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Chakrabarty2010 - A control theory approach to cancer remission aided by an optimal therapy

ABSTRACT: This is a reinvestigation of a previous model depicting cancer remission. It involves application of mathematical tools from control theory to assess the optimal approach during the use of Adaptive Cellular Immunotherapy and interleukin-2 treatment.

SUBMITTER: Johannes Meyer

PROVIDER: BIOMD0000000777 | BioModels | 2024-09-02

REPOSITORIES: BioModels

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			Action	DRS
	BIOMD0000000777?filename=Chakrabarty2010-biopax2.owl	Owl
	BIOMD0000000777?filename=Chakrabarty2010-biopax3.owl	Owl
	BIOMD0000000777?filename=Chakrabarty2010-matlab.m	Other
	BIOMD0000000777?filename=Chakrabarty2010-octave.m	Other
	BIOMD0000000777?filename=Chakrabarty2010.cps	Other

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Publications

Delay-induced model for tumor-immune interaction and control of malignant tumor growth.

Banerjee Sandip S Sarkar Ram Rup RR

Bio Systems 20071024 1

The paper deals with the qualitative analysis of the solutions of a system of delay differential equations describing the interaction between tumor and immune cells. The asymptotic stability of the possible steady states is showed and the occurrence of limit cycle of the system around the interior equilibrium is proved by the application of Hopf bifurcation theorem by using the delay as a bifurcation parameter. The length of the delay parameter for preserving stability of the system is also esti ...[more]

PMID: 18083299

Similar Datasets

Khajanchi2015 - The combined effects of optimal control in cancer remission

Project description:The combined effects of optimal control in cancer remission SubhasKhajanchi DibakarGhosh Abstract We investigate a mathematical model depicting the nonlinear dynamics of immunogenic tumors as envisioned by Kuznetsov et al. [1]. To understand the dynamics under what circumstances the cancer cells can be eliminated, we implement the theory of optimal control. We design two types of external treatment strategies, one is Adoptive Cellular Immunotherapy and another is interleukin-2. Our aim is to establish the treatment regimens that maximize the effector cell count and minimize the tumor cell burden and the deleterious effects of the total amount of drugs. We derive the existence of an optimal control by using the boundedness of solutions. We characterize the optimality system, in which the state system is coupled with co-states. The uniqueness of an optimal control of our problem is also analyzed. Finally, we demonstrate the numerical illustrations that the optimal regimens reduce the tumor burden under different scenarios.

2024-09-02 | BIOMD0000000897 | BioModels

Optimal Hormone Replacement Therapy in Hypothyroidism - A Model Predictive Control Approach.

Project description:In this paper, we address the problem of optimal thyroid hormone replacement strategy development for hypothyroid patients. This is challenging for the following reasons. First, it is difficult to determine the correct dosage leading to normalized serum thyroid hormone concentrations of a patient. Second, it remains unclear whether a levothyroxine L-T 4) monotherapy or a liothyronine/levothyroxine (L-T 3/L-T 4) combined therapy is more suitable to treat hypothyroidism. Third, the optimal intake frequency of L-T 3/L-T 4 is unclear. We address these issues by extending a mathematical model of the pituitary-thyroid feedback loop to be able to consider an oral intake of L-T 3/L-T 4. A model predictive controller (MPC) is employed to determine optimal dosages with respect to the thyroid hormone concentrations for each type of therapy. The results indicate that the L-T 3/L-T 4 combined therapy is slightly better (in terms of the achieved hormone concentrations) to treat hypothyroidism than the L-T 4 monotherapy. In case of a specific genetic variant, namely genotype CC in polymorphism rs2235544 of gene DIO1, the simulation results suggest that the L-T 4 monotherapy is better to treat hypothyroidism. In turn, when genotype AA is considered, the L-T 3/L-T 4 combined therapy is better to treat hypothyroidism. Furthermore, when genotype CC of polymorphism rs225014 (also referred to as c.274A>G or p.Thr92Ala) in the DIO2 gene is considered, the outcome of the L-T 3/L-T 4 combined therapy is better in terms of the steady-state hormone concentrations (for a triiodothyronine setpoint at the upper limit of the reference range of healthy individuals). Finally, the results suggest that two daily intakes of L-T 3 could be the best trade-off between stable hormone concentrations and inconveniences for the patient.

| S-EPMC9263720 | biostudies-literature

Conventionally Fractionated Adaptive Radiation Therapy of Bladder Cancer an Individualized Approach

Project description:This is a single-arm, prospective, Phase II, multi-center clinical trial designed to demonstrate that adaptive radiotherapy for muscle invasive bladder cancer will translate into a decreased rate of acute gastrointestinal toxicity compared with the historically reported rate for non-adaptive intensity modulated radiation therapy (IMRT).

| 2710638 | ecrin-mdr-crc

A control theory approach to optimal pandemic mitigation.

Project description:In the framework of homogeneous susceptible-infected-recovered (SIR) models, we use a control theory approach to identify optimal pandemic mitigation strategies. We derive rather general conditions for reaching herd immunity while minimizing the costs incurred by the introduction of societal control measures (such as closing schools, social distancing, lockdowns, etc.), under the constraint that the infected fraction of the population does never exceed a certain maximum corresponding to public health system capacity. Optimality is derived and verified by variational and numerical methods for a number of model cost functions. The effects of immune response decay after recovery are taken into account and discussed in terms of the feasibility of strategies based on herd immunity.

| S-EPMC7894916 | biostudies-literature

Optimal approach in early breast cancer: Radiation therapy.

