Optimal Treatment Control Research Articles

Adrenal Disorders in Pregnancy. A Comprehensive Review and Prospects for Future Research

Introduction and purpose: Adrenal disorders cover a spectrum of conditions, including adrenal insufficiency, Cushing's syndrome and others. Each disorder has its own implications for pregnancy and requires an individualised approach. This review aims to provide a comprehensive overview of adrenal disorders during pregnancy, such as endogenous Cushing's syndrome, adrenal insufficiency, primary aldosteronism, and pheochromocytoma. Brief description of the state of knowledge: During pregnancy, a number of adaptive processes take place in a woman's body including changes in the endocrine system. Given all these changes, adrenal diseases pose both diagnostic and therapeutic challenges. The symptoms of adrenal diseases often overlap with those observed during physiological pregnancy. Adrenal disorders during pregnancy if unrecognised or treated inadequately, can lead to negative consequences for the mother and foetus, indicating the importance of awareness of these conditions among physicians. Conclusions: Treating and diagnosing adrenal diseases during pregnancy is a major challenge for doctors. It is crucial to diagnose adrenal diseases in pregnant women as early as possible, and to meticulously plan pregnancies for women diagnosed before conception to prevent the negative consequences of untreated adrenal disorders. Optimal control of treatment before conception should be sought. Access to specialised centres with multidisciplinary teams experienced in treating these conditions is crucial for optimal maternal and foetal care.

Therapy of moderate-to-severe plaque psoriasis

Psoriasis therapy is an acute issue in modern medicine. To date, much progress has been made in the field of genetically engineered biological therapy (GEBT) for psoriatic disease. The new treatment paradigm was made possible by the continuous advancement of understanding of the pathophysiology of the disease. GEBT represents an evolved treatment regimen in which targeted immunomodulation has led to significant improvements in the safety and efficacy of biological agents. Understanding the key role of interleukin-23 (IL) in the pathogenesis of psoriasis has led to the development of new drugs. Risankizumab is a humanised monoclonal antibody – immunoglobulin class G1 – specifically targeted at cytokine IL-23 inhibition by binding to its subunit p19. The efficacy and safety of the agent have been demonstrated both by the results of clinical trials and studies of real clinical practice. The article presents key data on the applicability of the drug risankizumab, and describes the clinical experience of managing a patient with psoriasis and aggravated comorbid conditions. It is currently known that a significant problem in the management of patients receiving GEBT is the presence of comorbid diseases. Difficulty in optimal treatment control, decreased response to therapy and increased risks of adverse events have all been noted. This study confirms the efficacy and safety of risankizumab therapy in patients with psoriasis and comorbidities. Thus, risankizumab is a promising drug for the treatment of moderate and severe forms of psoriasis, its use can significantly improve the quality of life of patients suffering from this disease.

Optimal Control with Treatment and Water Sanitation for Cholera Epidemic Model

This paper proposes a mathematical model for cholera using optimal control of treatment through quarantine and water sanitation. Cholera is acute diarrhoea caused by Vibrio cholera bacteria infecting the intestinal tract. The analysis related to the spread of this disease is carried out through a mathematical approach. The constructed mathematical model is demonstrated epidemiologically. The proposed optimal control is the treatment of infected individuals during the quarantine period and sanitation, namely environmental hygiene, especially water. This strategy aims to suppress the number of infected individuals and reduce the concentration of bacteria due to cholera disease. To solve the optimal control problem, we employ the 4th-order forward-backward Runge-Kutta method. Based on the simulation results, the number of individuals infected by cholera and the concentration of bacteria decreased significantly. Moreover, the proposed method can transfer infected to recovered individuals faster than an optimal control treatment.

