1.
|
Urszula Ledzewicz, Heinz Schättler,
2014,
Chapter 10,
978-1-4939-0457-0,
295,
10.1007/978-1-4939-0458-7_10
|
|
2.
|
Yimae Wufuer, Xuefeng Shan, Magaoweiya Sailike, Kamile Adilaimu, Songfeng Ma, Huguo Wang,
GPVI-Fc-PEG improves cerebral infarct volume and cerebral thrombosis in mouse model with cerebral thrombosis,
2017,
16,
1791-2997,
7561,
10.3892/mmr.2017.7556
|
|
3.
|
Heinz Schättler, Urszula Ledzewicz,
2015,
Chapter 3,
978-1-4939-2971-9,
115,
10.1007/978-1-4939-2972-6_3
|
|
4.
|
URSZULA LEDZEWICZ, HEINZ SCHÄTTLER,
ON OPTIMAL CHEMOTHERAPY FOR HETEROGENEOUS TUMORS,
2014,
22,
0218-3390,
177,
10.1142/S0218339014400014
|
|
5.
|
David C. Norris,
Dose Titration Algorithm Tuning (DTAT) should supersede ‘the’ Maximum Tolerated Dose (MTD) in oncology dose-finding trials,
2017,
6,
2046-1402,
112,
10.12688/f1000research.10624.3
|
|
6.
|
Heinz Schättler, Urszula Ledzewicz,
2015,
Chapter 2,
978-1-4939-2971-9,
41,
10.1007/978-1-4939-2972-6_2
|
|
7.
|
Heinz Schättler, Urszula Ledzewicz,
Fields of extremals and sensitivity analysis for multi-input bilinear optimal control problems,
2015,
35,
1553-5231,
4611,
10.3934/dcds.2015.35.4611
|
|
8.
|
Patrícia de Oliveira Figueiredo, Renata Trentin Perdomo, Fernanda Rodrigues Garcez, Maria de Fatima Cepa Matos, João Ernesto de Carvalho, Walmir Silva Garcez,
Further constituents of Galianthe thalictroides (Rubiaceae) and inhibition of DNA topoisomerases I and IIα by its cytotoxic β-carboline alkaloids,
2014,
24,
0960894X,
1358,
10.1016/j.bmcl.2014.01.039
|
|
9.
|
Clara Rojas, Juan Belmonte-Beitia,
Optimal control problems for differential equations applied to tumor growth: state of the art,
2018,
3,
2444-8656,
375,
10.21042/AMNS.2018.2.00029
|
|
10.
|
Heinz Schättler, Urszula Ledzewicz, Helmut Maurer,
Sufficient conditions for strong local optimality in optimal control problems with $L_{2}$-type objectives and control constraints,
2014,
19,
1553-524X,
2657,
10.3934/dcdsb.2014.19.2657
|
|
11.
|
U. Ledzewicz, H. Schättler, S. Anita, N. Hritonenko, G. Marinoschi, A. Swierniak,
A Review of Optimal Chemotherapy Protocols: From MTD towards Metronomic Therapy,
2014,
9,
0973-5348,
131,
10.1051/mmnp/20149409
|
|
12.
|
Angela M. Jarrett, Danial Faghihi, David A. Hormuth, Ernesto A. B. F. Lima, John Virostko, George Biros, Debra Patt, Thomas E. Yankeelov,
Optimal Control Theory for Personalized Therapeutic Regimens in Oncology: Background, History, Challenges, and Opportunities,
2020,
9,
2077-0383,
1314,
10.3390/jcm9051314
|
|
13.
|
Omar Shindi, Jeevan Kanesan, Graham Kendall, Anand Ramanathan,
The combined effect of optimal control and swarm intelligence on optimization of cancer chemotherapy,
2020,
189,
01692607,
105327,
10.1016/j.cmpb.2020.105327
|
|
14.
|
Dominique Barbolosi, Joseph Ciccolini, Bruno Lacarelle, Fabrice Barlési, Nicolas André,
Computational oncology — mathematical modelling of drug regimens for precision medicine,
2016,
13,
1759-4774,
242,
10.1038/nrclinonc.2015.204
|
|
15.
|
Urszula Ledzewicz, Kenneth Bratton, Heinz Schättler,
A 3-Compartment Model for Chemotherapy of Heterogeneous Tumor Populations,
2015,
135,
0167-8019,
191,
10.1007/s10440-014-9952-6
|
|
16.
|
Clara Rojas Rodríguez, Juan Belmonte-Beitia,
Optimizing the delivery of combination therapy for tumors: A mathematical model,
2017,
10,
1793-5245,
1750039,
10.1142/S1793524517500395
|
|
17.
|
Rafael T. Guiraldello, Marcelo L. Martins, Paulo F.A. Mancera,
Evaluating the efficacies of Maximum Tolerated Dose and metronomic chemotherapies: A mathematical approach,
2016,
456,
03784371,
145,
10.1016/j.physa.2016.03.019
|
|
18.
|
Ami B. Shah, Katarzyna A. Rejniak, Jana L. Gevertz,
Limiting the development of anti-cancer drug resistance in a spatial model of micrometastases,
2016,
13,
1551-0018,
1185,
10.3934/mbe.2016038
|
|
19.
