Citation: 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[J]. Mathematical Biosciences and Engineering, 2017, 14(1): 217-235. doi: 10.3934/mbe.2017014
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Synchronization in complex networks has been a focus of interest for researchers from different disciplines[1,2,4,8,15]. In this paper, we investigate synchronous phenomena in an ensemble of Kuramoto-like oscillators which is regarded as a model for power grid. In [9], a mathematical model for power grid is given by
Pisource=I¨θi˙θi+KD(˙θi)2−N∑l=1ailsin(θl−θi),i=1,2,…,N, | (1) |
where
By denoting
(˙θi)2=ωi+KNN∑l=1sin(θl−θi),˙θi>0,i=1,2,…,N. | (2) |
Here, the setting
If
(˙θi)2=ωi+KNN∑l=1sin(θl−θi+α),˙θi>0,i=1,2,…,N. | (3) |
We will find a trapping region such that any nonstationary state located in this region will evolve to a synchronous state.
The contributions of this paper are twofold: First, for identical oscillators without frustration, we show that the initial phase configurations located in the half circle will converge to complete phase and frequency synchronization. This extends the analytical results in [5] in which the initial phase configuration for synchronization needs to be confined in a quarter of circle. Second, we consider the nonidentical oscillators with frustration and present a framework leading to the boundness of the phase diameter and complete frequency synchronization. To the best of our knowledge, this is the first result for the synchronization of (3) with nonidentical oscillators and frustration.
The rest of this paper is organized as follows. In Section 2, we recall the definitions for synchronization and summarize our main results. In Section 3, we give synchronization analysis and prove the main results. Finally, Section 4 is devoted to a concluding summary.
Notations. We use the following simplified notations throughout this paper:
νi:=˙θi,i=1,2,…,N,ω:=(ω1,ω2,…,ωN),ˉω:=max1≤i≤Nωi,ω_:=min1≤i≤Nωi,D(ω):=ˉω−ω_,θM:=max1≤i≤Nθi,θm:=min1≤i≤Nθi,D(θ):=θM−θm,νM:=max1≤i≤Nνi,νm:=min1≤i≤Nνi,D(ν):=νM−νm,θνM∈{θj|νj=νM},θνm∈{θj|νj=νm}. |
In this paper, we consider the system
(˙θi)2=ωi+KNN∑l=1sin(θl−θi+α),˙θi>0,α∈(−π4,π4),θi(0)=θ0i,i=1,2,…,N. | (4) |
Next we introduce the concepts of complete synchronization and conclude this introductory section with the main result of this paper.
Definition 2.1. Let
1. it exhibits asymptotically complete phase synchronization if
limt→∞(θi(t)−θj(t))=0,∀i≠j. |
2. it exhibits asymptotically complete frequency synchronization if
limt→∞(˙θi(t)−˙θj(t))=0,∀i≠j. |
For identical oscillators without frustration, we have the following result.
Theorem 2.2. Let
θ0∈A:={θ∈[0,2π)N:D(θ)<π}, |
then there exits
D(θ(t))≤D(θ0)e−λ1t,t≥0. | (5) |
and
D(ν(t))≤D(ν(t0))e−λ2(t−t0),t≥t0. | (6) |
Next we introduce the main result for nonidentical oscillators with frustration. For
Kc:=D(ω)√2ˉω1−√2ˉωsin|α|>0. |
For suitable parameters, we denote by
sinD∞1=sinD∞∗:=√ˉω+K(D(ω)+Ksin|α|)K√ω_−K,0<D∞1<π2<D∞∗<π. |
Theorem 2.3. Let
θ0∈B:={θ∈[0,2π)N|D(θ)<D∞∗−|α|}, |
then for any small
D(ν(t))≤D(ν(T))e−λ3(t−T),t≥T. | (7) |
Remark 1. If the parametric conditions in Theorem 2.3 are fulfilled, the reference angles
D(ω)√2ˉω1−√2ˉωsin|α|<K,1−√2ˉωsin|α|>0. |
This implies
√2ˉω(D(ω)+Ksin|α|)K<1. |
Then, by
sinD∞1=sinD∞∗:=√ˉω+K(D(ω)+Ksin|α|)K√ω_−K≤√2ˉω(D(ω)+Ksin|α|)K<1. |
Remark 2. In order to make
In this subsection we consider the system (4) with identical natural frequencies and zero frustration:
(˙θi)2=ω0+KNN∑l=1sin(θl−θi),˙θi>0,i=1,2,…,N. | (8) |
To obtain the complete synchronization, we need to derive a trapping region. We start with two elementary estimates for the transient frequencies.
