I work in quantitative medicine, an emerging field straddling fundamental biology, physiology, quantitative systems pharmacology, bioinformatics, and computational biology. My principal objective is to uncover the mechanisms that determine both healthy and pathological hemato-immune systems, and to translate these findings into the lab and clinic to concretely improve candidate drugs, therapeutic regimens, and patient outcomes. Research in my group is concentrated in three areas:
Delineating the mechanisms regulating healthy hemato-immune systems to better understand dysfunction;
Improving existing therapies for a variety of diseases, including cyclic thrombocytopenia, certain cancers, and HIV;
Proposing therapeutic strategies that leverage hemato-immune mechanisms to more effectively treat disease.
Pathological hematopoietic stem cell dynamics
In healthy individuals, approximately a trillion blood cells are produced each day through a tightly controlled process in which hematopoietic stem cells (HSCs) produce lineage restricted progenitor cells that in turn generate fully differentiated, mature blood cells. When disrupted, immature myeloid cells can accumulate in the blood and bone marrow due to their uncontrolled proliferation. This accumulation is a hallmark of leukemias, including acute myeloid leukemia (AML).
My work combines stochastic and deterministic approaches to hematopoiesis, with PK/PD drug models to understand how clones are generated during (pre-)leukemia. Together with collaborators, we explore these dynamics in ex vivo
xenotransplants to provide a comprehensive picture of the changing HSC landscape from health to disease.
Therapy personalization and optimization: in silico clinical trial platform
Modern treatments frequently combines multiple drugs. For example, combination chemotherapy can target different mechanisms of action against cancerous cells, and HAART integrates different classes of antiretrovirals to best control viral loads and disease symptoms. Unfortunately, combination therapy can carry a high therapy burden and may increase overall toxicity. Running clinical trials to test different combination therapies is a long and expensive process. Overall attrition along the drug development pipeline is high for a variety of reasons, including trial failures.
We have developed an in silico
clinical trial platformo efficiently test different drug combinations and treatment regimens before
clinical trials are run. Our approach puts together our various mechanistic disease and quantitative systems pharmacology models in a rational, quantitative approach to therapy scheduling and optimization that allows us to tailor or personalize regimens to patient cohorts or individuals.
Understanding heterogeneity in tumours and blood cancer to quantify its effects on drug resistance and therapy failure
Heterogeneity (in solid tumours and within the hematopoietic system) is a barrier to anti-cancer therapy success, and complicates clinical care strategies. Together with experimental and clinical collaborators, we work to understand the mechanisms of drug tolerance within heterogenous tumour and/or blood cell populations. In turn, the processes we uncover are used to modify current therapeutic designs to improve patient outcomes.
Reconstructing immune networks
Disordered hematopoietic conditions, like cyclic neutropenia and cyclic thrombocytopenia, give us a window into the multitude of control networks that regulate the production of blood cells. Using data from individuals with perturbed hematopoiesis and applying dynamical systems and statistical techniques like convergent cross mapping
and periodogram analysis, we reconstruct immunological networks of cytokines and blood cells. Clustering and threshold measures allow us to zoom in on the "hubs" that control hematopoiesis to give us a clearer picture of how hematopoiesis is regulated at homeostasis.
PBPK modelling of antiretrovirals to study new drug delivery systems
Though the development of combination antiretroviral (ARV) treatment (highly active antiretroviral therapy, or HAART) has transformed the management of HIV and the prognosis of those living with the infection, several factors account for why ARV treatment cannot be discontinued and why an HIV cure remains elusive. The selection of resistant HIV can be brought about by, for example, imperfect adherence leading to resistant HIV, imperfect drug penetration in HIV sanctuaries or transmission sites, the persistence of latent virus in memory cells.
To study how readily ARV drugs reach crucial sites, and the impact of that penetration on imperfect drug taking patterns, we use physiologically-based pharmacokinetic (PBPK) modelling, which takes into account the many elements affecting the disposition of ARVs in the body. Our hope is that a better understanding of how HIV resistance is impacted by the pharmacokinetics in the whole body will lead to better drug delivery systems and suggestions for HIV cure techniques.