Stanford Leaders Overhaul Drug Pipeline to End Lab-Clinic Deadlocks

斯坦福学者重塑药物研发流程，打破实验室与临床脱节僵局 除非研究人员从实验台阶段就直接融入商业、监管和计算规划，而非遵循传统的线性开发阶段，否则基础科学发现注定难以落地。 Dean Felsher博士与Joanna Liliental博士探讨了转化医学如何从刻板的线性链条转变为一个一体化、跨学科的生态系统；在该生态中，监管、商业和临床考量必须从一开始就予以解决。他们讨论了人工智能与计算生物学等现代催化剂如何重塑疗法、医疗设备及软件领域的湿实验研究、患者筛选和诊断发现。两位主讲人还详细阐述了斯坦福大学的TRAM和M-TRAM教育框架如何培养团队科学，将基础科学家、临床医生、风险投资人及法律专家连接起来，以打破机构壁垒并指导下一代生命科学领军人才。 转化医学正在迅速摆脱线性的“从实验台到病床”模式，转向一种必须在最早研发阶段就同步解决监管、临床和商业限制的一体化模式。 (6:40) 人工智能与计算生物学已成为转化研究的核心驱动力，目前M-TRAM同期项目中约有一半已融入计算方法。 (13:53) 转化应用已远超小分子疗法的范畴，全面涵盖了诊断技术、免疫疗法、疫苗、生物工程设备以及临床级软件平台。 (36:02) 跨学科教育与团队科学通过建立实验室科学家、临床医生、数据科学家和企业高管之间的互助指导网络，化解了繁重基础研究与临床诊疗之间的运作张力。 (33:58)

Stanford professors Dean Felsher and Joanna Lilienthal argue that translational medicine must move beyond rigid, sequential research models toward an integrated, team-based ecosystem where clinical, commercial, and computational realities inform discovery from the outset. Dissolving the Sequential Bench-to-Bedside Pipeline (6:40) Historically, translational research operated in three sequential phases: laboratory discovery, clinical trial evaluation, and commercialization. Lilienthal highlights that these historical boundaries are dissolving because successful translation requires scientists to confront downstream considerations—including intellectual property, regulatory clearance, scalable manufacturing, and clinical adoption—much earlier in the research cycle. Without addressing these requirements at the outset, basic scientific breakthroughs risk failing long before reaching patients. Felsher illustrates this shift using his work on the MYC oncogene. Although the foundational discovery of MYC earned J. Michael Bishop and Harold Varmus a Nobel Prize decades ago, converting that basic biological insight into an effective therapeutic requires simultaneously solving synthetic chemistry challenges, gathering clinician feedback on targeted indications, and designing regulatory pathways. Translational training now aims to equip researchers to hold the entire arc from molecular mechanism to health system implementation in mind simultaneously. Computational Advances and Cross-Disciplinary Cross-Pollination (13:53) Technological developments in artificial intelligence and computational biology have fundamentally accelerated translational timelines. Lilienthal observes that while computational modeling was an occasional side project five to seven years ago, roughly 50 percent of incoming projects in Stanford's Master's in Translational Research and Applied Medicine (M-TRAM) program now incorporate AI and computational methods to augment wet-lab chemistry. Furthermore, because biological disease mechanisms are finite while analytical and therapeutic tools are virtually infinite, translational progress relies on connecting researchers across disparate fields. Felsher notes that cross-pollinations—such as pairing an immunologist with a psychiatrist to examine inflammation-driven mental disorders, or linking an oncologist with a cardiologist to repurpose a cardiovascular mechanism—routinely solve impasses that specialized departmental silos overlook. Broadening Translation Beyond Traditional Drug Modalities (36:02) While translational programs initially focused almost exclusively on conventional therapeutics, Lilienthal and Felsher emphasize that the field now spans the full spectrum of medical intervention. Modern translational pipelines encompass small molecules, biologics, cancer vaccines, immunomodulatory agents, diagnostics, bioengineered medical devices, and clinical-grade computational software. As data science and software engineering increasingly intersect with patient care, computer scientists and engineers face the same translational hurdles as drug developers. They must design tools that meet clinical workflow requirements and satisfy regulatory validation standards, broadening the translational discipline into an interdisciplinary platform across multiple medical modalities. Resolving Operational Tensions Through Team Science (33:58) The push toward translational commercialization often creates practical friction with curiosity-driven basic science. Felsher emphasizes that this dilemma is primarily logistical rather than philosophical: conducting rigorous laboratory science, managing clinical patient care, and launching a regulated biotechnology company each require exhausting, full-time operational commitments that no single investigator can realistically manage alone. Rather than forcing individual basic scientists to become entrepreneurs, the TRAM model relies on team science and reciprocal mentorship. In this structure, laboratory scientists, clinicians, regulatory specialists, and venture professionals share expertise. Classrooms and collaborative projects allow laboratory investigators to spot commercial and regulatory blind spots early, while business and clinical professionals gain an accurate understanding of the underlying biology without derailing fundamental scientific inquiry. Felsher and Lilienthal observe that while multidisciplinary ecosystems bridge the gap between laboratory benches and clinical adoption, sustaining them requires overcoming the logistical strain of competing professional priorities and continuously aligning academic, clinical, and commercial incentives.