Lemma 3.1. Suppose
(˙θi−˙θj)(˙θi+˙θj)=2KNN∑l=1cos(θl−θi+θj2)sinθj−θi2. |
Proof. It is immediately obtained by (8).
Lemma 3.2. Suppose
˙θi≤√ω0+K. |
Proof. It follows from (8) and
(˙θi)2=ω0+KNN∑l=1sin(θl−θi)≤ω0+K. |
Next we give an estimate for trapping region and prove Theorem 2.2. For this aim, we will use the time derivative of
Lemma 3.3. Let
Proof. For any
T:={T∈[0,+∞)|D(θ(t))<D∞,∀t∈[0,T)}. |
Since
D(θ(t))<D∞,t∈[0,η). |
Therefore, the set
T∗=∞. | (9) |
Suppose to the contrary that
D(θ(t))<D∞,t∈[0,T∗),D(θ(T∗))=D∞. |
We use Lemma 3.1 and Lemma 3.2 to obtain
12ddtD(θ(t))2=D(θ(t))ddtD(θ(t))=(θM−θm)(˙θM−˙θm)=(θM−θm)1˙θM+˙θm2KNN∑l=1cos(θl−θM+θm2)sin(θm−θM2)≤(θM−θm)1˙θM+˙θm2KNN∑l=1cosD∞2sin(θm−θM2)≤(θM−θm)1√ω0+KKNN∑l=1cosD∞2sin(θm−θM2)=−2KcosD∞2√ω0+KD(θ)2sinD(θ)2≤−KcosD∞2π√ω0+KD(θ)2,t∈[0,T∗). |
Here we used the relations
−D∞2<−D(θ)2≤θl−θM2≤0≤θl−θm2≤D(θ)2<D∞2 |
and
xsinx≥2πx2,x∈[−π2,π2]. |
Therefore, we have
ddtD(θ)≤−KcosD∞2π√ω0+KD(θ),t∈[0,T∗), | (10) |
which implies that
D(θ(T∗))≤D(θ0)e−KcosD∞2π√ω0+KT∗<D(θ0)<D∞. |
This is contradictory to
Now we can give a proof for Theorem 2.2.
Proof of Theorem 2.2.. According to Lemma 3.3, we substitute
On the other hand, by (5) there exist
˙νi=K2NνiN∑l=1cos(θl−θi)(νl−νi). |
Using Lemma 3.2, we now consider the temporal evolution of
ddtD(ν)=˙νM−˙νm=K2NνMN∑l=1cos(θl−θνM)(νl−νM)−K2NνmN∑l=1cos(θl−θνm)(νl−νm)≤Kcosδ2NνMN∑l=1(νl−νM)−Kcosδ2NνmN∑l=1(νl−νm)≤K2Ncosδ√ω0+KN∑l=1(νl−νM)−K2Ncosδ√ω0+KN∑l=1(νl−νm)=Kcosδ2N√ω0+KN∑l=1(νl−νM−νl+νm)=−Kcosδ2√ω0+KD(ν),t≥t0. |
This implies that
D(ν(t))≤D(ν(t0))e−Kcosδ2√ω0+K(t−t0),t≥t0, |
and proves (6) with
Remark 3. Theorem 2.2 shows, as long as the initial phases are confined inside an arc with geodesic length strictly less than
In this subsection, we prove the main result for nonidentical oscillators with frustration.
Lemma 3.4. Let
(˙θi−˙θj)(˙θi+˙θj)≤D(ω)+KNN∑l=1[sin(θl−θi+α)−sin(θl−θj+α)]. |
Proof. By (4) and for any
(˙θi−˙θj)(˙θi+˙θj)=(˙θi)2−(˙θj)2, |
the result is immediately obtained.
