This week in MathOnco 185
Organoid environmental effects, classic growth models in humans, adaptive therapy, model-informed drug development, and more
“This week in Mathematical Oncology” — Oct. 28, 2021
From the editor:
This week’s edition includes papers on organoid environmental effects, classic growth models in humans, adaptive therapy, model-informed drug development, tumor-immune interactions and more.
Perspective on model-informed drug development
Lawrence J. Lesko
Prediction of overall survival in patients across solid tumors following atezolizumab treatments: A tumor growth inhibition–overall survival modeling framework
Phyllis Chan, Mathilde Marchand, Kenta Yoshida, Shweta Vadhavkar, Nina Wang, Alyse Lin, Benjamin Wu, Marcus Ballinger, Nitzan Sternheim, Jin Y. Jin, René Bruno
Multistate model for pharmacometric analyses of overall survival in HER2-negative breast cancer patients treated with docetaxel
Sreenath M. Krishnan, Lena E. Friberg, René Bruno, Ulrich Beyer, Jin Y. Jin, Mats O. Karlsson
Optimizing Adaptive Therapy Based on the Reachability to Tumor Resistant Subpopulation
Jiali Wang, Yixuan Zhang, Xiaoquan Liu, Haochen Liu
Modeling Prostate Cancer Treatment Responses in the Organoid Era: 3D Environment Impacts Drug Testing
Annelies Van Hemelryk, Lisanne Mout, Sigrun Erkens-Schulze, Pim J. French, Wytske M. van Weerden, Martin E. van Royen
Cells with cancer-associated mutations overtake our tissues as we age
Edward J. Evans Jr., James DeGregori
Towards integration of time-resolved confocal microscopy of a 3D in vitro microfluidic platform with a hybrid multiscale model of tumor angiogenesis
Caleb M. Phillips, Ernesto A. B. F. Lima, Manasa Gadde, Angela M. Jarrett, Marissa Nichole Rylander, Thomas E. Yankeelov
Dynamics of fibril collagen remodeling by tumor cells using individual cell-based mathematical modeling
Sharan Poonja, Mehdi Damaghi, Katarzyna A. Rejniak
Classical Mathematical Models for Prediction of Response to Chemotherapy and Immunotherapy
Narmin Ghaffari Laleh, Chiara Maria Lavinia Loeffler, Julia Grajek, Kateřina Staňková, Alexander T. Pearson, Hannah Sophie Muti, Christian Trautwein, Heiko Enderling, Jan Poleszczuk, Jakob Nikolas Kather
Spatio-temporal modelling of phenotypic heterogeneity in tumour tissues and its impact on radiotherapy treatment
Giulia L. Celora, Helen M. Byrne, P.G. Kevrekidis
Collective gradient sensing with limited positional information
Emiliano Perez Ipiña, Brian A. Camley
The Night Science Podcast
“Where do ideas come from? In each episode, scientists Itai Yanai and Martin Lercher explore science’s creative side with a leading colleague.”
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Caption: In the simplest sense, the ultimate goal of treating cancer is for the patient to remain alive. This is not synonymous with eradicating every tumor cell in the body. Similar to the failure of high-dose synthetic pesticides in agricultural pest management to result in “cured fields,” high dose treatments in metastatic disease rarely, if ever, result in a cure. So, until truly curative therapies are developed, the treatment of metastatic disease could greatly benefit from the development of a long-term management clinical paradigm that judiciously uses the plethora of therapies that are already available. Coined as “Integrated Metastatic Management,” this new clinical paradigm would draw heavily from the principles of agricultural pest management and could result in the slowing or curtailing of widespread resistance to treatment, reducing overall drug usage, and increasing the overall survival and quality of life of cancer patients.
Created by: Cover art and design by Leslie Caroline Wilcox, 2021.
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