Project description:Radiation therapy significantly reduces by at least 70% the relative risk of local and regional recurrences for breast cancer after surgery. A positive influence on overall survival has been clearly demonstrated, especially for patients with a high absolute risk for locoregional recurrences. However, this is partially counterbalanced by late toxicity (dependent upon the radiation dose) especially to cardiac structures. Apart from this toxicity, a clear influence of radiation-therapy-related factors on functional and cosmetic outcome has also been demonstrated. Over time, technical improvements have led to a marked reduction in dose to the neighbouring organs, with a consequent drop in acute and late toxicity. This has also allowed the introduction of shorter radiation schedules, lowering the burden of treatment to the patient and the hospital. Several tools, techniques and guidelines have been developed to optimise the balance between the desired reduction in recurrence rates and side effects. The multidisciplinary team should discuss all available treatment options for every individual breast cancer patient. Individualisation of the selection of the optimal combination of treatments, depending on patient and tumour-related factors, is of utmost importance. Apart from direct tumour-related outcomes, cosmesis and potential side effects have to be taken into account. Counselling should include known risk factors for survival and complications, including comorbidity.

| S-EPMC4041558 | biostudies-literature

Interleukin-17 mediated paracrine network promote tumor resistance to anti-angiogenic therapy

Project description:While angiogenesis inhibitors have provided significant clinical benefit as cancer therapeutics, the mechanisms of anti-VEGF resistance remain incompletely understood. We uncovered an interleukin-17 mediated paracrine network of signaling between the adaptive and innate immune system associated with resistance to anti-VEGF treatment in multiple tumor models. The expression of tumor-associated fibroblasts and tumor-associated granulocytes (defined as CD11b+Gr1+) and tumor-associated monocytic cells (defined as CD11b+Gr1-) were compared between wildtype and IL-17RC knockout tumor bearing mice.

2013-06-27 | E-GEOD-48329 | biostudies-arrayexpress

Interleukin-17 mediated paracrine network promote tumor resistance to anti-angiogenic therapy

2013-06-27 | GSE48329 | GEO

Effects of tocilizumab versus methotrexate therapy on gene expression profiles in the early rheumatoid arthrtis synovium

Project description:Rheumatoid arthritis (RA) is a chronic, systemic autoimmune inflammatory disease that is characterized by the presence of inflammatory cytokines, including interleukin-6 (IL-6). Here, we investigated the global molecular effects of Tocilizumab, an approved humanized anti-IL6 Receptor antibody, versus Methotrexate therapy, in synovial biopsy samples collected prospectively in early RA before and 12 weeks after administration of the drug. The results were compared with our previous data, generated in prospective cohorts of Adalimumab- and Rituximab-treated (Methotrexate- and anti-TNF-resistant, respectively) RA patients. We found that Tocilizumab induces a significant down-regulation of genes included in specific pathways: cytokines & chemokines (e.g. IL-6, IL-7, IL-22, CCL8, CCL11, CCL13, CCL19, CCL20), and T cell activation. By contrast, Tocilizumab induces a significant up-regulation of genes associated with healing processes. These effects are significantly more pronounced as compared to Methotrexate, Rituximab, or Adalimumab therapies. By opposition to the effects of Adalimumab, Tocilizumab therapy does not induce a decreased expression of genes involved in cell proliferation. Paired synovial biopsy samples were obtained from the affected knee of early RA patients before and 12 weeks after initiation of Tocilizumab (n=12) or Methotrexate (n=8) therapy. SDAI remission criteria were computed prospectively before, 3 months and 6 months after administration of the drugs and patientsM-bM-^@M-^Y responses were defined according to their SDAI remission status at 6 months. Gene expression studies were performed using GeneChip Human Genome U133 Plus 2.0 arrays.

2013-12-30 | E-GEOD-45867 | biostudies-arrayexpress

Uniform optimal framework for integrative next-gen sequence analysis

Project description:Here, we have collapsed multiple analysis problems into two coherent categories, signal detection and signal estimation and adapted linear-optimal solutions from signal processing theory. Our algorithms for detection (DFilter) and estimation (EFilter) extend naturally to integration of multiple datasets. In benchmarking tests, DFilter outperformed assay-specific algorithms at identifying promoters from histone ChIP-seq, binding sites from transcription factor (TF) ChIP-seq and open chromatin regions from DNase- and FAIRE-seq data. EFilter similarly outperformed an existing method for predicting mRNA levels from histone ChIP-seq data (Spearman correlation: 0.81 - 0.89). We performed H3K4me3 and H3K36me3 ChIP-seq on e11.5 mouse forebrain and used DFilter and EFilter to predict promoters and developmental gene expression, uncovering plausible gene targets for SNPs associated with neurodevelopmental disorders. Generated two histone modifiction ChiP-seq in developing embryo mouse forebrain and using them for making bioligical inferences

2013-06-10 | E-GEOD-34073 | biostudies-arrayexpress

Maximizing average throughput in oscillatory biochemical synthesis systems: an optimal control approach.

Project description:A dynamical system entrains to a periodic input if its state converges globally to an attractor with the same period. In particular, for a constant input, the state converges to a unique equilibrium point for any initial condition. We consider the problem of maximizing a weighted average of the system's output along the periodic attractor. The gain of entrainment is the benefit achieved by using a non-constant periodic input relative to a constant input with the same time average. Such a problem amounts to optimal allocation of resources in a periodic manner. We formulate this problem as a periodic optimal control problem, which can be analysed by means of the Pontryagin maximum principle or solved numerically via powerful software packages. We then apply our framework to a class of nonlinear occupancy models that appear frequently in biological synthesis systems and other applications. We show that, perhaps surprisingly, constant inputs are optimal for various architectures. This suggests that the presence of non-constant periodic signals, which frequently appear in biological occupancy systems, is a signature of an underlying time-varying objective functional being optimized.

| S-EPMC8456142 | biostudies-literature

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