Tag: computer science

Posted on

A Return to Jamaica Brings Seven Student-Invented Devices to Help People and Wildlife

by Melissa Pappas

Students test the GaitMate harness and structure as a tool to help recovering patients walk.

Penn students have been building their knowledge and hands-on experience in places all over the world through Penn Global Seminars. Last May, “Robotics and Rehabilitation” brought Penn students back to the tropical island of Jamaica to collaborate with local university students and make an impact on recovery and quality of life for patients in Kingston and beyond. 

Course leaders Camillo Jose (CJ) Taylor, Raymond S. Markowitz President’s Distinguished Professor in Computer and Information Science (CIS), and Michelle J. Johnson, Associate Professor of Physical Medicine and Rehabilitation at the Perelman School of Medicine and Associate Professor in Bioengineering (BE) and Mechanical Engineering and Applied Mechanics (MEAM) at Penn Engineering, brought the first cohort of students to the island in 2019. 

“CJ and I are both Jamaicans by birth,” says Johnson. “We were both excited to introduce the next generation of engineers to robotics, rehabilitation and the process of culturally sensitive design in a location that we are personally connected to.” 

As they built relationships with colleagues at the University of West Indies, Mona (UWI, Mona) and the University of Technology, Jamaica (UTECH), both Johnson and Taylor worked to tie the goals of the course to the location.

“In the initial iteration of the course, our goal was to focus on the applications of robotics to rehabilitation in a developing country where it is necessary to create solutions that are cost effective and will work in under-resourced settings,” says Taylor. 

Taylor and Johnson wanted to make the course a regular offering, however, due to COVID-related travel restrictions, it wasn’t until last spring that they were able to bring it back. But when they did, they made up for lost time and expanded the scope of the course to include solving health problems for both people and the environment.

“While we started with a focus on people, we realized that the health and quality of life of a community is also impacted by the health of the environment,” says Taylor. “Jamaica has rich terrestrial and marine ecosystems, but those resources need to be monitored and regulated. We ventured into developing robotics tools to make environmental monitoring more effective and cost-friendly.”

One of those student-invented tools was a climate survey drone called “BioScout.” 

“Our aim was to create a drone to monitor the ecosystem and wildlife in Jamaica,” says Rohan Mehta, junior in Systems Science and Engineering. “We wanted to help researchers and rangers who need to monitor wildlife and inspect forest sectors without entering and disturbing territories, but there were no available drones that met all of the following criteria necessary for the specific environment: affordable, modular, water-resistant and easy to repair. So we made our own.”

Another team of students created a smart buoy to reduce overfishing. The buoy was equipped with an alarm that goes off when fishermen get too close to a no-fishing zone.

Five other student teams dove into projects aligned to the original goals of the course. Their devices addressed patients’ decreased mobility due to diabetes, strokes and car accidents. These projects were sponsored by the Sir John Golding Rehabilitation Center.

One of which, the GaitMate, was engineered to help stroke patients who had lost partial muscle control regain their ability to walk.  

“We developed a device that supports a patient’s weight and provides sensory feedback to help correct their form and gait as they walk on a treadmill, ultimately enhancing the recovery process and providing some autonomy to the patient,” says Taehwan Kim, senior in BE. “The device is also relatively cheap and simple, making it an option for a wide variety of physical therapy needs in Jamaica and other countries.”

Read the full story in Penn Engineering Today.

Posted on

Two Penn Bioengineers Receive NIH Director Award

by Nathi Magubane

Jina Ko (left) and Kevin Johnson (right), both from the School of Engineering and the Perelman School of Medicine with appointments in Bioengineering, have received the National Institute of Health Director’s Award to support their “highly innovative and broadly impactful” research projects through the High-Risk, High-Reward program.

The National Institutes of Health (NIH) has awarded grants to three researchers from the University of Pennsylvania through the NIH Common Fund’s High-Risk, High-Reward Research program. The research of Kevin B. Johnson, Jina Ko, and Sheila Shanmugan will be supported through the program, which funds “highly innovative and broadly impactful” biomedical or behavioral research by exceptionally creative scientists.

The High-Risk, High-Reward Research program catalyzes scientific discovery by supporting highly innovative research proposals that, due to their inherent risk, may struggle in the traditional peer-review process despite their transformative potential. Program applicants are encouraged to think “outside the box” and pursue trail-blazing ideas in any area of research relevant to the NIH’s mission to advance knowledge and enhance health.

