Results for BIOE

Are you on an engineering pathway and trying to decide if opportunities in healthcare might be of interest to you? Or, are you committed to a career in medicine and eager to explore how to incorporate technology innovation into your plans? In either case, Needs Finding in Healthcare is the Sophomore College for you! Several courses offered during the regular academic year provide students with the opportunity to understand healthcare problems and invent new technologies to address them. However, this is the only one that gives undergraduates the chance to directly observe the delivery of healthcare in the real world and identify important unmet needs for themselves. Needs Finding in Healthcare is a Sophomore College course offered by Stanford Biodesign. We're looking for students who are passionate about innovation and interested in how technology can be applied to help make healthcare better for patients everywhere. Over approximately three weeks, you'll spend time: Learning the fundamentals of the need-driven biodesign innovation process for health technology innovation; Practicing how to conduct observations and shadow care providers to identify compelling unmet health-related needs, and then performing observations in Stanford's emergency department, operating rooms, and clinics; Conducting background research and interacting with physicians and patients to understand and prioritize needs you have been identified; Brainstorming and building early-stage prototypes to enhance your understanding of the unmet need and critical requirements for solving it; In addition, you'll meet experienced innovators from the health technology field and explore different career pathways in this dynamic space. Join us if you want to make a difference at the intersection of medicine and engineering!

This seminar is for anyone who loves food, cooking or science! We will focus on the science and biology behind the techniques and the taste buds. Not a single lecture will pass by without a delicious opportunity - each weekly meeting will include not only lecture, but also a lab demonstration and a chance to prepare classic dishes that illustrate that day's scientific concepts.

BIOE 42 is designed to introduce students to general engineering principles that have emerged from theory and experiments in biology. Topics covered will cover the scales from molecules to cells to organisms, including fundamental principles of entropy, diffusion, and continuum mechanics. These topics will link to several biological questions, including DNA organization, ligand binding, cytoskeletal mechanics, and the electromagnetic origin of nerve impulses. In all cases, students will learn to develop toy models that can explain quantitative measurements of the function of biological systems. Prerequisites: MATH 19, 20, 21 CHEM 31A, B (or 31X), PHYSICS 41; strongly recommended: CS 106A, CME 100 or MATH 51, and CME 106; or instructor approval.

An introduction to techniques in genetic, molecular, biochemical, cellular and tissue engineering. Lectures cover advances in the field of synthetic biology with emphasis on genetic engineering, plasmid design, gene synthesis, genetic circuits, and safety and bioethics. Lab modules will teach students how to conduct basic lab techniques, add/remove DNA from living matter, and engineer prokaryotic and eukaryotic cells. Team projects will support practice in component engineering with a focus on molecular design and quantitative analysis of experiments, device and system engineering using abstracted genetically encoded objects, and product development. Concurrent or previous enrollment in BIO 82 or BIO 83. Preference to declared BioE students. Students who have not declared BioE should email Alex Engel to get on a waitlist for a permission code to enroll. Class meets in Shriram 112, lab meets in Shriram 114. Scientific Method and Analysis (SMA).

Fundamental human anatomy, spanning major body systems and tissues including nerve, muscle, bone, cardiovascular, respiratory, gastrointestinal, and renal systems. Explore intricacies of structure and function, and how various body parts come together to form a coherent and adaptable living being. Correlate clinical conditions and therapeutic interventions. This course consists of a lecture and a lab component - both are required. All lectures are online asynchronous modules. Labs are in-person. Students must enroll in lecture and lab. For lab, students need to select their preferred Section.

The combination of the internet, phones/wearables, and diagnostic/generative AI allow fundamentally different approaches to healthcare to be conceived. Contemporary healthcare still relies heavily on human doctors, which restricts the number of people that can be helped, limits scaling and quality, and sets a basic cost floor on services. The purpose of this seminar is to explore a potential all-digital tech stack for healthcare, including diagnostic AI, data collection at the edge, and privacy-preserving compute. We will hear from industry experts and startup founders, and consider technical gaps as well as legal/societal barriers to ubiquitous adoption of healthcare provided primarily by computers.

BIOE 70Q invites students to apply design thinking to the creation of healthcare technologies. Students will learn about the variety of factors that shape healthcare innovation, and through hands-on design projects, invent their own solutions to clinical needs. Guest instructors will include engineers, doctors, entrepreneurs, and others who have helped bring ideas from concept to clinical use.

Future physicians, social and biological scientists, and engineers will be the core of teams that solve major problems threatening human health. Bridging these diverse areas will require thinkers who can understand human biology and also think broadly about approaching such challenges. Focusing on heart disease, students in this seminar will learn about the multi-factorial problems leading to the leading cause of death in the U.S., along with how to apply design thinking to innovate in the context of healthcare.

Students completing BIOE 80 should have a working understanding for how to approach the systematic engineering of living systems to benefit all people and the planet. Our main goals are (1) to help students learn ways of thinking about engineering living matter and (2) to empower students to explore the broader ramifications of engineering life. Specific concepts and skills covered include but are not limited to: capacities of natural life on Earth; scope of the existing human-directed bioeconomy; deconstructing complicated problems; reaction & diffusion systems; microbial human anatomy; conceptualizing the engineering of biology; how atoms can be organized to make molecules; how to print DNA from scratch; programming genetic sensors, logic, & actuators; biology beyond molecules (photons, electrons, etc.); constraints limiting what life can do; and possible health challenges in 2030. And we explore questions like, how does what we want shape bioengineering, and who should choose and realize various competing bioengineering futures?

Complex biological behaviors through the integration of computational modeling and molecular biology. Topics: reconstructing biological networks from high-throughput data and knowledge bases. Network properties. Computational modeling of network behaviors at the small and large scale. Using model predictions to guide an experimental program. Robustness, noise, and cellular variation. Prerequisites: CME 102; BIO 82, BIO 84; or consent of instructor.