[2:54] Dean Felsher: I was trained as a medical doctor and a scientist, and I found that it was very difficult sometimes for the two different groups of individuals to talk together in tackling a problem. So scientists in the laboratory sometimes found it hard to know what really were the clinical things that were needed and didn't even know if some science they discovered was useful, and clinicians, faced with the challenge of treating and taking care of people, sometimes didn't know well how to go about actually doing any science, or taking science, or even knowing what science was available. [2:54] Joanna Liliental: a great discovery can fail because some of those questions weren't asked early enough. [6:40] Joanna Liliental: We used to think more sequentially about discovery, then development, then commercialization, but what really strikes me as the biggest change I have seen is that you really need to be thinking about those downstream questions much earlier. For instance, the AI and computational approaches are changing discovery. Biomarkers and patient selection are becoming more and more important in development, as well as the commercial and regulatory considerations really influence what we, as scientists, do very early on. [11:44] Dean Felsher: right in front of your face. [23:41] Joanna Liliental: improving the patient's life [26:25] Dean Felsher: Most outstanding programs, the intention is to create a network of individuals who will be leaders, who will be mutually supportive and feel a common identity. [26:25] Joanna Liliental: really large family of leaders or like-minded people who really speak the same language. [33:58] Dean Felsher: There is a tension, which is part of the reason that Joanna and I built the program. It's very, very time consuming to take care of people clinically. It's very, very time consuming to do basic research. It's very, very time-consuming to try to run a company to develop a product. There can be a practical tension of just not having enough time to navigate being able to engage. [39:41] Joanna Liliental: change the translational medicine mindset [44:37] Dean Felsher: didn't even know what we didn't know. [44:37] Dean Felsher: feed forward and feed backward [48:34] Dean Felsher: truly remarkable

[0:09] Welcome, everyone. [0:11] Thank you so much for joining us today [0:13] for this webinar on the future of translational research. [0:17] It's my pleasure to be joined today by Doctors Dean Felsher [0:21] and Joanna Lilienthal. [0:23] Before we get started, I just wanted [0:25] to walk through a few housekeeping items. [0:29] So first, you should see in the interface [0:32] that you're looking at, there's a little Q&A button [0:34] on the left-hand side. [0:36] If you have any questions at any time during the session [0:40] about anything, feel free to put those in the Q&A, [0:43] we'll answer as many of them as we [0:45] can at the end of the session. [0:48] I have some colleagues who are also online, [0:50] and they may be able to answer some of those questions [0:52] as they come in. [0:53] And then again, at the end, we'll get to as many as we can. [0:56] We probably won't be able to get to every question, [0:58] but we'll do it the best that we can. [1:00] Additionally, if you have to leave or you have a colleague, [1:03] you really love the webinar and you [1:05] have a colleague who would enjoy it, [1:07] we will be sending a recording of the session [1:10] out in about a week or two weeks. [1:12] So at that point, you should be able to share that recording [1:15] with anybody who wanted to. [1:16] Or if you have to jump off in 30 or 40 minutes [1:18] and you miss the very end, you can jump back on [1:20] and watch the end of it. [1:23] With that, it's my pleasure, as I [1:25] said, to welcome Dean Felsher and Joanna Lilienthal. [1:28] So today, we're going to be talking [1:30] about the future of translational research. [1:33] And what that means is where we're going to begin. [1:37] And I can't think of two better speakers to be with us on this. [1:39] So Dr Dean Felsher is an MD And PhD, [1:42] is a professor of medicine oncology at Stanford University [1:45] School of Medicine. [1:46] And he's the director of the Translational Research [1:49] and Applied Medicine Program, or TRAM, which he's led since 2011. [1:54] His own laboratory investigates how oncogenes [1:56] initiate and sustain cancer. [1:58] And he has pioneered model systems [2:00] showing that inactivating a single oncogene, such as MYC, [2:03] can be sufficient to reverse tumor growth, a concept known [2:06] as oncogene addiction. [2:07] So he's going to be talking a little bit [2:09] about his own experience, both as an educator who's [2:11] someone who's trying to lead researchers through [2:14] and students and clinicians through this process [2:16] of translational research and his own practice. [2:20] Joanna Lilienthal, a PhD, is the executive director [2:24] of Stanford's Masters in Translational Research [2:26] and Applied Medicine. [2:27] She the director of the Translational Application [2:30] Service Center and the associate director [2:31] of Translational Research and Applied Medicine program. [2:34] And since 2011, she has worked alongside Dr. Dean Felsher, [2:39] entering researchers as they move scientific findings [2:42] from the lab into clinical application, [2:44] including biomarker research for early cancer detection. [2:47] So welcome, Dean Felsher and Joanna Lilienthal. [2:52] It's so great to have you here. [2:54] I want to start with just a very high-level question. [2:58] Dr. Felsher, can you tell us what is translational research? [3:01] Let's just start at a very high level. [3:04] I'm delighted to answer that question. [3:07] So at the very highest level, translational research [3:12] is what we describe when you take an idea discovered [3:16] in the laboratory and you make it relevant and applicable [3:21] to something in the real world, like a treatment, a therapeutic, [3:27] or a diagnostic. [3:29] And the process of making that actual scientific, basic science [3:36] observation to something real and tangible and useful, [3:40] requires translation, and, thus, the way we [3:43] describe it as process of translational research. [3:49] So following up on that, and this [3:51] is directed at either of you, what are the challenges? [3:54] So we're moving it from the research bench [3:57] all the way into the clinic to an actual therapy [3:59] that's being used. [4:01] What are typically some of the challenges or stages [4:04] that you have to go through moving a drug [4:07] or therapy from that researchers bench to the patient's bedside? [4:12] Well, I'd like to start answering the question. [4:14] But like everything we've done about TRAM, [4:16] it's been a team effort with Dr. Lilienthal. [4:19] We've been doing this together now for 16 years. [4:22] We're scientific siblings basically in this. [4:25] And I would say, that the part I brought to this [4:29] was, I was trained as a medical doctor and a scientist, [4:35] and I found that it was very difficult sometimes for the two [4:40] different groups of individuals to talk together [4:44] in tackling a problem. [4:45] So