27 papers · ranked by Valyu relevance
Navid Mohammad Mirzaei, Leili Shahriyari
Computational modeling of cancer can help unveil dynamics and interactions that are hard to replicate experimentally. Thanks to the advancement in cancer databases and data analysis technologies, these models have become more robust than ever. There are many mathematical models which investigate cancer through…
Sharvari Kemkar, Mengdi Tao, Alokendra Ghosh, Georgios Stamatakos + 5 more
Cancer exhibits substantial heterogeneity, manifesting as distinct morphological and molecular variations across tumors, which frequently undermines the efficacy of conventional oncological treatments. Developments in multiomics and sequencing technologies have paved the way for unraveling this heterogeneity.…
James Gu, Jake Y. Chen
We introduce the Multi-level Parameterized Automata (MLPA), an innovative digital twin model that revolutionizes personalized cancer growth simulation and treatment optimization. MLPA integrates macroscopic electronic health records and microscopic genomic data, employing stochastic cellular automata to model tumor…
Jakob Rosenbauer, Marco Berghoff, Alexander Schug
Despite decades of substantial research, cancer remains a ubiquitous scourge in the industrialized world. Effective treatments require a thorough understanding of macroscopic cancerous tumor growth out of individual cells. Clinical imaging methods, however, only detect late-stage macroscopic tumors, while many…
Ralf Gallasch, Mirjana Efremova, Pornpimol Charoentong, Hubert Hackl + 1 more
'Zlatko Trajanoski'] In the context of translational and clinical oncology, mathematical models can provide novel insights into tumor-related processes and can support clinical oncologists in the design of the treatment regime, dosage, schedule, toxicity and drug-sensitivity. In this review we present an overview of…
Serbulent Unsal, Aybar Acar, Mehmet Itik, Ayse Kabatas + 3 more
Cancer is one of the most complex phenomena in biology and medicine. Extensive attempts have been made to work around this complexity. In this study, we try to take a selective approach; not modeling each particular facet in detail but rather only the pertinent and essential parts of the tumor system are simulated and…
Yehor Surkov, Ihor Samofalov, Mironenko Anastasia
In the present article we demonstrate a new hybrid model of tumor growth. Our model is stochastic by tumor population development and strongly deterministic in cell motility dynamics and spatial propagation. In addition, it has excellent extendibility property. Described model is tested on general behavior and on…
Jaroslaw Smieja, Francisco Torrens
The paper presents a review of models that can be used to describe dynamics of lung cancer growth and its response to treatment at both cell population and intracellular processes levels. To address the latter, models of signaling pathways associated with cellular responses to treatment are overviewed. First, treatment…
Lesley A. Ogilvie, Aleksandra Kovachev, Christoph Wierling, Bodo M. H. Lange + 1 more
'Bodo M. H. Lange' 'Hans Lehrach'] Every patient and every disease is different. Each patient therefore requires a personalized treatment approach. For technical reasons, a personalized approach is feasible for treatment strategies such as surgery, but not for drug-based therapy or drug development. The development of…
Narmin Ghaffari Laleh, Chiara Maria Lavinia Loeffler, Julia Grajek, Kateřina Staňková + 6 more
Classical mathematical models of tumor growth have shaped our understanding of cancer and have broad practical implications for treatment scheduling and dosage. However, even the simplest textbook models have been barely validated in real world-data of human patients. In this study, we fitted a range of differential…
Loredana G. Marcu, Wendy M. Harriss-Phillips
Mathematical and stochastic computer (in silico) models of tumour growth and treatment response of the past and current eras are presented, outlining the aims of the models, model methodology, the key parameters used to describe the tumour system, and treatment modality applied, as well as reported outcomes from…
Xiaoyu Wang, Adrianne L. Jenner, Robert Salomone, Christopher Drovandi
Agent-based models (ABMs) are readily used to capture the stochasticity in tumour evolution; however, these models can pose a challenge in terms of their ability to be validated with experimental measurements. The Voronoi cell-based model (VCBM) is an off-lattice agent-based model that captures individual cell shapes…
E Blom, Stefan Engblom, Gesina Menz
We present a stochastic computational model of avascular tumors, emphasizing the detailed implementation of the first four so-called hallmarks of cancer: selfsufficiency in growth factors, resistance to growth inhibitors, avoidance of apoptosis, and unlimited growth potential. Our goal is to provide a foundational…
Guillermo Lorenzo, Syed Rakin Ahmed, David A. Hormuth, Brenna Vaughn + 4 more
