SBIR-STTR Award

Concern over toxins and public health threats resulting from Cyanobacterial Harmful Algal Blooms (CHABs) have gained attention as reoccurring and seasonal blooms persist in many waters. It has also been suggested that climate change is increasing the frequency, intensity, and duration of CHABs. Broadly, cyanotoxins can be described as having negative health impacts and can be grouped into neurotoxic, lipopolysaccharides, or hepatotoxic such as microcystins which tend to be the most frequently reported. The neurotoxin ?-N-methylamino-L-alanine (BMAA) can be produced by cyanobacteria and have been associated with CHABs and Amyotrophic lateral sclerosis (ALS) clusters across northern New England (Caller et al 2009, Torbick et al 2014, Banack 2015). The magnitude and complexity of CHABs in our freshwater lakes requires innovative technologies and multiscale analysis for detection, understanding, forecasting, and mitigating public health threats. Specifically, during this SBIR we partner with Cleveland Clinic and the ALS Research Center to evaluate linkages between Lake Erie CHABs and ALS cases). ALS is a progressive, fatal neurodegenerative disease with a lifetime risk of 1 in 400. The pathologic hallmark of ALS is the selective death of motor neurons in the brain and spinal cord, producing debilitating symptoms of progressive weakness, muscle wasting and spasticity. Mutations in genes underlying familial ALS (fALS) have been discovered in only 5-10% of the total population of ALS patients. Approximately 90% of ALS cases have no known genetic cause; this group is commonly called sporadic ALS (sALS). There is a broad scientific consensus that ALS is caused by gene-environment interactions. Evidence has shown potential linkages between water quality, cyanobacteria, and high ALS incidence. Decision Support Tools (DSTs) that integrate satellite remote sensing, web and cloud services, and mobile devices (e.g., phones, tablets) offer the capability to monitor CHABs at spatial and temporal scales not achievable by discrete point observations or traditional techniques. For CHAB detection, bio-optical algorithms use color remote sensing data to convert observed spectral light information into geophysical products, such as chlorophyll-a and phycocyanin concentration maps. Remote sensing can detail attributes over space, time and characterize location, duration, intensity, and frequency. The amount of historical satellite imagery is now thousands of terabytes, presenting data handling challenges for all but the most technically capable end users. Real time image processing flows, integration of mobile devices and crowd sourcing, and public health warning and forecasting tools are unobtainable for most applications due to technical challenges. Proposed Innovation: We propose to design, build, and operate a 'Cloud-based Lake Cyanobacterial Harmful Algal Bloom Mapping and Analysis Platform (CHAB-MAP) for supporting public health risk assessment'. The tool will automate the mapping and analysis of relevant satellite remote sensing data and real time imagery updates for mapping and analyzing CHAB metrics derived from MODIS, MERIS/Sentiel-3, and Landsat. Mobile apps and crowd sourcing tools will be designed in partnership with NOAA GLERL and EPA to improve access to information, decision making, and data gathering. In this SBIR we work closely with Cleveland Clinic to address the role of cyanotoxins and ALS in Ohio. Specific Aim #1: Design and apply BigData approaches and generate historical and real time MODIS (2001 - present), MERIS (2002-2012), and Landsat (1984 - present) Lake Erie CHABs metrics including chl-a, phycocyanin, and water temperature working with NOAA GLERL, NASA, and EPA partners Specific Aim #2: Design, test, and identify optimal web and cloud framework for managing, visualization, plotting tools, managing tabular data, and accessing products using web and mobile packages Specific Aim #3: Work in partnership with Cleveland Clinic (and Dr. Erik Pioro; Barry Winovich Chair for ALS Research in the Lerner Research Institute and director of the section of ALS in the Dept of Neurology) to assess the role of CHABs and cyanotoxins in ALS in northern and central Ohio. Grow other applications investigating neurodegenerative diseases and disorders potentially linked to CHABs

Public Health Relevance Statement:


Public Health Relevance:
Design, build, and operate a 'Cloud-based Lake Cyanobacterial Harmful Algal Bloom Mapping and Analysis Platform (Lake-CHAB-MAP) for investigating impact of cyanotoxins on ALS and developing public health applications'. Help address cyanobacteria, ALS, and toxicity public health threats.

Project Terms:
Access to Information; Address; Alanine; Algorithms; Amyotrophic Lateral Sclerosis; Attention; Brain; Cessation of life; Chlorophyll; climate change; Clinic; cloud based; Color; Consensus; crowdsourcing; Cyanobacterium; Data; Decision Making; design; Detection; Disease; Familial Amyotrophic Lateral Sclerosis; Frequencies (time pattern); Fresh Water; gene environment interaction; Genes; Genetic; handheld mobile device; harmful algal blooms; Health; image processing; Imagery; Improve Access; Incidence; innovation; innovative technologies; Internet; Lifetime Risk; Light; Link; Lipopolysaccharides; Location; Maps; microcystin; mobile application; Monitor; Motor Neurons; Muscle Spasticity; Muscular Atrophy; Mutation; Neurodegenerative Disorders; Neurology; neurotoxic; Neurotoxins; New England; Ohio; Optics; Pathologic; Patients; Population; Public Health Applications Research; public health medicine (field); remote sensing; Reporting; Research; Research Institute; Risk Assessment; Role; Services; Small Business Innovation Research Grant; Spinal Cord; support tools; Symptoms; Tablets; Techniques; Telephone; Temperature; Testing; Time; tool; Toxic effect; Toxin; United States National Aeronautics and Space Administration; Update; Water; water quality; Work

