Using network medicine to develop network-based models for drug repositioning.
Developed an automated framework for generating clinical reports from NGS data in collaboration with Boston Children’s Hospital
Developed a clinical trial simulation framework to statistically predict the result of a clinical trial.
Ph.D. Bioinformatics, Boston University
B.S. Mechanical Engineering, University of Florida
I am senior member of the Laboratory for Personalized Medicine at Harvard Medical School (HMS) and was awarded the highly prestigious “Pathways to Independence” K99/R00 grant, in 2011, to investigate drug repurposing using healthcare data. Previously, I was a National Library of Medicine Fellow during my postdoctoral training at HMS. I become an expert in biomedical cloud computing and frequently uses the cloud to accelerate translational research from whole genome sequencing to pharmacogenomics and clinical reporting. Prior to HMS, I did graduate research at the Broad Institute working in both the Proteomics and Computational Biology Platforms. While there, I researched novel computational methods to improve candidate protein biomarker validation using targeted mass spectrometry methods. I am well versed in machine learning, pattern recognition, and statistical analysis. Prior to graduate school, I worked at the National Cancer Institute with Drs. Lance Liotta and Emanuel Petricoin to develop computational algorithms to predict ovarian cancer using mass spectrometry-derived blood-based protein patterns.
1. Fusaro VA, Patil P, Chi CL, Contant CF, Tonellato PJ. (2013) “A systems approach to designing effective clinical trials using simulations.” Circulation. Jan 29;127(4):517-26. PMID: 23261867.
2. Fusaro VA, Patil P, Gafni E, Wall DP, Tonellato PJ. (2011) “Biomedical Cloud Computing With Amazon Web Services.” PLoS Computational Biology. Aug;7(8):e1002147. PMID: 21901085.
3. Fusaro VA, Mani D.R., Mesirov JP, Carr SA. (2009) “Prediction of high-responding peptides for targeted protein assays by mass spectrometry,” Nat. Biotechnology, Feb;27(2):190-8. PMCID: PMC2753399
4. Wall DP, Kosmicki J, DeLuca TF, Harstad E, Fusaro VA.(2012) “Use of machine learning to shorten observation-based screening and diagnosis of autism.” Transl. Psychiatry. Aprl 10;2e100 PMID: 22832900.
5. Conrads TP, Fusaro VA, Ross S, Johann D, Rajapakse V, Hitt BA, Steinberg SM, Kohn EC, Fishman DA, Whitely G, Barrett JC, Liotta LA, Petricoin EF III, Veenstra TD. (2004) “High-resolution Serum Proteomic Features for Ovarian Cancer Detection,” Endocrine-Related Cancer. Jun; 11(2): 163-178. PMID: 15163296
6. Petricoin EF, Ardekani AM, Hitt BA, Levine PJ, Fusaro VA, Steinberg SM, Mills GB, Simone C, Fishman DA, Kohn EC, Liotta LA. (2002) “Use of Proteomics Patterns in Serum to Identify Ovarian Cancer,” Lancet 359: 572-77. PMID: 11867112
1. NLM Informatics Training Conference 2009
2. American Society of Mass Spectrometry 2009 - poster:
Quantification of ion suppression on peptides in complex mixtures by
3. Personal Electronic Health Records 2009
4. American Society of Mass Spectrometry 2008 - poster: Computational prediction of the highest responding peptides per protein in electrospray mass spectrometry