'Jayashree Kalpathy–Cramer' 'Luis Solorio' 'Thomas E. Yankeelov' 'Héctor Gómez'] Despite the remarkable advances in cancer diagnosis, treatment, and management that have occurred over the past decade, malignant tumors remain a major public health problem. Further progress in combating cancer may be enabled by…
Patricio Cumsille, Aníbal Coronel, Carlos Conca, Cristóbal Quiñinao + 1 more
'Carlos Escudero'] One of the main challenges in cancer modelling is to improve the knowledge of tumor progression in areas related to tumor growth, tumor-induced angiogenesis and targeted therapies efficacy. For this purpose, incorporate the expertise from applied mathematicians, biologists and physicians is highly…
Maxim Polyakov, Valeria V. Ten
In the present article the diffusion equation is used to model the spatiotemporal dynamics of a tumor, taking into account the heterogeneous of the medium. This approach makes it possible to take into account the complex geometric shape of the tumor in modeling. The main purpose of the work is demonstration the…
John Metzcar, Rachael Guenter, Yafei Wang, Kimberly M Baker + 1 more
'Kate E Lines'] Neuroendocrine tumors (NETs) occur sporadically or as part of rare endocrine tumor syndromes (RETSs) such as multiple endocrine neoplasia 1 and von Hippel-Lindau syndromes. Due to their relative rarity and lack of model systems, NETs and RETSs are difficult to study, hindering advancements in…
Constantino Carlos Reyes-Aldasoro, David Wong, Ángele Juarranz, Arun Dharmarajan
'Arun Dharmarajan'] Simple Summary The word “model” can be used with different meanings and different contexts, like a model student, clay models or a model railway. In some cases, the context can clarify exactly what is meant by “model”, but sometimes several meanings of model can be present in one area. For instance…
Joseph Malinzi, Kevin Bosire Basita, Sara Padidar, Henry A. Adeola
The long-term efficacy of targeted therapeutics for cancer treatment can be significantly limited by the type of therapy and development of drug resistance, inter alia. Experimental studies indicate that the factors enhancing acquisition of drug resistance in cancer cells include cell heterogeneity, drug target…
Rachel Walker, Heiko Enderling
Mathematical modeling has made many important contributions to the understanding of tumor growth, dormancy, regression and recurrence in recent years. Many of these models also account for tumor-immune interactions and both the innate and adaptive immune response, and have generally been accepted as valuable tools in…
Xiaoran Lai, Oliver M Geier, Thomas Fleischer, Øystein Garred + 10 more
Mathematical modeling and simulation have emerged as a potentially powerful, time and cost effective approach to personalized cancer treatment. The usefulness of mechanistic models to disentangle complex multi-scale cancer processes such as treatment response has been widely acknowledged. However, a major barrier for…
Mohsen Pourmousa, Sankalp Jain, Elena Barnaeva, Wengong Jin + 15 more
Treatment regimens, especially in cancer, often include more than one medicine in order to achieve durable outcomes. Identifying the optimal combination of treatments has historically been done through clinical trial and error. And for many conditions, such as pancreatic cancer, an optimal treatment protocol has…
Authors not listed
Despite $100 billion in investment and more than 100,000 publications, nanomedicine translation fails primarily at biological validation, not at synthesis or characterization. We present the first systematic technology readiness assessment across autonomous nanomedicine components, revealing a critical finding: while…
Stefan Ivanov
In order for computer-aided drug design to fulfil its long held promise of delivering new medicines faster and cheaper, extensive development and validation work must be done first. This pertains particularly to molecular dynamics force fields where one important aspect – the hydration free energy (HFE) of small…
Authors not listed
Immuno-oncology, a rapidly evolving field at the forefront of cancer research, leverages the body’s immune system to fight cancer. In this follow up report, we extend our natural language processing (NLP)-based analysis to pinpoint the context of emergence of the previously identified emerging concepts. To achieve this…
Rumiana Tenchov, Aparna Sapra, Janet Sasso, Krittika Ralhan + 3 more
Cancer is one of the leading causes of death worldwide. Early cancer detection is critical because it can significantly improve treatment outcome thus saving lives, reducing suffering, and lessening psychological and economic burdens. Cancer biomarkers provide varied information about cancer, from early detection of…
Authors not listed
Predicting drug-induced toxicity remains a central challenge in computational toxicology, particularly for organ-specific adverse effects that arise from diverse structural, biochemical, and mechanistic origins. Existing deep learning models excel at pattern recognition but often lack mechanistic interpretability…