Stanford

SPADA (Predictives and Diagnostics)



SPADA, the Stanford Predictives and Diagnostics Accelerator, assists interdisciplinary innovators in research, development and deployment of technologies that improve human health through disease prediction and/or diagnosis.


Contact Information

Jim Zuegel
SPADA Program Manager
Phone: (650) 906-6099
Email:  email

Russ Altman, MD, PhD
SPADA Faculty Director
Email:  email


Program Overview

SPADA, the Stanford Predictives and Diagnostics Accelerator, was established in October 2013 under the umbrella of Spectrum, the Stanford Center for Clinical and Translational Reseaserch and Education.

Mission

    To assist interdisciplinary innovators in research, development and deployment of technologies that improve human health through disease prediction and/or diagnosis.

Program Initiatives

  • Innovation Accelerator Pilot Grants
  • Diagnostics and predictives innovation training
  • Mentoring on development, translation and technology transfer processes
  • Community educational events that bring researchers, engineers, health-care providers and industry experts together to cross-pollenate and collaborate

SPADA, the Stanford Predictives and Diagnostics Accelerator, was established to assist interdisciplinary innovators in research, development and deployment of technologies that improve human health through disease prediction and/or diagnostics.


Translating optical coherence tomography to diagnose Meniere’s disease

Year: 2015
Investigator: John Oghalai, MD, associate professor of otolaryngology


Microendoscopic sarcomere visualization for the diagnosis, prognosis and monitoring of ALS

Year: 2015
Investigator: Scott Delp, PhD, professor of bioengineering and of mechanical engineering; Mark Schnitzer, PhD, associate professor of biology and of applied physics


Machine vision for broad microbial detection: A rapid and automated approach for identifying pathogenic bacteria through DNA melting

Year: 2015
Investigator: Samuel Yang, MD, associate professor of surgery


Multiplex detection and sequencing of the viral repertoire in clinical samples

Year: 2015
Investigator: Curt Scharfe, senior scientist in biochemistry; Justin Odegaard, MD, PhD, instructor of pathology; Benjamin Pinsky, MD, PhD, assistant professor of pathology and of medicine; Martina Lefterova, MD, PhD, clinical pathology resident


Creating a $150 autism diagnosis

Year: 2015
Investigator: Dennis Wall, MD, PhD, associate professor of pediatrics; Maude David, postdoctoral scholar in pediatric systems medicine


Assessment and prediction of age-related macular degeneration progression through quantitative imaging biomarkers

Year: 2014
Investigator: Daniel Rubin, MD, assistant professor of radiology and of biomedical informatics; Luis de Sisternes Garcia, PhD in radiology; and Ted Leng, MD, assistant professor of ophthalmology at the Byers Eye Institute.
Journal articles:
http://www.ncbi.nlm.nih.gov/pubmed/25301882
http://www.ncbi.nlm.nih.gov/pubmed/4237666
http://www.ncbi.nlm.nih.gov/pubmed/25062439


The diagnosis and characterization of major depressive disorder by applying machine learning methods to human neuroimaging data

Year: 2014
Investigator: Matthew Sacchet, graduate student in neurosciences; Gautam Prasad, PhD, psychology visiting scholar; Ian Gotlib, PhD, professor and chair of psychology.


First in-human clinical trial of manganese-enhanced MRI (MeMRI) to assess peri-infarct injury

Year: 2014
Investigator: Phillip Yang, MD, associate professor of cardiovascular medicine; Rajesh Dash, MD, PhD, assistant professor of cardiovascular medicine; Dwight Nishimura, PhD, professor of electrical engineering.


Development of non-invasive, laser-based breath-ammonia sensor for urea-cycle-defect diagnosis and monitoring

Year: 2014
Investigator: Gregory Enns, MD, director of the Biochemical Genetics Program and associate professor of pediatrics; Victor Miller, mechanical engineering PhD candidate; Mitchell Spearrin, mechanical engineering PhD candidate; Christopher Strand, mechanical engineering PhD candidate; Ron Hanson, PhD, professor of mechanical engineering.



Enabling precision medicine through genomic interpretation

Enabling precision medicine through genomic interpretation
Monday, November 9, 2015
6:00 pm – 7:30 pm
Li Ka Shing Center, Room LK130
291 Campus Drive, Stanford, CA 94305


Martin Reese, PhD
Co-founder, President and CSO of Omica,
a leading provider of genomic analysis software

Russ Altman, MD, PhD, professor of bioengineering, medicine and genetics, will host a lively discussion with entrepreneur Martin Reese on the potential of genomic interpretation in the clinic.

Martin Reese has been a pioneer in bioinformatics and genomics for over 20 years. His research has contributed to various standards and large scale projects in genomics, including the UCSC genome browser, the Drosophila and Human Genome Projects, genome annotation resulting in the Gene Ontology, and the EGASP int’l gene assessment project. More recently, Martin has contributed to next generation sequencing-based Precision Medicine projects such as initial NGS sequencing using SOLiD, the GVF genome variant format, VAAST, the first probabilistic disease gene finder for personal genomes, and automatic clinical whole genome interpretation at scale using phenotype integration (PHEVOR) for the 100,000 Genomes Project in the UK and large US-based reference laboratories such as LabCorp.

Sponsored by Spectrum, the Stanford Center for Clinical and Translational Research and Education, and its innovation accelerator, SPADA, the Stanford Predictives and Diagnostics Accelerator (SPADA).

Contacts:
Jim Zuegel
Email:  email

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