Expanding the Precision of Modern Therapeutics
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Breakthroughs in biology, engineering, and computation continue to redefine what is possible in human health. Building on the momentum of prior MIT ILP Health Science Forums, which highlighted advances in drug discovery, AI-enabled biomolecular modeling, next-generation diagnostics, and precision biomanufacturing, the 2026 MIT Health Science Technology Forum will spotlight emerging research in diagnosis, brain science, microbial therapeutics, and targeted drug delivery.
This year’s program brings together leading MIT faculty working at the forefront of early detection, brain circuitry and neurodegeneration, the microbiome’s role in health and disease, and new therapeutic approaches that reach previously inaccessible tissues. Complementing the faculty program, MIT-connected startups will deliver rapid-fire presentations showcasing commercialization-ready innovations across diagnostics, delivery systems, computational biology, and health-enabling technologies.
Together, these sessions present a convergent vision for healthcare, one in which earlier detection, deeper biological insight, and engineered delivery platforms expand the reach, precision, and impact of modern therapeutics.
Designed for industry leaders, researchers, and innovators, the 2026 Forum offers a unique opportunity to connect with MIT experts and explore cross-disciplinary advances shaping the future of human health.
Registration Fee ILP Member: Complimentary General Public: $500 for in-person/ $250 for livestream MIT Faculty, Staff, and Students: Limited complimentary in-person seats available
Visiting MIT: https://www.mit.edu/visitmit/ Where to Stay: https://institute-events.mit.edu/visit/where-to-stay Registration Questions: ocrevents@mit.edu
The agenda below is subject to change without prior notice.
Postdoctoral Researcher, MIT Department of Biological Engineering
Georg Wachter completed his PhD between Imperial College London and MIT (’23), focusing on gene circuit engineering and mathematical biology. His research centers on two main areas: engineering emerging multicellular patterning and developing intracellular neural networks for advanced cellular information processing and pattern recognition. He also contributed to the development of a translation engine for gene circuit design, enabling high-level target functions to be converted into genetic programs in silico without additional in vivo optimization.
After leaving the Weiss Lab, Georg shifted his focus toward the translational applications of his work and is now a full-time co-founder of a company he established alongside Prof. Ron Weiss and Dr. Jean Disset.
Synthetic biology is revolutionizing how we conceptualize and engineer biological systems. Recent advances are enabling researchers to move beyond constructing and analyzing small gene networks toward implementing complex multicellular systems with diverse applications. In this talk, Georg Wachter will describe his and his team's integrated computational and experimental approach to engineering complex behaviors in various cell types, with a focus on mammalian cells. Their research draws on design principles from electrical engineering and other established fields, including abstraction, standardization, modularity, and computer-aided design. At the same time, they devote considerable effort to understanding what distinguishes synthetic biology from other engineering disciplines and to discovering new design and construction rules effective for this unique field. Georg will briefly describe the implementation of genetic circuits and modules exhibiting finely tuned digital, analog, and multicellular behaviors. The first system he will present is a multi-input genetic circuit capable of detecting and eliminating specific cancer cells based on the presence or absence of particular biomarkers. He will also discuss generating complex tissue from human induced pluripotent stem cells that recapitulates early developmental processes, exhibits a liver bud–like phenotype with integrated vasculature, and can be used for drug development and potentially for tissue transplantation. Finally, Georg will present a mechanism for creating artificial neural networks within cells using translational regulation. This approach provides a finely tuned means of achieving non-binary, non-monotonic behaviors, paving the way for cells that can be trained and autonomously learn to perform specific behavioral tasks.
Associate Professor, Institute for Medical Engineering and Science Associate Professor, MIT Civil and Environmental Engineering Hermann L.F. von Helmholtz Career Development Professor
Tami trained in molecular biology and mathematics at Northwestern University, where she conducted research in the laboratory of Jon Widom and was funded by a Barry M. Goldwater Scholarship. She then earned a PhD in Systems Biology from Harvard University, where she conducted research in Roy Kishony’s laboratory. During her graduate research, Tami developed new genomic approaches for understanding how bacteria evolve during infections of individual people. As a postdoc in Eric Alm’s lab at MIT, she further developed and applied these genomic approaches to understand the microbes that colonize us during health.
