Baskin will oversee a large, multidisciplinary cancer center comprising 250 scientists and clinical investigators. She will be the fifth director since Massey received its National Cancer Institute (NCI) designation in 1975—an inflection point that underscores how the center’s priorities are evolving alongside national expectations for translational impact and equity-focused outreach.

Her career has centered on a community-to-bench model of cancer care. Rather than treating engagement as an afterthought, Baskin’s approach integrates behavioral, social, and environmental determinants into the design of prevention, screening, treatment, and survivorship strategies. This framework supports technical pathways that connect real-world constraints—access, trust, and context—with measurable clinical and behavioral outcomes.

A major emphasis in her work involves lifestyle interventions aimed at improving cancer-related behaviors and health outcomes, including diet, physical activity, and obesity risk. Such outcomes are particularly relevant for rural populations and communities that have historically faced barriers to cancer prevention and care. By targeting modifiable behaviors, her research translates population-level risk factors into intervention-ready programs.

VCU President Michael Rao, Ph.D., highlighted Baskin’s publication record and community-centered research as central to her readiness for the role. He also noted her recent performance as Massey’s deputy director, describing her as a driver of cutting-edge research with direct impact for the center’s catchment area.

Since joining Massey in February 2025, Baskin has strengthened the center’s influence across central, southern, and eastern Virginia. She has also elevated Massey’s national profile through leadership in academic societies, including former presidency of the Society of Behavioral Medicine (SBM) and board service roles connected to academic medical centers and community outreach and education.

Baskin’s motivation is personal as well as scientific. Raised in Atlanta, she lost her father to colorectal cancer during her senior year of high school, and later experienced additional family losses to cancer. Those events guided her training in psychology and her focus on cancer prevention, early detection, and mental health.

With more than $70 million in National Institutes of Health (NIH) grant involvement as a principal investigator or team leader, Baskin has also contributed to Cancer Center Support Grant (CCSG) review panels. That experience positions her to lead Massey through renewal of its CCSG and comprehensive-designated status, which the center earned for the first time in 2023.

Beyond directing Massey, she serves as associate dean for cancer innovation in the VCU School of Medicine and holds professor appointments spanning internal medicine and social and behavioral sciences. Her appointment is expected to reinforce a data-driven, equity-forward translation engine—one that aims to reduce cancer burden through both science and community partnership.

Subject of Research: Community-to-bench cancer prevention and lifestyle interventions (behavioral, social, and environmental determinants)
Article Title: Monica L. Baskin to Become Next Director of VCU Massey Comprehensive Cancer Center
News Publication Date:
Web References:
References:
Image Credits: VCU Massey Comprehensive Cancer Center
Keywords: VCU Massey, Monica L. Baskin, cancer center director, community-to-bench model, NCI-designated, cancer prevention, screening, lifestyle interventions, health equity, rural health

Dr. Boutros will also assume roles as senior vice president of data sciences and professor, continuing his distinguished career trajectory that melds computational biology with clinical insights. Before this appointment, he was a professor at UCLA’s David Geffen School of Medicine, with joint appointments in human genetics and urology, and served as interim vice dean for research. His research prowess lies in harnessing artificial intelligence (AI), machine learning (ML), and the computational sciences to decode voluminous, complex datasets inherent in modern oncological studies, which are crucial for designing innovative and predictive cancer research projects.

At the core of Boutros’ scientific inquiry is the integration of diverse datasets — clinical, molecular, and imaging — to personalize cancer therapies. His commitment to identifying precise biomarkers epitomizes a critical shift in oncology: moving beyond one-size-fits-all treatments to precision medicine strategies that maximize therapeutic benefit while minimizing adverse effects. According to Sanford Burnham Prebys CEO David A. Brenner, Dr. Boutros exemplifies pioneering “over-the-horizon thinking,” using rapidly evolving computational methods to tackle previously insurmountable questions in cancer biology and treatment.

Paul Boutros’ academic background underpins his groundbreaking approach. He earned his Bachelor of Science in Chemistry from the University of Waterloo in 2004, followed by a PhD in Medical Biophysics from the University of Toronto in 2008, where he additionally completed an executive MBA. His early research career began at the Ontario Institute for Cancer Research, where he progressed from fellow to principal investigator. Throughout his career, Boutros has published over 200 peer-reviewed articles and received numerous accolades, including the Dorval Prize by the Canadian Cancer Society, recognizing the top early career investigator nationwide.

