SIAM LS Minisymposium: Industrial and Academic Interactions Within the Life Sciences Community

Thursday, June 17 at 02:15pm (PDT)
Thursday, June 17 at 10:15pm (BST)
Friday, June 18 06:15am (KST)

SMB2021 SMB2021 Follow during the "SIAM1" time block.
Share this


Kresimir Josic (University of Houston, US), Dean Bottino (Millennium Pharmaceuticals, Inc., Cambridge, MA, USA, a wholly owned subsidiary of Takeda Pharmaceutical Company Limited), Alexandra Jilkine (Notre Dame, US), Nick Cogan (Florida State University, US)


The goal of the Society of Industrial and Applied Mathematics (SIAM) is to “ advance the application of mathematics and computational science to engineering, industry, science, and society.” Within the life sciences (LS), this includes biotechnology, health services, and public health. The purpose of the SIAM-LSis minisymposium is to bring together industrial and academic representatives to discuss how industrial problems in the life sciences drive academic research, in turn, how academic research contributes to industrial and technological advances.

Jae Kyoung Kim

(Department of Mathematical Sciences, KAIST/ Biomedical Mathematics Group, IBS, Korea)
"Toward mathematical medicine: development of a new drug and digital medicine for sleep disorders"
In this talk, I will illustrate collaborative stories between our math group and industry to treat disrupted circadian rhythms and sleep. In collaboration with Pfizer Inc. to help the development of a new drug modulating circadian phase regulating sleep-wake cycles, we have used a mathematical model. In particular, I will illustrate how we helped Pfizer Inc. by resolving an obstacle for the drug development and designing a personalized treatment strategy. Specifically, we identified the major source of a large inter and intra-species variation in the efficacy of the clock-modulating drug by using the combination of in silico, molecular and behavioral experiments. To circumvent the large inter-patient variations, we developed the “adaptive” chronotherapy identifying personalized dosing regimens that restore normal circadian phase. Furthermore, in collaboration with Samsung medical center, we have analyzed complex sleep patterns of shift workers with a mathematical model to find optimal sleep patterns improving their sleep quality. This opens the chance for the development of an app providing personalized sleep schedules based on sleep patterns measured by wearable devices.

Ami Radunskaya

(Pomona College, US)
"Getting to the right place at the right time"
Abstract: Drugs can be a great thing, but too much of a good thing, in the wrong spot at the wrong time can also be dangerous. The manufacture of drug delivery devices such as tablets or drug-laden nanoparticles, raises many challenges that can be attacked using mathematics. In this talk I will describe several collaborations with pharmaceutical scientists and engineers where we look at problems such as: How can we design the ``best” time-release tablet? How can we use new technologies to get drugs through the blood brain barrier in a safe and effective way? As a mathematician, I’ve found that one must be flexible and inclusive in the tools that we use to solve problems in drug delivery. I will illustrate this philosophy in two specific applications, where we bring together computational and analytical techniques from partial differential equations, optimization, cellular automata and flows on networks. I will also describe that particular difficulties that we face when trying to estimate kinetic parameters inside the brain, and how mathematics can help with this issue as well.

Rada Savic

(UC San Francisco, US)
"Computational methods to study the dynamic interplay between disease progression, treatment regimen, and drug and biomarker response across relevant scales"
To be determined.

Dean Bottino

(Takeda Pharmaceuticals, US)
"Evaluating Strategies for Overcoming Rituximab (R) Resistance Using a Quantitative Systems Pharmacology (QSP) model of Antibody-Dependent Cell-mediated Cytotoxicity & Phagocytosis (ADCC & ADCP): An Academic/Industrial Collaboration"
Authors: Maria Veronica Ciocanel, Kaitlyn E Johnson, Josua Aponte, Nicolas Bajeux, Fanwang Meng, Dean Bottino. Despite the impressive performance of rituximab (R) containing regimens like R-CHOP in CD20+ Non-Hodgkin’s Lymphoma (NHL), 30-60% of R-naïve NHL patients are estimated to be resistant, and approximately 60% of those patients will not respond to subsequent single agent R treatment. Given that antibody dependent cell mediated cytotoxicity (ADCC) and phagocytosis (ADCP) are thought to be the major mechanisms of action of Rituximab, increasing the activation levels of natural killer (NK) and macrophage (MP) cells may be one strategy for overcoming R resistance. During (and after) the Fields Institute Industrial Problem Solving Workshop in August 2019, academic participants and industry mentors developed and calibrated to literature data a quantitative systems pharmacology (QSP) model of ADCC/ADCP to interrogate which mechanisms of R resistancecould be overcome by increased NK or MP activation, and how much effector cell activation would be required to overcome a given degree and mechanism of R resistance. This work was motivated by a real-world pharmaceutical drug development question, and the academic-industry interactions during and after the workshop resulted in a published QSP model (presented at American Association of Cancer Research Annual Meeting, 2021) that was able to address some of the key questions around overcoming R resistance. The published model was then incorporated into an in-house QSP modeling supporting the development of a Takeda investigational drug which is being developed to restore R sensitivity in an R-resistant patient population.

Hosted by SMB2021 Follow
Virtual conference of the Society for Mathematical Biology, 2021.