Specific Aim #1: Operationalize spatio-temporal CyanoHAB exposure epoch metrics • Fuse multi-scale and disparate satellite remote sensing platforms and automate retrievals over space and time to derive CyanoHAB exposure metrics. We will build enterprise software to fully automate the harmonization and fusion of NASA’s Landsat-8 OLI and ESA’s Sentinel-2 and Sentinel-3 satellite platforms to provide long-term (1984-present) moderate spatial resolution (30meter pixels) and high temporal frequency CyanoHAB exposure metrics (Cyanobacteria Intensity, Color Dissolved Organic Matter, Total Suspended Solids, Floating Algae Index, Chlorophyll-a Concentration, & toxins). The decision support tool automates epoch synthesis to understand incubation periods and exposure triggers for neurodegenerative diseases. Specific Aim #2: Scale on-demand CHABMAP commercial product services • Scale and implement CHABMAP data services for infinite scalability using BigData cloud technologies. This Aim involves three main development efforts: adapting our proprietary Geospatial Image and Processing System (GIPS) capabilities to an AWS-deployable auto-scaling cluster, creation of user interfaces and application programming interfaces (APIs) to interact with these services, and enhancements to the base GIPS framework to facilitate intercommunication between remote GIPS-enabled archives and the cloud processing streams. This includes the creation of deployable compute instances, optimization of computation and parallelization specific to AWS deployment, optimization of temporary and long-term storage of intermediate products, and optimization of communication and data transfer with end users. Ultimately, this Aim will allow for the assessment and monitoring of CyanoHAB conditions for any waterbody or region (i.e., North America) on the planet. Specific Aim #3: Execute risk assessment frameworks with public health partners • We will work in partnership with Cleveland Clinic, Dartmouth Hitchcock Medical Center, University of Miami, Macquarie University, NIH’s Neuromuscular Diseases Research Section and CDC’s Agency for Toxic Substances and Disease Registry (National ALS Registry) to assess the role of CyanoHABs exposure as a risk factor for Amyotrophic lateral sclerosis (ALS) using patients, clinic-, and population-based controls across diverse settings and geographies. Each application end user has ongoing risk assessment frameworks (i.e., Gene-Environment, Residential History Machine Learning, eco-epidemiological, molecular biology) which our CHABMAP technology will integrate exposure epoch metrics to understand the etiology or ALS and support drug discovery. Proposed Innovation CHABMAP technology automates the quantification of toxic Cyanobacterial Harmful Algal Bloom (CHAB) exposure epochs for any waterbody or catchment in the world for the past four decades using multi-scale harmonized satellites. We use custom and proprietary techniques combined with BigData software to generate historical exposure (“exposome”) profiles as well provide Decision Support Tools services for CHAB monitoring in near-real time. During Phase 2 and beyond we work with world experts to integrate our commercial products and services into neurodegenerative disease Gene-Environment (GxE) risk assessment frameworks. Proposed Products, Services, Outcomes • Develop historical CHAB exposure measurements working with environmental agency partners • Assessment of CyanoHABs as a risk factor for ALS across multiple, independent study regions • CHABMAP on-demand Analytics-as-a-Service platform operating at end of Phase 2 • Support discovery of etiology and drug development for neurological disorders and diseases

Public Health Relevance Statement:
Project Narrative Design, build, and operate a cloud-based Cyanobacterial Harmful Algal Bloom Mapping and Analysis Platform (CHAB-MAP) for developing public health applications’ in partnership with NASA, EPA, and medical centers. Assess as risk factor for ALS. Help address cyanobacteria and toxicity public help threats.

Project Terms:
Address; Algae; Amyotrophic Lateral Sclerosis; application programming interface; Archives; base; Big Data; Centers for Disease Control and Prevention (U.S.); Chlorophyll; Clinic; cloud based; Color; Communication; Computer software; Custom; Cyanobacterium; Data; data exchange; design; Development; disease registry; drug development; drug discovery; Environment; Epidemiology; Etiology; Frequencies; Genes; Geography; harmful algal blooms; image processing; indexing; innovation; Machine Learning; Measurement; Medical center; Molecular Biology; Monitor; nervous system disorder; Neurodegenerative Disorders; Neurodevelopmental Disorder; Neuromuscular Diseases; North America; Outcome; parallelization; Patients; Phase; Planets; Poison; population based; Public Health; Public Health Applications Research; Recording of previous events; Registries; remote sensing; Research; Resolution; Retrieval; Risk Assessment; Risk Factors; Role; Sentinel; Services; Solid; spatiotemporal; Stream; support tools; System; Techniques; Technology; Time; Toxic effect; Toxin; United States National Aeronautics and Space Administration; United States National Institutes of Health; Universities; Work