Lemma 3.5. Let
˙θi∈[√ω_−K,√ˉω+K],∀i=1,2,…,N. |
Proof. From (4), we have
ω_−K≤(˙θi)2≤ˉω+K,∀i=1,2,…,N, |
and also because
Lemma 3.6. Let
Proof. We define the set
T:={T∈[0,+∞)|D(θ(t))<D∞∗−|α|,∀t∈[0,T)},T∗:=supT. |
Since
T∗=∞. |
Suppose to the contrary that
D(θ(t))<D∞∗−|α|,t∈[0,T∗),D(θ(T∗))=D∞∗−|α|. |
We use Lemma 3.4 to obtain
12ddtD(θ)2=D(θ)ddtD(θ)=D(θ)(˙θM−˙θm)≤D(θ)1˙θM+˙θm[D(ω)+KNN∑l=1(sin(θl−θM+α)−sin(θl−θm+α))]⏟I. |
For
I=D(ω)+KcosαNN∑l=1[sin(θl−θM)−sin(θl−θm)]+KsinαNN∑l=1[cos(θl−θM)−cos(θl−θm)]. |
We now consider two cases according to the sign of
(1)
I≤D(ω)+KcosαsinD(θ)ND(θ)N∑l=1[(θl−θM)−(θl−θm)]+KsinαNN∑l=1[1−cosD(θ)]=D(ω)−K[sin(D(θ)+α)−sinα]=D(ω)−K[sin(D(θ)+|α|)−sin|α|]. |
(2)
I≤D(ω)+KcosαsinD(θ)ND(θ)N∑l=1[(θl−θM)−(θl−θm)]+KsinαNN∑l=1[cosD(θ)−1]=D(ω)−K[sin(D(θ)−α)+sinα]=D(ω)−K[sin(D(θ)+|α|)−sin|α|]. |
Here we used the relations
sin(θl−θM)θl−θM,sin(θl−θm)θl−θm≥sinD(θ)D(θ), |
and
cosD(θ)≤cos(θl−θM),cos(θl−θm)≤1,l=1,2,…,N. |
Since
I≤D(ω)−K[sin(D(θ)+|α|)−sin|α|] | (11) |
≤D(ω)+Ksin|α|−KsinD∞∗D∞∗(D(θ)+|α|). | (12) |
By (12) and Lemma 3.5 we have
12ddtD(θ)2≤D(θ)1˙θM+˙θm(D(ω)+Ksin|α|−KsinD∞∗D∞∗(D(θ)+|α|))=D(ω)+Ksin|α|˙θM+˙θmD(θ)−KsinD∞∗D∞∗(˙θM+˙θm)D(θ)(D(θ)+|α|)≤D(ω)+Ksin|α|2√ω_−KD(θ)−KsinD∞∗D∞∗2√ˉω+KD(θ)(D(θ)+|α|),t∈[0,T∗). |
Then we obtain
ddtD(θ)≤D(ω)+Ksin|α|2√ω_−K−KsinD∞∗2D∞∗√ˉω+K(D(θ)+|α|),t∈[0,T∗), |
i.e.,
ddt(D(θ)+|α|)≤D(ω)+Ksin|α|2√ω_−K−KsinD∞∗2D∞∗√ˉω+K(D(θ)+|α|)=KsinD∞∗2√ˉω+K−KsinD∞∗2D∞∗√ˉω+K(D(θ)+|α|),t∈[0,T∗). |
Here we used the definition of
D(θ(t))+|α|≤D∞∗+(D(θ0)+|α|−D∞∗)e−KsinD∞∗2D∞∗√ˉω+Kt,t∈[0,T∗), |
Thus
D(θ(t))≤(D(θ0)+|α|−D∞∗)e−KsinD∞∗2D∞∗√ˉω+Kt+D∞∗−|α|,t∈[0,T∗). |
Let
D(θ(T∗))≤(D(θ0)+|α|−D∞∗)e−KsinD∞∗2D∞∗√ˉω+KT∗+D∞∗−|α|<D∞∗−|α|, |
which is contradictory to
T∗=∞. |
That is,
D(θ(t))≤D∞∗−|α|,∀t≥0. |
Lemma 3.7. Let
ddtD(θ(t))≤D(ω)+Ksin|α|2√ω_−K−K2√ˉω+Ksin(D(θ)+|α|),t≥0. |
Proof. It follows from (11) and Lemma 3.5, Lemma 3.6 and that we have
12ddtD(θ)2=D(θ)ddtD(θ)≤D(θ)1˙θM+˙θm[D(ω)−K(sin(D(θ)+|α|)−sin|α|)]=D(ω)+Ksin|α|˙θM+˙θmD(θ)−Ksin(D(θ)+|α|)˙θM+˙θmD(θ)≤D(ω)+Ksin|α|2√ω_−KD(θ)−Ksin(D(θ)+|α|)2√ˉω+KD(θ),t≥0. |
The proof is completed.
