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New Institute Advances Lung Disease Research and Clinical Care with Scott Budinger, MD

The launch of the Simpson Querrey Lung Institute for Translational Science(SQLIFTS) aims to expedite the discovery and implementation of innovative lung disease treatments through a patient-centered, bedside-to-bench-to-bedside approach. In this episode, Scott Budinger, MD, the new executive director of the institute, discusses its launch and how it aims to transform lung disease research and clinical care. 

“The goal of this institute is really to develop a two-way street between our very robust high-volume, high-acuity clinical programs at Northwestern Medicine, along with our state-of-the-art and world-recognized research programs in fundamental lung biology, and to try to create some synergies between those two …to really think about ways that we can take information from patients, bring it to the lab, identify therapies, test those therapies in clinical trials and bring them to patient care.” — Scott Budinger, MD  

Episode Notes 

The Simpson Querrey Lung Institute for Translational Science (SQLIFTS) will lead to a new era of lung research, education and patient care, leveraging the transformative power of machine learning and artificial intelligence. 

  • Through a synergistic relationship between Northwestern Medicine's clinical programs and its globally recognized lung biology research programs, SQLIFTS will utilize input from lung disease patients, bring these inputs to the lab, identify therapies, test those therapies in clinical trials, and then bring these therapies back to patient care. 
  • The pace of discovery in the biomedical field is accelerating dramatically due to novel tools and technologies in AI and machine learning, Budinger says. In fact, the genesis of SQLIFTS was based on these very technologies, with a goal of developing an infrastructure based on lung disease first, with the hope of extending the infrastructure across the medical sciences.  
  • Given the extraordinary amount of clinical data that will be generated from this bedside-to-bench-to-bedside approach, a primary goal will be growing data science programs in both machine learning and artificial intelligence. The institute is focusing on recruiting, developing, and training data scientists in biology and clinical medicine to provide insights and develop new tools that can better integrate various kinds of data into clinical contexts. 
  • Machine learning and AI can be applied to a variety of data types including clinical data, multidimensional molecular data like genomic data, and spatial data. However, the integration of these data sets into a clinical context will require further innovation. 
  • Northwestern Medicine is only one of a handful of centers worldwide pioneering this innovative approach. The hope is that the institute will lead the way in developing a prototype for how these tools can be used to advance discovery and develop therapeutics, he says. 
  • Specific areas of research at SQLIFTS include lung aging, lung regeneration, pneumonia, and lung transplantation. Budinger, who specializes in lung aging, describes new research in better understanding how pneumonia is often a gateway into compounding multimorbidity that happens with advancing age. 
  • Prior to the pandemic, investigators had explored an unusual cell type in end-stage pulmonary fibrosis patients using single-cell RNA sequencing. During the COVID-19 outbreak, they observed similar lung complications in patients, and leveraged the same sequencing technologies through a warm autopsy program. These findings led to Northwestern Medicine conducting its first lung transplant on a COVID-19 patient. 
  • Regarding the future of SQLIFTS, Budinger envisions the possibility that every lung disease could have a molecular roadmap detailing disease development and potential treatments, customized to each patient's unique pathway. Using non-invasive procedures, doctors could predict and adjust treatments as necessary, creating a living model that improves care continually.  

Additional Reading 

  • Browse Budinger’s latest research 
  • Find out more about the $25 million gift that made the institute possible 
  • Listen to a past Breakthroughs podcast episode with Budinger  

Recorded on May 18, 2023.


Erin Spain, MS [00:00:10] This is Breakthroughs, a podcast from Northwestern University Feinberg School of Medicine. I'm Erin Spain, host of the show. Mortality rates from lung disease have dramatically increased in recent decades. In response, Northwestern University Feinberg School of Medicine has launched a new initiative, the Simpson Querrey Lung Institute for Translational Science, ushering in a new era of lung research, education and patient care at Northwestern Medicine. Dr. Scott Budinger, chief of Pulmonary and Critical Care in the Department of Medicine, is the new executive director of the Institute. He joins me to discuss the launch of this institute and why it is such a much-needed initiative. Welcome to the show.   