scientists in the laboratory sometimes [4:48] found it hard to know what really [4:50] were the clinical things that were needed [4:53] and didn't even know if some science they discovered [4:55] was useful, and clinicians, faced [4:59] with the challenge of treating and taking care of people, [5:01] sometimes didn't know well how to go about actually doing [5:07] any science, or taking science, or even knowing [5:09] what science was available. [5:11] So I'd say the first challenge is just [5:13] getting the different kinds and groups of people [5:17] who are involved that are required to make something [5:19] like translational research work together, [5:21] and a big part of actualizing this, [5:24] is what I then recruited, Joanna Lilienthal, Dr. Lilienthal, [5:29] to work together with me. [5:33] I know she has lots of thoughts and examples [5:36] of how we've thought about together as a team to overcome [5:41] some of the barriers. [5:42] Dr. Lilienthal? [5:45] Yeah, very well said. [5:47] So to me, one of the biggest challenges is that scientists, [5:51] and I was trained as a scientist myself, [5:55] they're often extraordinarily well-trained [5:57] in their own discipline. [6:00] But drug development really requires more than science. [6:04] It requires many different disciplines to come together. [6:09] So you need the science, but you also [6:11] need to understand the clinical need, the manufacturing, the IP, [6:16] the commercialization. [6:18] And most importantly, each of us needs to enter [AUDIO OUT]. [6:26] I rephrase what Dean said. [6:29] But more specifically, I just wanted [6:31] to emphasize that a great discovery can [6:34] fail because some of those questions [6:36] weren't asked early enough. [6:40] That's wonderful. [6:41] So coming back again at a high level [6:43] here, if I were to break it out, it [6:47] seems like there are three core stages. [6:49] And I'm sure there's a lot more nuance to that. [6:50] There's the research that's happening [6:52] by the scientists in the lab, coming up [6:55] with novel therapies, novel drugs, novel treatments. [6:59] And then there's this middle stage, which is partly, [7:02] the regulatory stage, which is moving these therapies [7:07] through clinical trials for approval. [7:09] And then there's that final stage where you had said, [7:12] this is bringing it to the clinics themselves. [7:14] This is helping commercialize, get that drug or therapy [7:18] out into the market. [7:19] So today, we're talking about the future [7:21] of this translational research. [7:23] So where, Dr. Lilienthal, have you [7:26] seen as you've worked on this over the past 15 years [7:30] as part of TRAM, and even before that, in your own work, [7:33] where have you seen the biggest changes in these three stages? [7:36] And what are the kinds of changes that you've seen? [7:40] So it's very interesting that you describe those sequentially, [7:44] because to me, the biggest change is [7:47] that the boundaries between these stages are disappearing. [7:51] We used to think more sequentially about discovery [7:56] than development, than commercialization, [7:58] but what really strikes me as the biggest change I have seen [8:04] is that you really need to be thinking [8:07] about those downstream questions much earlier. [8:11] For instance, the AI and computational approaches [8:14] are changing discovery. [8:17] Biomarkers and patient selection are [8:20] becoming more and more important in development, as well [8:25] as the commercial and regulatory considerations really [8:30] influence, what we, as scientists, do very early on. [8:37] The people who are listening now, who are entering the field, [8:41] need to understand the whole ecosystem, [8:44] even if they, ultimately, specialize [8:47] in one or the other part. [8:51] Dr. Felsher, what would you add to that? [8:55] Well, I think Joanne explained it outstandingly [8:58] as Joanne always does. [9:01] What I would add is to give an example of where [9:05] work that we've done together has enabled [9:07] such processes to occur. [9:10] For example, I work on a gene, the MYC oncogene, [9:14] and it's relatively obscure to people who are not [9:16] cancer people, but it turns out, it's [9:17] the cancer gene involved in most of human cancer. [9:23] The reality is that the science about knowing MYC [9:26] is responsive Cancers existed for literally decades. [9:30] Its discovery was part that won a Nobel Prize for Mike [9:34] Bishop and Harold Varmus. [9:36] Mike was one of my former mentors. [9:39] The reality is that right now, the idea [9:44] of taking the idea that this is a fulcrum of cancer, that's [9:48] one of the key nodal points of cancer [9:50] and translating, it's exactly as Joanna described, [9:54] solving the riddle of treating cancer [9:57] involves not just understanding the science, [9:59] but at the same time, having an idea. [10:02] Well, what is the clinical circumstance [10:04] where it would make sense? [10:05] And knowing chemistry and some of the tricks that [10:08] have existed to deal with trying to figure out [10:11] how to target such a gene. [10:14] In our program, we are even talking to our students. [10:19] Joanne and I were talking this morning [10:20] about how taking advantage of world class chemistry going on [10:25] at Stanford, taking advantage of insights from our clinicians [10:29] and taking advantage of science discovered [10:31] by me and other colleagues at Stanford. [10:34] We can enable our students to actually tackle the problem. [10:37] And like Joanna said, being aware [10:39] of all the steps at the same time. [10:42] You beautifully summarized the whole translational arc, [10:45] but it's hard for you to realize because you understand it [10:49] so well that when Joanna and I first trained, [10:52] nobody was educated in each step of translation, [10:57] we were usually trained, like, Joanne and I both [10:59] trained at UCLA. [11:00] We were trained in a very specific scientific domain [11:04] in a specific part of the arc of translation. [11:08] Whereas, now, we don't think about problems that way [11:11] in translational research. [11:12] Translational research is aware of all aspects. [11:16] They are aware of the kinds of tools that can [11:20] address scientific questions. [11:22] They're aware of issues in terms of how [11:24] to think about proving clinically something would work, [11:27] and they're aware of what would be required to get approval [11:31] and to get adoption. [11:32] All of these things need to be aspects of what you know, even, [11:36] as Joanna said, if you're an expert in a specific aspect. [11:40] That's wonderful. [11:41] I'd love to dig. [11:42] So I mean, it sounds actually one of the major things that [11:44] has just changed in translational research [11:46] is just the field of translational research. [11:48] It's this greater awareness that you cannot work in these sort [11:52] of siloed fields. [11:53] You cannot be a scientist just working on a novel treatment, [11:56] you also have to have insight into the clinical trial phase, [12:01] into what it takes to actually implement that in a hospital [12:04] or in a clinical setting, or how to even sell