Lemma 3.8. Let
D(θ(t))<D∞1−|α|+ε,t≥T. |
Proof. Consider the ordinary differential equation:
˙y=D(ω)+Ksin|α|2√ω_−K−K2√ˉω+Ksiny,y(0)=y0∈[0,D∞∗). | (13) |
It is easy to find that
|y(t)−y∗|<ε,t≥T. |
In particular,
D(θ(t))+|α|<D∞1+ε,t≥T, |
which is the desired result.
Remark 4. Since
sinD∞1≥D(ω)K+sin|α|>sin|α|, |
we have
Proof of Theorem 2.3. It follows from Lemma 3.8 that for any small
supt≥TD(θ(t))<D∞1−|α|+ε<π2. |
We differentiate the equation (4) to find
˙νi=K2NνiN∑l=1cos(θl−θi+α)(νl−νi),νi>0. |
We now consider the temporal evolution of
ddtD(ν)=˙νM−˙νm=K2NνMN∑l=1cos(θl−θνM+α)(νl−νM)−K2NνmN∑l=1cos(θl−θνm+α)(νl−νm)≤K2NνMN∑l=1cos(D∞1+ε)(νl−νM)−K2NνmN∑l=1cos(D∞1+ε)(νl−νm)≤Kcos(D∞1+ε)2N√ˉω+KN∑l=1(νl−νM−νl+νm)=−Kcos(D∞1+ε)2√ˉω+KD(ν),t≥T, |
where we used
cos(θl−θνM+α),cos(θl−θνm+α)≥cos(D∞1+ε),andνM,νm≤√ˉω+K. |
Thus we obtain
D(ν(t))≤D(ν(T))e−Kcos(D∞1+ε)2√ˉω+K(t−T),t≥T, |
and proves (7) with
In this paper, we presented synchronization estimates for the Kuramoto-like model. We show that for identical oscillators with zero frustration, complete phase synchronization occurs exponentially fast if the initial phases are confined inside an arc with geodesic length strictly less than
We would like to thank the anonymous referee for his/her comments which helped us to improve this paper.
[1] | [ E. Afenya, Using mathematical modeling as a resource in clinical trials, Math. Biosci. and Engr., (MBE), 2 (2005): 421-436. |
[2] | [ N. André,S. Abed,D. Orbach,C. Armari Alla,L. Padovani,E. Pasquier,J. C. Gentet,A. Verschuur, Pilot study of a pediatric metronomic 4-drug regimen, Oncotarget, 2 (2011): 960-965. |
[3] | [ N. André,L. Padovani,E. Pasquier, Metronomic scheduling of anticancer treatment: The next generation of multitarget therapy?, Future Oncology, 7 (2011): 385-394. |
[4] | [ D. Barbolosi,J. Ciccolini,B. Lacarelle,F. Barlési,N. André, Computational oncology-mathematical modelling of drug regimens for precision medicine, Nat. Rev. Clin. Oncol., 13 (2016): 242-254. |
[5] | [ J. Bellmunt, J. M. Trigo, E. Calvo, J. Carles, J. L. Pérez-Garci, J. Rubió, J. A. Virizuela, R. López, M. L´azaro and J. Albanell, Activity of a multitargeted chemo-switch regimen (sorafenib, gemcitabine, and metronomic capecitabine) in metastatic renal-cell carcinoma: a phase 2 study (SOGUG-02-06), Lancet Oncol., 11 (2010), 350-357, http://www.ncbi.nlm.nih.gov/pubmed/20163987. |
[6] | [ G. Bocci,K. Nicolaou,R. S. Kerbel, Protracted low-dose effects on human endothelial cell proliferation and survival in vitro reveal a selective antiangiogenic window for various chemotherapeutic drugs, Cancer Research, 62 (2002): 6938-6943. |
[7] | [ B. Bonnard and M. Chyba, Singular Trajectories and their Role in Control Theory, Series: Mathematics and Applications, Springer-Verlag, Berlin, 2003. |
[8] | [ A. Bressan and B. Piccoli, Introduction to the Mathematical Theory of Control, American Institute of Mathematical Sciences, 2007. |
[9] | [ T. Browder,C. E. Butterfield,B. M. Kräling,B. Shi,B. Marshall,M. S. O'Reilly,J. Folkman, Antiangiogenic scheduling of chemotherapy improves efficacy against experimental drug-resistant cancer, Cancer Research, 60 (2000): 1878-1886. |
[10] | [ A. Friedman,Y. Kim, Tumor cell proliferation and migration under the influence of their microenvironment, Mathematical Biosciences and Engineering -MBE, 8 (2011): 371-383. |
[11] | [ R. A. Gatenby,A. S. Silva,R. J. Gillies,B. R. Frieden, Adaptive therapy, Cancer Research, 69 (2009): 4894-4903. |
[12] | [ R. A. Gatenby, A change of strategy in the war on cancer, Nature, 459 (2009): 508-509. |