Principles of statistical physics, thermodynamics, and kinetics with applications to molecular biology. Topics include entropy, temperature, chemical forces, enzyme kinetics, free energy and its uses, self assembly, cooperative transitions in macromolecules, molecular machines, feedback, and accurate replication. Prerequisites: MATH 19, 20, 21; CHEM 31A, B (or 31X); strongly recommended: PHYSICS 41, CME 100 or MATH 51, and CME 106; or instructor approval.

Physiology of intact human tissues, organs, and organ systems in health and disease, and bioengineering tools used (or needed) to probe and model these physiological systems. Topics: Clinical physiology, network physiology and system design/plasticity, diseases and interventions (major syndromes, simulation, and treatment, instrumentation for intervention, stimulation, diagnosis, and prevention), and new technologies including tissue engineering and optogenetics. Discussions of pathology of these systems in a clinical-case based format, with a view towards identifying unmet clinical needs. Learning computational skills that not only enable simulation of these systems but also apply more broadly to biomedical data analysis. Prerequisites: CME 102; PHYSICS 41; BIO 82 OR 83; BIO 84. CS 106A or programming experience highly recommended.

ONLINE Offering of BIOE 103. This pilot class, BIOE103B, is an entirely online offering with the same content, learning goals, and prerequisites as BIOE 103. The class is open to BioE-declared students who are not on campus in the spring. Students attend class by watching videos and completing assignments remotely. Physiology of intact human tissues, organs, and organ systems in health and disease, and bioengineering tools used (or needed) to probe and model these physiological systems. Topics: Clinical physiology, network physiology and system design/plasticity, diseases and interventions (major syndromes, simulation, and treatment, instrumentation for intervention, stimulation, diagnosis, and prevention), and new technologies including tissue engineering and optogenetics. Discussions of pathology of these systems in a clinical case-based format, with a view towards identifying unmet clinical needs. Learning computational skills that not only enable simulation of these systems but also apply more broadly to biomedical data analysis. Prerequisites: CME 102; PHYSICS 41; BIO 82 OR 83; BIO 84. CS 106A or programming experience highly recommended.

Overview of the most pressing biosecurity issues facing the world today, with a special focus on the COVID-19 pandemic. Critical examination of ways of enhancing biosecurity and pandemic resilience to the current and future pandemics. Examination of how the US and the world are able to withstand a pandemic or a bioterrorism attack, how the medical/healthcare field, government, and technology sectors are involved in biosecurity and pandemic or bioterrorism preparedness and response and how they interface; the rise of synthetic biology with its promises and threats; global bio-surveillance; effectiveness of various containment and mitigation measures; hospital surge capacity; medical challenges; development, production, and distribution of countermeasures such as vaccines and drugs; supply chain challenges; public health and policy aspects of pandemic preparedness and response; administrative and engineering controls to enhance pandemic resilience; testing approaches and challenges; promising technologies for pandemic response and resilience, and other relevant topics. Guest lecturers have included former Secretary of State Condoleezza Rice, former Special Assistant on BioSecurity to Presidents Clinton and Bush Jr. Dr. Ken Bernard, former Assistant Secretary of Health and Human Services Dr. Robert Kadlec, eminent scientists, public health leaders, innovators and physicians in the field, and leaders of relevant technology companies. Open to medical, graduate, and undergraduate students. No prior background in biology necessary. Must be taken for at least 4 units to get WAYs credit. Students also have an option to take the class for 2 units as a speaker series/seminar where they attend half the class sessions (or more) and complete short weekly assignments. In -person, asynchronous synchronous online instruction are available.

The Bioengineering System Prototyping Laboratory is a fast-paced, team-based system engineering experience, in which teams of 2-3 students design and build a bioengineering-relevant system (e.g., centrifuge) that meets a set of common requirements along with a set of unique team-determined requirements. Students learn-by-doing hands-on skills in electronics and mechanical design and fabrication. Teams also develop process skills and an engineering mindset by aligning specifications with requirements, developing output metrics and measuring performance, and creating project proposals and plans. The course culminates in demonstration of a fully functioning system that meets the teams' self-determined metrics. Learning goals: 1) Design, fabricate, integrate, and characterize practical electronic and mechanical hardware systems that meet clear requirements in the context of Bioengineering (i.e., build something that works). 2) Use prototyping tools, techniques, and instruments, including: CAD, 3D printing, laser cutting, microcontrollers, and oscilloscopes. 3) Create quantitative system specifications and test measurement plans to demonstrate that a design meets user requirements. 4) Communicate design elements, choices, specifications, and performance through design reviews and written reports. 5) Collaborate as a team member on a complex system design project (e.g., a centrifuge). Limited enrollment, with priority for Bioengineering undergraduates. Prerequisites: Physics 43, or equivalent. Experience with Matlab and/or Python is recommended.

Bioengineering focuses on the development and application of new technologies in the biology and medicine. These technologies often have powerful effects on living systems at the microscopic and macroscopic level. They can provide great benefit to society, but they also can be used in dangerous or damaging ways. These effects may be positive or negative, and so it is critical that bioengineers understand the basic principles of ethics when thinking about how the technologies they develop can and should be applied. On a personal level, every bioengineer should understand the basic principles of ethical behavior in the professional setting. This course will involve substantial writing, and will use case-study methodology to introduce both societal and personal ethical principles, with a focus on practical applications

First course of two-quarter sequence. Team-based project introduces students to the process of designing new bioengineering technologies to address unmet societal needs. Methods and processes include need specification, brainstorming, concept selection, system specification, and system engineering/design via iterative prototyping and experimentation. First quarter focuses on the innovation process, with teams going from need-specification to initial project plans. Lectures and labs include interactive project work and expert speakers. Prerequisites: BIOE123 and BIOE44.

Second course of two-quarter sequence. Team based project introduces students to the process of designing new bioengineering technologies to address unmet societal needs. Focus is on implementation and demonstration of technical feasibility of the first quarter design. Primary deliverables/timelines based on each team's project plan, with weekly mentoring and design reviews during lecture/lab. Guest sessions introduce next-step aspects of bioengineering innovation projects: regulation, intellectual property, commercialization. Prerequisites: BIOE123 and BIOE44. Limited to seniors in Bioengineering (or instructor consent).

