Artificial intelligence is a new addition to the infectious disease researcher’s toolbox. Yet in merely half a decade, AI has accelerated progress on some of the most urgent issues in medical science and public health. Researchers in this field blend knowledge of life sciences with skill in computation, chemistry and design, satisfying decades-long appeals for interdisciplinary tactics to treat these disorders and stop their spread.
Diseases are “infectious” when they are caused by organisms, including parasites, viruses, bacteria and fungi. People and animals can contract infectious diseases from their environments or food, or through interactions with one another. Some, but not all, are contagious.
Infectious diseases are an intractable global challenge, posing problems that continue to grow in severity even as science has offered a steady pace of solutions. The world continues to become more interconnected, bringing people into new kinds and levels of relation, and the climate crisis is throwing environmental and ecological networks out of balance. Diseases that were once treatable by drugs have become resistant, and new drug discovery is more costly than ever. Uneven resource distribution means that certain parts of the world are perennial hotspots for diseases that others never fear.
In the paper, de la Fuente and co-authors assess the progress, limitations and promise of research in AI and infectious diseases in three major areas of inquiry: anti-infective drug discovery, infection biology, and diagnostics for infectious diseases.
Presented at the biennial American Peptide Symposium, the Makineni Lectureship Award recognizes an individual who has made a recent contribution of unusual merit to research in the field of peptide science, and is intended to acknowledge original and singular discoveries.
Established in 2003 by an endowment by PolyPeptide Laboratories and Murray and Zelda Goodman, this lectureship honors Rao Makineni, a long-time supporter of peptide science, peptide scientists, and the American Peptide Society.
In a recent CNN feature, César de la Fuente, Presidential Assistant Professor in Bioengineering, Psychiatry, Microbiology, and in Chemical and Biomolecular Engineering commented on a study about a new type of antibiotic that was discovered with artificial intelligence:
“I think AI, as we’ve seen, can be applied successfully in many domains, and I think drug discovery is sort of the next frontier.”
The de la Fuente lab uses machine learning and biology to help prevent, detect, and treat infectious diseases, and is pioneering the research and discovery of new antibiotics.
The Solomon R. Pollack Award for Excellence in Graduate Bioengineering Research is given annually to the most deserving Bioengineering graduate students who have successfully completed research that is original and recognized as being at the forefront of their field. This year, the Department of Bioengineering at the University of Pennsylvania recognizes the stellar work of four graduate students in Bioengineering.
Margaret Billingsley
Dissertation: “Ionizable Lipid Nanoparticles for mRNA CAR T Cell Engineering”
Maggie Billingsley
Margaret earned a bachelor’s degree in Biomedical Engineering from the University of Delaware where she conducted research in the Day Lab on the use of antibody-coated gold nanoparticles for the detection of circulating tumor cells. She conducted doctoral research in the lab of Michael J. Mitchell, J. and Peter Skirkanich Assistant Professor in Bioengineering. After defending her thesis at Penn in 2022, Margaret began postdoctoral training at the Massachusetts Institute of Technology (MIT) in the Hammond Lab where she is investigating the design and application of polymeric nanoparticles for combination therapies in ovarian cancer. She plans to use these experiences to continue a research career focused on drug delivery systems.
“Maggie was an absolutely prolific Ph.D. student in my lab, who pioneered the development of new mRNA lipid nanoparticle technology to engineer the immune system to target and kill tumor cells,” says Mitchell. “Maggie is incredibly well deserving of this honor, and I am so excited to see what she accomplishes next as a Postdoctoral Fellow at MIT and ultimately as a professor running her own independent laboratory at a top academic institution.”