Two Penn Bioengineering faculty, Johnson and Ko, are among 85 recipients for 2023.

Johnson, the David L. Cohen University Professor of Pediatrics, is a Penn Integrates Knowledge University Professor who holds appointments in the Department of Computer and Information Science in the School of Engineering and Applied Science and the Department of Biostatistics, Epidemiology, and Informatics in the Perelman School of Medicine. He also holds secondary appointments in Bioengineering, Pediatrics, and in the Annenberg School for Communication. He is widely known for his work with e-prescribing and computer-based documentation and, more recently, work communicating science to lay audiences, which includes a documentary about health-information exchange. Johnson has authored more than 150 publications and was elected to the American College of Medical Informatics, Academic Pediatric Society, National Academy of Medicine, International Association of Health Science Informatics, and American Institute for Medical and Biological Engineering.

Ko is an assistant professor in the Department of Pathology and Laboratory Medicine in the Perelman School of Medicine and Department of Bioengineering in the School of Engineering and Applied Science. She focuses on developing single molecule detection from single extracellular vesicles and multiplexed molecular profiling to better diagnose diseases and monitor treatment efficacy. Ko earned her Ph.D. in bioengineering at Penn in 2018, during which time she developed machine learning-based microchip diagnostics that can detect blood-based biomarkers to diagnose pancreatic cancer and traumatic brain injury. For her postdoctoral training, she worked at the Massachusetts General Hospital and the Wyss Institute at Harvard University as a Schmidt Science Fellow and a NIH K99/R00 award recipient. Ko developed new methods to profile single cells and single extracellular vesicles with high throughput and multiplexing.

Read the full announcement in Penn Today.

Posted on

View the 2023 Department of Bioengineering Juneteenth Address by Dr. Kevin B. Johnson

Thank you to everyone who attended the 2023 Department of Bioengineering Juneteenth Address. For those who were unable to attend or who may wish to share the opportunity to view the lecture, a recording of Dr. Kevin Johnson’s talk, “A White Neighbor, a Black Surgeon, and a Mormon Computer Scientist Walk into a Bar…” is available below.

Speaker:
Kevin B. Johnson, MD, MS, FAAP, FAMIA, FACMI
David L. Cohen University Professor
Computer and Information Science
Biostatistics, Epidemiology and Informatics
Bioengineering
Annenberg School for Communication
Pediatrics
VP for Applied Informatics (UPHS), University of Pennsylvania

Abstract:
As we recognize Juneteenth, a holiday that brings awareness to what journalist Corey Mitchell calls “…a complex understanding of the nation’s past,” we also need to understand how many of our neighbors, staff, and faculty — even those born in the last 100 years — continue to navigate through the environment that made Juneteenth remarkable. In this talk, Dr. Johnson  shares a bit of his personal story and how this story informs his national service and passion for teaching.

Posted on

On a Different Wavelength, Nader Engheta Leads a Community in Light

Nader Engheta was puzzled when he got a call from the psychology department about a fish.
In the early 1990s, Engheta, a newly minted associate professor of electrical engineering in Penn’s School of Engineering and Applied Science, was a respected expert in radio wave technologies. But in recent years, his work had been expanding into subjects at once more eccentric and fundamental.

Nader Engheta was puzzled when he got a call from the psychology department about a fish.

In the early 1990s, Engheta, a newly minted associate professor of electrical engineering in Penn’s School of Engineering and Applied Science, was a respected expert in radio wave technologies. But in recent years, his work had been expanding into subjects at once more eccentric and fundamental.

Engheta’s interest in electromagnetic waves was not limited to radio frequencies, as a spate of fresh publications could attest. Some studies investigated a range of wave interactions with a class of matter known as a “chiral media,” materials with molecular configurations that exhibit qualities of left or right “handedness.” Others established practical electromagnetic applications for a bewildering branch of mathematics called “fractional calculus,” an area with the same Newtonian roots as calculus proper but a premise as eyebrow-raising as the suggestion a family might literally include two-and-a-half children.

Electromagnetic waves are organized on a spectrum of wavelengths. On the shorter end of the spectrum are high-energy waves, such as X-rays. In the middle, there is the limited range we see as visible light. And on the longer end are the lower-energy regimes of radio and heat.

Researchers tend to focus on one kind of wave or one section of the spectrum, exploring quirks and functions unique to each. But all waves, electromagnetic or not, share the same characteristics: They consist of a repeating pattern with a certain height (amplitude), rate of vibration (frequency), and distance between peaks (wavelength). These qualities can define a laser beam, a broadcasting voice, a wind-swept lake, or a violin string.

