Outcomes and Assessment of Three Years of an REU Site in Multiscale Systems Bioengineering

Timothy E. Allen

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Conference: 2020 ASEE Virtual Annual Conference Content Access
Location: Virtual On line
Publication Date: June 22, 2020
Start Date: June 22, 2020
End Date: June 26, 2021
Conference Session: NSF Grantees: REU 2
Tagged Topics: Diversity and NSF Grantees Poster Session
Page Count: 14
DOI: 10.18260/1-2--35021
Permanent URL: https://strategy.asee.org/35021
Download Count: 368

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Timothy E. Allen University of Virginia

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Dr. Timothy E. Allen is an Associate Professor in the Department of Biomedical Engineering at the University of Virginia. He received a B.S.E. in Biomedical Engineering at Duke University and M.S. and Ph.D. degrees in Bioengineering at the University of California, San Diego. Dr. Allen's teaching activities include coordinating the core undergraduate teaching labs and the Capstone Design sequence in the BME department at the University of Virginia, and his research interests are in the fields of computational biology and bioinformatics. He is also interested in evaluating the pedagogical approaches optimal for teaching lab concepts and skills, computational modeling approaches, and professionalism within design classes. Dr. Allen also serves as PI and director for an NSF-funded Multi-Scale Systems Bioengineering and Biomedical Data Sciences REU site at U.Va.

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Abstract

Advances in medicine and in the biological sciences are increasingly dependent upon a quantitative understanding of how individual biological components—including DNA, proteins, cells, tissues, and organs—interact with one another as an integrated whole to yield functional outcomes relevant to healthy physiological function and to disease states. The ability to quantitatively describe these systems and to predict how they behave will be essential for not only identifying novel drug targets and ascertaining the etiology of complex diseases such as cancer and heart disease, but also for achieving truly personalized medical diagnostics, therapies, and surgical approaches toward treating these diseases. Biological systems can be defined and studied at multiple scales: the molecular scale (protein structure and folding), the pathway and cellular scale (network behavior and "emergent properties"), and the multicellular-to-population scales (tissue-, organ-, and population-level dynamics and interactions). The ability to apply rigorous and quantitative engineering-based approaches to characterize and interrogate biological systems across multiple scales will be foundational to medical advances going forward. Thus, it is imperative to train a diverse new generation of scientists in the concepts and practice of multi-scale systems bioengineering research.

At [home institution], we have developed an NSF-funded REU Site in Multi-Scale Systems Bioengineering. For the past three summers, a total of 31 students were recruited (out of 680 applicants total), with participants coming from 27 colleges and universities around the country. REU students have performed research in topics ranging anywhere from molecular biophysics modeling to models of cardiac cell signaling to genome-scale models of metabolism to tissue-level biomechanics models to image analysis algorithms for determining levels of happiness from social media photos. Of the 31 total students over the past three years, 15 were underrepresented minorities, 16 were women, 15 were from non-R1 institutions, and 9 were from primarily undergraduate institutions. Approximately one-third of the REU participants were biomedical engineering majors, with the remainder majoring in biochemistry, chemical engineering, chemistry, biology, mathematics, computer science, physics, and neuroscience, including nine double-majors. Of these participants, 71% have presented their work at national professional society meetings, and two of them have become co-authors on three papers. Of the 17 who have since graduated, 9 are now enrolled in STEM PhD programs, 3 are working in industry in STEM positions (all of whom are seriously considering graduate school at some point in the future), 1 is in a master’s program in data science (having formerly been pre-med), and 4 are either in medical school or taking a gap year. Based on ongoing conversations with the alumni from the first two cohorts, 3 REU alumni switched their career plans from medicine to a PhD due to the summer research experience.

Post-REU surveys of participants revealed that 100% of respondents rated their overall experience with the REU as either “very satisfied” or “satisfied” (average 4.79 on a Likert scale). When asked the extent to which they agreed with statements about mentors and lab matching, REU participants in all three cohorts were very happy with their mentor (average 4.79) and with the matching process (4.54). Virtually all students strongly agreed that participating in this REU will help them be more competitive for graduate school (4.96), as well as agreeing that they made valuable professional connections (4.75). In terms of impact on long-term goals, 88% of respondents said the REU helped solidify their interest in STEM, and 75% said that the REU encouraged them to pursue further education, as well as solidified their interest in a research or academic career, while 50% said the program helped solidify interest specifically in systems bioengineering.