Scott Budinger, MD [00:01:00] Thank you. 

Erin Spain, MS [00:01:01] So this new institute, it really is pioneering a new era of research for patients with lung disease. Tell me about the institute and why its launch is so vital right now in terms of lung health. 

Scott Budinger, MD [00:01:13] So, Erin, as you mentioned, while death rates for many diseases worldwide have been decreasing, death rates from lung disease have actually been increasing and increasing dramatically. So pneumonia was the number one cause of death from an infectious disease before the pandemic. But as we saw during the pandemic, pneumonia due to the SARS-CoV-2 virus caused devastation, a lot of morbidity and mortality across the population, particularly to our older friends, relatives, colleagues. And similarly, there's been a dramatic increase in death rates related to chronic obstructive pulmonary disease, emphysema and chronic bronchitis or some of the names that this goes by. And we've seen the death rates from those increased to now the fourth leading cause of death in the United States. Similarly, lung cancer is the most common cause of cancer related death. And actually deaths from lung cancer outnumber deaths from all of the other cancers combined in both men and women. And so lung diseases are really something that's very important to understand, to study and to develop new therapies for. And the goal of this institute is really to bring discoveries that are being made in the laboratory to the care of patients and to actually bring clinical experiences and clinical procedures that patients are undergoing as part of the treatment for their lung disease to the laboratory so that those discoveries can be accelerated. The goal of this institute is really to develop a two way street between our very robust, high volume, high acuity clinical programs at Northwestern Medicine, along with our really state of the art and world recognized research programs in fundamental lung biology, and to try to create some synergies between the patients and the researchers, along with other researchers at Northwestern University in engineering, drug discovery, to really think about ways that we can take information from patients, bring it to the lab, identify therapies, test those therapies and clinical trials, and bring them to patient care. 

Erin Spain, MS [00:03:12] This really is an ideal place to launch an institute like this. Can you just explain for the listeners what's been happening at Northwestern and Feinberg just in the past few years when it comes to studying and the treatment of lung diseases? There has just been a really extraordinary pace and number of discoveries. Share that with me. 

Scott Budinger, MD [00:03:32] We are really at a place not just in lung diseases, but across medicine, where the pace of discovery is accelerating dramatically. And a big reason for this is the development of really important and novel tools that we can apply to clinical samples that are being obtained as part of care in our clinical programs. For example, if you're a patient with lung cancer or you're a patient with any other lung disease that's undergoing a biopsy procedure, normally the pathologist would look at that biopsy specimen. They would make some annotations to it. It would go into long term storage and no one would look at that again. Or worse, the tissue might be destroyed. What we're facilitating through this institute is to take those samples that we do generate as part of clinical care and bring them to the laboratory. We now have new genomic technologies where we can actually break those tissues into single cells and we can measure all of the transcripts, the RNA molecules that are being made in each of the cells. We have new imaging technologies that let us look at thousands of transcripts and hundreds of proteins in that same specimen. We have tools where we can look at actually all of the metabolites, what are the pathways that those cells require to stay alive, which you can imagine would be very important for a cancer cell or another pathologic cell. And we can determine that all from a tiny thumbnail sized biopsy that you would normally get when you go to see your doctor, your surgeon, your provider. So those technologies were actually part of the genesis of this institute, was to develop an infrastructure starting with lung disease and maybe then generalizing to all diseases across northwestern medicine to actually obtain those samples from patients who want to participate in research. And many, many of our patients come to Northwestern Medicine because of the opportunity to participate in research and to bring those tissues to the laboratory, to investigators who might not be clinicians so that they can use them to inform their drug discovery or their pathway discovery based research. 

Erin Spain, MS [00:05:33] What an incredible amount of data you are going to have. Tell me what is going to happen with that data. Where do you see this all going? 