[13] | [ J. H. Goldie, Drug resistance in cancer: A perspective, Cancer and Metastasis Review, 20 (2001): 63-68. |
[14] | [ J. H. Goldie,A. Coldman, null, Drug Resistance in Cancer, Cambridge University Press, 1998. |
[15] | [ R. Grantab,S. Sivananthan,I. F. Tannock, The penetration of anticancer drugs through tumor tissue as a function of cellular adhesion and packing density of tumor cells, Cancer Research, 66 (2006): 1033-1039. |
[16] | [ J. Greene,O. Lavi,M. M. Gottesman,D. Levy, The impact of cell density and mutations in a model of multidrug resistance in solid tumors, Bull. Math. Biol., 74 (2014): 627-653. |
[17] | [ P. Hahnfeldt,L. Hlatky, Cell resensitization during protracted dosing of heterogeneous cell populations, Radiation Research, 150 (1998): 681-687. |
[18] | [ P. Hahnfeldt,D. Panigrahy,J. Folkman,L. Hlatky, Tumor development under angiogenic signaling: A dynamical theory of tumor growth, treatment response, and postvascular dormancy, Cancer Research, 59 (1999): 4770-4775. |
[19] | [ P. Hahnfeldt,J. Folkman,L. Hlatky, Minimizing long-term burden: The logic for metronomic chemotherapeutic dosing and its angiogenic basis, J. of Theoretical Biology, 220 (2003): 545-554. |
[20] | [ D. Hanahan,G. Bergers,E. Bergsland, Less is more, regularly: Metronomic dosing of cytotoxic drugs can target tumor angiogenesis in mice, J. Clinical Investigations, 105 (2000): 1045-1047. |
[21] | [ Y. B. Hao,S. Y. Yi,J. Ruan,L. Zhao,K. J. Nan, New insights into metronomic chemotherapy-induced immunoregulation, Cancer Letters, 354 (2014): 220-226. |
[22] | [ L.E. Harnevo,Z. Agur, Drug resistance as a dynamic process in a model for multistep gene amplification under various levels of selection stringency, Cancer Chemotherapy and Pharmacology, 30 (1992): 469-476. |
[23] | [ B. Kamen,E. Rubin,J. Aisner,E. Glatstein, High-time chemotherapy or high time for low dose?, J. Clinical Oncology, editorial, 18 (2000): 2935-2937. |
[24] | [ G. Klement,S. Baruchel,J. Rak,S. Man,K. Clark,D.J. Hicklin,P. Bohlen,R.S. Kerbel, Continuous low-dose therapy with vinblastine and VEGF receptor-2 antibody induces sustained tumor regression without overt toxicity, J. Clinical Investigations, 105 (2000): R15-R24. |
[25] | [ O. Lavi,J. Greene,D. Levy,M. Gottesman, The role of cell density and intratumoral heterogeneity in multidrug resistance, Cancer Research, 73 (2013): 7168-7175. |
[26] | [ U. Ledzewicz,B. Amini,H. Schättler, Dynamics and control of a mathematical model for metronomic chemotherapy, Math. Biosci. and Engr., (MBE), 12 (2015): 1257-1275. |
[27] | [ U. Ledzewicz,K. Bratton,H. Schättler, A 3-compartment model for chemotherapy of heterogeneous tumor populations, Acta Applicanda Mathematicae, 135 (2015): 191-207. |
[28] | [ U. Ledzewicz,H. Maurer,H. Schättler, Minimizing tumor volume for a mathematical model of anti-angiogenesis with linear pharmacokinetics, in: Recent Advances in Optimization and its Applications in Engineering, M. Diehl, F. Glineur, E. Jarlebring and W. Michiels, Eds., null (2010): 267-276. |
[29] | [ U. Ledzewicz,H. Schättler, Drug resistance in cancer chemotherapy as an optimal control problem, Discr. Cont. Dyn. Syst., Ser. B, 6 (2006): 129-150. |
[30] | [ U. Ledzewicz,H. Schättler, Antiangiogenic therapy in cancer treatment as an optimal control problem, SIAM J. Contr. Optim., 46 (2007): 1052-1079. |
[31] | [ U. Ledzewicz,H. Schättler, Singular controls and chattering arcs in optimal control problems arising in biomedicine, Control and Cybernetics, 38 (2009): 1501-1523. |