Combines biological knowledge and methods with quantitative engineering principles. Quantitative review of biochemistry and metabolism as well as recombinant DNA technology and synthetic biology (metabolic engineering). The course begins with a review of basic cell biology, proceeds to bioprocess design and development, and ends with applied synthetic biology methods and examples. Prerequisite: CHEMENG 181 or equivalent.

The relationships between molecular structure, morphology, and the unique physical, chemical, and mechanical behavior of polymers and other types of soft matter are discussed. Topics include methods for preparing synthetic polymers and examination of how enthalpy and entropy determine conformation, solubility, mechanical behavior, microphase separation, crystallinity, glass transitions, elasticity, and linear viscoelasticity. Case studies covering polymers in biomedical devices and microelectronics will be covered. Recommended: ENGR 50 and Chem 31A or equivalent.

The famous computer scientist, Alan Kay, once said, "The best way to predict the future is to invent it." As such, we are all responsible for inventing the future we hope we and our descendants will experience. In this highly interactive course, we will be exploring how to predict and invent the future and why this is important by focusing on a wide range of frontier technologies, such as robotics, AI, genomics, autonomous vehicles, blockchain, 3D Printing, VR/AR, synthetic meat, etc. The class will feature debates in which students present utopian and dystopian scenarios, and determine what has to be done to inoculate ourselves against the negative consequences. Limited enrollment. Admission by application: dschool.stanford.edu/classes.

This course will introduce you to research areas in human performance and a framework for planning a research project in the area. The course will enable you to gain experience at identifying compelling research needs, pitching research ideas, designing experiments, communicating scientific data and conducting meetings with your mentor to solicit helpful feedback on your work. The course will culminate in the preparation of a research proposal that addresses a research question of interest that you plan to pursue in the near-term.

Directed study and research for undergraduates on a subject of mutual interest to student and instructor. Prerequisites: consent of instructor and adviser. (Staff)

Individual research by arrangement with out-of-department instructors. Credit for 191X is restricted to declared Bioengineering majors pursuing honors and requires department approval. See http://bioengineering.stanford.edu/education/undergraduate.html for additional information. May be repeated for credit.

For undergraduate students participating in the Stanford ChEM-H Undergraduate Scholars Program. This course will expose students to interdisciplinary research questions and approaches that span chemistry, engineering, biology, and medicine. Focus is on the development and practice of scientific reading, writing, and presentation skills intended to complement hands-on laboratory research. Students will read scientific articles, write research proposals, make posters, and give presentations.

Biology as a technology is burgeoning, leading to diverse cultural, economic, geopolitical, and natural outcomes. Students in this course will learn to step back from the overwhelming immediacy of biotechnology's application and to instead adopt a culture of play that enables qualitative expansion of ideas and possibilities. So enriched students will also learn to map ideas onto a future constrained by practical realities and market dynamics. Active in-class participation and a team-based final project are required.

This course exposes students to the engineering principles and clinical application of medical devices through lectures and hands-on labs, performed in teams of two. Teams take measurements with these devices and fit their data to theory presented in the lecture. Devices covered include X-ray, CT, MRI, EEG, ECG, Ultrasound and BMI (Brain-machine interface). Prerequisites: BIOE 103 or BIOE 300B.

This course will cover the fundamental principles of genetic and epigenetic engineering, starting from the key biological discoveries to the current technological applications. We will be dissecting classic literature, formulating our own scientific questions, and designing experiments or calculations to test our answers. Topics include: gene editing using transposases, integrases and nucleases, gene regulation with a focus on transcriptional control, chromatin-mediated epigenetic regulation, and epigenetic editing.

Mixed reality uses transparent displays to place virtual objects in the user's field of vision such that they can be aligned to and interact with actual objects. This has tremendous potential for medical applications. The course aims to teach the basics of mixed-reality device technology, and to directly connect engineering students to physicians for real-world applications. Student teams will complete guided assignments on developing new mixed-reality technology and a final project applying mixed-reality to solve real medical challenges. Prerequisites: (1) Programming competency in a language such as C, C++. or Python. (2) A basic signal processing course such as EE102B (Digital Signal Processing), while not required, will be helpful. (3) A medical imaging course, while not required, will be helpful. Please contact the instructors with any questions about prerequisites.

The course covers mathematical and computational techniques needed to solve advanced problems encountered in applied bioengineering. Fundamental concepts are presented in the context of their application to biological and physiological problems including cancer, cardiovascular disease, infectious disease, and systems biology. Topics include Taylor's Series expansions, parameter estimation, regression, nonlinear equations, linear systems, optimization, numerical differentiation and integration, stochastic methods, ordinary differential equations and Fourier series. Python, Matlab and other software will be used for weekly assignments and projects.Prerequisites: Math 51, 52, 53; prior programming experience (Matlab or other language at level of CS 106a or higher)

Complex biological behaviors through the integration of computational modeling and molecular biology. Topics: reconstructing biological networks from high-throughput data and knowledge bases. Network properties. Computational modeling of network behaviors at the small and large scale. Using model predictions to guide an experimental program. Robustness, noise, and cellular variation. Prerequisites: CME 102; BIO 82, BIO 84; or consent of instructor.

Capstone Biomedical Data Science experience. Hands-on software building. Student teams conceive, design, specify, implement, evaluate, and report on a software project in the domain of biomedicine. Creating written proposals, peer review, providing status reports, and preparing final reports. Issues related to research reproducibility. Guest lectures from professional biomedical informatics systems builders on issues related to the process of project management. Software engineering basics. Because the team projects start in the first week of class, attendance that week is strongly recommended. Prerequisites: BIOMEDIN 210 or 214 or 215 or 217 or 260. Preference to BMI graduate students. Consent of instructor required.NOTE: For students in the Department of Biomedical Data Science Program, this core course MUST be taken as a letter grade only.

Theoretical analysis of dynamical processes: dynamical systems, stochastic processes, and spatiotemporal dynamics. Motivations and applications from biology and physics. Emphasis is on methods including qualitative approaches, asymptotics, and multiple scale analysis. Prerequisites: ordinary and partial differential equations, complex analysis, and probability or statistical physics.