Engheta has never been the kind of scholar to limit the scope of his curiosity to a single field of research. He is interested in waves, and his fascination lies equally in the physics that determine wave behavior and the experimental technologies that push the boundaries of those laws.

So, when Edward Pugh, a mathematical psychologist studying the physiology of visual perception, explained that green sunfish might possess an evolutionary advantage for seeing underwater, Engheta listened.

Soon, the two Penn professors were pouring over microscope images of green sunfish retinas.

Read Devorah Fischler’s full story about Nader Engheta and watch an accompanying video at Penn Today.

Nader Engheta is H. Nedwill Ramsey Professor of Electrical and Systems Engineering at Penn Engineering, with secondary appointments in the departments of Bioengineering, Materials Science and Engineering, and Physics and Astronomy in the School of Arts & Sciences.

Posted on

2023 Department of Bioengineering Juneteenth Address: “A White Neighbor, a Black Surgeon, and a Mormon Computer Scientist Walk into a Bar…” (Kevin B. Johnson)

Kevin B. Johnson, MD, MS

We hope you will join us for the 2023 Department of Bioengineering Juneteenth Address by Dr. Kevin B. Johnson.

Date: Wednesday, June 14, 2023
Start Time: 11:00 AM ET
Location: Berger Auditorium (Skirkanich Hall basement room 013)

Zoom link
Meeting ID: 925 0325 6013
Passcode: 801060

Following the event, a limited number of box lunches will be available for in-person attendees. If you would like a box lunch, please RSVP here by Monday, June 12 so we can get an accurate headcount.

Speaker: Kevin B. Johnson, MD, MS, FAAP, FAMIA, FACMI
David L. Cohen University Professor
Annenberg School for Communication, Bioengineering, Biostatistics, Epidemiology and Informatics, Computer and Information Science, Pediatrics
VP for Applied Informatics (UPHS), University of Pennsylvania

Title: “A White Neighbor, a Black Surgeon, and a Mormon Computer Scientist Walk into a Bar…”

Abstract: As we recognize Juneteenth, a holiday that brings awareness to what journalist Corey Mitchell calls “…a complex understanding of the nation’s past”, we also need to understand how many of our neighbors, staff, and faculty—even those born in the last 100 years—continue to navigate through the environment that made Juneteenth remarkable. Dr. Johnson will share a bit of his personal story and how this story informs his national service and passion for teaching.

Bio: Dr. Johnson is a leader of medical information technologies to improve patient care and safety. He is well regarded and widely known for pioneering discoveries in clinical informatics, leading to advances in data acquisition, medication management, and information aggregation in medical settings.

He is a board-certified pediatrician who has aligned the powers of medicine, engineering and technology to improve the health of individuals and communities. In work that bridges biomedical informatics, bioengineering and computer science, he has championed the development and implementation of clinical information systems and artificial intelligence to drive medical research. He has encouraged the effective use of technology at the bedside, and he has empowered patients to use new tools that help them to understand how medications and supplements may affect their health. He is interested in using advanced technologies such as smart devices and in developing computer-based documentation systems for the point of care. He also is an emerging champion of the use of digital media to enhance science communication, with a successful feature-length documentary describing health information exchange, a podcast (Informatics in the Round) and most recently, a children’s book series aimed at STEM education featuring scientists underrepresented in healthcare.

Dr. Johnson holds joint appointments in the Department of Computer and Information Science of the School of Engineering and Applied Science, and secondary appointments in Bioengineering and the Annenberg School for Communication. He serves as Vice President for Applied Informatics in the University of Pennsylvania Health System and as a Professor of Pediatrics at the Children’s Hospital of Philadelphia.

Before arriving at Penn, he served as the Cornelius Vanderbilt Professor and Chair of the Department of Biomedical Informatics at the Vanderbilt University School of Medicine, where he had taught since 2002. As Senior Vice President for Health Information Technology at the Vanderbilt University Medical Center, he led the development of clinical systems that enabled doctors to make better treatment and care decisions for individual patients, and introduced new systems to integrate artificial intelligence into patient care workflows.

