The following is a preliminary agenda. Please check back in the coming weeks for additions to the agenda, for additional information regarding the presentations
and the full two-day tiimeline of events.
THE POTENTIAL FOR TRANSFORMATION
KEYNOTE ADDRESS: The BRAIN Initiative
Walter Koroshetz, MD, Director, National Institute of Neurological Disorders and Stroke (NINDS), NIH
Towards a Molecular Taxonomy of Cancer
With the completion of the human genome project and the advent of next generation sequencing technologies, there has been an incredible advancement in our molecular understanding of cancer. This has led to the deciphering of the genetic basis of cancers at a depth never before possible. We will discuss the impact of these advancements on our ability to classify and treat a variety of cancers.
Chetan Bettegowda, MD, Ph.D., Associate Professor of Neurosurgery, Johns Hopkins University
Towards a Bioethical Framework for Personalized Medicine
In this presentation, Dr. Kass will discuss both the promise of large data analysis and personalized medicine as well as the ethical obligations in conducting this type of research. This will include not only often discussed responsibilities of patient privacy and data security, but also transparency in describing how data will be used, engagement of stakeholders about how and why data are being collected, translating the potential of precision medicine into accessible medical care for all and accountability in keeping promises to patients and the public.
Nancy E. Kass, ScD, Phoebe R. Berman Professor of Bioethics and Public Health, Berman Institute of Bioethics and Bloomberg School of Public Health, Johns Hopkins University
BIG SCIENCE
The All of UsSM Research Program in The Precision Medicine Initiative®: An Update
The talk will be an overview of the All of UsSM Research Program (formerly known as the Precision Medicine Initiative® Cohort Program). Dr. Rutter will discuss the following: Overview of the All of Us Program • Required data that will be collected • Data access and use processes to be expected • Potential research questions
Joni Rutter, Ph.D., Director, Programs and Strategic Implementation, All of Us Research Program, Precision Medicine Initiative, National Institutes of Health
Consortia to Discover the Role of Genetics in Stroke and Traumatic Brain Injury
Large-scale international collaboration has been the key to the revolution in human genetics that has grown out of the completion of the Human Genome Project and the launch of the GWAS era. The discoveries made by the International Stroke Genetics Consortium have already identified novel targets for stroke prevention and highlighted dozens of biological pathways with a role in both stroke susceptibility and stroke outcome. Multiple groups within the ISGC are now pursuing interdependent research agendas all aimed at exploiting genetic discoveries for the ultimate benefit of patients. The culture of the ISGC—open, welcoming, scientifically ambitious, and highly collegial—has been fundamental to its success. With the launch of the GAIN (Genetic Associations in Neurotrauma) Consortium, we have established a similar infrastructure to elucidate the role of genetic variation in outcome and recovery from traumatic brain injury.
Jonathan Rosand, MD, MSc, Chief, Division of Neurocritical Care & Emergency Neurology, Harvard University
Early Lessons from TRACK-TBI
TRACK-TBI is a US-based Consortium designed to evaluate biomarkers and outcome measures of traumatic brain injury, across the spectrum of age and severity, starting in the Emergency Department through one year after injury. The long-term goal of TRACK-TBI is to transform research and clinical practice by applying the principles of precision medicine to TBI. Since its inception in the Fall of 2013, TRACK-TBI has enrolled over 1800 participants (as of October, 2016), and several key lessons have been learned. This presentation will provide an update on the activities of the TRACK-TBI Consortium, review the major accomplishments of the first 4 years, and outline a path for the future.
Ramon Diaz-Arrastia, MD, Ph.D., Clinical Associate Professor of Neurology, University of Pennsylvania
The Cardiovascular Research Grid Project
The CardioVascular Research Grid (CVRG) Project is a multi-institutional effort to establish a national infrastructure to advance seamless sharing and analysis of cardiovascular research data. The infrastructure developed in this project is equally applicable to support research on neuroscience in intensive care. This talk will present an overview of CVRG technologies and their potential uses.
Rai Winslow, Ph.D., Director, Center for Cardiovascular Bioinformatics & Modeling, Johns Hopkins University
The Individual Functional Connectome: Relating Functional Brain Organization to Clinical Symptoms
This presentation will show how functional MRI can be used to develop patient profiles based on the functional organization of major circuits in the brain. A connectome based predictive modeling approach will then be reviewed that illustrates how the individual functional connectome can be used to predict symptoms or behavioral variables. Evidence will be provided that the functional connectome measured in individuals is unique, intrinsic, and stable, and that the individual connectome tells us something about a patients clinical/behavioral profile.
