Plenary Session 1.1 – Journey and Impact of IMAG-MSM on the Science and Career of early awardees

The goal of this session will be to highlight  the past 20 years of MSM funded projects starting with the early funded PIs, many of which are still working in MSM today.

Agenda:

9:20-9:25 (Ahmet): Introduction, Survey Form, Survey Results, Submit questions in Comment form below (wiki posted questions)

9:25-9:40: 2-minute take home messages from all 7 panelists

9:40-10:20: Moderated Q&A, submitted questions from the audience (via the wiki)

Organizers:

Denise Kirschner, Ahmet Erdemir, Stephanie George

{Table with 8 chairs 4-5 mics, 1 person at podium stating wiki questions, keep time}

Panelists:

Many of our colleagues, who engaged with IMG/MSM in its early years, indicated their interest in participating to this session: 

James Glazier,  Peter Hunter, George Karniadakis, Gregor Kovacic,  Jennifer Linderman,  James Moore (Confirmed panelists).

from left: Stephanie George (IMAG-NSF), James Moore, Peter Hunter, James Glazier, Jennifer Linderman, Gregor Kovacic
Panel from left: Stephanie George, James Moore, Peter Hunter, James Glazier, Jennifer Linderman, Gregor Kovacic

 

Charge for panelists and participants:

1) What are the biggest lessons you have learned from your MSM funded project(s)?

2) Describe your experience as an MSM investigator.

3) What were technical and societal challenges faced and how did you overcome them?

4) What types of opportunities opened up to you as a result of your MSM experiences?

5) What are current and future MSM related plans?

List of originally funded PIs:

Victor Barocas, James Bassingthwaighte (deceased), Daniel Beard, James Brasseur, Marco E. Cabrera (deceased), David Cai (deceased), Yoonsuck Choe, James Glazier, Trent Guess, Teresa L. Head-Gordon, Roger Kamm, George Karniadakis, Denise Kirschner, Robert Kunz, Anthony Ladd, Ching-Long Lin, Georg E. Luebeck, Andrew McCulloch, Peter Ortoleva, Niles Pierce, Jay Schieber, Stanislav Y. Shvartsman, Michela Taufer, Bridget S. Wilson

Survey Responders:

Early MSM awardees are asked to complete a survey (see file below) resonating with the charge of this panel. Many awardees already provided their insight to  incorporate into a description of their collective experiences an journeys: Victor Barocas, James Brasseur, Yoonsuck Choe, Ahmet Erdemir, Trent Guess, Peter Hunter, Roger Kamm, George Karniadakis, Denise Kirschner, Gregor Kovacic, Ching-Long Lin, Anrew McCulloch, Qing Nie.

Moderator Bios:

Ahmet Erdemir (MSM). In the past two decades, Dr. Erdemir has established a strong research program in computational biomechanics at the Cleveland Clinic. Currently, he is an Associate Staff in the Department of Biomedical Engineering, Chief Scientist of the Cleveland Clinic – IBM Discovery Accelerator, and the Interim Director of Office of Research Development at the Cleveland Clinic.  His scholarly contributions are predominantly in the area of musculoskeletal biomechanics, specifically on the explorations of multiscale deformations and movements of the knee. His translational focus has been on establishing computational modeling as a routine, reliable and efficient tool for healthcare delivery and biomedical science. Thus, his team conducted many simulation studies to accelerate development and evaluation of medical devices in musculoskeletal, cardiovascular, and neurological domains. Dr. Erdemir’s science of science research includes development and demonstration of good practices to enhance credibility, reproducibility, and reusability in modeling and simulation. These activities range across promotion and practice of sharing modeling assets and their incorporation to scientific review. Dr. Erdemir has been a part of the MSM community since 2006 and has has led many community initiatives to establish guidance on reporting of simulation studies and to codify credible practices in modeling and simulation in healthcare. 

Stephanie George (IMAG). Dr. Stephanie George is the Program Director for Engineering of Biomedical Systems (EBMS) within the Chemical, Bioengineering, Environmental and Transport Systems Division (CBET) at the National Science Foundation (NSF).  Dr. George is on “loan” to NSF from East Carolina University where she is an Associate Professor of Engineering. She joined the faculty of ECU in 2010 after completing a Post-Doctoral Fellowship at and Ph.D in Biomedical Engineering from Georgia Tech and Emory University.  Dr. George’s research applies engineering frameworks to address cardiovascular problems with particular emphasis on computational modeling and image processing.  Prior to her role at NSF, Dr. George served as PI for three NSF Research Experiences for Undergraduates (REU) Site awards and Co-PI for an NSF ADVANCE Adaptation award.  Dr. George has been recognized for her achievements in integrating research, education and equity.  She received ECU’s 2017 Scholar-Teacher Award and was selected to participated in the Diversity and Equity Leadership Program (ECU), BRIDGES Academic Leadership for Women (UNC System), and the BB&T Active Learning and Leadership Fellowship program (ECU).  Dr. George resides in a small town in eastern North Carolina with her husband and four children (ages 8 - 17). 