BIOMEDIN 214: Representations and Algorithms for Computational Molecular Biology (BIOE 214, CS 274, GENE 214)Topics: This is a graduate level introduction to bioinformatics and computational biology, algorithms for alignment of biological sequences and structures, BLAST, phylogenetic tree construction, hidden Markov models, basic structural computations on proteins, protein structure prediction, molecular dynamics and energy minimization, statistical analysis of 3D structure, knowledge controlled terminologies for molecular function, expression analysis, chemoinformatics, pharmacogenetics, network biology. Lectures are supplemented with assignments and programming projects, which allow students to implement important computational biology algorithms. Firm prerequisite: CS 106B. NOTE: For students in the Department of Biomedical Data Science Program, this core course MUST be taken as a letter grade only.

Analytic and interpretive methods to optimize the transformation of genetic, genomic, and biological data into diagnostics and therapeutics for medicine. Topics: access and utility of publicly available data sources; types of genome-scale measurements in molecular biology and genomic medicine; linking genome-scale data to clinical data and phenotypes; and new questions in biomedicine using bioinformatics. Case studies. Prerequisites: programming ability at the level of CS 106A and familiarity with statistics and biology.

This class will be a guided tour into regeneration biology, with an emphasis on fundamental developmental processes. Instead of focusing on what we know, the goal of this course is for students to trace how we know, and how we should ask questions for the future. In my opinion, the most important scientific problems are often left unresolved not for lack of adequate information, but for lack of insights to specify the questions that require explanation. Therefore, in this class, we will work together to search for important questions in the area, by reconstructing historical and controversial ideas, dissecting classic literature, formulating our own questions, and debating to test our answers. This class is a tour, as there is no intention for it to be comprehensive; students will be treated as my future colleagues and provided by a taste of science ? you should progress in your own way, at your own pace that matches your ambition in learning. Therefore, I expect the class to be interactive and even provocative, and the students to be willing to read beyond the class as active reading is essential to succeed in this course.

Focus on learning the fundamentals of each imaging modality including X-ray Imaging, Ultrasound, CT, and MRI, to learn normal human anatomy and how it appears on medical images, to learn the relative strengths of the modalities, and to answer, "What am I looking at?" Course website: http://bioe220.stanford.edu

Physics, instrumentation, and algorithms for radionuclide-based medical imaging, with a focus on positron emission tomography (PET) and single photon emission computed tomography (SPECT). Topics include basic physics of photon emission from the body and detection, sensors, readout and data acquisition electronics, system design, strategies for tomographic image reconstruction, system calibration and data correction algorithms, methods of image quantification, and image quality assessment, and current developments in the field. Prerequisites: A year of university-level mathematics and physics.

Preference to graduate students. Focus is on the human gut microbiota. Students will receive instruction on computational approaches to analyze microbiome data and must complete a related project.

Physics and Engineering Principles of Multi-modality Molecular Imaging of Living Subjects (RAD 222A). Focuses on instruments, algorithms and other technologies for non-invasive imaging of molecular processes in living subjects. Introduces research and clinical molecular imaging modalities, including PET, SPECT, MRI, Ultrasound, Optics, and Photoacoustics. For each modality, lectures cover the basics of the origin and properties of imaging signal generation, instrumentation physics and engineering of signal detection, signal processing, image reconstruction, image data quantification, applications of machine learning, and applications of molecular imaging in medicine and biology research.

CT scanning geometries, production of x-rays, interactions of x-rays with matter, 2D and 3D CT reconstruction, image presentation, image quality performance parameters, system components, image artirfacts, radiation dose. Prerequisites: differential and integral calculus. Knowledge of Fourier transforms (EE261) recommended.

We will focus on design, development, and application of imaging agents that target specific cellular and molecular aspects of disease. Covers the strengths and limitations of different imaging agents and how to optimize their design for image-guided intra-operative procedures, brain imaging, probing infection, or interrogating tumor metabolism. Emphasis this year will be on clinical molecular imaging, state-of-the-art strategies for early detection of dementia, imaging response to cancer immunotherapy, and how 'Deep Learning' can be used for probe design and high-throughput automated image analysis.

This course covers the basic concepts of ultrasound neuromodulation, including basic neurophysiology, ultrasound physics and applications, and comparison to other neuromodulation modalities. The physics component will include acoustic properties of biological tissues, transducer hardware, beam formation, and beam modeling. Lectures on applications will include ultrasonic manipulation of behavior with therapeutic implications.Comparisons will be made to other neuromodulation modalities including DBS and TMS. We will include guest appearances from world-class experts in the field. Lectures will be online for asynchronous viewing. In-class components will include hands-on laboratories to demonstrate the techniques described in lecture and discussions with ourselves and the external speakers. Course website: http://bioe225.stanford.edu.

This course covers fundamental principles of magnetic resonance imaging (MRI) and spectroscopy (MRS) focusing on the analytic tools needed to understand interactions among nuclear spins, relaxation processes, and image contrast. Starting from a quantum mechanical description of NMR, we'll study J-coupling, the most mathematically tractable coupling mechanism, and its fundamental importance in MRS. Next, we will extend these concepts to develop NMR relaxation theory, which provides the foundation for analyzing multiple in vivo MRI contrast mechanisms and contrast agents..

Basics of functional magnetic resonance neuroimaging, including data acquisition, analysis, and experimental design. Journal club sections. Cognitive neuroscience and clinical applications. Prerequisites: basic physics, mathematics; neuroscience recommended.

A combined lecture and laboratory course providing an introductory treatment of probability theory, including random variables/vectors, probability distributions, calculations of expectations and variances, limit theorems, hypothesis testing, model fitting (frequentist and Bayesian perspectives), assessing goodness of fit, and quantifying uncertainty. Practical applications include linear regression, logistical regression, and their applications to biomedical data.