Scott Budinger, MD [00:05:42] So you're absolutely right. One of the big challenges here is a data science challenge. And part of what we will be doing with this institute is growing our data science programs in both machine learning and artificial intelligence to deal with these large amounts of data. And, of course, none of these data that we generate from that small biopsy of tissue in the laboratory is very useful if it's not connected in some way back to the patient. And this is part of the reason that it's so important that this institute involves both clinician researchers and scientists. A lot of the investments that we're making are in extracting data from the electronic data warehouse. As you know, Northwestern Medicine has made huge investments in an integrated electronic health record across the entire 11 hospital health system. All of those data go into an electronic data warehouse where researchers can access them in a de-identified way to protect patient privacy. And that data can actually tell us about where that biopsy was obtained during the patient's course of disease. So we know where he or she was on their disease journey when those biopsies were obtained. And then what we can do is we can start to take patient journeys that are similar. We can take a patient who had a similar experience, a similar complication. We can group those with other patients and then we can start to say, okay, are the biopsies from those patients similar? And can we use that to understand why this complication happened to this group and not to another group that didn't get that complication? One analogy that I find useful to explain to people what we're trying to do is to think about the history of medicine, where we've learned a whole lot from pathology, from taking tissues from patients with disease, either patients that were alive or who had died, putting them under a microscope, looking at those tissues and trying to figure out what was it that went wrong. And we have learned a lot about medicine and how medicine works from pathology. What we're able to do now is pathology in a way that we as humans can't understand. So we can generate from that same tissue that our historical colleagues for hundreds of years have been looking at. We can now look at it in so many dimensions that our brains can't understand it. But a computer can put those all together and can start to see patterns in those data that aren't necessarily recognizable to us and then can start to use those data to make predictions about what the next therapy would be. Same way that ChatGPT is making a prediction about what the next word you're asking for is right? We can ask what is the next therapy that might be useful for this patient? 

Erin Spain, MS [00:08:21] So as you mentioned, this institute is really embracing machine learning. It's going to be a big part of what you do. Tell me how important that is that you are starting right now studying infrastructure and really moving towards using machine learning in your discoveries. 

Scott Budinger, MD [00:08:38] Machine learning and artificial intelligence are things that have actually been around for quite some time, but they've become very popular within the popular press because of the success of some of these large natural language models like ChatGPT. These same kinds of tools can be applied to any type of data, not just text data. They can be applied to clinical data, which actually often is in the form of texts or tables or numbers, and they can be applied to multi-dimensional molecular data like the genomic data, all the genes in your genomes or all the transcripts in your cell and spatial data where these cells are organized in the tissue. Putting together those different kinds of multidimensional data is going to require new innovations in data science. Right now, we don't have tools to do that. We have really great tools to predict the next word in a sentence, but we don't have great tools to actually integrate these very disparate kinds of data. And in particular, we don't have any tools really to integrate these kinds of data into the clinical course. And so a lot of what we have been focusing on is both recruiting and developing and training data scientists in biology and clinical medicine so that they can really provide insights as they're developing these tools.   

Erin Spain, MS [00:09:53] How unique is this approach? 

Scott Budinger, MD [00:09:55] I think that we are one of a handful of centers worldwide that are doing this. What we're trying to do with this gift is to actually show how this can be done for the world. I imagine that this is going to be something that's going to accelerate exponentially. It's going to be something that we're seeing being done at multiple medical centers around the world. What we really want to do through this institute is to lead the way in demonstrating how this can be done to develop sort of a prototype focusing on lung disease to show how these tools can be used to advance discovery and develop therapeutics.   

Erin Spain, MS [00:10:30] Let's drill into some of the research areas that are going to take place at the institute. There's lung aging, lung regeneration, pneumonia and lung transplantation. Can you just dive into each of those a little bit and tell me about your vision for the research in those areas? 