Tami joined the MIT faculty in January 2018, where she now leads a computational and experimental research group focused on within-person evolution in the skin microbiome, with projects spanning from theoretical population genetics to applied probiotics for the treatment of skin diseases. A major thrust of her lab is uncovering the mechanisms of colonization to enable precision microbiome therapies. She is the recipient of a 2020 NIH New Innovator Award.
Microbiome-based therapies for the skin and other body sites are a promising modality for treating disease and promoting wellness. However, a major challenge to realizing this potential is that most applied bacteria—even those taken from the same body site in healthy humans—do not remain or 'engraft' after application. In this talk, I will discuss how tracking evolution and ecology, along with the appropriate genomic and spatial resolutions, can help us design therapies with a higher chance of engraftment. I will present insights from Cutibacterium acnes and Staphylococcus epidermidis, which together comprise over 75% of the healthy facial skin microbiome and are both being actively explored as probiotics by industry.
Assistant Professor, MIT Media Lab Assistant Professor, MIT Department of Electrical Engineering and Computer Science
Paul Liang is an Assistant Professor at the MIT Media Lab and the Department of Electrical Engineering and Computer Science. He is the founding director of the Multisensory Intelligence research group, which studies the foundations of multisensory artificial intelligence to create human-AI symbiosis across scales and sensory mediums, enhancing productivity, creativity, and well-being.
Paul received his PhD in Machine Learning at Carnegie Mellon University, advised by Louis-Philippe Morency and Ruslan Salakhutdinov, and was a visiting researcher at the Simons Institute at UC Berkeley in the summer of 2024. During his PhD, he also spent time at the research labs of DeepMind, Facebook, Nvidia, and Google. Previously, he received an MS in Machine Learning and a BS with University Honors in Computer Science and Neural Computation from CMU.
Paul's research builds the theoretical foundations, large-scale resources, and neural network architectures to learn from multisensory data. These approaches are widely used to train and evaluate today's multimodal generative AI models used throughout academia and industry. In collaboration with practitioners, he has deployed these systems for problems in mental health, cancer prognosis, and robot control. His research has been recognized by the Siebel Scholars Award, Waibel Presidential Fellowship, Facebook PhD Fellowship, Center for ML and Health Fellowship, Rising Stars in Data Science, and four best paper awards at international conferences and workshops. Outside of research, Paul received the Alan J. Perlis Graduate Student Teaching Award for designing a new pedagogy for multimodal AI.
Building multisensory AI systems that learn from multiple sensory inputs such as text, speech, video, real-world sensors, wearable devices, and medical data holds great promise for impact in supporting human health and well-being. This talk will cover our recent work on large-scale multimodal clinical benchmarks, with a million patient samples distributed across imaging, 3D/video, temporal sensing, graphs, and multimodal data. Using CLIMB, we trained QoQ-Med, the first and most powerful open-source foundation model for clinical reasoning across medical images, time-series signals, and text reports. These models enable strong reasoning and diagnosis capabilities to assist clinicians in their workflows.
Principal Research Scientist and Principal Investigator, Koch Institute for Integrative Cancer Research
Dr. Ana Jaklenec is a Principal Investigator at the Koch Institute for Integrative Cancer Research at MIT. With over 15 years of experience, she’s a leader in the fields of bioengineering and materials science, focused on manufacturing controlled delivery systems and stabilizing therapeutics for global health. She is an inventor of several drug delivery technologies that have the potential to enable access to medical care globally, has published over 150 manuscripts, patents and patent applications and has founded three companies, Particles for Humanity, VitaKey, and OmniPulse Biosciences.
