Hi ! Welcome to my personal webpage
The focus of my investigations is to build personalized mathematical models of the biophysical mechanisms underlying cancer growth and therapeutic response, with which I can make patient-specific forecasts of tumor prognosis using computer simulations. I believe that this predictive approach can dramatically contribute to advance clinical practice in oncology by delivering personalized solutions aiming at optimizing clinical outcomes for each patient.
I also work in modeling the mechanisms of development, treatment, and spread of other pathologies. Additionally, I am interested in constructing robust computational methods to efficiently and accurately solve my models in clinically-relevant times.
Thanks to a "la Caixa" Foundation Postdoctoral Junior Leader Fellowship, I am currently working at the Medical Physics and Biomathematics Group of the Health Research Institute of Santiago de Compostela in Spain, but I am also a postdoctoral research affiliate at the Center for Computational Oncology at the Oden Institute in The University of Texas at Austin.
Check out my research below and feel free to contact me if you are interested in discussing my work or any of the topics in this webpage. I am always open to new collaborations, delivering academic and popular science talks, or having a drink to talk science and else.
Research
Patient-specific, imaging-based forecasting of prostate cancer growth
This research aims at integrating standard clinical and imaging data from individual patients into mathematical models to enable the prediction of tumor growth using computer simulations
Personalized prediction of PSA dynamics after external radiotherapy of prostate cancer
Exploring the biophysical mechanisms underlying PSA dynamics after external radiotherapy to define new biomarkers for the early identification of relapse
Optimal control of therapeutic regimens for advanced prostate cancer
This work aims at finding optimal combinations of cytotoxic and antiangiogenic therapies to treat advanced prostatic tumors by combining mathematical analysis and computer simulations
Personalized prediction of breast cancer response to neoadjuvant therapies by using biophysical models parameterized with patient-specific imaging data and constrained by comprehensive pharmacodynamic experimental data
Data-driven mechanistic models to forecast COVID-19 outbreaks
Constructing mathematical models to understand and predict the dynamics of COVID-19 infectious spread based on longitudinal epidemiological data series
Publications
Guillermo Lorenzo, Jon S Heiselman, Michael A Liss, Michael I Miga, Hector Gomez, Thomas E Yankeelov, Alessandro Reali, Thomas JR Hughes
Cancer Research Communications, vol. 4, 2024, pp. 617--633
Hugo JM Miniere, Ernesto ABF Lima, Guillermo Lorenzo, David A Hormuth, Sophia Ty, Amy Brock, Thomas E Yankeelov
Cancer Biology & Therapy, vol. 25, 2024, p. 2321769
Designing clinical trials for patients who are not average
Thomas E Yankeelov, David A Hormuth, Ernesto ABF Lima, Guillermo Lorenzo, Chengyue Wu, Lois C Okereke, Gaiane M Rauch, Aradhana M Venkatesan, Caroline Chung
Iscience, vol. 27, 2024, p. 108589
Anirban Chaudhuri, Graham Pash, David A Hormuth, Guillermo Lorenzo, Michael Kapteyn, Chengyue Wu, Ernesto ABF Lima, Thomas E Yankeelov, Karen Willcox
Frontiers in Artificial Intelligence, vol. 6, 2023, p. 1222612
Orhun O Davarci, Emily Y Yang, Alexander Viguerie, Thomas E Yankeelov, Guillermo Lorenzo
Engineering with Computers, 2023, pp. 1--25
View all
Pages
List of my experience in teaching university courses and supervising students
Contact
Guillermo Lorenzo, PhD
"la Caixa" Foundation Postdoctoral Junior Leader Fellow
guillermo.lorenzo.gomez@sergas.es
Medical Physics and Biomathematics Group
Health Research Institute of Santiago de Compostela
Hospital Clínico de Santiago de Compostela
Travesía da Choupana S/N
15706 Santiago de Compostela
Spain
