Control of infection dynamics, with applications to the HIV disease

The human immunodeficiency virus (HIV) infection, that causes acquired immune deficiency syndrome (AIDS), is a dynamic process that can be modeled via differential equations. The primary goal of this thesis is to show how to drive any initial state into an equilibrium, called the long-term nonprogressor, in which the infected patient does not develop symptoms of AIDS. We first propose three control methods for HIV treatment. These methods are designed for antiretroviral drug therapy and are based on the understanding of the system dynamics. We apply these control strategies to several HIV dynamic models as well as a general disease dynamic model. Then we derive a new output feedback control scheme from one of the proposed methods. To show the feasibility of the output feedback control, the HIV model is studied analytically. This control method guarantees that the immune state is enhanced to a certain level, which is enough for a typical patient to be driven into the long-term nonprogressor. We also investigate methods to estimate approximately the state of the immune system based on the available outputs of the HIV model. The feasibility and effectiveness of the control strategies and estimation ideas are demonstrated by computer simulations. Key Words. HIV dynamic model, AIDS, output feedback control, drug scheduling, biological system analysis

Addressing current challenges in cancer immunotherapy with mathematical and computational modeling

The goal of cancer immunotherapy is to boost a patient's immune response to a tumor. Yet, the design of an effective immunotherapy is complicated by various factors, including a potentially immunosuppressive tumor microenvironment, immune-modulating effects of conventional treatments, and therapy-related toxicities. These complexities can be incorporated into mathematical and computational models of cancer immunotherapy that can then be used to aid in rational therapy design. In this review, we survey modeling approaches under the umbrella of the major challenges facing immunotherapy development, which encompass tumor classification, optimal treatment scheduling, and combination therapy design. Although overlapping, each challenge has presented unique opportunities for modelers to make contributions using analytical and numerical analysis of model outcomes, as well as optimization algorithms. We discuss several examples of models that have grown in complexity as more biological information has become available, showcasing how model development is a dynamic process interlinked with the rapid advances in tumor-immune biology. We conclude the review with recommendations for modelers both with respect to methodology and biological direction that might help keep modelers at the forefront of cancer immunotherapy development.Comment: Accepted for publication in the Journal of the Royal Society Interfac

The role of Computer Aided Process Engineering in physiology and clinical medicine

This paper discusses the potential role for Computer Aided Process Engineering (CAPE) in developing engineering analysis and design approaches to biological systems across multiple levels—cell signalling networks, gene, protein and metabolic networks, cellular systems, through to physiological systems. The 21st Century challenge in the Life Sciences is to bring together widely dispersed models and knowledge in order to enable a system-wide understanding of these complex systems. This systems level understanding should have broad clinical benefits. Computer Aided Process Engineering can bring systems approaches to (i) improving understanding of these complex chemical and physical (particularly molecular transport in complex flow regimes) interactions at multiple scales in living systems, (ii) analysis of these models to help to identify critical missing information and to explore the consequences on major output variables resulting from disturbances to the system, and (iii) ‘design’ potential interventions in in vivo systems which can have significant beneficial, or potentially harmful, effects which need to be understood. This paper develops these three themes drawing on recent projects at UCL. The first project has modeled the effects of blood flow on endothelial cells lining arteries, taking into account cell shape change resulting in changes in the cell skeleton which cause consequent chemical changes. A second is a project which is building an in silico model of the human liver, tieing together models from the molecular level to the liver. The composite model models glucose regulation in the liver and associated organs. Both projects involve molecular transport, chemical reactions, and complex multiscale systems, tackled by approaches from CAPE. Chemical Engineers solve multiple scale problems in manufacturing processes – from molecular scale through unit operations scale to plant-wide and enterprise wide systems – so have an appropriate skill set for tackling problems in physiology and clinical medicine, in collaboration with life and clinical scientists

Monitoring the dynamics of Src activity in response to anti-invasive dasatinib treatment at a subcellular level using dual intravital imaging

Optimising response to tyrosine kinase inhibitors in cancer remains an extensive field of research. Intravital imaging is an emerging tool, which can be used in drug discovery to facilitate and fine-tune maximum drug response in live tumors. A greater understanding of intratumoural delivery and pharmacodynamics of a drug can be obtained by imaging drug target-specific fluorescence resonance energy transfer (FRET) biosensors in real time. Here, we outline our recent work using a Src-FRET biosensor as a readout of Src activity to gauge optimal tyrosine kinase inhibition in response to dasatinib treatment regimens in vivo. By simultaneously monitoring both the inhibition of Src using FRET imaging, and the modulation of the surrounding extracellular matrix using second harmonic generation (SHG) imaging, we were able to show enhanced drug penetrance and delivery to live pancreatic tumors. We discuss the implications of this dual intravital imaging approach in the context of altered tumor-stromal interactions, while summarising how this approach could be applied to assess other combination strategies or tyrosine kinase inhibitors in a preclinical setting

Targeting Oncogenic BRAF: Past, Present, and Future.

Identifying recurrent somatic genetic alterations of, and dependency on, the kinase BRAF has enabled a "precision medicine" paradigm to diagnose and treat BRAF-driven tumors. Although targeted kinase inhibitors against BRAF are effective in a subset of mutant BRAF tumors, resistance to the therapy inevitably emerges. In this review, we discuss BRAF biology, both in wild-type and mutant settings. We discuss the predominant BRAF mutations and we outline therapeutic strategies to block mutant BRAF and cancer growth. We highlight common mechanistic themes that underpin different classes of resistance mechanisms against BRAF-targeted therapies and discuss tumor heterogeneity and co-occurring molecular alterations as a potential source of therapy resistance. We outline promising therapy approaches to overcome these barriers to the long-term control of BRAF-driven tumors and emphasize how an extensive understanding of these themes can offer more pre-emptive, improved therapeutic strategies

Simulations of Antigenic Variability in Influenza A

Computational models of the immune system (IS) and pathogenic agents have several applications, such as theory testing and validation, or as a complement to first stages of drug trials. One possible application is the prediction of the lethality of new Influenza A strains, which are constantly created due to antigenic drift and shift. Here, we present several simulations of antigenic variability in Influenza A using an agent-based approach, where low level molecular antigen-antibody interactions are explicitly described. Antigenic drift and shift events are analyzed regarding the virulence of emergent strains against the IS. Results are discussed from a qualitative point of view taking into account recent and generally recognized immunology and influenza literature