Alind Gupta

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Adjunct Lecturer, Division of Epidemiology
Dalla Lana School of Public Health, University of Toronto

I am a consultant and researcher specializing in data science aimed at improving health outcomes and facilitating decision making. I work primarily with pharma companies, biotechs and public agencies globally.

My research interests and expertise are in:

  • Applied methods for causal inference & bias
  • Prospective & retrospective observational study design
  • Generalizability & transportability
  • Treatment policy optimization
  • Machine learning
  • Public health in low- and middle-income countries

news

May 07, 2024 Workshop on transportability was accepted at ICPE 2024 in Berlin
Feb 06, 2023 Our workshop abstract on target trial emulation with Stephen Duffield (National Institute for Health and Care Excellence), Joy Shi (Harvard/CAUSALab) and Kristian Thorlund (McMaster) accepted at ISPOR 2023
Jul 20, 2022 Our paper on quantitative bias analysis was cited by NICE’s real-world evidence framework as a case study!

selected publications

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    Assessment of alectinib vs ceritinib in ALK-positive non-small cell lung cancer in phase 2 trials and in real-world data
    Samantha Wilkinson ,  Alind Gupta ,  Nicolas Scheuer , and 7 more authors
    JAMA Network Open, 2021
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    Transportability of overall survival estimates from US to Canadian patients with advanced non-small cell lung cancer with implications for regulatory and health technology assessment
    Sreeram V Ramagopalan ,  Sanjay Popat ,  Alind Gupta , and 8 more authors
    JAMA Network Open, 2022