The design and engineering of biomolecules with biotechnological applications, with special emphasis on binders and enzymes. Overview of protein structure, function, biophysical analysis, computational design, rational engineering, and directed evolution. Discussions of examples with conceptual or medical significance. Prerequisite: Chem 141, BioE 241, or similar upon instructor approval

Laboratory and lectures. Advanced microscopy and imaging, emphasizing hands-on experience with state-of-the-art techniques. Students construct and operate working apparatus. Topics include microscope optics, Koehler illumination, contrast-generating mechanisms (bright/dark field, fluorescence, phase contrast, differential interference contrast), and resolution limits. Laboratory topics vary by year, but include single-molecule fluorescence, fluorescence resonance energy transfer, confocal microscopy, two-photon microscopy, microendoscopy, and optical trapping. Limited enrollment. Recommended: basic physics, basic cell biology, and consent of instructor.

The efficient transport of energy, mass, and momentum is essential to the normal function of living systems. Changes in these processes often result in pathological conditions. Transport phenomena are also critical to the design of instrumentation for medical applications and biotechnology. The course aims to introduce the integrated study of transport processes and their biological applications. It covers the fundamental driving forces for transport in biological systems and the biophysics across multiple length scales (molecules, cells, tissues, organs, whole organisms). Topics include chemical gradients, electrical interactions, fluid flow, mass transport. Pre-requisites: Calculus, MATLAB, basic fluid mechanics, heat transfer, solid mechanics.

The innate immune system provides the first line of defense against infections and cancers. Dysregulated innate immunity underlies neoplastic, autoimmune and neurodegenerative diseases. Many cell types (neutrophils, macrophages, NK & T cells, epithelial and endothelial cells) deploy and/or are modulated by innate immune effectors, e.g. host defense peptides. From primary literature, we discuss the breadth, structures, and functions of cellular and molecular innate immune effectors, their relation to disease, and how bioengineering these systems can benefit human health. Appropriate for grads and undergrads with knowledge of biochemistry, molecular/cell biology, biophysics, and/or bioengineering.

A practical introduction to the science of measurement. Emphasis is on the tools used to parse a biological measurement problem. Students will learn to identify and quantitatively address the critical sources of variability and bias using the core concepts of uncertainty, traceability, and validation. Case studies will illustrate use of metrology in current and emergent bioscience and engineering applications.

Synthetic biology is the fundamental science and engineering research that advances building with biology. The key idea is to make biology easier to engineer, which enables biology as a general use technology to make what is needed, where and when it is needed, on a sustainable and renewable basis. From just-add-water biotechnology to cellular therapies to distributed diagnostics for human and environmental health to transforming pollution into materials we use every day, synthetic biology holds promise to allow us to rethink how we meet human needs on a planetary scale. In this course, the field of synthetic biology and its natural scientific and engineering basis are introduced and discussed.

The physical and chemical basis of macromolecular function. Topics include: forces that stabilize macromolecular structure and their complexes; thermodynamics and statistical mechanics of macromolecular folding, binding, and allostery; diffusional processes; kinetics of enzymatic processes; the relationship of these principles to practical application in experimental design and interpretation. The class emphasizes interactive learning, and is divided among lectures, in-class group problem solving, and discussion of current and classical literature. Enrollment limited to 30. Prerequisites: Background in biochemistry and physical chemistry recommended but material available for those with deficiency in these areas; undergraduates with consent of instructor only.

Concepts and techniques for the design and implementation of engineered genetic systems. Topics covered include the quantitative exploration of tools that support (a) molecular component engineering, (b) abstraction and composition of functional genetic devices, (c) use of control and dynamical systems theory in device and systems design, (d) treatment of molecular "noise", (e) integration of DNA-encoded programs within cellular chassis, (f) designing for evolution, and (g) the use of standards in measurement, genetic layout architecture, and data exchange. Prerequisites: CME104, CME106, CHEM 33, BIO41, BIO42, BIOE41, BIOE42, and BIOE44 (or equivalents), or permission of the instructors.

Regulatory approval and reimbursement for new health technologies are critical success factors for product commercialization. This course explores the regulatory and payer environment in the U.S. and abroad, as well as common methods of health technology assessment. Students will learn frameworks to identify factors relevant to the adoption of new health technologies, and the management of those factors in the design and development phases of bringing a product to market through case studies, guest speakers from government (FDA) and industry, and a course project.

Principles of tissue engineering and design strategies for practical applications for tissue repair. Topics include tissue morphogenesis, stem cells, biomaterials, controlled drug and gene delivery, and paper discussions. Students will learn skills for lab research through interactive lectures, paper discussions and research proposal development. Students work in small teams to work on develop research proposal for authentic tissue engineering problems. Lab sessions will teach techniques for culturing cells in 3D, as well as fabricating and characterizing hydrogels as 3D cell niche.

3D bioprinting promises engineered tissues with precise structure, composition, and cellular architecture. This biofabrication technology lies at the interface of biology, bioengineering, materials science, and instrumentation. This course will teach some of the latest technologies through fundamental lectures and hands-on 3D bioprinting workshops. Student groups will embark on independent projects to innovate in any aspect or application of 3D bioprinting hardware, wetware, or software. Experience in tissue engineering ( BIOE260), instrumentation ( BIOE123), or biomaterials ( MATSCI 381) is helpful but not required.

The goal of the course is to provide students with hands-on experience in applying single-cell sequencing technology to examine marine animals with cellular resolution, both at the bench and on computers. Throughout the course, students learn how to collect animals, dissect and dissociate tissues, generate single-cell sequencing libraries, process and analyze their own data, and compare cell types across animals using the computational pipelines. This pipeline is optimized to study organisms without extensive prior knowledge and provides students with a valuable set of tools for future work in this field. This course uses a diverse set of animals in order to study the conservation and divergence of cell types and their gene regulatory programs across the animal kingdom. The course includes lectures on Mondays, and web and dry lab components, which have flexible schedules. Pre-requite: BioE219 (recommended for engineering students) or instructor consent.

