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Boston QSP January Event: The Blog

πiChemo: Quantitative Systems Pharmacology in Personalized Acute Myeloid Leukemia Treatment

Author: Sarah Yunes

Editors: Jae Yang and Rajiv P. Shrestha

Dr. Sakis Mantarlaris and Dr. Nicki Panoskaltsis presenting to Boston QSP audience

Dr. Sakis Mantarlaris and Dr. Nicki Panoskaltsis presenting to Boston QSP audience.

One of the leading avenues of pharmacology research today is personalized medicine. If treatment for a disease can be matched specifically to the biology of the patient as well as to that of the disease, it is likely the treatment will be more effective. Quantitative systems pharmacology (QSP) has a lot to offer in this avenue, allowing for predictive models of patient response. In this vein, Boston QSP invited Dr. Athanasios (Sakis) Mantalaris and Dr. Nicki Panoskaltsis to speak at our January event. Dr. Mantalaris is a Professor in the Wallace H. Coulter Department of Biomedical Engineering at Georgia Tech/Emory University and specializes in Bioprocess Engineering. Dr. Panoskaltsis is an Associate Professor in the Department of Hematology and Oncology at the Winship Cancer Institute at Emory University and specializes in the study of and treatment of patients with Leukemia. Together, the husband-and-wife team run a fully interdisciplinary lab. Their talk was titled, “Model-Based Personalized and Optimized Chemo-Immunotherapy for Acute Myeloid Leukemia (AML)”.

Dr.  Sakis Mantalaris (left), Dr. Nicki Panoskaltis (center) and Scientific Writer Sarah Yunes (right) during the interview

Dr. Sakis Mantarlaris (left), Dr. Nicki Panoskaltsis (center), and Scientific Writer Sarah Yunes (right) during the interview.

AML is a cancer of the bone marrow, an organ which normally makes hundreds of millions of different cell types every day for the vital functioning of the blood and immune systems. The critical balance, or homeostasis, of all of these cells is maintained dynamically by the bone marrow. In AML, white blood cell progenitors are mutated to divide uncontrollably, throwing the system out of balance and the cancer which results takes over the bone marrow. Currently, the disease has a cure rate of approximately 40% for people under the age of 65, and much less in those older where it is becoming a more prevalent condition as people live longer. In addition to the risk of the cancer returning, patients also suffer toxic secondary effects of treatment, like infections. One of the challenges to treating this disease is the large amount of heterogeneity, not only between patients, but within the tumor itself. Within a patient, there can be many different clonal populations of diseased cells that will respond differently to medications normally used to treat leukemia.

To address these challenges, the lab of Dr. Mantalaris and Dr. Panoskaltsis is working on πiChemo, a dynamic computational model designed to capture patient treatment outcomes by taking into account the heterogeneous nature of the disease. Starting with commonly-acquired patient information, such as differential cell counts in the bone marrow and peripheral blood, combined with standard PK/PD and chemotherapeutic actions on the cell cycle, the model accounts for cellular heterogeneity in each compartment and can capture how these parameters will respond to chemotherapy. In a retrospective study, πiChemo was able to closely match the disease remission outcomes and cell counts of the patients across both the intensive and non-intensive therapy options, as well as provide an optimized solution for what the patients should have ideally received in terms of drug dose and schedule to improve efficacy (achieve prolonged remission) and reduce toxicity (lessen the risk of infection). This optimization requires a minimum threshold of neutrophils in the blood throughout each cycle of chemotherapy, critical for preventing infections, in turn enhancing survival rates and outcomes.

The next step for πiChemo is to use it in a prospective clinical trial to see if it is truly predictive of patient outcomes. Also, this model could be used to determine optimal treatment based on genetic resistance markers and the distribution of different cell populations for each individual patient throughout treatment, leading to precision chemo-immunotherapy. When asked if they had any advice for students looking to get into QSP, Dr. Mantalaris and Dr. Panoskaltsis both agreed that the important things are to communicate openly between disciplines and to keep an open mind. Dr. Mantalaris said that it was important to, “move outside [your] comfort zone” and that “a successful collaboration results in the creation of a new language” to communicate between the mathematicians, engineers, biologists, and clinicians. Dr. Panoskaltsis emphasized to remember that in QSP “it’s not just a mathematical model…there is a patient at the receiving end, so it has to be responsible and it has to be right”. She also agreed about open communication across people with diverse backgrounds, with this type of collaborative research being able to “translate the new language into the creation of novel ideas and solutions in biology and medicine”.

Boston QSP guests during the post talk reception

Boston QSP guests during the mixer.

Dr. Mantalaris and Dr. Panoskaltsis’s talk was followed by a mixer event where community members discussed and socialized over food and drinks. Check out the January Event: The Photo Blog for more details and highlights.

We would like to thank Pfizer for sponsoring the event and CIC for sponsoring the venue.

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About Boston QSP

Boston QSP is a 501(c)(3) non-profit organization whose mission is to foster the sharing of QSP knowledge, challenges, solutions, and opportunities to advance the field​ as an interdisciplinary community in Boston.

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