Denise Kirschner (MSM). My research for the past 25 years has focused on building multi-scale models (MSMs) of the immune response to host-pathogen interactions during infection. My main focus has been to study the immune response to persistent infections (e.g. Helicobacter pylori and Mycobacterium tuberculosis (Mtb) and HIV-1).  Such pathogens have evolved strategies to evade or circumvent the host-immune response and my goal is to understand the complex dynamics involved, together with how perturbations to this interaction (via treatment with chemotherapies or vaccines) can lead to prolonged or permanent health. My research focus has pioneered models of the host immune response to HIV-1 and Mtb at multiple spatial and time scales and in multiple physiological compartments including lung, lymph nodes and blood. Our models are continually updated with the latest data from our wetlab collaborators, using primarily non-human primate models of TB. We also have focused on developing tools for analyzing MSMs. We also perform PK/PD drug studies, asking questions about drug efficacy, drug distributions within heterogenous microenvironments, drug resistance, and drug-drug interactions.   I have served as president of the Society for Mathematical Biology and also Editor in Chief of the Journal of Theoretical Biology for 20 years. She is a Fellow of both the SMB and SIAM societies.

Panel Bios:

Jennifer Linderman.  I received my PhD in Chemical and Biochemical Engineering from the Univ. of Pennsylvania, followed by a postdoc at the Univ. of Massachusetts.  Since then, I’ve been in the Depts. of Chemical Engineering and Biomedical Engineering at the Univ. of Michigan.  I also direct the Univ. of Michigan ADVANCE Program, which focuses on faculty diversity and excellence (faculty recruitment, retention, workplace climate, and leadership development). My research interests include tuberculosis, cancer, immunology, signal transduction, receptor dynamics, developing and analyzing multi-scale models, and PK/PD.

Gregor Kovacic.  I received my PhD in Applied Mathematics from CALTECH, and had a 2 year postdoc at the Los Alamos National Laboratory.  In the past 30 years, at Rensselaer Polytechnic Institute, I have developed a broad research program in mathematical modeling and computation of physical and biological phenomena evolving on many spatial and temporal scales.  My interests range from statistical mechanics of disordered wave systems through optics of composites and nonlinear media, to theoretical and computational neuroscience.   I worked on the latter topic mainly in collaboration with the late David Cai and a group of students.   We have explored topics ranging from statistical description and coarse-graining of neuronal networks, through oscillations and compressed sensing in sensory pathways, the role of gap junctions in neuronal network dynamics, to statistical methods of network reconstruction from its firing activity.  I am an associate editor for Frontiers in Computational Neuroscience and Discrete and Continuous Dynamical Systems, Series S.

James Moore. Prof. Moore received his Ph.D. from the Georgia Institute of Technology, followed by postdoctoral training at the Swiss Institute of Technology at Lausanne.  Prior to coming to Imperial College, he was the Carolyn S. and Tommie E. Lohman ’59 Professor of Biomedical Engineering at Texas A&M University. In January 2013, he joined Imperial College as the Bagrit and Royal Academy of Engineering Chair in Medical Device Design in the Department of Bioengineering.  Prof. Moore’s research interests include Cardiovascular Biomechanics, Stents, Implantable Devices, Atherosclerosis, and the Lymphatic System. His research focuses on the role of biomechanics in the formation and treatment of diseases such as atherosclerosis and cancer. His cardiovascular biomechanics work resulted in the development of two novel stent designs aimed at optimizing post-implant biomechanics for the prevention of restenosis, as well as new testing devices for implants that employ more physiologic mechanical forces. His research on lymphatic system biomechanics has provided unprecedented insight into the pumping characteristics of the system and the transport of nitric oxide, antigens, and chemokines in lymphatic tissues. He is currently developing two technologies for preventing and resolving secondary lymphedema, which typically forms subsequent to cancer surgery. Along with his funding from government, charity, and industry sources, Prof. Moore has received multiple patents for medical devices and testing equipment.  Prof. Moore has also co-founded four startup companies.

