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Papers by Ryan Zurakowski

Research paper thumbnail of Modelling HIV-1 2-LTR dynamics following raltegravir intensification

Research paper thumbnail of Modeling uncertainty in single-copy assays for HIV

Journal of clinical microbiology, 2012

Research paper thumbnail of Modeling and control for in vitro combination therapy using ONYX015 replicating adenovirus

Replicating genetically modified adenoviruses have shown promise as a new treatment approach agai... more Replicating genetically modified adenoviruses have shown promise as a new treatment approach against cancer. Recombinant adenoviruses replicate only in cancer cells which contain certain mutations, such as the loss of functional p53, as is the case in the virus ONYX-015. The successful entry of the viral particle into target cells is strongly dependent on the presence of the main receptor for adenovirus, the coxsackie- and adeno-virus receptor (CAR). This receptor is frequently down-regulated in highly malignant cells, rendering this population less vulnerable to viral attack. It has been shown that use of MEK inhibitors can up-regulate CAR expression, resulting in enhanced adenovirus entry into the cells. However, inhibition of MEK results in G1 cell cycle arrest, rendering infected cells temporarily unable to produce virus. This forces a tradeoff. While drug mediated up-regulation of CAR enhances virus entry into cancer cells, the consequent cell cycle arrest inhibits production of new virus particles and the replication of the virus. Optimal control-based schedules of MEK inhibitor application should increase the efficacy of this treatment, maximizing the overall tumor toxicity by exploiting the dynamics of CAR expression and viral production. We introduce two mathematical models of these dynamics and show simple optimal control based strategies which motivate this approach

Research paper thumbnail of Optimal Antiviral Switching to Minimize Resistance Risk in HIV Therapy

Research paper thumbnail of Nonlinear observer output-feedback MPC treatment scheduling for HIV

Biomedical Engineering Online, 2011

Background Mathematical models of the immune response to the Human Immunodeficiency Virus demonst... more Background Mathematical models of the immune response to the Human Immunodeficiency Virus demonstrate the potential for dynamic schedules of Highly Active Anti-Retroviral Therapy to enhance Cytotoxic Lymphocyte-mediated control of HIV infection. Methods In previous work we have developed a model predictive control (MPC) based method for determining optimal treatment interruption schedules for this purpose. In this paper, we introduce a nonlinear observer for the HIV-immune response system and an integrated output-feedback MPC approach for implementing the treatment interruption scheduling algorithm using the easily available viral load measurements. We use Monte-Carlo approaches to test robustness of the algorithm. Results The nonlinear observer shows robust state tracking while preserving state positivity both for continuous and discrete measurements. The integrated output-feedback MPC algorithm stabilizes the desired steady-state. Monte-Carlo testing shows significant robustness to modeling error, with 90% success rates in stabilizing the desired steady-state with 15% variance from nominal on all model parameters. Conclusions The possibility of enhancing immune responsiveness to HIV through dynamic scheduling of treatment is exciting. Output-feedback Model Predictive Control is uniquely well-suited to solutions of these types of problems. The unique constraints of state positivity and very slow sampling are addressable by using a special-purpose nonlinear state estimator, as described in this paper. This shows the possibility of using output-feedback MPC-based algorithms for this purpose.

Research paper thumbnail of Exploiting immune response dynamics in HIV therapy

UMI, ProQuest ® Dissertations & Theses. The world's most comprehensive collection of dis... more UMI, ProQuest ® Dissertations & Theses. The world's most comprehensive collection of dissertations and theses. Learn more... ProQuest, Exploiting immune response dynamics in HIV therapy. by Zurakowski, Ryan Mark, Ph.D ...

Research paper thumbnail of HIV model parameter estimates from interruption trial data including drug efficacy and reservoir dynamics

Research paper thumbnail of Utilizing alternate target cells in treating HIV infection through scheduled treatment interruptions

… Control Conference, 2004. …, 2004

Research paper thumbnail of Closed-loop minimal sampling method for determining viral-load minima during switching

… Control Conference (ACC), …, 2010

Research paper thumbnail of Modeling-error robustness of a viral-load preconditioning strategy for HIV treatment switching

… Control Conference (ACC), …, 2010

Research paper thumbnail of Controlling the evolution of resistance

Journal of process …, 2011

Research paper thumbnail of An output-feedback MPC-based scheduling method for enhancing immune response to HIV

