention to the discipline. In this perspective, we discuss QSP in the context of other modeling approaches and highlight the impact of QSP across various stages of drug development and therapeutic areas. We discuss challenges to the field as well as future opportunities.

Metabolomics activity screening for identifying metabolites that modulate phenotype.

Metabolomics, in which small-molecule metabolites (the metabolome) are identified and quantified, is broadly acknowledged to be the omics discipline that is closest to the phenotype. Although appreciated for its role in biomarker discovery programs, metabolomics can also be used to identify metabolites that could alter a cell's or an organism's phenotype. Metabolomics activity screening (MAS) as described here integrates metabolomics data with metabolic pathways and systems biology information, including proteomics and transcriptomics data, to produce a set of endogenous metabolites that can be tested for functionality in altering phenotypes. A growing literature reports the use of metabolites to modulate diverse processes, such as stem cell differentiation, oligodendrocyte maturation, insulin signaling, T-cell survival and macrophage immune responses. This opens up the possibility of identifying and applying metabolites to affect phenotypes. Unlike genes or proteins, metabolites are often readily available, which means that MAS is broadly amenable to high-throughput screening of virtually any biological system.

Preclinical QSP Modeling in the Pharmaceutical Industry: An IQ Consortium Survey Examining the Current Landscape.

A cross-industry survey was conducted to assess the landscape of preclinical quantitative systems pharmacology (QSP) modeling within pharmaceutical companies. This article presents the survey results, which provide insights on the current state of preclinical QSP modeling in addition to future opportunities. Our results call attention to the need for an aligned definition and consistent terminology around QSP, yet highlight the broad applicability and benefits preclinical QSP modeling is currently delivering.

Assessment of near-infrared fluorophores to study the biodistribution and tumor targeting of an IL13 receptor α2 antibody by fluorescence molecular tomography.

Non-invasive imaging using radiolabels is a common technique used to study the biodistribution of biologics. Due to the limited shelf-life of radiolabels and the requirements of specialized labs, non-invasive optical imaging is an attractive alternative for preclinical studies. Previously, we demonstrated the utility of fluorescence molecular tomography (FMT) an optical imaging modality in evaluating the biodistribution of antibody-drug conjugates. As FMT is a relatively new technology, few fluorophores have been validated for in vivo imaging. The goal of this study was to characterize and determine the utility of near-infrared (NIR) fluorophores for biodistribution studies using interleukin-13 receptor subunit alpha-2 antibody (IL13Rα2-Ab). Eight fluorophores (ex/em: 630/800 nm) with an N-hydroxysuccinimide (NHS) linker were evaluated for Ab conjugation. The resulting antibody-fluorophore (Ab-F) conjugates were evaluated in vitro for degree of conjugation, stability and target-binding, followed by in vivo/ex vivo FMT imaging to determine biodistribution in a xenograft model. The Ab-F conjugates (except Ab-DyLight800) showed good in vitro stability and antigen binding. All Ab-F conjugates (except for Ab-BOD630) resulted in a quantifiable signal in vivo and had similar biodistribution profiles, with peak tumor accumulation between 6 and 24 h post-injection. In vivo/ex vivo FMT imaging showed 17-34% ID/g Ab uptake by the tumor at 96 h. Overall, this is the first study to characterize the biodistribution of an Ab using eight NIR fluorophores. Our results show that 3-dimensional optical imaging is a valuable technology to understand biodistribution and targeting, but a careful selection of the fluorophore for each Ab is warranted.

Found in Translation: Maximizing the Clinical Relevance of Nonclinical Oncology Studies.

Purpose: The translation of nonclinical oncology studies is a subject of continuous debate. We propose that translational oncology studies need to optimize both pharmacokinetic (drug exposure) and pharmacodynamic (xenograft model) aspects. While improvements in pharmacodynamic translatability can be obtained by choosing cell lines or patient-derived xenograft models closer to the clinical indication, significant ambiguity and variability exists when optimizing the pharmacokinetic translation of small molecule and biotherapeutic agents.Experimental Design and Results: In this work, we propose a pharmacokinetic-based strategy to select nonclinical doses for approved drug molecules. We define a clinically relevant dose (CRD) as the dosing regimen in mice that most closely approximates the relevant pharmacokinetic metric in humans. Such metrics include area under the time-concentration curve and maximal or minimal concentrations within the dosing interval. The methodology is applied to six drugs, including targeted agents and chemotherapeutics, small and large molecules (erlotinib, dasatinib, vismodegib, trastuzumab, irinotecan, and capecitabine). The resulting efficacy response at the CRD is compared with clinical responses.Conclusions: We conclude that nonclinical studies designed with the appropriate CRDs of approved drug molecules will maximize the translatability of efficacy results, which is critical when testing approved and investigational agents in combination. Clin Cancer Res; 23(4); 1080-90. ©2016 AACR.

