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Black Knight, the University of Central Florida's vehicle in the 11th Intelligent Ground Vehicle Competition (IGVC) competed in 2003. Completing in 5th place in the navigational challenge and 10th in the autonomous challenge in its first competition has proven our vehicle to be a strong competitor in this competition. The vehicle has many interesting features that allow it to achieve its success. The vehicle's 300 lb. capacity allows for two onboard full-sized computers and two 12 V marine batteries that power the computers for up to 2 h. The vision system is not a simple reactive system but rather it classifies its view into objects and builds a map of the territory as it learns of its features while traveling. Two transformations and the location data from the GPS and other sensors are used to associate the locations in the image to locations in the map. The operations of the vehicle are modeled after the typical operations of a ship. We have programs that perform the functions of the captain, the helm, the navigator, and the engineer. In addition we have a program performing sensor data fusion from the GPS, compass, and wheel encoder data. The navigation uses an adapted two-dimensional approximate cell decomposition method that satisfies the nonholononic constraints of our vehicle and allows it to find the shortest path to the goal while avoiding all obstacles.

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Precision oncology requires predictive models for therapy selection using variety of biomarkers and clinical features as input. Building and validating these models requires analysis of large numbers of diverse cases in order to relate markers and treatments to positive outcomes. The -omics technologies provide a rich source of genetic and epigenetic markers but demand large compute and storage systems to process the data. Thus, there is an urgent need for scalable and reliable information systems to support nation-scale research and delivery of precision oncology. At Lockheed Martin, we deliver operational solutions to complex problems. Here, we present our vision for a precision oncology platform. This solution integrates best-in-class capabilities from multiple sources/vendors to support innovation, research and clinical care for a whole nation. We not only thought about the basic -omics based data collection, but also an infrastructure to collect and store data within a compliant privacy and security framework that also facilitates collaborative analytics and data sharing for deeper insight. Taking a systems engineering approach, we have examined some of the challenges to implement such a platform. For instance, running the basic genomic data processing pipelines to yield variant calls, which in turn will feed the variant store, should be a single scalable workflow. Accounting for multiple data sources, various use cases and selections of tools are at the core of an adaptable workflow. A variant store design that can scale and support a national cohort with an overlaying cohort selection tool are all part of this intricate design. It is our vision that a systems engineering and integration approach can deliver a unified solution for the national precision oncology roadmap. It is paramount that all the individual pieces should be well tuned to deliver scalability and reliability and simultaneously work in complete harmony. Only then we can process data at-scale needed for finding actionable mutations, designing effective treatments and implementing prevention strategies, affordably and reliably. Citation Format: Ogan Abaan, Amrita Basu, David Deal, Michael Hultner. Adaptive operations and technology platform for nation-scale precision oncology. [abstract]. In: Proceedings of the 107th Annual Meeting of the American Association for Cancer Research; 2016 Apr 16-20; New Orleans, LA. Philadelphia (PA): AACR; Cancer Res 2016;76(14 Suppl):Abstract nr 3632.

Our understanding of the genetic basis for cancer is advancing at a rapid rate due to the application of next generation sequencing (NGS) technologies. It is becoming common to sequence tumors and patients in an attempt to find actionable mutations that could offer the patient a more targeted and effective treatment. However, the genomics of cancer is very complex and only a handful of actionable mutations have been characterized. Larger-scale studies are needed to understand the pathogenic spectrum of cancer variants and deliver reliable clinical decision-making support to providers. Several large-scale sequencing projects are underway to collect NGS data on tumors (e.g. TCGA, ICGC, and TARGET) but a national platform for analysis, interpretation, and reporting does not exist. We propose that a consolidated informatics platform for the collection of outcomes data with genomics and clinical data would accelerate research and provide patients with the opportunity for personalized cancer treatment. In addition, with 1,665,540 new cancer cases predicted in the US for 2014, a national-scale genomics platform is needed, capable of sequencing 3 million genomes per year, storing exabytes of data, while supporting over 20,000 oncologists, researchers, and analysts. At Lockheed Martin, we deliver highly scalable and reliable information systems for a variety of missions and citizen services. Here, we will present our vision for a national cancer genomics platform to include NGS data collection, cost-efficient storage, scalable and modular processing pipelines, and collaborative analytics and data sharing capabilities, within a compliant privacy and security framework. In conclusion, by leveraging the scale of clinical cancer sequencing and capturing these data into a case management system for translational research, this platform provides data at-scale needed for finding actionable mutations, designing effective treatments and implementing prevention strategies, faster. Citation Format: Ogan Abaan, Amrita Basu, Noah Brown, Bret Light, David Deal, Michael Hultner. A population-based approach to address clinical cancer care: The national genomics platform. [abstract]. In: Proceedings of the 106th Annual Meeting of the American Association for Cancer Research; 2015 Apr 18-22; Philadelphia, PA. Philadelphia (PA): AACR; Cancer Res 2015;75(15 Suppl):Abstract nr 4743. doi:10.1158/1538-7445.AM2015-4743