Victoria Muir
Dissertation: “Designing Hyaluronic Acid Granular Hydrogels for Biomaterials Applications”
Victoria Muir
Victoria is currently a Princeton University Presidential Postdoctoral Research Fellow in the lab of Sujit S. Datta, where she studies microbial community behavior in 3D environments. She obtained her Ph.D. in 2022 as an NSF Graduate Research Fellow at Penn Bioengineering under the advisement of Jason A. Burdick, Adjunct Professor in Bioengineering at Penn and Bowman Endowed Professor in Chemical and Biological Engineering at the University of Colorado, Boulder. She received a B.ChE. in Chemical Engineering from the University of Delaware in 2018 as a Eugene DuPont Scholar. Outside of research, Victoria is highly active in volunteer and leadership roles within the American Institute of Chemical Engineers (AIChE), currently serving as Past Chair of the Young Professionals Community and a member of the Career and Education Operating Council (CEOC). Victoria’s career aspiration is to become a professor of chemical engineering and to lead a research program at the interaction of biomaterials, soft matter, and microbiology.
“Victoria was a fantastic Ph.D. student,” says Burdick. “She worked on important projects related to granular materials from the fundamentals to applications in tissue repair. She was also a leader in outreach activities, a great mentor to numerous undergraduates, and is already interviewing towards an independent academic position.”
Sadhana Ravikumar
Dissertation: “Characterizing Medial Temporal Lobe Neurodegeneration Due to Tau Pathology in Alzheimer’s Disease Using Postmortem Imaging”
Sadhana Ravikumar
Sadhana completed her B.S. in Electrical Engineering at the University of Cape Town, South Africa in 2014 and her M.S. in Biomedical Engineering from Carnegie Mellon University in 2017. Outside of the lab, she enjoys spending time in nature and exploring restaurants in Philadelphia with friends. She focused her doctoral work on the development of computational image analysis techniques applied to ex vivo human brain imaging data in the Penn Image Computing and Science Laboratory of Paul Yushkevich, Professor of Radiology at the Perelman School of Medicine and member of the Penn Bioengineering Graduate Group. She hopes to continue working at the intersection of machine learning and biomedical imaging to advance personalized healthcare and drug development.
“Dr. Sadhana Ravikumar’s Ph.D. work is a tour de force that combines novel methodological contributions crafted to address the challenge of anatomical variability in ultra-high resolution ex vivo human brain MRI with new clinical knowledge on the contributions of molecular pathology to neurodegeneration in Alzheimer’s disease,” says Yushkevich. “I am thrilled that this excellent contribution, as well as Sadhana’s professionalism and commitment to mentorship, have been recognized through the Sol Pollack award.”
Hannah Zlotnick
Dissertation: “Remote Force Guided Assembly of Complex Orthopaedic Tissues”
Hannah Zlotnick
Hannah was a Ph.D. candidate in the lab of Robert Mauck, Mary Black Ralston Professor in Orthopaedic Surgery and in Bioengineering. She successfully defended her thesis and graduated in August 2022. During her Ph.D., Hannah advanced the state-of-the-art in articular cartilage repair by harnessing remote fields, such as magnetism and gravity. Using these non-invasive forces, she was able to control cell positioning within engineered tissues, similar to the cell patterns within native cartilage, and enhance the integration between cartilage and bone. Her work could be used in many tissue engineering applications to recreate complex tissues and tissue interfaces. Hannah earned a B.S. in Biological Engineering from the Massachusetts Institute of Technology (MIT) in 2017 during which time she was also a member of the women’s varsity soccer team. At Penn, Hannah was also involved in the Graduate Association of Bioengineers (GABE) intramurals & leadership, and helped jumpstart the McKay DEI committee. Since completing her Ph.D., Hannah has begun her postdoctoral research as a Schmidt Science Fellow in Jason Burdick’s lab at the University of Colorado Boulder where she looks to improve in vitro disease models for osteoarthritis.
“Hannah was an outstanding graduate student, embodying all that is amazing about Penn BE – smart, driven, inventive and outstanding in every way,” says Mauck. “ I can’t wait to see where she goes and what she accomplishes!”
Congratulations to our four amazing 2023 Sol Pollack Award winners!