it. [12:07] What are those aspects? [12:09] So it sounds like that's a major part of it [12:11] is just this awareness that is obviously part of it. [12:20] Exactly. [12:21] And another aspect of this is exactly why I recruited Joanna [12:26] many years ago, is that Joanna, in her role, [12:30] Dr. Lilienthal facilitates across areas of science [12:34] because sometimes the solution in cancer [12:36] will actually lead to a solution in another disease. [12:41] So there has to be a more general understanding. [12:45] And if you're siloed, you could miss something right [12:48] in front of your face. [12:49] And many times, I've heard Joanna bring together [12:52] somebody from psychiatry and somebody [12:55] who's working in immunology to come up with an idea that [12:59] can lead to a treatment for a psychiatric disorder that [13:01] may have been thought of something that was involved [13:03] in the immune system or inflammation, [13:06] or a cardiologist realizing something they've discovered [13:09] would be useful in cancer. [13:11] So it's this ability to think across basic and clinical. [13:14] But it's also the ability, like you said, holistically, [13:18] across the areas of different areas of science [13:21] and having an understanding of what would be a solution, most [13:24] importantly, to have enough colleagues [13:26] you know across the areas that you can get help [13:31] at different steps that you may not have the most expertise in. [13:35] So I want to come back to that, because I think from what [13:37] I understand, that's a lot of what the TRAM is doing here [13:41] at Stanford, and this unique spot, that's a university-- [13:45] and well, not totally unique. [13:46] There are lots of universities with hospitals or vice-versa. [13:49] But I want to maybe dig in a little bit. [13:53] Dr. Lilienthal, if you can talk a little bit more about, [13:56] you had mentioned maybe some recent scientific advances that [14:00] had also changed this process. [14:03] So you mentioned biomarker research and patient selection. [14:06] And also, I think what's probably [14:08] on everybody's mind is some of this stuff around the advances [14:11] in data science. [14:12] I mean, here we are at Stanford. [14:14] And obviously, artificial intelligence and maybe more [14:17] broadly speaking, data science, this ability [14:19] to look at a lot of data when coming up [14:21] with whether that's a novel solutions [14:23] or perhaps in trying to understand [14:26] the clinical outcomes, et cetera. [14:28] So I'd love to hear a little bit more, [14:30] if you have some more insights to share [14:32] and what you've seen in those scientific advances [14:34] and how they've been impacting or influencing [14:37] these three stages. [14:41] Definitely, the biggest change, we have seen over, I would say, [14:46] even the last five years, is the AI and computational biology [14:50] and how it drives the discoveries [14:54] in probably every discipline of medicine, [15:00] not to replace medicinal chemistry. [15:04] But there are so many new discoveries [15:07] that make the medicinal chemistries science more robust. [15:15] And we see a lot of students coming to this area, [15:21] for instance, even five, seven years ago, [15:26] there was maybe one side project. [15:29] Right now, half of our cohort is trying [15:32] to solve the problem using AI and computational biology. [15:35] So that's probably the strongest example. [15:38] But overall, just to put it at a higher level, [15:41] I think, what we do at TRAM and how [15:45] we address that challenge is that sometimes the most [15:48] valuable thing we can do is simply [15:50] connect the right people who, otherwise, might never [15:55] have found each other. [15:58] And really seeing those collaborations, [16:01] bringing in a cardiologist and a computational biology person [16:07] who can write a code and who can use AI platforms for diagnosis [16:13] versus someone in infectious disease. [16:15] So basically, we can think of mechanisms as being finite, [16:23] but ways to address it are infinite. [16:27] So collaborations can become very interesting [16:31] because it doesn't really matter which disease area you're [16:35] trying to solve the problem. [16:37] One disease area thought can affect another disease area. [16:43] And we can all learn from each other. [16:46] Dr. Felsher, is there anything you would add to that, [16:48] in terms of some of the specific science or advances [16:51] that you're really seeing impact what you're [16:54] doing in interesting ways? [16:57] Well, only to point out, I think Joanna summarized it [17:00] beautifully. [17:01] I would only point out that we're [17:04] incredibly sensitive in the TRAM center [17:08] to what are the newest areas, and we made our program really [17:15] organically evolve with the students [17:17] and Fellows and faculty. [17:21] And now, as you realize, we're going on 20 years of experience [17:27] in doing this, and the program is definitely much more [17:31] than Joanna and I. Always the intention was exactly [17:35] to take leverage off of the brilliance at Stanford [17:38] and the brilliance of the people that we bring into our program. [17:43] It's all that Joanna described. [17:45] But Joanna and I, just before getting started, [17:47] were talking about students that were going to join our program [17:50] and how excited we were, how much talent they brought. [17:53] So it's important to realize that that's [17:55] a very real part of the educational experience [17:58] in our program is that we incorporate the students who [18:02] come, people who ask us questions, [18:04] people who participate in any way. [18:06] And we are constantly evolving the program, [18:09] just like translational research is evolving. [18:12] So we've added new courses. [18:14] We're adding, we keep adding other elements. [18:18] We started mainly with therapeutics. [18:20] We're adding diagnostics. [18:23] We've added aspects that enable people to think about vaccine [18:27] therapy, immune therapy. [18:29] All of these were based on what we appreciated [18:32] were new aspects of program. [18:33] And we're adding formalized elements [18:35] for mentorship and training in AI, as Joanna has brought up. [18:42] In the big picture, we appreciate this. [18:44] But we're also fine tuning and making the program a dynamic, [18:50] just as the field of biotechnology is very dynamic. [18:53] It's also important that we're in an epicenter of success [18:57] in biotech, and many of our advisors [18:59] are successful leaders in some of the most exciting companies. [19:03] We directly collaborate and interact with these individuals. [19:08] And so we're very aware of the pulse of what it that is [19:10] being successful and exciting. [19:12] And we bring that into our program. [19:14] We bring that into all of our programs, into the education. [19:18] So the speakers that we invite are not just Stanford faculty. [19:21] Of course, we have world class faculty, but also [19:23] people involving the entire-- [19:26] I think I like the way Joanna described, the whole ecosystem. [19:30] The whole ecosystem involved these individuals. [19:35] So I want