The author of more than 150 publications, Dr. Johnson has held numerous leadership positions in the American Medical Informatics Association and the American Academy of Pediatrics. He leads the American Board of Pediatrics Informatics Advisory Committee, directs the Board of Scientific Counselors of the National Library of Medicine, and is a member of the NIH Council of Councils. He is an elected member of the National Academy of Medicine, American College of Medical Informatics and Academic Pediatric Society. He has received awards from the Robert Wood Johnson Foundation and American Academy of Pediatrics, among many others.

Posted on

Folding@Home: How You, and Your Computer, Can Play Scientist

by Alex Gardner

Greg Bowman kneels, working on a server.
Folding@home is led by Gregory Bowman, a Penn Integrates Knowledge Professor who has appointments in the Departments of Biochemistry and Biophysics in the Perelman School of Medicine and the Department of Bioengineering in the School of Engineering and Applied Science. (Image: Courtesy of Penn Medicine News)

Two heads are better than one. The ethos behind the scientific research project Folding@home is that same idea, multiplied: 50,000 computers are better than one.

Folding@home is a distributed computing project which is used to simulate protein folding, or how protein molecules assemble themselves into 3-D shapes. Research into protein folding allows scientists to better understand how these molecules function or malfunction inside the human body. Often, mutations in proteins influence the progression of many diseases like Alzheimer’s disease, cancer, and even COVID-19.

Penn is home to both the computer brains and human minds behind the Folding@home project which, with its network, forms the largest supercomputer in the world. All of that computing power continually works together to answer scientific questions such as what areas of specific protein implicated in Parkinson’s disease may be susceptible to medication or other treatment.

Led by Gregory Bowman, a Penn Integrates Knowledge professor of Biochemistry and Biophysics in the Perelman School of Medicine who has joint appointments in the Department of Biochemistry and Biophysics in the Perelman School of Medicine and the Department of Bioengineering in the School of Engineering and Applied Science, Folding@home is open for any individual around the world to participate in and essentially volunteer their computer to join a huge network of computers and do research.

Using the network hub at Penn, Bowman and his team assign experiments to each individual computer which communicates with other computers and feeds info back to Philly. To date, the network is comprised of more than 50,000 computers spread across the world.

“What we do is like drawing a map,” said Bowman, explaining how the networked computers work together in a type of system that experts call Markov state models. “Each computer is like a driver visiting different places and reporting back info on those locations so we can get a sense of the landscape.”

Individuals can participate by signing up and then installing software to their standard personal desktop or laptop. Participants can direct the software to run in the background and limit it to a certain percentage of processing power or have the software run only when the computer is idle.

When the software is at work, it’s conducting unique experiments designed and assigned by Bowman and his team back at Penn. Users can play scientist and watch the results of simulations and monitor the data in real time, or they can simply let their computer do the work while they go about their lives.

Read the full story at Penn Medicine News.

Posted on

Why is Machine Learning Trending in Medical Research but not in Our Doctor’s Offices?

by Melissa Pappas

Illustration of a robot in a white room with medical equipment.Machine learning (ML) programs computers to learn the way we do – through the continual assessment of data and identification of patterns based on past outcomes. ML can quickly pick out trends in big datasets, operate with little to no human interaction and improve its predictions over time. Due to these abilities, it is rapidly finding its way into medical research.

People with breast cancer may soon be diagnosed through ML faster than through a biopsy. Those suffering from depression might be able to predict mood changes through smart phone recordings of daily activities such as the time they wake up and amount of time they spend exercising. ML may also help paralyzed people regain autonomy using prosthetics controlled by patterns identified in brain scan data. ML research promises these and many other possibilities to help people lead healthier lives.

But while the number of ML studies grow, the actual use of it in doctors’ offices has not expanded much past simple functions such as converting voice to text for notetaking.

The limitations lie in medical research’s small sample sizes and unique datasets. This small data makes it hard for machines to identify meaningful patterns. The more data, the more accuracy in ML diagnoses and predictions. For many diagnostic uses, massive numbers of subjects in the thousands would be needed, but most studies use smaller numbers in the dozens of subjects.

But there are ways to find significant results from small datasets if you know how to manipulate the numbers. Running statistical tests over and over again with different subsets of your data can indicate significance in a dataset that in reality may be just random outliers.

This tactic, known as P-hacking or feature hacking in ML, leads to the creation of predictive models that are too limited to be useful in the real world. What looks good on paper doesn’t translate to a doctor’s ability to diagnose or treat us.

These statistical mistakes, oftentimes done unknowingly, can lead to dangerous conclusions.