As a society, we find ourselves surrounded by planetary-scale challenges ranging from lack of equitable access to health care to environmental degradation to dramatic loss of biodiversity. One common theme that runs across these challenges is the need to invent cost-effective solutions with the potential to scale. The COVID-19 pandemic provides yet another example of such a need. In this course, participants will learn principles of frugal science to design scalable solutions with a cost versus performance rubric and explore creative means to break the accessibility barrier. Using historic and current examples, we will emphasize the importance of first-principles science to tackle design challenges with everyday building blocks. Enrollment is open to all Stanford students from all schools/majors, who will team up with collaborators from across the globe to build concrete solutions to planetary-scale challenges. Come learn how to solve serious challenges with a little bit of play.

Health care is facing significant cross-industry challenges and opportunities created by a number of factors, including the increasing need for improved access to affordable, high-quality care; growing demand from consumers for greater control of their health and health data; the shift in focus from sick care to prevention and health optimization; aging demographics and the increased burden of chronic conditions; and new emphasis on real-world, measurable health outcomes for individuals and populations. Moreover, the delivery of health information and services is no longer tied to traditional brick and mortar hospitals and clinics: it has increasingly become "mobile," enabled by apps, sensors, wearables. Simultaneously, it has been augmented and often revolutionized by emerging digital and information technologies, as well as by the data that these technologies generate. This multifactorial transformation presents opportunities for innovation across the entire cycle of care, from wellness, to acute and chronic diseases, to care at the end of life. But how does one approach innovation in digital health to address these health care challenges while ensuring the greatest chance of success? At Stanford Biodesign, we believe that innovation is a process that can be learned, practiced, and perfected; and, it starts with an unmet need. In Biodesign for Digital Health, students will learn about digital health and the Biodesign needs-driven innovation process from over 50 industry experts. Over the course of 10weeks, these speakers will join the teaching team in a dynamic classroom environment that includes lectures, panel discussions, and breakout sessions. These experts represent startups, corporations, venture capital firms, accelerators, research labs, healthcare providers, and more. Student teams will take actual digital and mobile health challenges and learn how to apply Biodesign innovation principles to research and evaluate needs, ideate solutions, and objectively assess them against key criteria for satisfying the needs. Teams take a hands-on approach with the support of need coaches and other mentors. On the final day of class, teams present to a panel of digital health experts and compete for project extension funding. Friday section will be used for team projects and for scheduled workshops. Limited enrollment for this course. Students should submit their application online via: https://stanforduniversity.qualtrics.com/jfe/form/SV_dnY6nvUXMYeILkO

Computational techniques for investigating and designing the three-dimensional structure and dynamics of biomolecules and cells. These computational methods play an increasingly important role in drug discovery, medicine, bioengineering, and molecular biology. Course topics include protein structure prediction, protein design, drug screening, molecular simulation, cellular-level simulation, image analysis for microscopy, and methods for solving structures from crystallography and electron microscopy data. Prerequisites: elementary programming background (CS 106A or equivalent) and an introductory course in biology or biochemistry.

Experimental techniques to study human and animal movement including motion capture systems, EMG, force plates, medical imaging, and animation. The mechanical properties of muscle and tendon, and quantitative analysis of musculoskeletal geometry. Projects and demonstrations emphasize applications of mechanics in sports, orthopedics, and rehabilitation.

Introduction to the mechanical analysis of tissues (biomechanics), and how mechanical cues play a role in regulating tissue development, adaptation, regeneration, and aging (mechanobiology). Topics include tissue viscoelasticity, cardiovascular biomechanics, blood rheology, interstitial flow, bone mechanics, muscle contraction and mechanics, and mechanobiology of the musculoskeletal system. Undergraduates should have taken ME70 and ME80, or equivalent courses.

Mechanical cues play a critical role in development, normal functioning of cells and tissues, and various diseases. This course will cover what is known about cellular mechanotransduction, or the processes by which living cells sense and respond to physical cues such as physiological forces or mechanical properties of the tissue microenvironment. Experimental techniques and current areas of active investigation will be highlighted. This class is for graduate students only.

This course introduces computational modeling methods for cardiovascular blood flow and physiology. Topics in this course include analytical and computational methods for solutions of flow in deformable vessels, one-dimensional equations of blood flow, cardiovascular anatomy, lumped parameter models, vascular trees, scaling laws, biomechanics of the circulatory system, and 3D patient specific modeling with finite elements; course will provide an overview of the diagnosis and treatment of adult and congenital cardiovascular diseases and review recent research in the literature in a journal club format. Students will use SimVascular software to do clinically-oriented projects in patient specific blood flow simulations. Pre-requisites: CME102, ME133 and CME192.

Principles and practice of optical control of biological processes (optogenetics), emphasizing bioengineering approaches. Theoretical, historical, and current practice of the field. Requisite molecular-genetic, optoelectronic, behavioral, clinical, and ethical concepts, and mentored analysis and presentation of relevant papers. Final projects of research proposals and a laboratory component in BioX to provide hands-on training. Contact instructor before registering.

This course runs in parallel with the bioengineering departmental seminars featuring external speakers. While the seminars are open to the public, the attendance of enrolled students is required. Following each seminar, enrolled students have the opportunity to engage in an open dialogue with the speaker to discuss topics including the speaker's paths into science and their methodologies for selecting scientific problems.

This weekly seminar will explore best practices through guided discussions and workshops on effective and equitable pedagogy. Emphasis is on building practical skills for defining and accomplishing course objectives. Participants will be able to implement these actionable inclusive teaching strategies to foster a community of belonging and equity within the classroom. Activities also build personal and professional skills useful for diverse future careers.

Educational opportunities in high technology research and development labs in industry. Students engage in internship work and integrate that work into their academic program. Following internship work, students complete a research report outlining work activity, problems investigated, key results, and follow-up projects they expect to perform. Meets the requirements for curricular practical training for students on F-1 visas. Student is responsible for arranging own internship/employment and faculty sponsorship. Register under faculty sponsor's section number. All paperwork must be completed by student and faculty sponsor, as the student services office does not sponsor CPT. Students are allowed only two quarters of CPT per degree program. Course may be repeated twice.