to then maybe transition-- [19:37] Just to add-- [19:37] Oh, go for it. [19:38] Yes. [19:38] Yes. [19:39] I just wanted to add one more aspect of that. [19:42] So yes, we have added the new courses. [19:44] So that students are exposed to those emerging technologies. [19:48] But one other thing that we have added strategically is we [19:52] have greatly expanded the experiential component. [19:57] So students can now pursue individual projects. [20:02] We call them TREP, where they work individually [20:05] in labs of a faculty mentor. [20:08] But they can also work in team projects [20:13] where multidisciplinary teams work together [20:16] on real translational challenges. [20:19] And that team experience is particularly important, [20:23] because that is exactly how drug development actually happens. [20:30] Wonderful. [20:31] Joanna, I'm going to just mute you for a second. [20:33] Oh, there we go. [20:33] Perfect. [20:34] Yes. [20:36] That's really fascinating. [20:39] You're already transitioning talking about, [20:41] and I guess that's part of, it's hard to disentangle these things [20:44] because you created TRAM or you helped create TRAM here [20:47] at Stanford, exactly to address these kinds of problems. [20:50] So let's again, starting at a high level [20:52] for those who are joining us, who [20:54] maybe are a data scientist or an AI researcher, or maybe [20:57] they're a doctor at a hospital, outside of the enrolling [21:04] in a specific program, what should they be thinking about [21:06] as they try to think about how to get more involved. [21:09] Or say, I'm a clinician, and I want [21:11] to be more aware of the science, or I'm a data scientist, [21:16] maybe I'm a data scientist. [21:18] And I think, why do I need to know? [21:21] I'm just looking at it. [21:22] I'm just crunching data. [21:23] Why do I need to know the end stage [21:25] or how it will work in a clinical trial? [21:26] So can you maybe back up and pitch it to those [21:29] specific people. [21:30] Why do they need to think about these bigger things? [21:32] Why is it so important for them to be thinking about the bigger [21:35] picture, and the whole ecosystem, as opposed [21:38] to their one slice? [21:41] Dr. Felsher, maybe, I'll hand it off to you. [21:43] Sure. [21:44] So I'll start. [21:45] But I think we both thought about this deeply. [21:49] So one very important reason for there [21:54] to be an interest, pretty much everybody [21:56] who would be in the audience, is that there's [22:00] such a dramatic change in the acceleration at which we [22:05] can translate findings because of advances in science [22:10] and bioinformatics and the information that we have. [22:16] It's a real desire, whether you're [22:17] a scientist, or an engineer, or a CEO, or a medical doctor, [22:24] or a basic scientist to not feel that you've gotten behind [22:27] and that you're not aware of the state [22:29] of the art across the range of what is translational science. [22:32] If you're a medical doctor, diagnostics [22:35] and therapeutic decision-making are changing before your eyes. [22:39] In our education programs, you get exposed to, [22:43] how is it changing? [22:44] What are people doing? [22:45] How are they thinking about health care? [22:47] How are they thinking about delivery of health care? [22:49] If you're a basic scientist, working in an area [22:52] that you know has translational potential, [22:55] it can help you engage in thinking, well, [22:57] what is it that I'm doing that could have high value? [23:00] And how would I go about finding who [23:03] to talk to in the clinical world or the business world [23:07] to recognize that value? [23:09] If you are a business person or an investor, [23:14] one challenge is having access in an organized way [23:19] to the summation of the state-of-the-art knowledge. [23:22] In many cases, I've interacted with people who are already [23:25] in biotech doing translational science, [23:27] but it's hard to keep up with the actual science. [23:31] It's like the language of the science is challenging. [23:34] So those are some examples of reasons why, I think, [23:38] that the curriculum and education programs, [23:41] we built would be of interest to not only people who are earlier [23:45] in their stage of career, and they want to figure out what [23:48] they want to do, but people who have been already engaged [23:50] in some aspect of the medical establishment and want to buff [23:57] up their ability to understand, what is the state-of-the-art [23:59] in the full range of going from idea to commercialization? [24:04] What are the latest thinking of how this happens? [24:07] What are people doing? [24:08] What are the most exciting ideas and applications [24:12] to develop therapeutics, diagnostics, vaccines, [24:16] immune modulatory agents, bioengineer medical devices. [24:24] Dr Lilienthal, maybe just digging into that a little bit [24:28] more, let's go into some of the specific programs [24:30] that you're doing within TRAM that help address this. [24:34] You've talked a lot about your educational programs, [24:36] but there's much more than just the educational programs. [24:39] So could you give us the broader view of this center [24:41] and how it have envisioned it again, [24:44] to help address what it sounds like the core issue [24:47] is, and the core change is just facilitating these conversations [24:51] between practitioners of different stages [24:54] in the process of bringing a discovery to the clinic. [25:01] Absolutely. [25:04] One thing I would emphasize is that TRAM is not simply [25:07] an educational program. [25:10] I already refer to this as an ecosystem. [25:13] It's an ecosystem around translational medicine. [25:16] So we bring together clinicians, scientists, industry experts, [25:21] entrepreneurs, and of course learners. [25:24] And then we support projects, create collaborations, [25:28] connect people with expertise, as well as provide [25:33] education and mentorship. [25:35] So the common thread is helping promising science move forward [25:40] and actually improve patient lives. [25:43] It's not just creating new applied therapeutics diagnostic. [25:52] The common theme is actually making a difference [25:55] in the patient life. [25:56] So that's basically ties in together. [26:02] It's not just the classes. [26:05] It's the entire ecosystem, it's all the horizontal learning. [26:11] It is the learning from experts. [26:14] It is making the people meet each other, people, [26:19] who are the stakeholders in this big equation. [26:25] And Dr. Felsher, maybe we could then expand into that. [26:29] And I really like that concept. [26:30] It's not about, I've laid out this arc, [26:32] but fundamentally the mission of this is a lot of things are [26:35] is actually improving the patient's life. [26:36] I mean, that is the end goal. [26:38] We want to bring something from the lab [26:40] to people to improve their lives, [26:43] to help cure something, to help treat something. [26:46] So thinking about that, can you talk [26:49] through the specific educational programs? [26:51] So you have courses. [26:53] You have a master's degree. [26:56] I think a