Election to the AIMBE College of Fellows is among the highest professional distinctions accorded to a medical and biological engineer, with AIMBE Fellows representing the top 2% of medical and biological engineers. College membership honors those who have made outstanding contributions to “engineering and medicine research, practice, or education” and to “the pioneering of new and developing fields of technology, making major advancements in traditional fields of medical and biological engineering, or developing/implementing innovative approaches to bioengineering education.”
Nominated and reviewed by peers and members of the College of Fellows, de la Fuente was elected Fellow “for the development of novel antimicrobial peptides designed using principles from computation, engineering and biology.”
A formal ceremony will be held during the AIMBE Annual Event in Arlington, Virginia on March 27, 2023, where de la Fuente will be inducted along with 140 colleagues who make up the AIMBE College of Fellows Class of 2023.
AIMBE Fellows are among the most distinguished medical and biological engineers, including 3 Nobel Prize laureates and 17 Fellows having received the Presidential Medal of Science and/or Technology and Innovation, along with 205 having been inducted into the National Academy of Engineering, 105 into the National Academy of Medicine and 43 into the National Academy of
Sciences.
César de la Fuente, Presidential Assistant Professor in Bioengineering, Microbiology, Psychiatry, and Chemical and Biomolecular Engineering, co-led a team of researchers who created autonomous particles covered with patches of protein “motors,” with the goal that these bots can eventually carry livesaving drugs through bodily fluids.
César de la Fuente, Presidential Assistant Professor in Psychiatry, Bioengineering, Microbiology, and in Chemical and Biomolecular Engineering has been honored with a 2022 Young Investigator Award by the Royal Spanish Society of Chemistry (RSEQ) for his pioneering research efforts to combine the power of machines and biology to help prevent, detect, and treat infectious diseases.
The antimicrobial peptides the researchers studied are “encrypted” in that they are contained within Apolipoprotein B, a blood plasma protein that is not directly involved in the immune response, but are not normally expressed on their own.
The rise of drug-resistant bacteria infections is one of the world’s most severe global health issues, estimated to cause 10 million deaths annually by the year 2050. Some of the most virulent and antibiotic-resistant bacterial pathogens are the leading cause of life-threatening, hospital-acquired infections, particularly dangerous for immunocompromised and critically ill patients. Traditional and continual synthesis of antibiotics will simply not be able to keep up with bacteria evolution.
To avoid the continual process of synthesizing new antibiotics to target bacteria as they evolve, Penn Engineers have looked at a new, natural resource for antibiotic molecules.
César de la Fuente, Ph.D.
A recent study on the search for encrypted peptides with antimicrobial properties in the human proteome has located naturally occurring antibiotics within our own bodies. By using an algorithm to pinpoint specific sequences in our protein code, a team of Penn researchers along with collaborators, led by César de la Fuente, Presidential Assistant Professor in Psychiatry, Bioengineering, Microbiology, and Chemical and Biomolecular Engineering, and Marcelo Torres, a post doc in de la Fuente’s lab, were able to locate novel peptides, or amino acid chains, that when cleaved, indicated their potential to fend off harmful bacteria.
Now, in a new study published in ACS Nano, the team along with Angela Cesaro, the lead author and post doc in de la Fuente’s lab, have identified three distinct antimicrobial peptides derived from a protein in human plasma and demonstrate their abilities in mouse models. Angela Cesaro performed a great part of the activities during her PhD under the supervision of corresponding author, Professor Angela Arciello, from the University of Naples Federico II. The collaborative study also includes Utrecht University in the Netherlands.
“We identified the cardiovascular system as a hot spot for potential antimicrobials using an algorithmic approach,” says de la Fuente. “Then we looked closer at a specific protein in the plasma.”
Dani S. Bassett, J. Peter Skirkanich Professor in Bioengineering and in Electrical and Systems Engineering
Bassett runs the Complex Systems lab which tackles problems at the intersection of science, engineering, and medicine using systems-level approaches, exploring fields such as curiosity, dynamic networks in neuroscience, and psychiatric disease. They are a pioneer in the emerging field of network science which combines mathematics, physics, biology and systems engineering to better understand how the overall shape of connections between individual neurons influences cognitive traits.