Impact of nonlinear infection rate on HIV/AIDS considering prevalence‐dependent awareness

An HIV/AIDS transmission model is constructed and analyzed that assimilates spontaneous change in human behavior depending on the disease prevalence incorporating self‐shielding mechanism and treatment control. It is assumed that human population become aware of HIV disease from exposed environment and are conscious enough to make their knowledge fruitful by adopting self‐protective measures to reduce disease transmission. We introduce Hill type of behavioral change function and an awareness‐induced transmission function associated with nonlinear infection rate. We emphasize the effectiveness of human awareness in controlling HIV epidemic by investigating the impact of nonlinear incidence rate. Further, an optimal control model is formulated and solved to find the strategy of applying treatment considering spontaneous response of people towards HIV disease. In the numerical simulation segment, impacts of significant parameters have been assessed using sophisticated techniques. We calibrate the proposed model with the real data of HIV cases in India and estimate some crucial model parameters. Moreover, different amalgamations of preventive and treatment controls are introduced. The optimal treatment control has massive impact in curbing HIV epidemic. Also, combined strategy of prevention and treatment can curtail the disease with economic gain. It reveals that effective response of individuals can suppress the disease in such an unexpected situation when treatment rate is low. Increasing the efficacy of human consciousness is much beneficial in curbing HIV outbreak. Thus, our findings highlight a path to control HIV epidemic with uninstructed modification of human behavior by boosting up the productivity of their existing knowledge.

Optimal control for SIR Model with The Influence of Vaccination, Quarantine and Immigration factor

The SIR model is one of the mathematical model which describes the characteristic of the spread of infectious disease in differential equation form by dividing the human populations into three groups. There are individual susceptible group, individual infective group, and individual recovered group. This model involves vaccination, quarantine, and immigration factors. Vaccination and quarantine must be given as much as it needs, so a control is required to minimize infection of disease and the number of individual infective with a minimum costs. In this research, optimal control of SIR model with vaccination, quarantine, and immigration factor is solved by using Pontryagin maximum principle and numerically simulated by using Runge-Kutta method. Numerical simulation results show optimal control of treatment, citizen of vaccination, immigrant of vaccination, and quarantine will accelerate the decline of infected number with the minimum cost, compared with the optimal control of SIR model without quarantine factor.

KONTROL OPTIMAL PADA PEYEBARAN TUBERKULOSIS DENGAN EXOGENOUS REINFECTION

Tuberculosis is a disease caused by Mycobacterium tuberculosis. Tuberculosis can be controlled through treatment, chemoprophylaxis and vaccination. Optimal control of treatment in the exposed compartment can be done in an effort to reduce the number of exposed compartments individual into the active compartment of tuberculosis. Optimal control can be completed by the Pontryagin Maximum Principle Method. Based on numerical simulation results, optimal control of treatment in the exposed compartment can reduce the number of infected compartments individual with active TB.Keywords : Exogenous Reinfection, Optimal Control, Pontryagin's Maximum Principle, Spread Of Tuberculosis.

Hopf bifurcation analysis and optimal control of Treatment in a delayed oncolytic virus dynamics

During cancer viral therapy, there is a time delay from the initial virus infection of the tumor cells up to the time those infected cells reach the stage of being able to infect other cells. Because the duration of this “time delay” varies with each virus, it is important to understand how the delay affects the cancer viral therapy. Herein, we have introduced a mathematical model to explain this time delay. The existence of equilibrium (i.e., whether the treatment was unsuccessful or partially successful) was determined in this model by using a basic reproduction ratio of viral infection (R0) to immune response (R1). By using the bifurcation parameter as a delay τ, we proved a sufficient condition for the local asymptotic stability of two equilibrium points and the existence of Hopf bifurcation. In addition, we observed that the time delay caused the partial success equilibrium to be unstable and worked together with Hopf bifurcation to create a stable periodic oscillation. Therefore, we investigated the effects of viral cytotoxicity or infection rate, which are characteristics of viruses, on the Hopf bifurcation point. In order to support the analytical findings and to further analyze the effects of delay during cancer viral therapy, we reconstructed the model to include two controls: cancer viral therapy and immunotherapy. In addition, using numerical simulation, we suggested an optimal control problem to examine the effects of delay on oncolytic immunotherapy.