American Control Conference, 2006, 2006

Research paper thumbnail of HIV treatment scheduling via robust nonlinear model predictive control

… Conference, 2004. 5th …, 2004

Research paper thumbnail of Model-driven approaches for in vitro combination therapy using ONYX015 replicating oncolytic adenovirus

Journal of theoretical biology, 2007

Research paper thumbnail of A generalized multi-strain model of HIV evolution with implications for drug-resistance management

… Control Conference, 2009. …, 2009

Research paper thumbnail of A new strategy to decrease risk of resistance emerging during therapy switching in HIV treatment

American Control Conference, 2008, 2008

Research paper thumbnail of Treatment interruptions to decrease risk of resistance emerging during therapy switching in HIV treatment

Decision and Control, 2007 46th …, 2007

Research paper thumbnail of Enhancing immune response to HIV infection using MPC-based treatment scheduling

Proceedings of the American Control …, 2003

Research paper thumbnail of A model predictive control based scheduling method for HIV therapy

Journal of Theoretical Biology, 2006

Recently developed models of the interaction of the human immune system and the human immunodefic... more Recently developed models of the interaction of the human immune system and the human immunodeficiency virus (HIV) suggest the possibility of using interruptions of highly active anti-retroviral therapy (HAART) to simulate a therapeutic vaccine and induce cytotoxic lymphocyte (CTL) mediated control of HIV infection. We have developed a model predictive control (MPC) based method for determining optimal treatment interruption schedules for this purpose. This method provides a clinically implementable framework for calculating interruption schedules that are robust to errors due to measurement and patient variations. In this paper, we discuss the medical motivation for this work, introduce the MPC-based method, show simulation results, and discuss future work necessary to implement the method.

Research paper thumbnail of Treatment interruptions to decrease risk of resistance emerging during therapy switching in HIV treatment

I. INTRODUCTION The development of resistance to a particular drug regimen necessitates a change ... more I. INTRODUCTION The development of resistance to a particular drug regimen necessitates a change in regimen, and there are, for every ap-plication, only a limited number of drug regimens available. If resistance develops to every available drug regimen, the patient will die. It is ...

Research paper thumbnail of Modelling HIV-1 2-LTR dynamics following raltegravir intensification

Research paper thumbnail of Modeling uncertainty in single-copy assays for HIV

Journal of clinical microbiology, 2012

Research paper thumbnail of Modeling and control for in vitro combination therapy using ONYX015 replicating adenovirus

Replicating genetically modified adenoviruses have shown promise as a new treatment approach agai... more Replicating genetically modified adenoviruses have shown promise as a new treatment approach against cancer. Recombinant adenoviruses replicate only in cancer cells which contain certain mutations, such as the loss of functional p53, as is the case in the virus ONYX-015. The successful entry of the viral particle into target cells is strongly dependent on the presence of the main receptor for adenovirus, the coxsackie- and adeno-virus receptor (CAR). This receptor is frequently down-regulated in highly malignant cells, rendering this population less vulnerable to viral attack. It has been shown that use of MEK inhibitors can up-regulate CAR expression, resulting in enhanced adenovirus entry into the cells. However, inhibition of MEK results in G1 cell cycle arrest, rendering infected cells temporarily unable to produce virus. This forces a tradeoff. While drug mediated up-regulation of CAR enhances virus entry into cancer cells, the consequent cell cycle arrest inhibits production of new virus particles and the replication of the virus. Optimal control-based schedules of MEK inhibitor application should increase the efficacy of this treatment, maximizing the overall tumor toxicity by exploiting the dynamics of CAR expression and viral production. We introduce two mathematical models of these dynamics and show simple optimal control based strategies which motivate this approach

Research paper thumbnail of Optimal Antiviral Switching to Minimize Resistance Risk in HIV Therapy

Research paper thumbnail of Nonlinear observer output-feedback MPC treatment scheduling for HIV