A novel CXCR4 antagonist IgG1 antibody (PF-06747143) for the treatment of hematologic malignancies.

The chemokine receptor CXCR4 is highly expressed and associated with poor prognosis in multiple malignancies. Upon engagement by its ligand, CXCL12, CXCR4 triggers intracellular signaling pathways that control trafficking of cells to tissues where the ligand is expressed, such as the bone marrow (BM). In hematologic cancers, CXCR4-driven homing of malignant cells to the BM protective niche is a key mechanism driving disease and therapy resistance. We developed a humanized CXCR4 immunoglobulin G1 (IgG1) antibody (Ab), PF-06747143, which binds to CXCR4 and inhibits CXCL12-mediated signaling pathways, as well as cell migration. In in vivo preclinical studies, PF-06747143 monotherapy rapidly and transiently mobilized cells from the BM into the peripheral blood. In addition, PF-06747143 effectively induced tumor cell death via its Fc constant region-mediated effector function. This Fc-mediated cell killing mechanism not only enhanced antitumor efficacy, but also played a role in reducing the duration of cell mobilization, when compared with an IgG4 version of the Ab, which does not have Fc-effector function. PF-06747143 treatment showed strong antitumor effect in multiple hematologic tumor models including non-Hodgkin lymphoma (NHL), acute myeloid leukemia (AML), and multiple myeloma (MM). Importantly, PF-06747143 synergized with standard-of-care agents in a chemoresistant AML patient-derived xenograft model and in an MM model. These findings suggest that PF-06747143 is a potential best-in-class anti-CXCR4 antagonist for the treatment of hematologic malignancies, including in the resistant setting. PF-06747143 is currently in phase 1 clinical trial evaluation (registered at www.clinicaltrials.gov as #NCT02954653).

Conversion of alpha-linolenic acid in humans is influenced by the absolute amounts of alpha-linolenic acid and linoleic acid in the diet and not by their ratio.

BACKGROUND: Human in vivo data on dietary determinants of alpha-linolenic acid (ALA; 18:3n-3) metabolism are scarce. OBJECTIVE: We examined whether intakes of ALA or linoleic acid (LA; 18:2n-6) or their ratio influences ALA metabolism. DESIGN: During 4 wk, 29 subjects received a control diet (7% of energy from LA, 0.4% of energy from ALA, ALA-to-LA ratio = 1:19). For the next 6 wk, a control diet, a low-LA diet (3% of energy from LA, 0.4% of energy from ALA, ratio = 1:7), or a high-ALA diet (7% of energy from LA, 1.1% of energy from ALA, ratio = 1:7) was consumed. Ten days before the end of each dietary period, [U-13C]ALA was administered orally for 9 d. ALA oxidation was determined from breath. Conversion was estimated by using compartmental modeling of [13C]- and [12C]n-3 fatty acid concentrations in fasting plasma phospholipids. RESULTS: Compared with the control group, ALA incorporation into phospholipids increased by 3.6% in the low-LA group (P = 0.012) and decreased by 8.0% in the high-ALA group (P < 0.001). In absolute amounts, it increased by 34.3 mg (P = 0.020) in the low-LA group but hardly changed in the high-ALA group. Nearly all ALA from the plasma phospholipid pool was converted into eicosapentaenoic acid. Conversion of eicosapentaenoic acid into docosapentaenoic acid and docosahexaenoic acid hardly changed in the 3 groups and was <0.1% of dietary ALA. In absolute amounts, it was unchanged in the low-LA group, but increased from 0.7 to 1.9 mg (P = 0.001) in the high-ALA group. ALA oxidation was unchanged by the dietary interventions. CONCLUSION: The amounts of ALA and LA in the diet, but not their ratio, determine ALA conversion.

Automated identification of axonal growth cones in time-lapse image sequences.

The isolation and purification of axon guidance molecules has enabled in vitro studies of the effects of axon guidance molecule gradients on numerous neuronal cell types. In a typical experiment, cultured neurons are exposed to a chemotactic gradient and their growth is recorded by manual identification of the axon tip position from two or more micrographs. Detailed and statistically valid quantification of axon growth requires evaluation of a large number of neurons at closely spaced time points (e.g. using a time-lapse microscopy setup). However, manual tracing becomes increasingly impractical for recording axon growth as the number of time points and/or neurons increases. We present a software tool that automatically identifies and records the axon tip position in each phase-contrast image of a time-lapse series with minimal user involvement. The software outputs several quantitative measures of axon growth, and allows users to develop custom measurements. For, example analysis of growth velocity for a dissociated E13 mouse cortical neuron revealed frequent extension and retraction events with an average growth velocity of 0.05 +/- 0.14 microm/min. Comparison of software-identified axon tip positions with manually identified axon tip positions shows that the software's performance is indistinguishable from that of skilled human users.