James Glazier. I received a PhD in experimental Physics from the University of Chicago in 1989 and developed my research in experimental and computational biology as an NSF/JSPS Postdoctoral Fellow at the Research Institute of Electrical Communication, Tohoku University, Sendai, Japan. Since 2002, I have served on the faculty of Indiana University, Bloomington, first as a professor of Physics and then as a founding member of the Department of Intelligent Systems Engineering. My research on applying physics-based computer simulations to understand embryonic development, developmental and chronic toxicity, and developmental and infectious diseases has had two main components, the development of multiscale modeling tools for use by the broader MSM community and the collaborative modeling of specific problems in tissue organization and disfunction. For the past 20 years I have led the development of CompuCell3D (www.compucell3d.org), a widely used, open-source framework for the specification and execution of multiscale, multicellular Virtual Tissues. As part of this effort, I have taught an annual course on Virtual Tissue Modeling which has reached more than 400 interdisciplinary researchers at levels of seniority from high-school students to emeritus professors. I have applied these methods to study the interaction between molecular signaling and biomechanics in developmental somitogenesis, the mechanisms leading to the cystic phenotype in Autosomal Dominant Polycystic Kidney Disease, the origin of the pattern of acetaminophen-induced liver necrosis, the feedback mechanisms leading to retinal choroidal neovascularization and diabetic retinopathy and the consequences of spatial heterogeneity on viral infection in epithelia. I have served as Chair of the Division of Biological Physics of the American Physical Society and currently co-lead the IMAG/MSM Working Group on Multiscale Modeling and Viral Pandemics. More recently, I have become active in the development of infrastructure and community for the creation of biomedical digital twins.

Peter Hunter. Peter is Director of the Auckland Bioengineering Institute (ABI) at the University of Auckland, New Zealand. His research interests are in modeling human physiology using an anatomical and biophysically-based multiscale approach that links molecular processes to tissue level phenotypes. He is an elected Fellow of the Royal Society (London and NZ), a recent Executive Chair of the World Council of Biomechanics and a recent Vice-President of the International Union of Physiological Sciences (IUPS). He is the academic lead for a project to create a new medical technologies precinct in Auckland (called the Medtech Innovation Quarter or Medtech-iQ).

George Karniadakis. George is from Crete. He is a member of the National Academy of Engineering and a Vannevar Bush Faculty Fellow. He received his S.M. and Ph.D. from Massachusetts Institute of Technology (1984/87). He was appointed Lecturer in the Department of Mechanical Engineering at MIT and subsequently he joined the Center for Turbulence Research at Stanford/ Nasa Ames. He joined Princeton University as Assistant Professor in the Department of Mechanical and Aerospace Engineering and as Associate Faculty in the Program of Applied and Computational Mathematics. He was a Visiting Professor at Caltech in 1993 in the Aeronautics Department and joined Brown University as Associate Professor of Applied Mathematics in the Center for Fluid Mechanics in 1994. After becoming a full professor in 1996, he continued to be a Visiting Professor and Senior Lecturer of Ocean/Mechanical Engineering at MIT. He is an AAAS Fellow (2018-), Fellow of the Society for Industrial and Applied Mathematics (SIAM, 2010-), Fellow of the American Physical Society (APS, 2004-), Fellow of the American Society of Mechanical Engineers (ASME, 2003-) and Associate Fellow of the American Institute of Aeronautics and Astronautics (AIAA, 2006-). He received the SIAM/ACM Prize on Computational Science & Engineering (2021), the Alexander von Humboldt award in 2017, the SIAM Ralf E Kleinman award (2015), the J. Tinsley Oden Medal (2013), and the CFD award (2007) by the US Association in Computational Mechanics. His h-index is 130 and he has been cited over 84,000 times.

Memory Lane:

Please post your pictures here or to the comments for a gallery from IMAG/MSM history.

The originally funded MSM PIs at the 3rd annual of the MSM consortium meeting held in Montreal as part of the 2008 SIAM annual meeting.

Group photo - 2017 IMAG/MSM Meeting

Photo Gallery - 2019 IMAG/MSM Meeting

See materials from all past IMAG MSM Consortium meetings - since 2006!

2009 IMAG Futures Meeting - FINAL MEETING REPORT Media:IMAG_Futures_Report.pdf‎

Comment

MSM2023 Early Awardees Inquiry Survey

 If you are an MSM awardee and would like to share your experinces, please download and fillin the survey:

You can upload your responses as a comment to this wiki page or send them to Ahmet Erdemir, erdemira@ccf.org

Submitted by aerdemir on Fri, 04/14/2023 - 11:34

MSM2023 Early Awardees Inquiry Survey Responses

Pre-meeting responses to the survey can be found here: 

Submitted by aerdemir on Mon, 06/26/2023 - 11:40

Ahmet's Test Question

Can you see me?

Submitted by aerdemir on Wed, 06/28/2023 - 08:12

Yes

We can see your comments!

PLEASE ADD YOUR COMMENTS AND QUESTIONS HERE.....