Scott Budinger, MD [00:10:47] All of these areas are areas that are important to human health, starting with lung aging. Age is the biggest risk factor for the development of acute and chronic lung disease. There's really something about the biology of aging that puts you at increased risk of developing lung diseases as well as many other diseases. And what is it about that biology that we might intervene on to actually make the incidence or mortality from lung disease decrease along with the incidence and mortality of every other disease? So one of the things that we really want to understand from a scientific question is what happens to an aging lung or actually an aging tissue in any organ? What is it that changes? How does the biology of that organ change and how is that related to disease? We had been studying this question even before the pandemic from the perspective of pneumonia. I don't need to explain to the world now that pneumonia actually disproportionately affects older individuals. Many people who recover from pneumonia end up with chronic diseases. They have chronic respiratory disease. They have an increased risk of cardiovascular disease and stroke. They have an increased risk of developing dementia. They have increased risk of skeletal muscle dysfunction that limits mobility, really important problems. What most people don't know is that we knew all of this before the pandemic, so that there was an epidemiologic literature that showed that survivors of pneumonia, particularly elderly survivors of pneumonia, develop all of these complications in the year after pneumonia. And so we've been thinking for a long time about pneumonia and how pneumonia can be a gateway into the compounding multimorbidity that happens with advancing age. And the novel tools that I described to you earlier that we can now apply both to patient samples and to aging animals in the lab, mice and other animals. Now, let us get to some insights into really at a molecular level, what's different about aging? How does cells function during aging? And just as an example of that, prior to the pandemic, we had been working on understanding why the lung failed to repair itself in patients with pulmonary fibrosis. So why some patients who got an injury got better, everything recovered. While other patients that got an injury went on to develop progressive fibrosis in their lungs and actually died or required lung transplantation. We were the first group in the world to apply single cell RNA sequencing to transplant specimens that were coming in from patients in our transplant program with end stage pulmonary fibrosis. We and others used those data to identify this unusual cell population within the lung that emerges only in the diseased lung. You never find it in a normal lung except for a very brief transient window during development. And we were able to recapitulate this in mouse models when the COVID pandemic came and we were taking care of patients with COVID-19 in our intensive care unit. We noticed that many of them were developing diseases that looked a lot like pulmonary fibrosis, and this is by CT scan and the clinical presentation. So with our Ankit Bharat, who's one of the directors of the institute, we started a warm autopsy program in the patients who unfortunately died from COVID-19 in our intensive care unit. When their families would consent, we would obtain a biopsy of that lung tissue at the time of their death. We again use that same single cell RNA sequencing technology is one of these transformative technologies I mentioned earlier, and we applied it to those lung explants where we found this same unusual cell population emerging. That finding was in part what spurred us to perform the first lung transplant for a patient with COVID-19 here at Northwestern Medicine, because we knew those cells only were there in pathology and we had only seen them in end stage pathology in humans. So we really thought that it was unlikely patients would recover from that severe an injury. We subsequently published that work, but at the same time, those experiments led to laboratory experiments where we found a small molecule, a drug that is called ISRIB, it's a drug that was developed by Peter Walter's group at the University of California, San Francisco. And is currently in clinical trials for patients with ALS. When we administered this drug to mice, we were able to accelerate the differentiation of those cells, actually make them finish their differentiation, offering sort of a novel target for therapy that we might use moving forward in the future. Another example related to that is our work in the acute phases of COVID-19, and this is actually gets more to the work in pneumonia that you had asked about. We were interested in understanding why it is that pneumonia disproportionately affects the elderly. And to answer this question, we had developed a project in our intensive care unit, along with our medical director, Rich Wunderink, to really understand what was going on in pneumonia and to understand how the host was responding to a bacteria in the lung or a virus in the lung when they were older compared to when they were younger or when they were getting successful therapy compared to failed therapy. And we leveraged the fact in that study that our clinicians in the intensive care unit sample the alveolar space with a procedure called the Bronchoalveolar Lavage. This basically means that we take essentially a suction tube in a patient that's on a ventilator, put it into the lung with a catheter that has a camera at the end so we can see that we're doing this safely. We scored some saline in suck the sailing back out, and we send that all to the clinical labs in the clinical labs and tell us what bug the patient has so that we can give them the right antibiotics. What we did with support from Kimberly Querrey and Lou Simpson and with support from the NIH, we developed tools to apply all these molecular discovery tools to that small sample of fluid that wasn't used by the clinical lab but would come to our research labs. So we might get a milliliter of this fluid. And from this we could get enormous amounts of data about what was going on with the patient. We had started doing that a couple of years before the COVID-19 pandemic, so we had already collected samples from about 200 patients with severe pneumonia from other pathogens, not SARS-CoV-2, before the pandemic came. Because of that, we were able to, we were actually unique in the world. Literally, I think we have not heard of anybody else that has a similar dataset. We were able to answer the question what was different about SARS-CoV-2 pneumonia compared to pneumonia secondary to other pathogens? Because we actually had that group of patients and we had all these tools in place. And so working with Feinberg Biosafety Committee, we were able to collect samples from more than 200 patients with COVID-19 in our intensive care unit over the course of the pandemic. And we performed a molecular analysis on these patients. We used those data to develop a model of pneumonia of how SARS-CoV-2 was different from other pneumonia, and to explain why it lasted so much longer than other pneumonias. And then we were able to use that model to predict a drug that might be effective. That drug was already in a multi-center clinical trial, which we participated in. That drug was associated with about a 56 percent reduction in 30 day mortality in patients hospitalized with SARS-CoV-2 pneumonia in a phase two randomized controlled trial. So, again, just showing the power of bedside to bench to bedside approach that we're talking about in the institute, the data that I just told you was generated from a very small subset of those patients. We are in the process over the next year of actually generating publishing and making publicly available sequencing data from that entire cohort of patients. And we're hoping that resource that we provide over the next year will be useful when the next strain of SARS-CoV-2 comes along or when we have the next pandemic respiratory virus. 

