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The interactions between tumor cells and the immune system play a crucial role in cancer evolution. In this study, we explore how these interactions influence cancer progression by modeling the relationships among naive T cells, effector T…

Tissues and Organs · Quantitative Biology 2025-03-19 Haifeng Zhang , Changjing Zhuge , Jinzhi Lei

The ability to accurately predict disease progression is paramount for optimizing multiple myeloma patient care. This study introduces a hybrid neural network architecture, combining Long Short-Term Memory networks with a Conditional…

Combination therapies are often needed for effective clinical outcomes in the management of complex diseases, but presently they are generally based on empirical clinical experience. Here we suggest a novel application of search algorithms,…

There is tremendous interest in precision medicine as a means to improve patient outcomes by tailoring treatment to individual characteristics. An individualized treatment rule formalizes precision medicine as a map from patient information…

Machine Learning · Statistics 2020-05-28 Daniel J. Luckett , Eric B. Laber , Michael R. Kosorok

One primary goal of precision medicine is to estimate the individualized treatment rules (ITRs) that optimize patients' health outcomes based on individual characteristics. Health studies with multiple treatments are commonly seen in…

Methodology · Statistics 2025-05-07 Xuqiao Li , Qiuyan Zhou , Ying Wu , Ying Yan

Phase I dose-finding trials in oncology seek to find the maximum tolerated dose (MTD) of a drug under a specific schedule. Evaluating drug-schedules aims at improving treatment safety while maintaining efficacy. However, while we can…

The goal of cancer immunotherapy is to boost a patient's immune response to a tumor. Yet, the design of an effective immunotherapy is complicated by various factors, including a potentially immunosuppressive tumor microenvironment,…

Tissues and Organs · Quantitative Biology 2017-06-29 Anna Konstorum , Anthony T. Vella , Adam J. Adler , Reinhard Laubenbacher

The use of drug combinations in clinical trials is increasingly common during the last years since a more favorable therapeutic response may be obtained by combining drugs. In phase I clinical trials, most of the existing methodology…

Methodology · Statistics 2020-02-17 José L. Jiménez , Sungjin Kim , Mourad Tighiouart

We continue our study of a model for cancer treatment, constructed in Dutta et. al., 2025, by adding Virotherapy to the Chemotherapy and Immunotherapy studied there. It is a dynamical system model for the spread of cancer in healthy tissue.…

Other Quantitative Biology · Quantitative Biology 2026-03-02 Tarini Kumar Dutta , Silmera A Sangma , Janice Moore , Meir Shillor

A treatment regime formalizes personalized medicine as a function from individual patient characteristics to a recommended treatment. A high-quality treatment regime can improve patient outcomes while reducing cost, resource consumption,…

Methodology · Statistics 2015-04-30 Yichi Zhang , Eric B. Laber , Anastasios Tsiatis , Marie Davidian

Dynamic treatment regimes formalize precision medicine as a sequence of decision rules, one for each stage of clinical intervention, that map current patient information to a recommended intervention. Optimal regimes are typically defined…

Methodology · Statistics 2024-07-09 Kyle Duke , Eric B. Laber , Marie Davidian , Michael Newcomb , Brian Mustanksi

Recent clinical trials have shown that the adaptive drug therapy can be more efficient than a standard MTD-based policy in treatment of cancer patients. The adaptive therapy paradigm is not based on a preset schedule; instead, the doses are…

Quantitative Methods · Quantitative Biology 2020-08-06 Mark Gluzman , Jacob G. Scott , Alexander Vladimirsky

We investigate a new dynamical system that describes tumor-host interaction. The equation that describes the untreated tumor growth is based on non-extensive statistical mechanics. Recently, this model has been shown to fit successfully…

Health policy decisions regarding patient treatment strategies require consideration of both treatment effectiveness and cost. Optimizing treatment rules with respect to effectiveness may result in prohibitively expensive strategies; on the…

Methodology · Statistics 2021-10-20 Nicholas Illenberger , Andrew J. Spieker , Nandita Mitra

In this paper, we explore the application of ensemble optimal control to derive enhanced strategies for pharmacological cancer treatment, and we tackle the problem of the long-term management of the disease, i.e., when the complete…

Optimization and Control · Mathematics 2026-04-23 Alessandro Scagliotti , Federico Scagliotti , Laura Deborah Locati , Federico Sottotetti

Decision curve analysis can be used to determine whether a personalized model for treatment benefit would lead to better clinical decisions. Decision curve analysis methods have been described to estimate treatment benefit using data from a…

The effects of molecularly targeted drug perturbations on cellular activities and fates are difficult to predict using intuition alone because of the complex behaviors of cellular regulatory networks. An approach to overcoming this problem…

Systems and Control · Computer Science 2019-01-15 Afroza Shirin , Isaac Klickstein , Song Feng , Yen Ting Lin , William S. Hlavacek , Francesco Sorrentino

The problem of chemotherapy treatment optimization can be defined in order to minimize the size of the tumor without endangering the patient's health; therefore, chemotherapy requires to achieve a number of objectives, simultaneously. For…

Neural and Evolutionary Computing · Computer Science 2023-03-21 Mina Jafari , Behnam Ghavami , Vahid Sattari Naeini

Precision medicine is currently a topic of great interest in clinical and intervention science. One way to formalize precision medicine is through a treatment regime, which is a sequence of decision rules, one per stage of clinical…

Methodology · Statistics 2016-06-07 Yichi Zhang , Eric B. Laber , Anastasios Tsiatis , Marie Davidian

Large variability between cell lines brings a difficult optimization problem of drug selection for cancer therapy. Standard approaches use prediction of value for this purpose, corresponding e.g. to expected value of their distribution.…

Quantitative Methods · Quantitative Biology 2022-09-15 Jarek Duda