On This Episode Of The Public Health Epidemiology Conversations (PHEC) Podcast
There will always be the need for professionals to make informed, evidence-based decisions when it comes to public health. Dr. Paul Arora, vice president of Cytel, joins us to discuss the importance of using evidence to make decisions about public health, to explain quantitative bias analysis, and share his passion for oncology. Tune in to hear all about what drew Paul to public health, how his epidemiology background makes him excellent at his job, and even get some pearls of wisdom for pursuing a career in public health. Thanks for listening in!
Meet Dr. Paul Arora
Paul Arora is an epidemiologist with significant experience in global public health and the application of epidemiological methods for evidence synthesis. He is presently the Vice President of Advanced Epidemiology at Cytel, the largest provider of statistical software and advanced analytics for clinical trial design and execution, globally. There he plays a key role in the domain of real-world evidence, facilitating the expansion and management of diverse business lines.
Before his tenure at Cytel, Paul co-founded Lighthouse Outcomes, a consulting firm specializing in advanced analytics for epidemiology and health economics research. Lighthouse Outcomes was successfully acquired by Cytel in 2020. During his time at Lighthouse, Paul and his team developed BUGSnet, a software tool used for the Bayesian network meta-analysis of clinical trials, and also promoted the application of graphical machine learning models for risk prediction in clinical epidemiology.
Paul maintains a status position as an Assistant Professor at the Dalla Lana School of Public Health, within the Division of Epidemiology at the University of Toronto. There, he provides instruction on epidemiological methods and communicable disease epidemiology. His PhD thesis explored and characterized the HIV epidemic in India, underlining his longstanding interest in infectious diseases. Paul's wide-ranging interests span from comparative effectiveness methods using causal inference to machine learning and quantitative bias analysis, which serve to improve our understanding of uncertainty in medical studies.
As a researcher, Paul has contributed to over 60 peer-reviewed scientific articles. His most recent contributions include notable insights into the understanding and treatment of COVID-19, published in the New England Journal of Medicine this year, and a leading role in a large-scale application of quantitative bias analysis to target trial emulation in oncology (the QBASEL study).
Paul’s work strives to integrate cutting-edge epidemiological methods, machine learning, and the ever-increasing corpus of real-world data to deepen our understanding of disease dynamics and to enhance health outcomes and drug development processes.
Listen To This Episode Of The Public Health Epidemiology Conversations (PHEC) Podcast
Conversation Highlights
Our incredible guest: ‘jack of all trades’ epidemiologist, Dr. Paul Arora
How a couple of books inspired Paul to become interested in public health
Why Paul is particularly passionate about oncology
How Paul started his business, Lighthouse Outcomes, and it’s focus
Quantitative bias analysis (QBA) and how the data is collected and measured
Paul’s ideal client
The importance of using quality evidence to make decisions
Paul’s understanding of epidemiology and public health
Paul’s advice for anyone wanting to get into his line of work
“The training that – we receive as epidemiologists to focus our attention on bias has been absolutely pivotal to the kind of solutions that we can offer to our customers who are increasingly relying on new-world evidence to make decisions.” — Dr. Paul Arora
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