In this paper, the recruitment process, lab matching, student training and enrichment activities, selected projects, program outcomes, and lessons learned from the past three years will be presented. We will also discuss challenges we faced -- e.g. managing large numbers of applications and selecting students who fit the program best, matching students to labs that are appropriate to their background and interests, developing an initial boot camp experience that serves students working in a wide array of project topics, etc.

Citation
Format

Allen, T. E. (2020, June), Outcomes and Assessment of Three Years of an REU Site in Multiscale Systems Bioengineering Paper presented at 2020 ASEE Virtual Annual Conference Content Access, Virtual On line . 10.18260/1-2--35021

TY  - CPAPER
AB  - Advances in medicine and in the biological sciences are increasingly dependent upon a quantitative understanding of how individual biological components—including DNA, proteins, cells, tissues, and organs—interact with one another as an integrated whole to yield functional outcomes relevant to healthy physiological function and to disease states. The ability to quantitatively describe these systems and to predict how they behave will be essential for not only identifying novel drug targets and ascertaining the etiology of complex diseases such as cancer and heart disease, but also for achieving truly personalized medical diagnostics, therapies, and surgical approaches toward treating these diseases. Biological systems can be defined and studied at multiple scales: the molecular scale (protein structure and folding), the pathway and cellular scale (network behavior and &quot;emergent properties&quot;), and the multicellular-to-population scales (tissue-, organ-, and population-level dynamics and interactions). The ability to apply rigorous and quantitative engineering-based approaches to characterize and interrogate biological systems across multiple scales will be foundational to medical advances going forward. Thus, it is imperative to train a diverse new generation of scientists in the concepts and practice of multi-scale systems bioengineering research.

At [home institution], we have developed an NSF-funded REU Site in Multi-Scale Systems Bioengineering. For the past three summers, a total of 31 students were recruited (out of 680 applicants total), with participants coming from 27 colleges and universities around the country. REU students have performed research in topics ranging anywhere from molecular biophysics modeling to models of cardiac cell signaling to genome-scale models of metabolism to tissue-level biomechanics models to image analysis algorithms for determining levels of happiness from social media photos. Of the 31 total students over the past three years, 15 were underrepresented minorities, 16 were women, 15 were from non-R1 institutions, and 9 were from primarily undergraduate institutions. Approximately one-third of the REU participants were biomedical engineering majors, with the remainder majoring in biochemistry, chemical engineering, chemistry, biology, mathematics, computer science, physics, and neuroscience, including nine double-majors. Of these participants, 71% have presented their work at national professional society meetings, and two of them have become co-authors on three papers. Of the 17 who have since graduated, 9 are now enrolled in STEM PhD programs, 3 are working in industry in STEM positions (all of whom are seriously considering graduate school at some point in the future), 1 is in a master’s program in data science (having formerly been pre-med), and 4 are either in medical school or taking a gap year. Based on ongoing conversations with the alumni from the first two cohorts, 3 REU alumni switched their career plans from medicine to a PhD due to the summer research experience.

Post-REU surveys of participants revealed that 100% of respondents rated their overall experience with the REU as either “very satisfied” or “satisfied” (average 4.79 on a Likert scale). When asked the extent to which they agreed with statements about mentors and lab matching, REU participants in all three cohorts were very happy with their mentor (average 4.79) and with the matching process (4.54). Virtually all students strongly agreed that participating in this REU will help them be more competitive for graduate school (4.96), as well as agreeing that they made valuable professional connections (4.75). In terms of impact on long-term goals, 88% of respondents said the REU helped solidify their interest in STEM, and 75% said that the REU encouraged them to pursue further education, as well as solidified their interest in a research or academic career, while 50% said the program helped solidify interest specifically in systems bioengineering.

In this paper, the recruitment process, lab matching, student training and enrichment activities, selected projects, program outcomes, and lessons learned from the past three years will be presented. We will also discuss challenges we faced -- e.g. managing large numbers of applications and selecting students who fit the program best, matching students to labs that are appropriate to their background and interests, developing an initial boot camp experience that serves students working in a wide array of project topics, etc.
AU  - Timothy E. Allen
CY  - Virtual On line 
DA  - 2020/06/22
PB  - ASEE Conferences
TI  - Outcomes and Assessment of Three Years of an REU Site in Multiscale Systems Bioengineering
UR  - https://strategy.asee.org/35021
DO  - 10.18260/1-2--35021
ER  -