one-year master's degree, as well as [26:58] the individual courses that are part of a graduate certificate [27:01] that again, a data scientist in the area who's not been admitted [27:05] to Stanford can be approved to take those courses [27:08] and earn a graduate certificate. [27:09] So can you talk through what are those courses? [27:12] How have you structured them to address this problem? [27:15] And I guess I already have one follow-up [27:17] question that I'm going to embed in there already. [27:22] It sounds like there are two aspects to this challenge. [27:24] One is you need to facilitate and bring people together [27:28] to constantly be learning and listening to your colleagues? [27:31] Now that seems like an ongoing process. [27:33] And so an educational program can't. [27:35] They can do it that once, but they [27:36] can't do it, unless they're retaking the courses all [27:40] the time. [27:41] So I guess my question is my follow-up question embedded [27:43] in there is the courses themselves will convene these [27:47] practitioners and give you the state-of-the-art of what is [27:50] happening across all these fields. [27:52] How do you also equip people, therefore, [27:54] to then go out in the field and continue that education? [27:57] Is it just awareness of those different aspects? [27:59] Are there certain skills you're imparting [28:01] that allow the data scientists to talk [28:04] to doctors and the doctors to talk to data scientists? [28:07] That's a big loaded question. [28:08] So let me pass it back to you. [28:10] Well, let me answer the two parts of the question, [28:14] big picture. [28:14] And then I'll go into more specific details [28:16] about the actual structure of the curriculum. [28:19] So in big picture, the curriculum, in some sense, [28:22] gives from beginning, middle, end, [28:25] the arc of how to do translation with lectures that [28:30] go all the way from well, how do you form a scientific question, [28:34] to how do you test that scientific question, how do you [28:37] do a clinical study? [28:38] How do you get the capital? [28:42] Make sure that you have a patent and protection [28:45] of intellectual property and commercialize and get [28:47] regulatory approval. [28:48] So there literally is coursework that takes you [28:51] through the entire sequence. [28:53] That's the big picture. [28:55] In terms of the second question, so we use the word "ecosystem." [28:59] And as Joanna said, we often talk [29:01] about horizontal and vertical learning [29:04] and ecosystem in terms of creating environment [29:06] at Stanford, but it's bigger than that. [29:09] We have trained hundreds of people. [29:11] We have hundreds of faculty who've [29:12] been associated with the program. [29:14] We have literally dozens of advisors [29:18] that are global advisors from Stanford [29:20] and several dozen advisors that are from industry. [29:24] Our network is huge. [29:26] The students who are part of our programs [29:29] maintain part of that network. [29:32] And we actively keep them as part of the whole system. [29:39] So when people graduate from any of our programs, [29:43] they often come back to us. [29:45] Many of the people are lecturers, [29:47] who are students, or are advisors who once were students. [29:52] Or faculty come back and become part of the global advisors. [29:58] Former students know each other. [30:00] And they help each other build programs, get jobs, [30:05] serve as advisors. [30:08] So the program has an aspect of it [30:10] that is larger than just simply Joanne [30:14] and I in the leadership or simply the collection [30:17] of lectures. [30:21] Most outstanding programs, the intention [30:25] is to create a network of individuals [30:28] who will be leaders, who will be mutually supportive [30:31] and feel a common identity. [30:33] Now, the curriculum involves a series [30:36] of classes that lead through each step in translation, [30:40] and they're very specific didactic, [30:43] such as chemistry or patent law or vaccine development. [30:52] So there's specific classes. [30:53] And then there are also we keep expanding the curriculum [30:57] to include other areas that we realize students have [30:59] of interest, but they're very deliberate coursework [31:03] on specific areas of medical translation [31:07] that we think are part of the core fabric of what everybody [31:11] needs to have some knowledge about in terms of everybody [31:15] needs to have some knowledge of how to design a clinical study. [31:19] Regardless of whether or not you do [31:20] are going to be a clinical researcher, if you're [31:23] going to do translation, you have to have the concept of, [31:25] what is a clinical study? [31:27] What are the basics of designing clinical study? [31:30] And similarly, in specific domains of science, [31:33] having some understanding of well, [31:34] how does one find a small molecule [31:38] and know that it has some activity. [31:41] How do you make an assay to detect that? [31:44] And then how does one get regulatory approval? [31:46] What are the steps for getting an ID for the FDA? [31:50] What is it that is required? [31:52] What are some of the medical affairs [31:54] issues that are required of a company [31:57] to remain in compliance with a regulation? [32:01] So there's a lot of granularity, but there's also [32:05] a lot of big picture, and the intention [32:08] is for people to feel comfortable with the full range. [32:11] But it's very important that the learning does not [32:13] end with the program. [32:15] You're part of a world class university [32:18] and you're connected with like-minded, very talented [32:23] individuals, who are also part of the program. [32:25] And you become part of that. [32:27] As Joanna described, we're creating an ecosystem. [32:32] The ecosystem includes the students [32:33] who are part of the program. [32:37] And to add to this, for me, the goal [32:40] simply isn't just to teach the students in the classroom. [32:45] It's to give people a framework to understand the field that [32:51] will continue to change throughout their careers, [32:55] to give them a different perspective. [32:59] And many of our M-TRAM graduates, [33:03] as well as TRAM scholars, go on to, either academic positions [33:11] as faculty or leaders in biotech and pharma, [33:17] and they continue to collaborate with us. [33:23] So they invite us for site visits to their companies. [33:29] They hire our more recent graduates. [33:33] They provide career development to our current students [33:39] and more recent graduates. [33:40] So it becomes a large ecosystem, of course, but a really large [33:46] family of leaders or like-minded people who [33:51] really speak the same language. [33:53] It's not just the classroom. [33:55] It's much more than that. [33:58] That's wonderful. [33:59] We had a great question. [34:00] And I think is worth asking now. [34:03] And it's just this there's is there [34:05] a tension between, I guess, basic science [34:08] and applied science in this case? [34:11] And in fact, from what I'm hearing from you, [34:13] you're also bringing in people who are doing basic science [34:15] and finding the applied