Photo of Maha R. Farhat, MDCM

Maha R. Farhat, MDCM


Accepting New Patients



Pulmonary & Critical Care Medicine


Clinical Interests
  • Lung Infections
  • Critical care
Medical Education
  • MDCM, McGill University Faculty of Medicine
  • Residency, Massachusetts General Hospital
  • Fellowship, Brigham and Women's Hospital|Fellowship, Massachusetts General Hospital
Board Certifications
  • Internal Medicine
  • Pulmonary Disease
  • Critical Care Medicine
  • Boston: Massachusetts General Hospital
Insurances Accepted
  • Aetna Health Inc.
  • Beech Street
  • Blue Cross Blue Shield - Blue Care 65
  • Blue Cross Blue Shield - Indemnity
  • Blue Cross Blue Shield - Managed Care
  • Blue Cross Blue Shield - Partners Plus
  • Centene/Celticare
  • Cigna (PAL #'s)
  • Fallon Community HealthCare
  • Great-West Healthcare (formally One Health Plan)
  • Harvard Pilgrim Health Plan - ACD
  • Harvard Pilgrim Health Plan - PBO
  • Health Care Value Management (HCVM)
  • Humana/Choice Care PPO
  • MassHealth
  • Medicare
  • Medicare - ACD
  • Neighborhood Health Plan - ACD
  • Neighborhood Health Plan - PBO
  • OSW - Connecticut
  • OSW - Maine
  • OSW - New Hampshire
  • OSW - Rhode Island
  • OSW - Vermont
  • Private Health Care Systems (PHCS)
  • Railroad Medicare
  • Senior Whole Health
  • TriCare
  • Tufts Health Plan
  • Unicare
  • United Healthcare (non-HMO) - ACD
  • United Healthcare (non-HMO) - PBO
Patient Age Group

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Research & Publications

Research Summary
My current area of interest lies at the intersection of epidemiology, bioinformatics, computational and evolutionary biology as applied to microbial genome science and more specifically to understanding the biology of drug resistant Mycobacterium tuberculosis.

My previous work has included highly cited work on the accuracy of tuberculin skin tests for the diagnosis of latent tuberculosis, and the development of mathematical metabolic models to understand M. tuberculosis biology and response to drug exposure.

My most recent work has focused on the analysis and interpretation of signatures of natural selection in whole genome sequences of M. tuberculosis to uncover novel genes and cellular mechanisms associated with resistance. Through performing this work I developed a novel interface for storage and access of combined genomic and phenotypic data in Mtb that can significantly decrease time necessary for data retrieval and analysis. Additionally we have applied machine learning techniques to predict the M. tuberculosis resistance phenotype using the genetic sequence data of the established resistance genes in a large set of drug resistant M. tuberculosis strains. In other work we have performed a meta-analysis reviewing mutations in TB that are causative of drug resistance as determined by allelic exchange experiments and summarizing the evidence supporting this. We are also designing a schema for clinical strain selection and statistical power assessment for the prospective design of studies examining genotypic correlated of binary phenotypes in microbial populations, investigating  genomic sequence applications to decipher disease outbreaks of drug resistant M. tuberculosis, and predicting the clinical implications of using novel diagnostics for detection and guidance of TB patient therapy.

Farhat M, Greenaway C, Pai M, Menzies D. False-positive tuberculin reactions due to non-tuberculous mycobacterial infections. Int J Tuberc Lung Dis 2006 10(11): 1192

Colijn C, Brandes A, Zucker A, Zucker J, Lun DS, Weiner B, Farhat MR, et al. Interpreting expression data with metabolic flux models: predicting Mycobacterium tuberculosis mycolic acid production. PLoS Comput Biol. 2009 5(8):e1000489

Farhat MR, Shapiro BJ, et a.. Convergent Evolution Reveals Targets of Positive Selection in Drug Resistant Tuberculosis. In press Nature Genetics.

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Pulmonary and Critical Care
55 Fruit Street
Boston MA, 02114-2696
Phone: 617-726-8854

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