Learn some of the fundamental principles and cutting edge research topics in molecular and cellular bioengineering, while improving your scientific communication and quantitative skills. The course is structured around weekly discussions of selected articles, and includes oral presentations, written critiques, and problem sets. Example topics: DNA sequencing, transcriptional regulation, genetic engineering, protein engineering, cell signaling, and synthetic biological circuits. In addition, you will practice computing probabilities, solving differential equations, and coding stochastic simulations (some require Python).

An engineering approach to understanding physiological phenomenon. Course introduces weekly topics in biology and human physiology paired with a mathematical approach to modeling and understanding that week's topic. No strict prerequisites. No prior background in biology is required or assumed. Familiarity with linear algebra, statistics, and programming is recommended. Course information at: http://bioe300b.stanford.edu

Preference to Bioengineering graduate students. Practical applications of biotechnology and molecular bioengineering including recombinant DNA techniques, molecular cloning, microbial cell growth and manipulation, and library screening. Emphasis is on experimental design and data analysis. Limited enrollment.

This course introduces bioengineering students to medical technology as it is used in the modern tertiary care hospital. Required elements include labs, in which small groups of students participate in hands-on experiences using advanced clinical technologies such as medical imaging, robotic surgery, and minimally invasive treatment. Other elements included shadowing clinical faculty mentors for an in-depth exposure in two clinical areas, and tours of bay area medical technology companies. Final grades will be based on attendance and final presentations. Because many course activities require observation in the clinical environment, all students are required to complete medical clearance and observer training prior to enrollment. This course is graded primarily by in-person attendance, and most course activities occur outside of regular class hours.

This course exposes students to the engineering principles and clinical application of medical devices through lectures and hands-on labs, performed in teams of two. Teams take measurements with these devices and fit their data to theory presented in the lecture. Devices covered include X-ray, CT, MRI, EEG, ECG, Ultrasound and BMI (Brain-machine interface). Prerequisites: BIOE 103 or BIOE 300B.

BIOE 301D is a hands-on laboratory class designed to teach students the basics of microfluidic device design, fabrication, operation, and troubleshooting. During the first week of class, life science and clinical labs across campus will come and pitch ideas for devices that would advance their own research. Students will then choose projects, form teams, and attempt to create devices to meet these needs via two design/build/test iterations. In the process, students will learn how to design efficient experiments, navigate uncertainty, and communicate with end users and consider their needs. BIOE 301D is an intensive 3-4 unit course that requires significant student effort and enrollment is limited to 15 students due to space constraints within the Microfluidics Foundry. To prioritize students likely to get the most out of the course, we will ask students to fill out a course application form prior to the start of spring quarter; priority will be given to students that need this course as a requirement to graduate

This course covers hands-on computational methods related to protein structural modeling. Through solving a series of curated problems, students build their own software tools and develop protocols to model and analyze structures. Topics: protein visualization, Rosetta software suite, structural prediction, homology modeling and protein design.

Computational lab course that spans research data processing workflow starting just after the point of acquisition through to computation and visualization. Topics will span Stanford specific best practices for data storage, code management, file formats, data curation, toolchain creation, interactive and batch computing, dynamic visualization, and distributed computing. Students will work with a dataset of their choosing when working through topics. Course information at: http://bioe301p.stanford.edu

In this course, students will explore feedback control mechanisms that living organisms (cells) implement to execute their function. In addition, students will learn the basics of re-engineering feedback control systems in order for cells to execute new decision making behaviors. The focus will be on molecular level feedback control mechanisms for single cells with mention of cooperative feedback control for multicellular coordination as time permits. We will incorporate principles from Systems Biology, Control and Dynamical Systems Theory with Numerical and Stochastic Simulation. Basic biological mechanisms will be reviewed within the course to provide context and conceptual understanding. Ultimately, students with interest in control theoretic applications will learn how to use notions from control theory to accurately reason about cellular behavior.

While traversing through the natural world, you effortlessly perceive and react to a rich stream of stimuli. This constantly changing stream evokes spatiotemporal patterns of spikes that propagate through your brain from one ensemble of neurons to another. An ensemble may memorize a spatiotemporal pattern at the speed of life and recall it at the speed of thought. In the first half of this course, we will discuss and model how a neural ensemble memorizes and recalls such a spatiotemporal pattern. In the second half, we will explore how neuromorphic hardware could exploit these neurobiological mechanisms to run AI not with megawatts in the cloud but rather with watts on a smartphone. Prerequisites: Either computational modeling (BIOE 101, BIOE 300B) or circuit analysis (EE 101A).

Biophysical principles of cryogenic electron microscopy and tomography from sample preparation to data collection, image reconstruction, modeling and structure validation. Molecular and cellular examples will be used to demonstrate the types of biological questions that can be answered with this imaging method.

The design and engineering of biomolecules with biotechnological applications, with special emphasis on binders and enzymes. Overview of protein structure, function, biophysical analysis, computational design, rational engineering, and directed evolution. Discussions of examples with conceptual or medical significance. Prerequisite: Chem 141, BioE 241, or similar upon instructor approval

The human body is a wondrous system. It is able to maintain healthy function despite huge molecular and environmental variations. But the circuits that enable it to function so robustly have specific fragilities that lead to diseases. This course will provide basic principles for understanding human physiological circuits and show how these principles help to understand disease processes and their dynamics. The course will include guitar songs and other enjoyable methods to improve learning.

Physical mechanisms of mechanochemical coupling in biological molecular motors, using F1 ATPase as the major model system. Applications of biochemistry, structure determination, single molecule tracking and manipulation, protein engineering, and computational techniques to the study of molecular motors.

Observation plays an integral role in scientific explorations - being the first moment that inquiry begins and actively generates questions we pursue. In this class - using table top experiments and explorations in natural philosophy - we will practice the art of observation and learn to use this framework to ask questions. Amongst other approaches - the class will heavily utilize open source microscopy based tools to broadly observe microscopic life forms from various ecosystems including the ocean (plankton) and table top soft-matter experiments to uncover fascinating phenomena visible in our daily lives. This is a project based class culminating with participants making original observations and pursuing imaginative questions that spring from above.

