Borislav Savkovic

T-lymphocyte perturbation following large-scale apheresis and hematopoietic stem cell transplantation in HIV-infected individuals

Analysis and mathematical modeling of T-lymphocyte perturbation following administration of granulocyte colony stimulating factor (G-CSF) and two large-scale aphereses are reported. 74 HIV-1 positive antiretroviral-treated individuals were infused with gene- or sham-transduced CD34+ hematopoietic stem cells (HSC) in a Phase II clinical trial. T cell numbers were examined in four phases: 1) during steady state; 2) increases in peripheral blood (PB) following G-CSF administration; 3) depletion post-aphereses and 4) reconstitution post HSC infusion. The present analysis provides the first direct estimate of CD4+ T cell distribution and trafficking in HIV-infected individuals on stable HAART, indicating that CD4+ T lymphocytes in PB represent 5.5% of the pool of CD4+ T lymphocytes that traffic to PB.

A Quantitative Comparison of Anti-HIV Gene Therapy Delivered to Hematopoietic Stem Cells versus CD4+ T Cells

Gene therapy represents an alternative and promising anti-HIV modality to highly active antiretroviral therapy. It involves the introduction of a protective gene into a cell, thereby conferring protection against HIV. While clinical trials to date have delivered gene therapy to CD4+T cells or to CD34+ hematopoietic stem cells (HSC), the relative benefits of each of these two cellular targets have not been conclusively determined. In the present analysis, we investigated the relative merits of delivering a dual construct (CCR5 entry inhibitor + C46 fusion inhibitor) to either CD4+T cells or to CD34+ HSC. Using mathematical modelling, we determined the impact of each scenario in terms of total CD4+T cell counts over a 10 year period, and also in terms of inhibition of CCR5 and CXCR4 tropic virus. Our modelling determined that therapy delivery to CD34+ HSC generally resulted in better outcomes than delivery to CD4+T cells. An early one-off therapy delivery to CD34+ HSC, assuming that 20% of CD34+ HSC in the bone marrow were gene-modified (G+), resulted in total CD4+T cell counts ≥180 cells/ µL in peripheral blood after 10 years. If the uninfected G+ CD4+T cells (in addition to exhibiting lower likelihood of becoming productively infected) also exhibited reduced levels of bystander apoptosis (92.5% reduction) over non gene-modified (G-) CD4+T cells, then total CD4+T cell counts of ≥350 cells/ µL were observed after 10 years, even if initially only 10% of CD34+ HSC in the bone marrow received the protective gene. Taken together our results indicate that: 1.) therapy delivery to CD34+ HSC will result in better outcomes than delivery to CD4+T cells, and 2.) a greater impact of gene therapy will be observed if G+ CD4+T cells exhibit reduced levels of bystander apoptosis over G- CD4+T cells.

Robust Model Predictive Control for automated trajectory tracking of an Unmanned Ground Vehicle

This work presents a Robust Model Predictive Control (RMPC) approach for trajectory tracking of an Unmanned Ground Vehicle (UGV). In addition to robustness against unknown but bounded disturbances, the controller presented here is also able to deal with constraints on inputs and states due to its formulation as an RMPC. The proposed approach represents an extension of previous Model Predictive Control (MPC) laws based on the concept of constraint restriction (i.e. optimal trajectories via MPC are computed subject to stringent constraints assuming no uncertainty, and a linear local controller ensures that the actual system robustly follows the optimized MPC trajectory). The presented controller carries a low computational complexity overhead, making it attractive for real-time applications. Applying the proposed control approach to the UGV trajectory tracking problem, simulation results demonstrate robust UGV automated trajectory tracking.

Stochastic model of in-vivo X4 emergence during HIV infection: implications for the CCR5 inhibitor maraviroc.

The emergence of X4 tropic viral strains throughout the course of HIV infection is associated with poorer prognostic outcomes and faster progressions to AIDS than for patients in whom R5 viral strains predominate. Here we investigate a stochastic model to account for the emergence of X4 virus via mutational intermediates of lower fitness that exhibit dual/mixed (D/M) tropism, and employ the model to investigate whether the administration of CCR5 blockers in-vivo is likely to promote a shift towards X4 tropism. We show that the proposed stochastic model can account for X4 emergence with a median time of approximately 4 years post-infection as a result of: 1.) random stochastic mutations in the V3 region of env during the reverse transcription step of infection; 2.) increasing numbers of CXCR4-expressing activated naive CD4+ T cells with declining total CD4+ T cell counts, thereby providing increased numbers of activated target cells for productive infection by X4 virus. Our model indicates that administration of the CCR5 blocker maraviroc does not promote a shift towards X4 tropism, assuming sufficient efficacy of background therapy (BT). However our modelling also indicates that administration of maraviroc as a monotherapy or with BT of suboptimal efficacy can promote emergence of X4 tropic virus, resulting in accelerated progression to AIDS. Taken together, our results demonstrate that maraviroc is safe and effective if co-administered with sufficiently potent BT, but that suboptimal BT may promote X4 emergence and accelerated progression to AIDS. These results underscore the clinical importance for careful selection of BT when CCR5 blockers are administered in-vivo.