research, the applied mechanism. [34:18] So I guess, do you see that as a basic tension. [34:21] Do you have concerns about of too much of a focus or too much [34:25] knowledge of these different stages, [34:27] maybe crowding out something that's just basic science [34:29] research that maybe doesn't seem to have any applied aspect now, [34:33] maybe will down the road or maybe won't. [34:37] What is that tension? [34:39] Or is there a tension there? [34:41] There is a tension, which is part of the reason [34:44] that Joanne and I built the program. [34:47] It's very, very time consuming to take [34:49] care of people clinically. [34:51] It's very, very time consuming to do basic research. [34:53] It's very, very time-consuming to try to run a company [34:57] to develop a product. [34:59] There can be a practical tension of just not having enough time [35:04] to navigate being able to engage. [35:10] And what Joanna and I have done is create an environment [35:12] that encourages this to happen. [35:14] And people, who, in an organized way, are excited about this. [35:21] And on the other side, the reality [35:24] is that there's daily examples of major, major breakthroughs [35:29] that are being made. [35:33] I don't want to promote any one particular company, [35:35] but many of the companies that are in the news, [35:38] in breakthroughs, in translational research, [35:40] include science that we provide training and guidance regarding. [35:50] It's very common because there are [35:53] many examples of breakthroughs happening translationally [35:56] in the Bay area. [35:58] And our goal is not to force people to engage, [36:02] but what we do is create an environment, makes it very easy [36:05] and reduces the tension. [36:06] It makes it easier for an individual with a basic science [36:11] background to network, connect with somebody [36:13] with a clinical background. [36:14] It makes it easier for somebody with a clinical background [36:17] to find a scientist or find somebody [36:19] with business experience. [36:21] Another theme that we haven't talked about, but we've implied [36:25] is a big aspect, and this is a major aspect [36:28] that Joanna's championed, was to take a team approach. [36:33] There are a lot of what we do is encouraging people [36:36] to work as teams. [36:37] Recognizing that that's often the most effective way of being [36:41] successful is to bring together people [36:43] who appreciate each other. [36:45] But you're not expected to become an expert in every area. [36:48] You're expected to appreciate the value each person brings. [36:53] Joanne and I appreciate your expertise. [36:56] We don't have the ability to bring more education [36:58] programs outside of Stanford. [37:01] You have built a program. [37:03] We've known you for years. [37:04] You built a program that enables us to provide access [37:08] to this knowledge in a way that's understandable, [37:12] that people can consume in a way that's practical. [37:16] And we are revolutionaries in education, [37:19] with you as an expert. [37:21] In our program, we embrace you as an example of translation. [37:27] You are facilitating-- [37:29] I'm part of TRAM too. [37:32] Unequivocally, you are. [37:34] That's fantastic. [37:36] And again, I have another good follow-up question [37:40] that's very specific about the program and offering. [37:43] I've been referring to drugs or treatments. [37:46] But someone was asking, this translational research, [37:50] does it apply to people who are interested in creating [37:52] health care grade software or clinical devices? [37:56] Does it also apply to them? [37:57] Or is that itself a kind of different field? [38:05] Just very quickly, I'm going to answer that, [38:08] and Dean can elaborate. [38:10] But very quickly, our intention originally [38:14] was not to just concentrate on drugs or therapeutics. [38:20] Our intention is really a very holistic approach [38:24] to expand the knowledge of translational medicine, which [38:28] includes therapeutics, diagnostics, devices, [38:35] computational platforms, preventatives. [38:39] And we can appreciate how every year, [38:43] we get new students who are interested [38:46] in those different aspects of translational medicine. [38:52] And as I mentioned before, there are more and more [38:54] computational computer scientists and people [38:59] who know machine learning and AI, who [39:04] want to build platforms for diagnostics or devices. [39:09] So definitely not just therapeutics. [39:13] It does include all other aspects. [39:16] And we discuss all those other aspects in our courses as well. [39:25] Anything you would add to that one, Dr. Felsher? [39:32] I think Joanna's stated it perfectly. [39:35] This is something that completely resonated with both [39:37] of us from the very beginning. [39:41] I have one more question, I think. [39:43] And again, I want to remind everyone, [39:45] we've gotten some great questions. [39:46] If you have more questions, feel free to just put them [39:49] in the Q&A box. [39:50] We're nearing the end of the presentation. [39:52] But I'd love to hear now, again, someone who takes, [39:59] let's say, the graduate certificate, what [40:01] do you hope they would walk away from this program having? [40:04] What do you think they would still be [40:05] thinking about in five years? [40:06] Now, again, I think we have the high-level answer, which [40:09] is that they're thinking across these different aspects [40:13] of science and application. [40:16] But what else would you be hoping, [40:18] maybe it's just partnership in this long-standing group? [40:25] Well, at Stanford, if there's one general high-level idea is [40:31] we really are hoping people will recognize that they'll [40:34] become leaders in medical translation, in whatever aspect [40:40] of the domain. [40:40] They'll be team players. [40:41] We're going to encourage them to work [40:43] with other people in their leadership capacity. [40:47] But we want people to use this as a way to launch themselves, [40:51] to become revitalized or motivated in their own arc. [40:58] And people have been part of the program, [41:00] have been from students who are right out of college, to people [41:04] who have significant amount of work experience. [41:07] Most people have some work experience. [41:09] We prefer people to have some idea they've [41:10] engaged in some aspect of translation, [41:13] so they have an idea that this program makes sense for them. [41:16] But we want to build leaders, we want to build teams. [41:20] And we hope people will be in positions [41:22] that some people will want to be a Dean Felsher, a professor. [41:26] Some people want to be a Joanne Lilienthal, a director [41:32] of education programs that build education as their major focus, [41:38] whether it be in academia like Dr. Lilienthal [41:41] or through programs in industry. [41:44] And we hope people will be involved [41:47] in journalism education, such as you playing a role in education. [41:52] And we hope people will become pharma leaders. [41:54] We hope people will become clinical researchers. [41:57] We hope people will be involved in each step of the