Matthew Might, PhD
Disclosures: Scientific Advisor-Q State Biosciences
OMB No. 0925-0046, Biographical Sketch Format Page

 

OMB No. 0925-0001 and 0925-0002 (Rev. 09/17 Approved Through 03/31/2020)

BIOGRAPHICAL SKETCH

Provide the following information for the Senior/key personnel and other significant contributors.
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NAME: Matthew Might

eRA COMMONS USER NAME (credential, e.g., agency login): MATTMIGHT

POSITION TITLE: Director and Professor, University of Alabama at Birmingham

EDUCATION/TRAINING (Begin with baccalaureate or other initial professional education, such as nursing, include postdoctoral training and residency training if applicable. Add/delete rows as necessary.)

INSTITUTION AND LOCATION

DEGREE

(if applicable)

 

Completion Date

MM/YYYY

 

FIELD OF STUDY

 

Georgia Tech, Atlanta

B.S.

12/2001

Computer Science

Georgia Tech, Atlanta

M.S.

05/2005

Computer Science

Georgia Tech, Atlanta

Ph.D.

08/2007

Computer Science

 

 

A.              Personal Statement
 

Over the past three years, I’ve made a full pivot from foundational computer science (with major applications in cybersecurity, cyberbiophysical systems and scientific computing) to the intersection of biology, medicine and computation.  My motivation for moving deeply into a new field is personal: thanks to a clinical research effort on exome sequencing, my son was diagnosed with NGLY1 deficiency, and he was in fact the first and only patient known to date. In order to find other patients and create a research community, I pioneered the use of social media to connect with other patients for novel, ultra-rare disorders.  To date, roughly 60 such patients have been identified and an active research community has been formed.

 

Working from the first principles of the altered metabolism regarding NGLY1 deficiency, I also reasoned that NGLY1 patients could be suffering a deficit of cytosolic N-Acetylglucosamine. Subsequent dietary supplementation with this sugar reversed the alacrimal and nocturnal neurogenic aspects of phenotype in humans and substantially improved survival in drosophila. In tandem, I worked toward full drug development and repurposing for NGLY1 deficiency, all the way from target validation (ENGase) to docking simulation to biochemical validation to clinical administration of the repuposed drug (lansoprazole).

 

From beachhead successes in NGLY1 deficiency, I have become interested in developing an “algorithm” for precision medicine: it is a process that follows from an n=1 diagnosis: from case-finding and functional studies, to assay development, to screening, to medicinal chemistry, to clinical trials. I sent over three years engaged with the White House leadership on constructing this algorithm as part of the Precision Medicine Initiative (whose large cohort program has become the All of Us Initiative).  Having now successfully deployed this algorithm in finding treatments for other patients (most recently, SCN8A-driven epilepsy), I have become Director of the Hugh Kaul Precision Medicine Insitute at UAB with a mission to scale this algorithm up to all patients.

 

I have brought with me to medicine a broad skillset that spans much of modern computer science – including mechanized logic, machine learning, Big Data, high-performance computing, security and computational simulation and verification of physical systems.

 

  1. Talia A. Atkin, Chani M. Maher, Aaron C. Gerlach, Bryant C. Gay, Brett M. Antonio, Sonia C. Santos, Karen M. Padilla, JulieAnn Rader, Douglas S. Krafte, Matthew A. Fox, Gregory R. Stewart, Slavé Petrovski, Orrin Devinsky, Matthew Might, Steven Petrou, David B. Goldstein. "A comprehensive approach to identifying repurposed drugs to treat SCN8A epilepsy." Epilepsia. Volume 59. Issue 4. pages 802--813. https://doi.org/10.1111/epi.14037 25 March 2018.
  2. Yiling Bi, Matthew Might, Hariprasad Vankayalapati and Kuberan Balagurunathan. "Repurposing of Proton Pump Inhibitors as First Identified Small Molecule Inhibitors of Endo-β-N-acetylglucosaminidase (ENGase) for the Treatment of Rare NGLY1 Genetic Disease." Bioorganic & Medicinal Chemistry Letters. 5 May 2017.
  3. Might M & Wilsey M (2014). The shifting model in clinical diagnostics: how next-generation sequencing and families are altering the way rare diseases are discovered, studied, and treated. Genetics in Medicine, 16(10), 736-7. PMID: 24651604.
  4. Katie G Owings, Joshua B Lowry, Yiling Bi, Matthew Might, Clement Y Chow. "Transcriptome and functional analysis in a Drosophila model of NGLY1 deficiency provides insight into therapeutic approaches." Human Molecular Genetics. Volume 27. Issue 6. pages 1055--1066. https://doi.org/10.1093/hmg/ddy026 15 March 2018. 