Toward a Robust Model Predictive Controller Applied to Mobile Vehicle Trajectory Tracking Control

Abstract This paper presents an improved formulation of tube-based (i.e. a tube is a sequence of sets) robust model predictive control (MPC) paradigm to be applied to time-varying systems. In particular it is concerned with the trajectory tracking control problem. The improved formulation of tubes employs a tighter online prediction for the evolution of difference between nominal disturbance-free and actual states of the system, therewith ensuring improved performance. The proposed robust control approach is applied to the trajectory tracking control problem of UGVs (Unmanned Ground Vehicle) subject to bounded disturbance. Simulation results illustrate that the proposed control law yields suitable robust trajectory tracking with low level of conservativeness.

Time-variant robust model predictive control under limited capacity communication constraints

This paper is concerned with robust model predictive control (MPC) of an input and state constrained system, when the system and controller are separated by a digital communication channel of limited capacity. To achieve performance and robustness, in the presence of time-variant uncertainty due to a dynamic coding/decoding policy employed to communicate state information across the channel, a time-variant robust MPC policy is employed. The rationale behind the time-variant nature of the control law of this paper is to provide a time-variant adjustment mechanism for achieving a good balance between performance (i.e. small minimal achievable costs) and robustness (i.e. stability and constraint satisfaction) achieved by the controller. The presented theory is illustrated with a simulation example. Some conclusive remarks are made regarding future work and extensions of the results of this paper.

Robust Time-Varying Model Predictive Control with Application to Mobile Robot Unmanned Path Tracking

Abstract This work presents a tube-based Robust Model Predictive Controller (RMPC) with an application to the control of a mobile robot performing unmanned path tracking. In addition to robustness against unknown but bounded uncertainties, the RMPC algorithm proposed in this work is implementable (i.e. it imposes low complexity and conservativeness), thus making it highly amenable to real-time applications. This is due to an improved formulation of the tube over previous works (here a tube is sequence of sets) which is constructed by predicting the evolution of the difference between the actual uncertain system under control and its respective nominal disturbance-free system. Moreover, a feedback corrective controller formulated as a time-varying finite-time Linear Quadratic Regulator (LQR) is proposed to regulate the uncertain system around its respective nominal uncertainty-free system and thereby suppress the effect of uncertainties acting on the actual system. The proposed RMPC algorithm is applied to a Pioneer P 3 – DX mobile robot platform performing unmanned path tracking. Experimental results demonstrate robust and stable performance of the proposed RMPC algorithm.

Cell-Delivered Gene Therapy for HIV

Scott Ledger1, Borislav Savkovic2, Michelle Millington3, Helen Impey3, Maureen Boyd3, John M. Murray2,4,5 and Geoff Symonds3,5 1The Faculty of Medicine, The University of New South Wales, Sydney 2The School of Mathematics and Statistics, The University of New South Wales, Sydney 3Calimmune Australia, 405 Liverpool St Darlinghurst, NSW 4The Kirby Institute, The University of New South Wales, Sydney NSW 5St Vincent’s Institute for Applied Medical Research 405 Liverpool St Darlinghurst, NSW Australia

Decorrelating Properties of Chromatic Derivative Signal Representations

This letter is concerned with the decorrelating properties of the recently introduced chromatic derivative signal expansions, which encode signal information by employing suitably orthogonalized differential operators. An upper bound is derived on the condition number of the autocorrelation matrix of chromatic derivative expansion coefficients, extracted at a sampling instant. It is shown that chromatic derivative signal representations may be matched to the power spectrum of the signal under analysis, in order to effect maximum signal decorrelation and in order to ensure a small condition number of the autocorrelation matrix under the chromatic derivative signal representation.

Analysis and dissociation of anti-HIV effects of shRNA to CCR5 and the fusion inhibitor C46

The gene therapeutic Cal‐1 comprises the anti‐HIV agents: (i) sh5, a short hairpin RNA to CCR5 that down‐regulates CCR5 expression and (ii) maC46 (C46), a peptide that inhibits viral fusion with the cell membrane. These constructs were assessed for inhibition of viral replication and selective cell expansion in a number of settings.