The Sanford Burnham Prebys Cancer Center’s mission reflects a focus on fundamental cancer biology and translational studies that drive novel clinical applications. Faculty expertise spans multiple disciplines, including cell biology, immunology, epigenetics, metabolism, aging, and computational science. Collaborations with the Center for Therapeutics Discovery and the Center for Data Science and Artificial Intelligence further augment the center’s capabilities, promoting innovation at the intersection of biological research and computational analysis.

A recent notable example of Boutros’ innovative research leverages AI and computational tools to investigate the interplay between exercise and prostate cancer progression. Prostate cancer remains the second leading cause of cancer deaths among American men, and despite its prevalence, the role of lifestyle interventions like exercise in altering disease trajectory has been poorly quantified under controlled conditions. In a 2024 study published in JAMA Oncology, Boutros and colleagues carried out a decentralized, Phase I controlled trial examining how prescribed treadmill walking impacts biomarkers linked to prostate cancer outcomes.

The trial enrolled 53 previously inactive men aged 47 to 74 with diagnosed prostate cancer, equipping participants nationwide with a home treadmill, smartwatch, iPad, and other health monitoring devices. This infrastructure allowed real-time remote supervision of exercise regimens ranging from 90 to 450 minutes per week. The dual biomarkers assessed were Ki-67, a proliferative index marking the rate of cancer cell division, and prostate-specific antigen (PSA), an established marker for prostate cancer risk and progression. Their methodological rigor ensured quantifiable evaluation of exercise dose and corresponding biological impact.

Findings from this pioneering trial revealed that high levels of exercise were safely tolerated and that exercising approximately 225 minutes weekly emerged as the optimal “dose” for mitigating prostate cancer risk, as evidenced by favorable changes in Ki-67 and PSA biomarkers. Lesser durations yielded no significant biomarker change, while more extensive exercise produced only marginally increased benefits. This outcome signals a potential paradigm shift in prostate cancer management, suggesting that precisely prescribed exercise could function as an adjunct therapy, modifiable through computational precision.

Building upon this work, Boutros’ team has initiated a multi-institutional Phase 2 clinical trial, now listed on ClinicalTrials.gov, to compare the progression of prostate cancer in men performing targeted exercise regimens to those following typical activity levels. The integration of wearable technology, real-time data analytics, and personalized exercise prescriptions exemplifies how computational medicine can redefine treatment approaches. This strategy juxtaposes traditional pharmaceutical interventions with novel lifestyle-modification therapies under data-driven oversight.

In sum, Paul Boutros embodies the transformative power of computational biology and data science in oncology. His leadership at Sanford Burnham Prebys is poised to accelerate fundamental discoveries and translation into clinical innovation. By bridging artificial intelligence, big data, and patient-centered trials, Boutros is setting a new standard for combating complex diseases like cancer through integrative, technology-empowered research paradigms. As the landscape of cancer research evolves, computationally driven insights such as these are critical to developing precision oncology that improves outcomes for millions globally.

Subject of Research: Computational Biology and Cancer Research, Exercise Therapy in Prostate Cancer
Article Title: Paul Boutros Appointed Director of Sanford Burnham Prebys Cancer Center, Pioneers Computational Oncology and Exercise Therapy Research
News Publication Date: 2024
Web References:
– National Cancer Institute Cancer Centers: https://www.cancer.gov/research/infrastructure/cancer-centers
– JAMA Oncology Exercise Trial Article: https://jamanetwork.com/journals/jamaoncology/fullarticle/2821207
– Sanford Burnham Prebys Centers:
– Center for Therapeutics Discovery: https://sbpdiscovery.org/research/centers/center-for-therapeutics-discovery/
– Center for Data Science and Artificial Intelligence: https://sbpdiscovery.org/research/centers/center-for-data-science/
– Clinical Trial Registration: https://www.clinicaltrials.gov/study/NCT05751434
Image Credits: Sanford Burnham Prebys
Keywords: Cancer, Prostate cancer, Physical exercise, Computational biology, Informatics, Computer science, Machine learning, Artificial intelligence