Dr. Jaklenec received a B.S. in Biomedical Engineering from Boston University and a Ph.D. in Biomedical Engineering from Brown University. Her postdoctoral training was with Institute Prof. Robert Langer at MIT, where her research focused on drug delivery of biologics (among other projects). Jaklenec was elected to the National Academy of Inventors (NAI) Class of Fellows, the highest professional distinction awarded solely to inventors. She is the recipient of the Ruth L. Kirschstein National Research Service Award (NRSA) from the National Institutes of Health (NIH). She was elected to the American Institute for Medical and Biological Engineering (AIMBE) College of Fellows in 2022 for her work in controlled delivery of vaccines and heat-stable micronutrients for global health and was elected to the Controlled Release Society (CRS) 2022 College of Fellows for her research at the interface of engineering and immunology that utilizes precise fabrication and design of materials at the nano- and micro-scale for use in controlled drug delivery for global health. She has supervised over 50 pre- and postdoctoral students. She is an active member of the Biomedical Engineering Society, the Controlled Release Society, and the Society for Biomaterials.
Dr. Jaklenec’s research is at the interface of material science and immunology with a focus on the study and development of polymers to deliver liable drugs, particularly vaccines, DNA vectors and mRNAs, in stable form for prolonged periods of time with unique kinetics. Her lab is currently working in the following areas: developing single-injection self-boosting vaccines; nanocarrier-based vaccine approaches targeting protective memory responses after parenteral immunization; advanced manufacturing including 3D printed on-demand microneedle vaccines; developing on patient medical records using invisible dyes; creating long-term drug delivery systems for cancer immunotherapy; developing heat stable polymer-based carriers for oral delivery of micronutrients and probiotics.
Engineering translatable technologies for vaccine delivery remains a critical challenge, particularly in the context of infrastructure limitations, patient access, and cold-chain dependence across both developing regions and rural or remote settings. In this talk, I will discuss how polymer-based design and engineering can be leveraged to develop scalable solutions that bridge the gap between innovation and real-world implementation.I will highlight the development of SEAL (StampEd Assembly of polymer Layers), a platform that enables controlled, pulsatile release of biologics over days to months following a single administration. This approach supports single-injection, self-boosting vaccines and has broader implications for cancer immunotherapy. I will also present a microneedle-based vaccine printing platform designed for decentralized manufacturing of thermostable mRNA vaccines, enabling more flexible and distributed production models. Together, these technologies illustrate how advances in materials science and engineering can reshape vaccine delivery by reducing logistical constraints and enabling new paradigms for manufacturing and deployment at scale.
James W. (1963) and Patricia T. Poitras Professor, MIT Department of Brain and Cognitive Sciences Associate Director, McGovern Institute Director, Hock E. Tan and K. Lisa Yang Center for Autism Research Director, Model Systems and Neurobiology, Stanley Center for Psychiatric Research Institute Member, Broad Institute of MIT and Harvard
Guoping Feng is a faculty member of the MIT Department of Brain and Cognitive Sciences, where he holds the James W. (1963) and Patricia T. Poitras Professorship. He also joined the McGovern Institute in 2010 and currently serves as its associate director. Feng is also the director of the Hock E. Tan and K. Lisa Yang Center for Autism Research at MIT, as well as director of model systems and neurobiology in the Stanley Center for Psychiatric Research at the Broad Institute.
Originally from Zhejiang Province in China, Guoping Feng studied medicine at Zhejiang University School of Medicine. He obtained his PhD from the State University of New York at Buffalo in the laboratory of Linda Hall and postdoctoral training at Washington University in St. Louis under the guidance of Joshua Sanes. Prior to joining the faculty at MIT in 2010, he was a faculty member in the neurobiology department at Duke University School of Medicine.
RareNet is built around a global, collaborative consortium of neuroscientists, clinicians, patient advocates, and industry partners that connects fragmented research efforts, expands access to patient data and samples, and fosters trust and shared goals. Central to its mission is a therapeutic pipeline accelerator that reduces early research risk, strengthens safety and reliability, and speeds translation from discovery to clinical and commercial readiness. Led by faculty director Guoping Feng, RareNet integrates MIT expertise with advanced tools such as disease modeling and artificial intelligence to extract insights from biological and clinical datasets, enabling a deeper understanding of complex and rare brain conditions and generating insights with broad relevance across uncommon neurological disorders.
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