Todd Constable, Ph.D., Professor of Radiology and Neurosurgery, Director MRI Research, Yale University
METHODOLOGIES
Statistical Modeling of Very Large Biological Datasets
This presentation will cover important problems associated with the analysis of very large biological data sets including design of experiments, data storage, statistical analysis, and reproducibility. I will focus on issues related to data visualization, multiplicity testing, the use of reproducible software and methods, and reporting. Special attention will be given to cross-sectional and longitudinal analyses of large studies of clinical brian imaging. The ideas and problems were motivated by and applied to a longitudinal study of multiple sclerosis patients and a clinical trial of stroke patients.
Ciprian Crainiceanu, Ph.D., Professor of Biostatistics, Johns Hopkins University
Adaptive Clinical Trial Design in Acute Neurology
The goal of the presentation is to describe novel adaptive clinical trial designs that can be applied to Phase II clinical trials investigating promising neuroprotective agents.
Jose Suarez, MD, Professor of Neurology-Vascular Critical Care, Baylor College of Medicine
Multi-omics: A Systems Biology Approach to Biomarker Discovery and Validation
In this presentation, Dr. Everett will review and give examples of the overlapping use of proteomics, peptidomics, lipidomics and metabolomics for brain injury biomarker discovery.
Allen Dale Everett, MD, Director of the Pediatric Proteome Center, Professor of Pediatrics, Johns Hopkins University
Model-based Data Integration in Neurocritical Care
Large volumes of heterogeneous data are now routinely collected and archived from patients in a variety of clinical environments, to support real-time decision-making, monitoring of disease progression, and titration of therapy. This rapid expansion of available physiological data has resulted in a data-rich – but often knowledge-poor – environment. Yet the abundance of clinical data also presents an opportunity to systematically fuse and analyze the available data streams, through appropriately chosen mathematical models, and to provide clinicians with insights that may not be readily extracted from visual review of the available data streams. In this talk, Dr. Heldt will highlight his team's work in model-based signal processing to derive additional and clinically useful information from routinely available data streams. He will present their model-based approach to noninvasive, patient-specific and calibration free estimation of intracranial pressure, and will elaborate on the challenges of collecting high-quality clinical data for validation.
Thomas Heldt, Ph.D., MS, Mphil, Assistant Professor Electrical and Biomedical Engineering, Massachusetts Institute of Technology
Machine Learning for Clinical Prediction
Suchi Saria, Ph.D., Assistant Professor, Johns Hopkins University
Precision Medicine in the Neuro ICU: Multiparametric Prediction of Vasospasm After Subarachnoid Hemorrhage
Soojin Park, MD, FAHA, FNCS, Assistant Professor of Neurology, Neurocritical Care Fellowship Director, Columbia University College of Physicians and Surgeons
BIOLOGICAL METHODS
Computational Modeling of Stroke Recovery in Humans
Data and ideas will be presented related to the notion of spontaneous biological recovery and how motor learning and brain repair relate to each other.
John Krakauer, MA, MD, Professor of Neurology and Rehabilitation Medicine, Johns Hopkins University
The Gut-Brain Connection in Stroke and Dementia: More Than Meets the Eye
Owing to the blood-brain barrier, the brain has traditionally been considered an “immune privileged” organ, nearly impenetrable to immune cells. However, a growing body of evidence indicates that cells of the immune system traffic in and out of the brain and can have either beneficial or detrimental effects on the brain tissue. The gut is a major reservoir of immune cells, and is emerging as a key player in acute and chronic brain pathologies. Whereas innate immunity contributes to the acute phase of the tissue damage associated with experimental cerebral ischemia, immune cells originating from the gut protect the brain from impending damage in models of intestinal dysbiosis. In addition, intestinal immune cells play a critical role in the vascular dysregulation associated with cognitive impairment, a model of vascular dementia. The realization that the gut immune system is critically involved in the pathobiology of major brain diseases provides the opportunity to modulate immune function in order to reset the balance between its protective and destructive effects, and to develop new approaches for the prevention or treatment of stroke and dementia.