To help scientists avoid these mistakes and push ML applications forward, Konrad Kording, Nathan Francis Mossell University Professor with appointments in the Departments of Bioengineering and Computer and Information Science in Penn Engineering and the Department of Neuroscience at Penn’s Perelman School of Medicine, is leading an aspect of a large, NIH-funded program known as CENTER – Creating an Educational Nexus for Training in Experimental Rigor. Kording will lead Penn’s cohort by creating the Community for Rigor which will provide open-access resources on conducting sound science. Members of this inclusive scientific community will be able to engage with ML simulations and discussion-based courses.

“The reason for the lack of ML in real-world scenarios is due to statistical misuse rather than the limitations of the tool itself,” says Kording. “If a study publishes a claim that seems too good to be true, it usually is, and many times we can track that back to their use of statistics.”

Such studies that make their way into peer-reviewed journals contribute to misinformation and mistrust in science and are more common than one might expect.

Read the full story in Penn Engineering Today.

Posted on

This Patterned Surface Solves Equations at the Speed of Light

by Devorah Fischler

A tailored silicon nanopattern coupled with a semi-transparent gold mirror can solve a complex mathematical equation using light. (Image credit: Ella Maru studio)

Researchers at the University of Pennsylvania, AMOLF, and the City University of New York (CUNY) have created a surface with a nanostructure capable of solving mathematical equations.

Powered by light and free of electronics, this discovery introduces exciting new prospects for the future of computing.

Nader Engheta, H. Nedwill Ramsey Professor of Electrical and Systems Engineering at the University of Pennsylvania School of Engineering and Applied Science, is a visionary figure in optics and in electromagnetic platforms. For the last two decades, he has created theory and designed experiments to make electromagnetic and optical devices that operate at the fastest rate in the universe.

Engheta is the founder of the influential field of “optical metatronics.” He creates materials that interact with photons to manipulate data at the speed of light. Engheta’s contribution to this study marks an important advance in his quest to use light-matter interactions to surpass the speed and energy limitations of digital electronics, bringing analog computing out of the past and into the future.

“I began the work on optical metatronics in 2005,” says Engheta, “wondering if it were possible to recreate the elements of a standard electronic circuit at nanoscale. At this tiny size, it would be possible to manipulate the circuit with light, rather than electricity. After achieving this, we became more ambitious, envisioning collections of these nanocircuits as processors. In 2014, we were designing materials that used these optical nanostructures to perform mathematical operations, and in 2019, we anted up to entire mathematical equations using microwaves. Now, my collaborators and I have created a surface that can solve equations using light waves, a significant step closer to our larger goals for computing materials.”

The study, recently published in Nature Nanotechnology, demonstrates the possibility of solving complex mathematical problems and a generic matrix inversion at speeds far beyond those of typical digital computing methods.

The solution converges in about 349 femtoseconds (less than one trillionth of a second), orders of magnitude faster than the clock speed of a conventional processor.

Read the full story in Penn Engineering Today.

Nader Engheta is the H. Nedwill Ramsey Professor in the Departments of Electrical and Systems Engineering and in Bioengineering in the School of Engineering and Applied Science and Professor in Physics and Astronomy in the School of Arts & Sciences at the University of Pennsylvania.

Posted on

Gregory Bowman Appointed Penn Integrates Knowledge University Professor

by Ron Ozio

Greg Bowman
Gregory Bowman, the Louis Heyman University Professor, has joint appointments in the Department of Biochemistry and Biophysics in the Perelman School of Medicine and the Department of Bioengineering in the School of Engineering and Applied Science. (Image: Courtesy of School of Engineering and Applied Sciences)

Gregory R. Bowman, a pioneer of biophysics and data science, has been named a Penn Integrates Knowledge University Professor at the University of Pennsylvania. The announcement was made today by President Liz Magill and Interim Provost Beth A. Winkelstein.

Bowman holds the Louis Heyman University Professorship, with joint appointments in the Department of Biochemistry and Biophysics in the Perelman School of Medicine and the Department of Bioengineering in the School of Engineering and Applied Science.

His research aims to combat global health threats such as COVID-19 and Alzheimer’s disease by better understanding how proteins function and malfunction, especially through new computational and experimental methods that map protein structures. This understanding of protein dynamics can lead to effective new treatments for even the most seemingly resistant diseases.

“Delivering the right treatment to the right person at the right time is vital to sustaining—and saving—lives,” Magill said. “Greg Bowman’s novel work holds enormous promise and potential to advance new forms of personalized medicine, an area of considerable strength for Penn. A gifted researcher and consummate collaborator, we are delighted to count him among our distinguished PIK University Professors.”