[32] | [ U. Ledzewicz,H. Schättler, On optimal chemotherapy for heterogeneous tumors, J. of Biological Systems, 22 (2014): 177-197. |
[33] | [ U. Ledzewicz,H. Schättler,M. Reisi Gahrooi,S. Mahmoudian Dehkordi, On the MTD paradigm and optimal control for multi-drug cancer chemotherapy, Math. Biosci. and Engr. (MBE), 10 (2013): 803-819. |
[34] | [ D. Liberzon, null, Calculus of Variations and Optimal Control Theory, Princeton University Press, Princeton, NJ, 2012. |
[35] | [ A. Lorz,T. Lorenzi,M. E. Hochberg,J. Clairambault,B. Berthame, Population adaptive evolution, chemotherapeutic resistance and multiple anti-cancer therapies, ESAIM: Mathematical Modelling and Numerical Analysis, 47 (2013): 377-399. |
[36] | [ A. Lorz,T. Lorenzi,J. Clairambault,A. Escargueil,B. Perthame, Effects of space structure and combination therapies on phenotypic heterogeneity and drug resistance in solid tumors, Bull. Math. Biol., 77 (2015): 1-22. |
[37] | [ P. S. Malik, V. Raina and N. André, Metronomics as maintenance treatment in oncology: Time for chemo-switch, Front. Oncol., 10 (2014), 1-7, http://www.ncbi.nlm.nih.gov/pubmed/24782987. |
[38] | [ N. McGranahan and C. Swanton, Biological and therapeutic impact of intratumor heterogeneity in cancer evolution, Cancer Cell, 27 (2015), 15{26, http://www.ncbi.nlm.nih.gov/pubmed/25584892 |
[39] | [ L. Norton,R. Simon, Tumor size, sensitivity to therapy, and design of treatment schedules, Cancer Treatment Reports, 61 (1977): 1307-1317. |
[40] | [ L. Norton,R. Simon, The Norton-Simon hypothesis revisited, Cancer Treatment Reports, 70 (1986): 41-61. |
[41] | [ E. Pasquier,M. Kavallaris,N. André, Metronomic chemotherapy: New rationale for new directions, Nature Reviews|Clinical Oncology, 7 (2010): 455-465. |
[42] | [ K. Pietras,D. Hanahan, A multi-targeted, metronomic and maximum tolerated dose "chemo-switch" regimen is antiangiogenic, producing objective responses and survival benefit in a mouse model of cancer, J. of Clinical Oncology, 23 (2005): 939-952. |
[43] | [ L. S. Pontryagin, V. G. Boltyanskii, R. V. Gamkrelidze and E. F. Mishchenko, The Mathematical Theory of Optimal Processes, Macmillan, New York, 1964. |
[44] | [ H. Schättler and U. Ledzewicz, Geometric Optimal Control: Theory, Methods and Examples, Springer Verlag, 2012. |
[45] | [ Schättler,Ledzewicz, null, Optimal Control for Mathematical Models of Cancer Therapies, Springer Publishing Co., New York, USA, 2015. |
[46] | [ H. Schättler,U. Ledzewicz,B. Amini, Dynamical properties of a minimally parametrized mathematical model for metronomic chemotherapy, J. of Math. Biol., 72 (2016): 1255-1280. |
[47] | [ C. Swanton, Cancer evolution: The final frontier of precision medicine? Ann. Oncol., 25 2014), 549-551, http://www.ncbi.nlm.nih.gov/pubmed/24567514. |
[48] | [ A. Swierniak,J. Smieja, Cancer chemotherapy optimization under evolving drug resistance, Nonlinear Analysis, 47 (2000): 375-386. |
[49] | [ S. Wang,H. Schättler, Optimal control of a mathematical model for cancer chemotherapy under tumor heterogeneity, Math. Biosci. and Engr. -MBE, 13 (2016): 1223-1240. |
[50] | [ J. Wares,J. Crivelli,C. Yun,I. Choi,J. Gevertz,P. Kim, Treatment strategies for combining immunostimulatory oncolytic virus therapeutics with dendritic cell injections, Math. Biosci. and Engr. -MBE, 12 (2015): 1237-1256. |
[51] | [ S. D. Weitman,E. Glatstein,B. A. Kamen, Back to the basics: the importance of concentration × time in oncology, J. of Clinical Oncology, 11 (1993): 820-821. |
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