Stanford OnlineStanford Webinar - A Conversation on the Future of Translational Medicine
Stanford Online
Webinar Introduction and Speakers 0:10
The host opens the webinar on the future of translational research and introduces the two guests, Dr. Dean Felchshire and Dr. Joanna Lillian Tal. Dr. Felchshire is a physician-scientist at Stanford who studies how oncogenes drive cancer and has led the Translational Research and Applied Medicine program, known as TRAM, since 2011. Dr. Lillian Tal is the executive director of Stanford's master's program in translational research and applied medicine and has worked alongside Dr. Felchshire since 2011, mentoring researchers who move findings from the lab toward clinical use, including biomarker work for early cancer detection.
Defining Translational Research 3:02
Dr. Felchshire explains that translational research means taking an idea discovered in the laboratory and turning it into something real and useful in the world, such as a treatment or a diagnostic test. That shift from a basic science observation to something tangible and useful is why the process is called translation.
Why the Bench to Bedside Path Is Hard 4:01
Dr. Felchshire says the first challenge is simply getting scientists and clinicians to work together, since scientists in the lab often do not know what clinical problems actually need solving, and clinicians often do not know what science is available to help them. He describes himself and Dr. Lillian Tal as scientific siblings who have worked on this together for sixteen years. Dr. Lillian Tal adds that drug development needs far more than good science, since it also requires understanding clinical need, manufacturing, intellectual property, and commercialization, and a great discovery can fail simply because those questions were not asked early enough.
Boundaries Between Stages Disappearing 8:00
Dr. Lillian Tal notes that discovery, development, and commercialization used to be treated as separate, sequential stages, but the biggest change she has seen is that these boundaries are dissolving. Scientists now need to think about downstream questions much earlier, since artificial intelligence and computational approaches are reshaping discovery, biomarkers and patient selection matter more during development, and commercial and regulatory thinking now influences scientists' choices from the start. Dr. Felchshire illustrates this with his own work on the MYC gene, a central driver of cancer discovered decades ago, explaining that translating this kind of insight into treatment now requires combining the underlying biology, an understanding of the clinical context, and chemistry expertise all at once, something students at Stanford are trained to do together rather than in isolation.
Connecting People Across Disciplines 14:30
Dr. Felchshire explains that one reason he recruited Dr. Lillian Tal was her ability to connect people across fields, since a solution found in cancer research can sometimes unlock a treatment for a psychiatric disorder or a cardiology finding can prove useful in oncology. Dr. Lillian Tal describes the rise of AI and computational biology as the biggest change of the last five years, noting that a program area that drew barely one project seven years ago now involves roughly half the current cohort. She frames TRAM's core value as connecting the right people who might otherwise never meet, since disease mechanisms may be limited but the ways of addressing them are not.
How TRAM Keeps Evolving 19:30
Dr. Felchshire describes TRAM as an almost twenty-year-old program that grows organically with its students, fellows, and faculty, expanding from an original focus on therapeutics into diagnostics, vaccine therapy, and immune therapy, while adding formal mentorship and training in AI. He notes that the program's advisors include leaders at some of the most successful biotech companies, which keeps the curriculum tied to what is actually working in the field. Dr. Lillian Tal adds that TRAM has expanded its experiential component so students can pursue individual lab projects, called trips, or join multidisciplinary team projects that mirror how drug development actually happens in practice.
Why Everyone Needs the Bigger Picture 21:31
Asked why a data scientist or clinician outside a formal program should care about the whole translational arc, Dr. Felchshire says the pace of translation is accelerating so quickly that professionals across roles, from scientists to CEOs to physicians, risk falling behind if they only know their own slice. He explains that a physician benefits from seeing how diagnostics and treatment decisions are changing, a basic scientist benefits from learning how to find the right clinical or business contacts to realize a discovery's value, and an investor benefits from getting organized access to state of the art science that can otherwise feel like a foreign language.
TRAM as an Ecosystem, Not Just Classes 25:01
Dr. Lillian Tal stresses that TRAM is not simply an educational program but an ecosystem that brings together clinicians, scientists, industry experts, entrepreneurs, and learners, supporting projects, building collaborations, and connecting people with expertise. She says the common thread running through all of it is helping promising science move forward to actually improve patients' lives, not just producing new therapeutics or diagnostics for their own sake. Dr. Felchshire adds that the curriculum walks students through the full arc, from forming a scientific question and testing it, through clinical study design, to raising capital, securing patents, and gaining regulatory approval, and that the program's real strength lies in its network of hundreds of trained alumni, faculty, and advisors from both Stanford and industry who continue to mentor, hire, and collaborate with one another long after graduation.
Curriculum structure and lifelong learning 30:30
The program's curriculum walks students through every step of translation with specific classes on topics like chemistry, patent law, and vaccine development, and it keeps expanding as new student interests emerge. Everyone is expected to grasp core basics such as how to design a clinical study, how a small molecule is identified and tested through an assay, and what is required to get an IND approved by the FDA. The learning is meant to continue past the program itself, since graduates stay connected to a network of talented people at Stanford who invite each other to site visits, hire recent graduates, and offer career development, forming a lasting professional family.
Tension between basic and applied science 34:00
There is a real tension because clinical care, basic research, and running a company are each extremely time consuming, leaving little room to do all three. Rather than forcing engagement, the program builds an environment that makes it easier for someone with a basic science background to connect with a clinician, or for a clinician to find a business-minded collaborator. A major part of this is encouraging a team approach, where people are not expected to master every area but are expected to appreciate the expertise others bring, such as a business person's question exposing a gap in scientific assumptions and vice versa.
Beyond drugs to devices and software 37:31
The program was never meant to focus only on drugs or therapeutics. It takes a holistic view of translational medicine that includes diagnostics, devices, computational platforms, and preventatives, and each year brings more computer scientists and machine learning experts interested in building diagnostic or device platforms. The goal is to build leaders and team players across every part of the field, whether that means becoming a professor, a pharma leader, a clinical researcher, a patent attorney, or a venture investor with a better grasp of the science behind their decisions. The certificate format exists because many working scientists, clinicians, and industry professionals want this knowledge but cannot commit to a full degree, and alumni have gone on to start companies, become professors, and lead major biotech efforts, drawing on the full range of Stanford's expertise and faculty willingness to participate.
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