 

B.              Positions and Honors
 

Positions and Employment

2017-                                          Director, Hugh Kaul Precision Medicine Institute, University of Alabama at Birmingham

2017-                                          Professor, Department of General Internal Medicine, University of Alabama at Birmingham

2017-                                          Hugh Kaul Endowed Chair in Personalized Medicine

2017-                                          Senior Lecturer, Biomedical Informatics, Harvard Medical School

2016-2018                            Strategist for Precision Medicine, Executive Office of the President at the White House

2016-2018                            Research Affiliate, Department of Veterans Affairs

2016-2018                            Adjunct Associate Professor, Pharmaceutical Chemistry, University of Utah

2015-2017                            Visiting Associate Professor, Biomedical Informatics, Harvard Medical School

2014-2017                            Associate Professor, School of Computing, University of Utah

2008-2014               Assistant Professor, School of Computing, University of Utah

 

Other Experience and Professional Memberships (related to medicine)

2016                                          Precision Medicine Task Force, HHS

2016- (est)                            Council Member, Advisory Council, NCATS, NIH

2016- (est)                            Board Member, Cures Acceleration Network Review Board, NCATS, NIH

2015                                          White House Roundtable on Precision Medicine: Security and Privacy Policy

2015                                          White House Roundtable on Precision Medicine: Data Privacy and Participant Engagement

2015                                          White House Roundtable on Precision Medicine: Regulatory Challenges

2015                                          Invited Presentation on Precision Medicine at the White House

2015                                          NIH Precision Medicine Workshops, Patient Engagement Working Group Member

2014-                                          Advisor, Undiagnosed Disease Network Coordinating Center, Harvard University

 

Honors

2015                                          White House Champions of Change in Precision Medicine Host

2014-2017                            Presidential Scholar, University of Utah

2012                                          Instructor of the Year Award, School of Computing, University of Utah

 

 

C.              Contributions to Science
 

1.              I have made foundational contributions in computer science in fundamental data structures, machine understanding of grammar, automated reasoning, automatic detection of security vulnerabilities and provably-secure software, logic programming and domain-specific languages for scientific computing.

 

a.              Might M, Darais D & Spiewak D. (2011). Parsing with derivatives: a functional pearl. Proceedings of the 16th ACM SIGPLAN international conference on Functional programming. Pp. 189-195.

b.              Van Horn D & Might M. (2010). Abstracting abstract machines. ICFP 2010. Pp. 51-62.

c.              William E. Byrd, Michael Ballantyne, Greg Rosenblatt and Matthew Might. "Functional Pearl: A Unified Approach to Solving Seven Programming Problems." Proceedings of the 22nd ACM SIGPLAN International Conference on Functional Programming (ICFP 2017). Oxford, United Kingdom. September 2017.

d.              Prabhu T, Ramalingam S, Might M & Hall M. EigenCFA: Acceleratring Flow Analysis with GPUs. POPL, 511-522.

 

2.              My first work in medicine focused on variant interpretation and the network effects associated with collective genomic databases, as well as novel strategies (often patient-driven) for accelerating diagnosis and discovery of ultra-rare disorders. 

 

a.              Might M & Wilsey M. (2014). The shifting model in clinical diagnostics: how next-generation sequencing and families are altering the way rare diseases are discovered, studied and treated. Genetics in Medicine, 16(10) 736-7. PMID: 24651604.

b.              Lambertson KF, Damiani SA, Might M, Shelton R & Terry SF. (2015). Participant-Driven Matchmaking in the Genomic Era. Human Mutation, 36(10) 965-73. PMID: 26252162.

c.   Rachel Ramoni, et al. "The Undiagnosed Diseases Network: Accelerating Discovery about Health and Disease." American Journal of Human Genetics. Volume 100. Issue 2. pages 185--192. 2 February 2017.

d.  Nicole A. Vasilevsky, Erin D. Foster, Mark E. Engelstad, Leigh Carmody, Matt Might, Chip Chambers, Hugh J. S. Dawkins, Janine Lewis, Maria G. Della Rocca, Michelle Snyder, Cornelius F. Boerkoel, Ana Rath, Sharon F. Terry, Alastair Kent, Beverly Searle, Gareth Baynam, Erik Jones, Pam Gavin, Michael Bamshad, Jessica Chong, Tudor Groza, David Adams, Adam C. Resnick, Allison P. Heath, Chris Mungall, Ingrid A. Holm, Kayli Rageth, Catherine A. Brownstein, Kent Shefchek, Julie A. McMurry, Peter N. Robinson, Sebastian Köhler, Melissa A. Haendel. "Plain-language medical vocabulary for precision diagnosis." Nature Genetics. Volume 50. pages 474--476. 9 April 2018.

 

 

3.              While working toward understanding, treatment and cure for NGLY1, I have rapidly educated myself (and continue to do so) in genetics, gene regulation, protein folding and structure, glycobiology, signaling, model organism construction and phenotyping, assay development, high-throughput screening and medicinal chemistry.  I have also made significant intellectual investments in understanding therapeutic strategies in rare disease, including suppression screens, read-through compounds, exon-skipping, inhibitor-mediated rescue, enzyme replacement (and PEGylation and TAT peptides in particular), gene editing and gene therapy. My recent work has moved in a more clinical direction, focusing on therapeutics for NGLY1 deficiency and clinical practice for family planning in the event of undiagnosed disease with a suspected genetic basis.