Jason Burdick, Ph.D.
Jason A. Burdick, Robert D. Bent Professor in Bioengineering
Burdick runs the Polymeric Biomaterials Laboratory which develops polymer networks for fundamental and applied studies with biomedical applications with a specific emphasis on tissue regeneration and drug delivery. The specific targets of his research include: scaffolding for cartilage regeneration, controlling stem cell differentiation through material signals, electrospinning and 3D printing for scaffold fabrication, and injectable hydrogels for therapies after a heart attack.
César de la Fuente, Ph.D.
César de la Fuente, Presidential Assistant Professor in Bioengineering and Chemical & Biomedical Engineering in Penn Engineering and in Microbiology and Psychiatry in the Perelman School of Medicine
De la Fuente runs the Machine Biology Group which combines the power of machines and biology to prevent, detect, and treat infectious diseases. He pioneered the development of the first antibiotic designed by a computer with efficacy in animals, designed algorithms for antibiotic discovery, and invented rapid low-cost diagnostics for COVID-19 and other infections.
Carl June, M.D.
Carl H. June, Richard W. Vague Professor in Immunotherapy in the Perelman School of Medicine and member of the Bioengineering Graduate Group
June is the Director for the Center for Cellular Immunotherapies and the Parker Institute for Cancer Therapy and runs the June Lab which develops new forms of T cell based therapies. June’s pioneering research in gene therapy led to the FDA approval for CAR T therapy for treating acute lymphoblastic leukemia (ALL), one of the most common childhood cancers.
Vivek Shenoy, Ph.D.
Vivek Shenoy, Eduardo D. Glandt President’s Distinguished Professor in Bioengineering, Mechanical Engineering and Applied Mechanics (MEAM), and in Materials Science and Engineering (MSE)
Shenoy runs the Theoretical Mechanobiology and Materials Lab which develops theoretical concepts and numerical principles for understanding engineering and biological systems. His analytical methods and multiscale modeling techniques gain insight into a myriad of problems in materials science and biomechanics.
The highly anticipated annual list identifies researchers who demonstrated significant influence in their chosen field or fields through the publication of multiple highly cited papers during the last decade. Their names are drawn from the publications that rank in the top 1% by citations for field and publication year in the Web of Science™ citation index.
Bassett and Burdick were both on the Highly Cited Researchers list in 2019 and 2020.
The methodology that determines the “who’s who” of influential researchers draws on the data and analysis performed by bibliometric experts and data scientists at the Institute for Scientific Information™ at Clarivate. It also uses the tallies to identify the countries and research institutions where these scientific elite are based.
David Pendlebury, Senior Citation Analyst at the Institute for Scientific Information at Clarivate, said: “In the race for knowledge, it is human capital that is fundamental and this list identifies and celebrates exceptional individual researchers who are having a great impact on the research community as measured by the rate at which their work is being cited by others.”
The full 2021 Highly Cited Researchers list and executive summary can be found online here.
The impending danger of bacterial resistance to antibiotics is well-documented within the scientific community. Bacteria are the most efficient evolvers, and their ability to develop tolerance to drugs, in addition to antibiotic overuse and misuse, means that researchers have had to get particularly resourceful to ensure the future of modern medicine.
WIRED’s Max G. Levy recently spoke with de la Fuente and postdoctoral researcher and study collaborator Marcelo Torres about the urgency of the team’s work, and why developing these solutions is critical to the survival of civilization as we know it. The team’s algorithm, based on pattern recognition software used to analyze images, makes an otherwise insurmountable feat tangible.
De la Fuente’s lab specializes in using AI to discover and design new drugs. Rather than making some all-new peptide molecules that fit the bill, they hypothesized that an algorithm could use machine learning to winnow down the huge repository of natural peptide sequences in the human proteome into a select few candidates.
“We know those patterns—the multiple patterns—that we’re looking for,” says de la Fuente. “So that allows us to use the algorithm as a search function.”