Erin Spain, MS [00:18:47] What do you see if you're looking in your crystal ball 10 to 15 years from now after the launch of this institute? What do you hope is going to be transpiring? 

Scott Budinger, MD [00:18:57] I would like to see that for every disease that we treat lung disease and others, that we have a molecular roadmap for how that disease develops and how it might be treated. And that we understand that there's lots of different pathways through that molecular map, and each patient will take a slightly different one. And that we're able to use noninvasive procedures may be just a blood draw, right? Maybe something a little more invasive than that to actually predict which pathway the patient is going down and identify the right treatment for her disease and then give them that treatment. And when things go wrong, be able to go back and sample that patient again and say, what was it that went wrong? And that way we will inform the model. So the next patient that comes along will actually have learned from whatever happened to that patient before. And so we actually start to develop a living model that's integrated into our clinical care that's making things better almost automatically. Just by getting your care at Northwestern Medicine, you will be making the care for yourself and for people who might have the same disease in the future better, that's where I'd like to see it go. 

Erin Spain, MS [00:20:17] Thank you so much for explaining this new institute and all of the amazing work that's taking place. I really appreciate your time today. 

Scott Budinger, MD [00:20:26] Thank you. It's been a pleasure.  

Erin Spain, MS [00:20:35] And thanks for listening. And be sure to subscribe to this show on Apple Podcasts or wherever you listen to podcasts and rate and reviews. Also, for medical professionals, this episode of Breakthroughs is available for CME credit. Go to our website Feinberg.Northwestern.Edu and search CME. 

Continuing Medical Education Credit

Physicians who listen to this podcast may claim continuing medical education credit after listening to an episode of this program.

Target Audience

Academic/Research, Multiple specialties

Learning Objectives

At the conclusion of this activity, participants will be able to:

  1. Identify the research interests and initiatives of Feinberg faculty.
  2. Discuss new updates in clinical and translational research.

Accreditation Statement

The Northwestern University Feinberg School of Medicine is accredited by the Accreditation Council for Continuing Medical Education (ACCME) to provide continuing medical education for physicians.

Credit Designation Statement

The Northwestern University Feinberg School of Medicine designates this Enduring Material for a maximum of 0.25 AMA PRA Category 1 Credit(s)™. Physicians should claim only the credit commensurate with the extent of their participation in the activity.

Disclosure Statement

Scott Budinger, MD, has nothing to disclose. Course director, Robert Rosa, MD, has nothing to disclose. Planning committee member, Erin Spain, has nothing to disclose. Feinberg School of Medicine's CME Leadership and Staff have nothing to disclose: Clara J. Schroedl, MD, Medical Director of CME, Melissa Brugger, MD, Assistant Medical Director, Sheryl Corey, Manager of CME, Allison McCollum, Senior Program Coordinator, Katie Daley, Senior Program Coordinator, and Rhea Alexis Banks, Administrative Assistant 2.

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