 

  1. Might, M., & Might, C. C. (2017). What happens when N = 1 and you want plus 1? Prenatal Diagnosis, 37(1), 70-72. DOI: 10.1002/pd.4975
  2. Talia A. Atkin, Chani M. Maher, Aaron C. Gerlach, Bryant C. Gay, Brett M. Antonio, Sonia C. Santos, Karen M. Padilla, JulieAnn Rader, Douglas S. Krafte, Matthew A. Fox, Gregory R. Stewart, Slavé Petrovski, Orrin Devinsky, Matthew Might, Steven Petrou, David B. Goldstein. "A comprehensive approach to identifying repurposed drugs to treat SCN8A epilepsy." Epilepsia. Volume 59. Issue 4. pages 802--813. https://doi.org/10.1111/epi.14037 25 March 2018.
  3. Katie G Owings, Joshua B Lowry, Yiling Bi, Matthew Might, Clement Y Chow. "Transcriptome and functional analysis in a Drosophila model of NGLY1 deficiency provides insight into therapeutic approaches." Human Molecular Genetics. Volume 27. Issue 6. pages 1055--1066. https://doi.org/10.1093/hmg/ddy026 15 March 2018.
  4. Yiling Bi, Matthew Might, Hariprasad Vankayalapati, Balagurunathan Kuberan, Repurposing of Proton Pump Inhibitors as first identified small molecule inhibitors of endo-β-N-acetylglucosaminidase (ENGase) for the treatment of NGLY1 deficiency, a rare genetic disease, Bioorganic & Medicinal Chemistry Letters, Volume 27, Issue 13, 2017, Pages 2962-2966, ISSN 0960-894X, http://dx.doi.org/10.1016/j.bmcl.2017.05.010.s

 

 

Complete Publication List:  Please see the following URL link for the complete publication list in computer science of Matt Might: http://dblp.uni-trier.de/pers/hd/m/Might:Matthew

 

 

 

 

D.              Additional Information: Research Support and/or Scholastic Performance

 

Ongoing Research Support

 

  National Science Foundation.               Might (PI)                                                                                                                                                                        01/2014-01/2020

CAREER Award: Static analysis-driven software engineering

The goal of this research is to develop advanced techniques in static analysis to aid software engineering.

Role: Lead PI

 

NIH                                              Might (Co-PI)                                                             07/2018/-08/2022

Coordinating Center for the Undiagnosed Diseases Network (UDN)

The goal of this research is to accelerate discovery and innovation in the way patients with previously undiagnosed diseases are diagnosed and treated.

Role: Sub PI

 

NIH                                              Might (PI)                                                                  12/2017-01/2020

National Center for Advancing Translational Sciences (NCATS)

The goal of this research is to apply automated reasoning to biomedical data sets and knowledge sources in order to gain new insight into and identify treatments for diseases.

Role: Lead PI

 

NIH                                                                                                                 Might (Co-PI)                                                                                                                                                          08/2019-07/2023

RDCRN for Congenital Disorders of Glycosylation.

The goal of this research is to develop a network for natural history studies in CDGs and clinical trials.

Role: Sub PI

 

 

Previous support

 

DARPA.                                                                                                   Might (PI)                                                                                                                                                                        04/2015-03/2019

A4V: Automated Analysis for Algorithmic Attack Vectors.

The goal of this research is to detect space-time security vulnerabilities in complex software.

Role: Lead PI

 

Department of Energy                                          Smith (PI)                                                                                                                                                                        04/2014-03/2019

Carbon Capture Multidisciplinary Simulation Center (CCMSC).

This research is focused on simulating turbulent reacting flow at exascale to design carbon-neutral boilers.

Role: Co-PI

 

DARPA:                                                                                                   Might (PI)                                                                                                                                                                        01/2014-12/2016

Supplement. “Analysis of UI-driven malware.”

This research is largely focused on analysis of scripting languages.

Role: Lead PI

 

DARPA                                                                                                  Might (PI)                                                                                                                                                                        02/2012-01/2016

Scalable and precise abstractions of software for trustworthy programs.

This research focuses on detecting novel malware automatically using the semantics of software.

Role: Lead PI

 

National Science Foundation               Berzins (PI)                                                                                                                                                          09/2013-08/2016

XPS:CLCCA (XPS:DSD) Future Extreme Scale Frameworks Using DSL and ERTS.

The research focuses on designing languages to support high-performance scientific computing.

Role: Co-PI

 

 

DARPA                                                                                                  Might (PI)                                                                                                                                                                        06/2013-08/2015

DARPA: Supplement. “Scalable and precise abstraction interpretation of client-side programs.

This research focuses on analysis of client-side software.

Role: Lead PI

 

National Science Foundation               Might (PI)                                                                                                                                                                        09/2012-08/2014

EAGER: Platform-Agnostic Supercomputing from Scientific Metaprogramming.

This research focuses on meta-programming to support platform-independent scientific computing.

Role: Lead PI

 

DARPA                                                                                                  Might (PI)                                                                                                                                                                        09/2010-08/2015

CRASH.

This research focuses on developing novel computational substrates that are resistant to cyberattack.

Role: Lead PI for Utah