Biomedical Engineering Online, 2011

Background Mathematical models of the immune response to the Human Immunodeficiency Virus demonst... more Background Mathematical models of the immune response to the Human Immunodeficiency Virus demonstrate the potential for dynamic schedules of Highly Active Anti-Retroviral Therapy to enhance Cytotoxic Lymphocyte-mediated control of HIV infection. Methods In previous work we have developed a model predictive control (MPC) based method for determining optimal treatment interruption schedules for this purpose. In this paper, we introduce a nonlinear observer for the HIV-immune response system and an integrated output-feedback MPC approach for implementing the treatment interruption scheduling algorithm using the easily available viral load measurements. We use Monte-Carlo approaches to test robustness of the algorithm. Results The nonlinear observer shows robust state tracking while preserving state positivity both for continuous and discrete measurements. The integrated output-feedback MPC algorithm stabilizes the desired steady-state. Monte-Carlo testing shows significant robustness to modeling error, with 90% success rates in stabilizing the desired steady-state with 15% variance from nominal on all model parameters. Conclusions The possibility of enhancing immune responsiveness to HIV through dynamic scheduling of treatment is exciting. Output-feedback Model Predictive Control is uniquely well-suited to solutions of these types of problems. The unique constraints of state positivity and very slow sampling are addressable by using a special-purpose nonlinear state estimator, as described in this paper. This shows the possibility of using output-feedback MPC-based algorithms for this purpose.

Research paper thumbnail of Exploiting immune response dynamics in HIV therapy

UMI, ProQuest ® Dissertations & Theses. The world's most comprehensive collection of dis... more UMI, ProQuest ® Dissertations & Theses. The world's most comprehensive collection of dissertations and theses. Learn more... ProQuest, Exploiting immune response dynamics in HIV therapy. by Zurakowski, Ryan Mark, Ph.D ...

Research paper thumbnail of HIV model parameter estimates from interruption trial data including drug efficacy and reservoir dynamics

Research paper thumbnail of Utilizing alternate target cells in treating HIV infection through scheduled treatment interruptions

… Control Conference, 2004. …, 2004

Research paper thumbnail of Closed-loop minimal sampling method for determining viral-load minima during switching

… Control Conference (ACC), …, 2010

Research paper thumbnail of Modeling-error robustness of a viral-load preconditioning strategy for HIV treatment switching

… Control Conference (ACC), …, 2010

Research paper thumbnail of Controlling the evolution of resistance

Journal of process …, 2011

Research paper thumbnail of An output-feedback MPC-based scheduling method for enhancing immune response to HIV

American Control Conference, 2006, 2006

Research paper thumbnail of HIV treatment scheduling via robust nonlinear model predictive control

… Conference, 2004. 5th …, 2004

Research paper thumbnail of Model-driven approaches for in vitro combination therapy using ONYX015 replicating oncolytic adenovirus

Journal of theoretical biology, 2007

Research paper thumbnail of A generalized multi-strain model of HIV evolution with implications for drug-resistance management

… Control Conference, 2009. …, 2009

Research paper thumbnail of A new strategy to decrease risk of resistance emerging during therapy switching in HIV treatment

American Control Conference, 2008, 2008

Research paper thumbnail of Treatment interruptions to decrease risk of resistance emerging during therapy switching in HIV treatment

Decision and Control, 2007 46th …, 2007

Research paper thumbnail of Enhancing immune response to HIV infection using MPC-based treatment scheduling

Proceedings of the American Control …, 2003

Research paper thumbnail of A model predictive control based scheduling method for HIV therapy

Journal of Theoretical Biology, 2006

Recently developed models of the interaction of the human immune system and the human immunodefic... more Recently developed models of the interaction of the human immune system and the human immunodeficiency virus (HIV) suggest the possibility of using interruptions of highly active anti-retroviral therapy (HAART) to simulate a therapeutic vaccine and induce cytotoxic lymphocyte (CTL) mediated control of HIV infection. We have developed a model predictive control (MPC) based method for determining optimal treatment interruption schedules for this purpose. This method provides a clinically implementable framework for calculating interruption schedules that are robust to errors due to measurement and patient variations. In this paper, we discuss the medical motivation for this work, introduce the MPC-based method, show simulation results, and discuss future work necessary to implement the method.

Research paper thumbnail of Treatment interruptions to decrease risk of resistance emerging during therapy switching in HIV treatment

I. INTRODUCTION The development of resistance to a particular drug regimen necessitates a change ... more I. INTRODUCTION The development of resistance to a particular drug regimen necessitates a change in regimen, and there are, for every ap-plication, only a limited number of drug regimens available. If resistance develops to every available drug regimen, the patient will die. It is ...