Costantino Iadecola, MD, Director, Brain & Mind Research Institute, Cornell University
Biological Model of Brain Dysfunction in Sepsis
In this presentation, Dr. Sharshar will discuss animal models, neurobiological techniques and behavioral tests that enables the reproduction of the main features of sepsis related acute and long-term brain dysfunction, in order to better phenotype the pathogenic mechanisms with their clinical correlates.
Tarek Sharshar, Ph.D., Senior Consultant, Intensive Care Medicine, University of Versailles, France
Genomics, What We Have learned from Ischemic Stroke
Paul Nyquist, MD, MPH, Johns Hopkins Bayview Neurocritical Care Unit, Associate Professor of Neurology, Johns Hopkins University
CLINICAL TRIALS
Goals for Blood Pressure Management in Intracerebral Hemorrhage
Adnan Qureshi, MD, Professor of Neurology, Neurosurgery and Radiology, University of Minnesota
Biomarkers for Predictive Enrichment in Neurocritical Care Trials
Clinical trials in traumatic brain injury have been disappointing. One reason is that traumatic brain injury is so heterogeneous and not every patient may respond to the same treatment. Biomarkers may be useful to select patients that will have the greatest chance for benefit from a treatment.
Claudia Robertson, MD, Professor, Department of Neurosurgery, Baylor College of Medicine
Personalized Targets for Hemodynamic Management in Neurocritical Care
In this presentation Dr. Lazaridis will cover the physiologic background, monitoring techniques, and clinical interventions aimed at managing brain dysoxia and organ-systems physiologic conflicts.
Christos Lazaridis, MD, Assistant Professor, Neurology, Baylor College of Medicine
Selection of Intracerebral Hemorrhage Patients for Minimally Invasive Surgery
Daniel Hanley, MD, Professor of Neurology, Johns Hopkins University
Selection of Ischemic Stroke Patients for Reperfusion
Tudor G. Jovin, MD, Associate Professor of Neurology, Chief, Stroke Division, Director, UPMC Stroke Institute, University of Pittsburgh
PREDICTION
Predictive Analytics for Impending Clinical Deterioration
Dana Edelson, MD, Assistant Professor of Medicine, University of Chicago
Quantitative Electroencephalographic Signatures for Prediction in Severe Brain Injury
The presentation will focus on reviewing insights into quantitative electroencephalographic signatures that help assess and predict recovery of patients with severe brain injury. Specifically, Dr Claassen will investigate emerging application of quantitative EEG analysis for the detection of seizures, ischemia, and recovery of consciousness in acutely brain injured patients.
Jan Claassen, MD, Ph.D., FNCS, Head of Neurocritical Care and Medical Director of the Neurological ICU, Columbia University
Leveraging MRI Advances in Concussion Patients: Machine Learning and More
In this presentation, Dr. Lui will discuss how to better understand concussions using MRI (macrostructure, microstructure, functional and metabolic imaging). She will also discuss how machine learning can be applied to help aid diagnosis and treatment (classification, prediction, dealing with artifacts).
Yvonne Lui, MD, Associate Professor, Radiology, New York University
Discriminative Mapping for Coma Recovery Prediction
Recent investigations on the structure and function of the brain have yielded fundamental insights into the neuroscience of conscious awareness. This discovery is driven by advances in our ability to map the brain including anatomical and functional neuroimaging, electroencephalography and event-related potentials. Inferences from mapping are intrinsically constrained by the technology used for signal acquisition and the analytical paradigms employed to interpret the signal. Across different paradigms including sleep, anesthesia, seizures and brain injury, a model emerges in which changes in the conscious state are intrinsically linked to modifications in the degree of functional segregation and integration of distributed neuronal systems.
Robert Stevens, MD, Associate Professor, Anesthesiology & Critical Care Medicine, Johns Hopkins University
Right Care, Right Now, Every Patient, Every Time: Towards Precision Medicine in Critical Care
Clinical decision-making in critical care has two foundations: knowledge and data. Knowledge is typically derived from randomized clinical trials, presented as guidelines and used as order sets and algorithms. Data reside in data warehouses, are typically recovered through structured queries and are only infrequently used on an ad hoc, patient-specific basis. This lecture focuses on the convergence of knowledge-driven and data-driven decision making as a strategy to customize and personalize acute and critical care. Considerations will include data types, reasoning frameworks and enabling technologies.
Tim Buchman, Ph.D., MD, Director, Emory Critical Care Center, Emory University