Optimal treatment control and bifurcation analysis of a tuberculosis model with effect of multiple re-infections

We derive and analyze a tuberculosis (TB) model including exogenous re-infection and endogenous reactivation, and the re-infection among the treated individuals. The disease-free equilibrium and the existence criterion of endemic equilibrium are investigated. The basic reproduction number $$R_0 $$ is derived and it is found that the disease-free equilibrium is stable when $$R_0 <1$$ , unstable for $$R_0 >1$$ , and the system undergoes a transcritical bifurcation at the disease-free equilibrium when $$R_0 =1$$ . Furthermore, for $$R_0 <1$$ , there are two endemic equilibria, one of which is stable and other one is unstable, indicating the occurrence of backward bifurcation. The local stability analysis of the disease-free and the endemic equilibrium is shown. Also, we studied the sensitivity analysis of the system in refer to some crucial model parameters and the sensitivity indices of $$R_0$$ to parameters for the TB model are obtained. Using Pontryagin’s maximum principle, we have discussed about the optimal control of the disease. Various simulation works are given throughout the paper to support our analytical results.

Optimal control of treatment in a mathematical model of chronic myelogenous leukemia

We consider a mathematical model of drug therapy for chronic myelogenous leukemia for an individual patient over a fixed time horizon. The disease dynamics are given by a system of ordinary differential equations that describe the interaction between naive T cells, effector T cells and leukemic cancer cells in a hypothetical patient. We introduce two drug therapies into this model, one a targeted therapy, and the other a broad cytotoxic therapy. Our goal is to find treatment regimens that minimize the cancer cell count and the deleterious effects of the drugs for a given patient. We examine the control setting analytically, and include numerical solutions to illustrate the optimal regimens under various assumptions.

Biological variation of International Normalized Ratio for prothrombin times, and consequences in monitoring oral anticoagulant therapy: computer simulation of serial measurements with goal-setting for analytical quality

Oral anticoagulant therapy (OAT) has a well-established efficacy in prophylaxis and treatment of thromboembolic disorders. Because complications are related to intensity of OAT, optimal control of treatment is mandatory. In studies of OAT, as many as 30% of International Normalized Ratio (INR) measurements for prothrombin times fall outside the therapeutic interval. Preanalytical, analytical, and biological variation all contribute to this. Computer simulations of serial INR measurements were performed for various assumed in-treatment setpoints within the therapeutic interval INR 2.0-3.0 and for an "in-treatment within-subject variation" (CV) of 10.1%. Results are presented in difference plots with therapeutic intervals and critical differences. If the in-treatment setpoint is mid-interval (INR = 2.5), only 5% of simulated INR values fall outside the therapeutic interval. Setpoints deviating from the mid-interval and increases in the in-treatment within-subject variation considerably increase the number of observations outside the therapeutic interval and the critical differences. In conclusion, random variation, biological or analytical, and setpoints (targets) deviating from mid-interval explain a substantial number of the INR values outside therapeutic intervals observed in clinical studies. Analytical imprecision should be kept < 5% and analytical bias < +/- 0.2 INR.

Influence of heparin treatment on biochemical markers of an activation of the coagulation system

Monitoring of anticoagulant treatment is not yet satisfactory. Otherwise optimal treatment control in special situations as low dose heparin prophylaxis in hip surgery or high dose anticoagulant treatment in patients after coronary stent implantation may be desirable. Recently available thrombin markers were analyzed in 51 patients under low dose (group 1) and 30 patients under high dose therapy with unfractionated heparin (group 2a and b) as well as in controls (n=26). Before therapy these parameters were significantly elevated in both patient groups. Elevated thrombin-antithrombin III-complexes (TAT) despite adequate prolongation of aPTT under high dose heparin in 38.2% of patients indicate that therapeutic concentrations of heparin in these cases are insufficient for depressing this parameter completely. During low dose therapy only prothrombin fragment (F1+2) significantly decreased. This may be explained by catalytic induction of TAT-complex formation by heparin. Decrease of D-Dimer under heparin therapy in both groups does not parallel with TAT and F1+2 but was more prolonged. This can be explained by dependence of the D-Dimer level on spontaneous fibrinolytic activity and by a longer plasma half-life as well as a chronic and continuous fibrinolytic process in an older thrombus. In conclusion, thrombin markers seem to be helpful in estimating anticoagulant treatment efficacy. As a consequence, anticoagulant treatment has to be intensified in high-risk patients for complete depression of these markers. Whether the benefit of higher heparin doses is worth the risk of drug-induced hemorrhage, however, remains to be clarified in clinical studies.