Applying Systems Biology and Predictive Genomic Analytics on Patients with Lung Squamous Cell Carcinoma and RNA-Seq Gene Expression

The future of healthcare will be transformed by flexible frameworks designed to discover complex signals in rich datasets through the merger of predictive genomic analytics and systems biology. Smart machine learning algorithms designed to incorporate information about molecular and cellular systems can revolutionize our ability to discover complex hierarchical genomic effects driving disease pathogenesis or severity and treatment response patterns. To meet modern research demands, Precision for Medicine has engineered PATH™ to provide a secure, scalable, cloud-based solution for predictive genomic analytics and an intuitive graphical user interface for interactive data visualization and exploration.

In this case study, the speakers will show the power of using a novel combination of machine learning

algorithms with a systems biology based approach for identifying genes and the subsequent exonic regions driving prognosis for patients with lung squamous cell carcinoma (SQCC). PATH™ will be applied on 553 lung SQCC patients with survival outcomes and RNA-Seq exon-level mRNA expression data obtained from The Cancer Genome Atlas. This webinar will focus on two of the PATH™ Analytics Platform’s suites:

• PATH™ Select: A novel predictive analytics engine, built on a combination of machine learning algorithms fused with a systems biology approach provides for high-throughput feature selection
• PATH™ Explore: A secure, web based data visualization suite enables real-time, “what-if” data exploration to accelerate research and support decision making

Big data has the potential to enable a precision medicine focused drug development process, resulting in increased benefit-risk profiles for patients with a particular biomarker profile and smaller, shorter clinical trials. Navigating the process from biomarker discovery to a companion or complementary diagnostic requires that researchers get the support necessary to make sense of big data being generated in NGS pipelines. Ultimately it will be demonstrated how a cloud-based solution powered by a predictive analytics engine and an intuitive, user interface driven by interactive graphics can deliver to the needs of precision medicine programs.

Speakers

Scott Marshall, Ph.D., Managing Director, Analytics, Precision for Medicine

Scott Marshall, PhD, is Managing Director of Biomarker and IVD Analytics at Precision for Medicine. He has extensive industry experience in a leadership role, consulting in the Pharmaceutical, biotechnology, and biodefense industries, specializing in the analytical component of personalized medicine, biomarker R&D, analytical methods, and strategy development, as well as medical device/diagnostic development.

Prior to joining Precision for Medicine, Scott served as the Head of Bioanalytics at a statistical consulting company serving the Pharmaceutical, biotechnology, and biodefense industries. In addition to his scientific role, his responsibilities included helping develop the company’s business and analytical R&D strategies, as well as the organizational structure and operational system. Scott’s expertise spans multiple spaces, with a specific emphasis in precision medicine-guided efforts, and strategy development focused on patient selection.

He has authored, coauthored, and presented analytical strategies and methods for use in precision medicine in various publications, including The Pharmacogenomics Journal,Pharmacogenomics, Biometrics, and the Journal of Pharmacogenomics and Personalized Medicine. Areas of focus include genomic region-based testing (method and strategy manuscript) and the estimation of molecular signatures toward patient stratification. In addition, he has authored or coauthored more than 150 confidential technical documents, such as statistical analysis plans, statistical analysis reports, and other US Food and Drug Administration (FDA) and European Medicines Agency submission documents.

Scott completed his PhD in Biostatistics at the Medical College of Virginia, Virginia Commonwealth University. As a trainee on a National Institute of Environmental Health Sciences grant, Scott developed novel methodologies for the evaluation of complex chemical mixtures. Scott earned a Bachelor of Science in Applied Mathematics from the University of Tennessee at Chattanooga.

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Jared Kohler, Ph.D., Managing Director, Analytics, Precision for Medicine

Jared Kohler, PhD, is a Managing Director of Precision Analytics at Precision for Medicine. He has extensive industry experience operating in a leadership role consulting for the Pharmaceutical and biotechnology industries, and specializing in the analytical component of personalized medicine and biomarker research and development.

Prior to joining Precision for Medicine, Jared served as the Head of Biomarker Statistics at a statistical consulting company, where he led scientific operations that delivered on over 150 translational medicine efforts in clinical drug development or post-marketing. He also has experience with analyzing large-scale disease genetics studies, developing and validating biomarker-based IVDs, and implementing molecular assays at the bench. Jared’s previous work allows him a unique perspective in support of strategic planning and analytics for biomarker programs and translational research.

He has co-authored various manuscripts and presented analytical strategies for use in personalized medicine, including publications in Pharmacogenomics and Journal of Pharmacogenomics and Personalized Medicine. His areas of focus include improving the likelihood of success in the discovery and replication of PGx/biomarker effects, translating biomarker data to patient selection and differentiation strategies, enabling informed decision-making, and developing diagnostics (or tests) with clinical and commercial utility. In addition, he has also co-authored over 200 confidential technical documents such as statistical analysis plans, clinical study reports, or other FDA and EMA submission documents.

Jared completed his PhD in human genetics with a concentration in statistical genetics at The Johns Hopkins University School of Medicine. As a pre-doctoral fellow at the McKusick-Nathans Institute of Genetic Medicine, Jared developed the first model-based statistical genetics software capable of detecting and testing copy number variation in SNP genotyping studies. Jared also earned a BS in biochemistry from Juniata College.

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Tobias Guennel, Ph.D., Principal, Analytics, Precision for Medicine

Tobias Guennel, PhD, is the Principal of Precision Analytics for Precision for Medicine. He has extensive industry experience, including a leadership role consulting in the Pharmaceutical, biotechnology, and bio-defense industries, specializing in the analytical component of personalized medicine, biomarker R&D, analytical methods, together with strategy development and medical device/diagnostic development.

Prior to joining Precision for Medicine, Tobias served as the Group Leader of the Bioanalytics Division at a statistical consulting company serving the Pharmaceutical, biotechnology, and bio-defense industries, where he led or supported the development of over 50 translational medicine efforts. In addition to his scientific role, his responsibilities included supporting the company’s business development efforts, leading the company’s analytical R&D group, and facilitating several operational aspects of the company’s day-to-day activities.

Tobias has authored and co-authored various publications, including The Pharmacogenomics Journal, Pharmacogenomics, Biometrics, and Journal of Pharmacogenomics and Personalized Medicine. His areas of focus include genomic region-based testing (method and strategy manuscript), estimation of molecular signatures toward patient stratification, and analytical strategies for pharmacogenomics studies. He has also authored or co-authored over 100 confidential technical documents such as statistical analysis plans, statistical analysis reports, clinical study reports, and other FDA and EMA submission documents.

Tobias completed his PhD in Biostatistics with a concentration in Statistical Genetics and Genomics at Virginia Commonwealth University (VCU). At VCU, he was a predoctoral fellow at the Virginia Institute for Psychiatric and Behavioral Genetics on a National Institute for Drug Abuse training grant where he developed novel methodologies to normalize and analyze data from high-throughput assays, including array-CGH and RNA-Seq.

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