Dr. Van Allen is developing machine-learning algorithms to analyze genomic, imaging, and clinical data from over 3000 prostate cancer patients that can be used to predict clinical outcomes, inform care decisions, and accelerate new biological discoveries. This work will create a clinical and translational discovery engine in prostate cancer that will ultimately be translated into an open source platform that can be used by both clinicians and researchers. These efforts will also lay a foundation for innovative data science efforts across cancer types. Originally from Los Angeles, Dr. Van Allen studied Symbolic Systems at Stanford University, obtained his MD from UCLA, and completed a residency in internal medicine at UCSF before completing a medical oncology fellowship at the Dana-Farber/Partners CancerCare program.
Berchuck JE, Zhang Z, Silver R, Kwak L, Xie W, Lee GM, Freedman ML, Kibel AS, Van Allen EM, McKay RR, Taplin ME. Impact of Pathogenic Germline DNA Damage Repair alterations on Response to Intense Neoadjuvant Androgen Deprivation Therapy in High-risk Localized Prostate Cancer. Eur Urol. 2021.
He MX, Cuoco MS, Crowdis J, Bosma-Moody A, Zhang Z, Bi K, Kanodia A, Su MJ, Ku SY, Garcia MM, Sweet AR, Rodman C, DelloStritto L, Silver R, Steinharter J, Shah P, Izar B, Walk NC, Burke KP, Bakouny Z, Tewari AK, Liu D, Camp SY, Vokes NI, Salari K, Park J, Vigneau S, Fong L, Russo JW, Yuan X, Balk SP, Beltran H, Rozenblatt-Rosen O, Regev A, Rotem A, Taplin ME, Van Allen EM. Transcriptional mediators of treatment resistance in lethal prostate cancer. Nat Med. 2021.
Tewari AK, Cheung ATM, Crowdis J, Conway JR, Camp SY, Wankowicz SA, Livitz DG, Park J, Lis RT, Bosma-Moody A, He MX, AlDubayan SH, Zhang Z, McKay RR, Leshchiner I, Brown M, Balk SP, Getz G, Taplin ME, Van Allen EM. Molecular features of exceptional response to neoadjuvant anti-androgen therapy in high-risk localized prostate cancer. Cell Rep. 2021.