PLEASE ADD YOU COMMENTS/Questions  HERE!

Submitted by kirschne on Wed, 06/28/2023 - 08:51

New Math for Biology

Thank you for bringing up the debate between math and computation. I’m really interested to hear from others about efforts in “new” math or approaches. With the momentum of quantum sensing applications and quantum driven behaviors in biology how best to link these scales? How to best to communicate/explain these types of models that bridge quantum scale and cell/tissue level models?

New Math for Biology

Thank you for bringing up the debate between math and computation. I’m really interested to hear from others about efforts in “new” math or approaches. With the momentum of quantum sensing applications and quantum driven behaviors in biology how best to link these scales? How to best to communicate/explain these types of models that bridge quantum scale and cell/tissue level models?

Future Directions in Interdisciplinary Work

I wanted to ask the panelists if they could comment on the value, and future, of interdisciplinary work and communication across domains for multiscale modeling. For early career scientists, how do we effectively build relationships across disciplines (e.g., mathematicians, statisticians, experimentalists, engineers, and physicians)?

Submitted by mjcolebank on Wed, 06/28/2023 - 09:40

I would also like to see to…

I would also like to see to elaborate on how MSM as a community will be able to enable and support this.

Advocating for Mechanistic Modeling

Many domain scientists are being influenced by big data and machine learning in their fields. How do we also advertise and advocate for mechanistic modeling when the "future" in many fields is directed towards AI/machine learning?

Submitted by mjcolebank on Wed, 06/28/2023 - 09:45

This is an important topic…

This is an important topic to address head on as a community as well.

peter hunter-- reproducibility is key! could not agree more.

this means different things for different people.

 

Also, did Simon Levin's work on Ecological Scale (he won the MacArthur award for this work) influence your impressions about scale within the body?

Submitted by kirschne on Wed, 06/28/2023 - 09:49

Standards help enormously with reproducibility

A comment not a question: Standards help enormously with reproducibility but getting funding to support the development is extremely hard. It's telling that two of the main standards SBML and CellML were not developed in the US. There is also continual criticism that these standards don't support multiscale modeling, that is true but trying to get new standards developed to support multiscale modeling is almost impossible. 

Operationalization of models towards translation

An important challenge is modifying, reusing, combining models for their operationalization, i.e. for seamless decision making. What challenges the panelist see inthis regard where the community can tackle together?

Submitted by aerdemir on Wed, 06/28/2023 - 09:56

context of use and flexibility in application

The standards that have been developed on from this group has been incredibly encouraging but aren't used in other modeling frameworks. For example machine learning and large language models are being deployed into almost every language application and are extensively funded because of these "big ideas" that they may lead to (even though testing in domain specific applications is lacking). How do we balance going slow and deliberate with making bold claims about where the models may be deployed and possibly improve patient health and outcomes? Do you believe  sensational headlines lead to the funding needed to advance the field to some degree?

Submitted by ajbaird on Wed, 06/28/2023 - 10:01

MSM = Complex models for complex problems => novel approaches

Not a question but rather a comment. What appears to be a pervasive theme is that the panel looked at problems that challenged "traditional" concepts (and reviewers) about what could and needed to be done. These projects push the limits of existing methods and needs: simulation/computational limits, integration of multiple data types, the whole importance of reproducibility and credibility (less important if you have a simple math equation) and biological domains wo a classical "home" (integrative in of itself). This community is critical because it is here that the important methodological advances have a chance to be developed. 

Submitted by Gary_An on Wed, 06/28/2023 - 10:02

Growing Beyond MSM Community

How can we grow our community to more tightly integrate with end-users of our models or even stakeholders (patients, policy makers) that are impacted by the decisions made by the models?

Submitted by aerdemir on Wed, 06/28/2023 - 10:06

Dedicated review panels

A comment not a question: I'd like to add to kirchne's comment that there is an up hill battle to get funding because the current panel reviewers simply aren't qualified to review modeling proposals. With the push to AI/ML we're also seeing reviewers push back on mechanistic modeling as being a dated approach.. 

Submitted by hsauro on Wed, 06/28/2023 - 10:11

To All Panelists

How can we replicate your successful trajectories for emerging scientists, modelers? Would you be able to do what you did then now? What advise you would give to to your younger self as you first engaged with MSM?

Submitted by aerdemir on Wed, 06/28/2023 - 10:19

Reproduce vs. replicate findings

Reproducibility can be a difficult bar when involving long simulation times, large unwieldy datasets, complex software dependencies, etc.
Can replicating the findings and reaching the same conclusions be more suitable in these edge cases?

Submitted by pnanda@umich.edu on Wed, 06/28/2023 - 11:45