process. [42:00] If they're a patent attorney, they'll [42:03] be more capable of helping drive intellectual property. [42:08] If they're a venture person, they'll [42:10] have a wiser appreciation of how to make decisions [42:12] to launch the best companies. [42:14] If they're a scientist, they'll be [42:16] able to do their clinical or basic research more vitalized [42:19] with greater skill and ability. [42:21] So there's lots of different areas, [42:23] but, overall, I hope we create people who say to themselves, [42:28] I trained at Stanford, and I feel now [42:30] that the world is open more for me [42:33] to have a bigger success as a leader in medical translation, [42:38] regardless of what specific asks for the domain [42:42] or the specific setting. [42:46] And just to add to this, traditional education [42:56] has to do with going to the classrooms, [42:58] doing things internally here at Stanford. [43:00] But we quickly realized that there is yet [43:03] another group of people. [43:05] And these are the working scientists, the clinicians, [43:08] the industry professionals who need the knowledge [43:12] but don't necessarily have the time or ability to complete [43:18] a full master's degree or PhD degree [43:22] or full residential degree. [43:24] And that's really where the certificate comes in, [43:29] we really want to change the translational medicine mindset, [43:36] not only at Stanford because it's already changing, [43:39] but we want to change it anywhere in the world that [43:45] needs those changes. [43:46] And that's the beauty of the certificate course [43:49] or the certificate program. [43:53] I appreciate that. [43:54] So I mean, there are a lot of levels [43:55] where you can get engaged. [43:57] And it does sound like that this is broadly applicable to anybody [44:00] who's broadly speaking, the health care field, [44:03] whether you're doing basic science research that [44:05] might have applications down the road, [44:07] whether you're an epidemiologist, maybe even who's [44:10] helping run-- [44:11] not an epidemiologist, but someone [44:12] who's helping run clinical trials to someone [44:15] to a doctor or a venture capitalist [44:17] or even someone who just works in a hospital, [44:21] and who's maybe an administrator helping run the hospitals [44:24] day to day, is having that understanding [44:26] of that whole pipeline. [44:28] It's very broadly applicable and probably to people [44:31] beginning and mid to late stage in their career [44:33] where they can come back and gain this. [44:37] Absolutely. [44:40] The VCs, for instance, how do you make financial decisions [44:44] about who to invest in if you don't understand the science [44:53] or if you don't understand some of the more [44:56] mundane regulatory aspects? [44:58] I think that in order to make better therapeutics, [45:03] diagnostics, devices, everyone really [45:06] needs to understand the entire spectrum of knowledge [45:10] and translational medicine. [45:13] And we should point out that, so far, people [45:16] have been part of our program, have gone into all these areas. [45:20] So people have come started companies, [45:22] people have gone to become professors. [45:24] People have gone and become leaders [45:27] in driving clinical research in emerging [45:32] major biotech companies, many, many different areas. [45:37] Our entire intention was to bring [45:40] the brilliance and the amazing range of abilities at Stanford [45:49] to the world, to enable translational research [45:52] on a bigger scale on a much more magnitude scale. [45:57] Joanna and I have often mused that what we're doing [46:01] has an ambition well beyond any kind [46:05] of individual project or particular clinical discipline. [46:07] It's exactly as you described it. [46:10] And realize that one of the themes we've had [46:12] is we're both trained as PhD scientists. [46:16] And one real advantage of the scientific training [46:19] is there's a mentorship where there are advisors, [46:22] but you learn from the other people in the lab. [46:24] And in a good lab, there are people [46:26] who are junior, brand new students to very seasoned people [46:29] who are almost at the range of being professors to people [46:32] with technical ability, and you learn [46:35] from being amongst people with different interests, [46:37] different backgrounds. [46:39] It's the circumstance of where somebody's [46:42] asking a question from another discipline exposes us [46:46] all to understanding, when the more business-oriented person [46:49] has a scientific question, the scientists [46:51] realize that we take for granted. [46:52] We thought we knew the answer. [46:54] We don't. [46:54] When the scientists ask a business question [46:57] that somebody with more business or legal or medical affairs [47:02] has more insight, they realize what is not [47:04] understood by the scientist. [47:08] It really is the synergy. [47:12] And our excitement is often when the students will say, [47:14] they'll have an epiphany. [47:16] They'll say, Joanna, we love this program [47:19] because we've actualized things we didn't even know. [47:21] we didn't even know what we didn't know. [47:23] And now, we know things. [47:24] We're just so excited that we have a deeper appreciation. [47:28] That is the intention. [47:30] We want to make people better than they were [47:32] before they joined our program. [47:36] We hope they'll feed forward and feed backward, [47:39] that they'll appreciate it, and then they'll [47:41] want to help the next group. [47:43] Because if we do it collectively together, [47:47] we can do it much, much, much better. [47:49] And what's also important is that Joanne and I, [47:53] when we ask people to participate at Stanford, [47:56] it's very rare that somebody is not willing to participate. [48:00] Our challenge is fitting in as many people [48:02] who want to participate. [48:04] So sometimes people don't really believe [48:06] that the really famous faculty at Stanford-- [48:09] no, generally, we are able to accommodate and bring [48:15] on board many of the most famous scientists, [48:19] most famous leaders at Stanford will participate. [48:24] The dean's often participate in our program. [48:28] Fantastic AI scientist, chemist, biologist, cancer biologist, [48:34] cardiologist, infectious disease people, [48:36] all across different domains. [48:38] I mean, it's just that has never been the issue. [48:41] And also that's true across the school. [48:44] Joanna will be modest about it, but I'm not [48:46] modest in Joanna's behalf. [48:48] Joanna, having done this for years, [48:50] knows every other program, every other resource at Stanford, [48:56] over 16 years of doing this. [48:58] And as a consequence, part of our program, [49:02] we get questions answered, taking advantage of everything [49:06] available at Stanford. [49:07] It's just truly remarkable, often, [49:09] what we see that our students and people that [49:12] are mentored by program are able to accomplish, [49:15] because just the amazing ability that we work as a team. [49:23] I want to thank both of you for joining us today, [49:26] and thank everyone who joined us online.