Bowman came to Penn from the Washington University School of Medicine’s Department of Biochemistry and Molecular Biophysics, where he served on the faculty since 2014. He previously completed a three-year postdoctoral fellowship at the University of California, Berkeley.

Bowman’s research utilizes high-performance supercomputers for simulations that can better explain how mutations and disease change a protein’s functions. These simulations are enabled in part through the innovative Folding@home project, which Bowman directs. Folding@home empowers anyone with a computer to run simulations alongside a consortium of universities, with more than 200,000 participants worldwide.

His research has been supported by the National Science Foundation, National Institutes of Health, National Institute on Aging, and Packard Foundation, among others, and he has received a CAREER Award from the NSF, Career Award at the Scientific Interface from the Burroughs Wellcome Fund, and Thomas Kuhn Paradigm Shift Award from the American Chemical Society. He received a Ph.D. in biophysics from Stanford University and a B.S. (summa cum laude) in computer science, with a minor in biomedical engineering, from Cornell University.

“Greg Bowman’s highly innovative work,” Winkelstein said, “exemplifies the power of our interdisciplinary mission at Penn. He brings together supercomputers, biophysics, and biochemistry to make a vital impact on public health. This brilliant fusion of methods—in the service of improving people’s lives around the world—will be a tremendous model for the research of our faculty, students, and postdocs in the years ahead.”

The Penn Integrates Knowledge program is a University-wide initiative to recruit exceptional faculty members whose research and teaching exemplify the integration of knowledge across disciplines and who are appointed in at least two schools at Penn.

The Louis Heyman University Professorship is a gift of Stephen J. Heyman, a 1959 graduate of the Wharton School, and his wife, Barbara Heyman, in honor of Stephen Heyman’s uncle. Stephen Heyman is a University Emeritus Trustee and member of the School of Nursing Board of Advisors. He is Managing Partner at Nadel and Gussman LLC in Tulsa, Oklahoma.

This story originally appeared in Penn Today.

Dr. Bowman is Penn Bioengineering’s third PIK Professor after Kevin Johnson and Konrad Kording. See the full list of University PIK Professors here.

Posted on

More Cancers May be Treated with Drugs than Previously Believed

by Alex Gardner

3D illustration of cancer cells
nucleus and membrane of pathogen micro organisms in blue background

Up to 50 percent of cancer-signaling proteins once believed to be immune to drug treatments due to a lack of targetable protein regions may actually be treatable, according to a new study from the Perelman School of Medicine at the University of Pennsylvania. The findings, published this month in Nature Communications, suggest there may be new opportunities to treat cancer with new or existing drugs.

Researchers, clinicians, and pharmacologists looking to identify new ways to treat medical conditions—from cancer to autoimmune diseases—often focus on protein pockets, areas within protein structures to which certain proteins or molecules can bind. While some pockets are easily identifiable within a protein structure, others are not. Those hidden pockets, referred to as cryptic pockets, can provide new opportunities for drugs to bind to. The more pockets scientists and clinicians have to target with drugs, the more opportunities they have to control disease.

The research team identified new pockets using a Penn-designed neural network, called PocketMiner, which is artificial intelligence that predicts where cryptic pockets are likely to form from a single protein structure and learns from itself. Using PocketMiner—which was trained on simulations run on the world’s largest super computer—researchers simulated single protein structures and successfully predicted the locations of cryptic pockets in 35 cancer-related protein structures in thousands of areas of the body. These once-hidden targets, now identified, open up new approaches for potentially treating existing cancer.

What’s more, while successfully predicting the cryptic pockets, the method scientists used in this study was much faster than previous simulation or machine-learning methods. The network allows researchers to nearly instantaneously decide if a protein is likely to have cryptic pockets before investing in more expensive simulations or experiments to pursue a predicted pocket further.

“More than half of human proteins are considered undruggable due to an apparent lack of binding proteins in the snapshots we have,” said Gregory R. Bowman, PhD, a professor of Biochemistry and  Biophysics and Bioengineering at Penn and the lead author of the study. “This PocketMiner research and other research like it not only predict druggable pockets in critical protein structures related to cancer but suggest most human proteins likely have druggable pockets, too. It’s a finding that offers hope to those with currently untreatable diseases.”

Read the full story in Penn Medicine News.