|
Urszula Ledzewicz, Heinz Schättler,
Application of mathematical models to metronomic chemotherapy: What can be inferred from minimal parameterized models?,
2017,
401,
03043835,
74,
10.1016/j.canlet.2017.03.021
|
|
20.
|
Urszula Ledzewicz, Shuo Wang, Heinz Schättler, Nicolas André, Marie Amélie Heng, Eddy Pasquier,
On drug resistance and metronomic chemotherapy: A mathematical modeling and optimal control approach,
2017,
14,
1551-0018,
217,
10.3934/mbe.2017014
|
|
21.
|
David C. Norris,
Dose Titration Algorithm Tuning (DTAT) should supersede ‘the’ Maximum Tolerated Dose (MTD) in oncology dose-finding trials,
2017,
6,
2046-1402,
112,
10.12688/f1000research.10624.2
|
|
22.
|
Clara Rojas, Juan Belmonte-Beitia, Víctor M. Pérez-García, Helmut Maurer,
Dynamics and optimal control of chemotherapy for low grade gliomas: Insights from a mathematical model,
2016,
21,
1531-3492,
1895,
10.3934/dcdsb.2016028
|
|
23.
|
Derek S. Park, Kimberly A. Luddy, Mark Robertson-Tessi, Cliona O'Farrelly, Robert A. Gatenby, Alexander R.A. Anderson,
Searching for Goldilocks: How Evolution and Ecology Can Help Uncover More Effective Patient-Specific Chemotherapies,
2020,
80,
0008-5472,
5147,
10.1158/0008-5472.CAN-19-3981
|
|
24.
|
Urszula Ledzewicz, Heinz Schaettler,
2016,
Chapter 11,
978-3-319-42021-9,
209,
10.1007/978-3-319-42023-3_11
|
|
25.
|
David C. Norris,
Dose Titration Algorithm Tuning (DTAT) should supersede the Maximum Tolerated Dose (MTD) concept in oncology dose-finding trials,
2017,
6,
2046-1402,
112,
10.12688/f1000research.10624.1
|
|
26.
|
Seho Kweon, Yoo-Seong Jeong, Seung Woo Chung, Hanul Lee, Ha Kyeong Lee, Seong Jin Park, Jeong Uk Choi, Jooho Park, Suk-Jae Chung, Youngro Byun,
Metronomic dose-finding approach in oral chemotherapy by experimentally-driven integrative mathematical modeling,
2022,
286,
01429612,
121584,
10.1016/j.biomaterials.2022.121584
|
|
27.
|
Cristian Axenie, Daria Kurz, Matteo Saveriano,
Antifragile Control Systems: The Case of an Anti-Symmetric Network Model of the Tumor-Immune-Drug Interactions,
2022,
14,
2073-8994,
2034,
10.3390/sym14102034
|
|
28.
|
Urszula Ledzewicz, Heinz Schättler,
The Structure of Optimal Protocols for a Mathematical Model of Chemotherapy with Antiangiogenic Effects,
2022,
60,
0363-0129,
1092,
10.1137/21M1395326
|
|
29.
|
Malgorzata Kardynska, Daria Kogut, Marcin Pacholczyk, Jaroslaw Smieja,
Mathematical modeling of regulatory networks of intracellular processes – Aims and selected methods,
2023,
21,
20010370,
1523,
10.1016/j.csbj.2023.02.006
|
|
30.
|
Ana Amiama-Roig, Eva M. Verdugo-Sivianes, Amancio Carnero, José-Ramón Blanco,
Chronotherapy: Circadian Rhythms and Their Influence in Cancer Therapy,
2022,
14,
2072-6694,
5071,
10.3390/cancers14205071
|
|
31.
|
Mohsen Yousefnezhad, Chiu-Yen Kao, Seyyed Abbas Mohammadi,
Optimal Chemotherapy for Brain Tumor Growth in a Reaction-Diffusion Model,
2021,
81,
0036-1399,
1077,
10.1137/20M135995X
|
|
32.
|
M.A.R. Strobl, J. Gallaher, M. Robertson-Tessi, J. West, A.R.A. Anderson,
Treatment of evolving cancers will require dynamic decision support,
2023,
34,
09237534,
867,
10.1016/j.annonc.2023.08.008
|
|
33.
|
Mariusz Bodzioch, Juan Belmonte-Beitia, Urszula Foryś,
Asymptotic dynamics and optimal treatment for a model of tumour resistance to chemotherapy,
2024,
135,
0307904X,
620,
10.1016/j.apm.2024.07.008
|
|
34.
|
Chiu-Yen Kao, Seyyed Abbas Mohammadi, Mohsen Yousefnezhad,
Is maximum tolerated dose (MTD) chemotherapy scheduling optimal for glioblastoma multiforme?,
2024,
139,
10075704,
108292,
10.1016/j.cnsns.2024.108292
|
|
35.
|
Richa Pathak, Nisha Singh, Arti Parganiha,
2025,
Chapter 4,
978-981-97-7323-7,
69,
10.1007/978-981-97-7324-4_4
|
|