Cell mechanobiology topics including cell structure, mechanical models, and chemo-mechanical signaling. Review and apply methods for controlling and analyzing the biomechanics of cells using traction force microscopy, AFM, micropatterning and cell stimulation. Practice and theory for the design and application of methods for quantitative cell mechanobiology.

Combines biological knowledge and methods with quantitative engineering principles. Quantitative review of biochemistry and metabolism; recombinant DNA technology and synthetic biology (metabolic engineering). The production of protein pharaceuticals as a paradigm for the application of chemical engineering principles to advanced process development within the framework of current business and regulatory requirements. Prerequisite: CHEMENG 181 (formerly 188) or BIOSCI 41, or equivalent.

Materials design and engineering for regenerative medicine. How materials interact with cells through their micro- and nanostructure, mechanical properties, degradation characteristics, surface chemistry, and biochemistry. Examples include novel materials for drug and gene delivery, materials for stem cell proliferation and differentiation, and tissue engineering scaffolds. Prerequisites: undergraduate chemistry, and cell/molecular biology or biochemistry.

Provides an opportunity for student and faculty interaction, as well as academic credit and financial support, to medical students who undertake original research. Enrollment is limited to students with approved projects.

This course (BIOE371, MED271) exposes students to the challenges and opportunities of developing and implementing innovative health technologies to help patients around the world. Non-communicable diseases, such as metabolic and chronic respiratory disease, now account for 7 in 10 deaths worldwide, creating the need for innovative health technologies that work across diverse global markets. At the beginning of the quarter, the course will provide an overview of the dynamic global health technology industry. Next, faculty members, guest experts, and students will discuss key differences and similarities when commercializing new products in the for-profit health technology sector across six important regions: the US and Europe, China and Japan, and India and Brazil. Finally, the course will explore critical 'global health' issues that transcend international borders and how technology can be leveraged to address them. This section will culminate with an interactive debate focused on whether for-profit, nonprofit, or hybrid models are best for implementing sustainable global health solutions. The last class will be devoted to synthesis, reflection, and a discussion of career opportunities in the global health technology field.

In this two-quarter course series ( BIOE 374A/B, MED 272A/B, ME 368A/B, OIT 384/5), multidisciplinary student teams identify real-world unmet healthcare needs, invent new health technologies to address them, and plan for their implementation into patient care. During the first quarter (winter), students select and characterize an important unmet healthcare problem, validate it through primary interviews and secondary research, and then brainstorm and screen initial technology-based solutions. In the second quarter (spring), teams select a lead solution and move it toward the market through prototyping, technical re-risking, strategies to address healthcare-specific requirements (regulation, reimbursement), and business planning. Final presentations in winter and spring are made to a panel of prominent health technology experts and/or investors. Class sessions include faculty-led instruction and case studies, coaching sessions by industry specialists, expert guest lecturers, and interactive team meetings. Enrollment is by application only, and students are required to participate in both quarters of the course. Visit http://biodesign.stanford.edu/programs/stanford-courses/biodesign-innovation.html to access the application, examples of past projects, and student testimonials. More information about Stanford Biodesign, which has led to the creation of 50 venture-backed healthcare companies and has helped hundreds of student launch health technology careers, can be found at http://biodesign.stanford.edu/.

In this two-quarter course, multidisciplinary teams identify real unmet healthcare needs, invent health technologies to address them, and plan for their implementation into patient care. In second quarter, teams select a lead solution to advance through technical prototyping, strategies to address healthcare-specific requirements (IP, regulation, reimbursement), and business planning. Class sessions include faculty-led instruction, case studies, coaching sessions by experts, guest lecturers, and interactive team meetings. Enrollment is by application. Students are required to take both quarters of the course.

Addressing the systemic (Behavioral, Social, Environmental, Structural) drivers of health is a new frontier of entrepreneurship to improve global and public health at scale. In this hybrid seminar-based and experiential course, you will learn about challenges and opportunities for innovating in these areas. You will also design solutions and ventures aimed at tackling specific societal health problems. Our instructors and speakers are inspiring innovators and leaders in the fields of entrepreneurship and health. Cardinal Course certified by the Haas Center.

Startup Garage is an intensive, hands-on, project-based course where students apply human-centric design, lean startup methodology, and the Business Model Canvas to conceive, design, and field-test new business concepts that address real world needs. Teams get out of the building and interact directly with users, industry participants, and advisors to deeply understand one or more unmet customer needs. They proceed to design, prototype, and test their proposed products or services and a business model. Teams working on impact-focused ventures will apply the same methodology to address the needs of their beneficiaries. Students develop entrepreneurial skills as they learn critical, cutting-edge techniques about launching a venture. The course is offered by the Graduate School of Business. PREREQUISITE: Team application required. See details and apply at http://startupgarage.stanford.edu/details (login required).

In this intensive, hands-on project based course, teams continue to develop their ventures based on a user need that they validated in preparation for the course. They build out more elaborate versions of their prototypes and Business Model Canvas; test hypotheses about the product/service, business model, value proposition, customer acquisition, revenue generation, and fundraising; and deliver a seed round financing pitch to a panel of investors. Students develop entrepreneurial skills as they 1) Get out of the building and gather insights from users, investors, and advisors, 2) Make decisions about pivoting, 3) Work through their operating plans and unit economics, 4) Test go-to-market strategies, 5) Consider equity splits, 6) Learn term sheet negotiations, and 7) Practice their pitches. PREREQUISITE: SUSTAIN 376 or a team application. See details and apply at http://startupgarage.stanford.edu/details (login required).

Engineering approaches applied to the musculoskeletal system in the context of surgical and medical care. Fundamental anatomy and physiology. Material and structural characteristics of hard and soft connective tissues and organ systems, and the role of mechanics in normal development and pathogenesis. Engineering methods used in the evaluation and planning of orthopaedic procedures, surgery, and devices. Open to graduate students and undergraduate seniors.

Fundamental concepts in engineering materials for drug delivery. The human body is a highly interconnected network of different tissues and there are all sorts of barriers to getting pharmaceutical drugs to the right place at the right time. Topics include drug delivery mechanisms (passive, targeted), therapeutic modalities and mechanisms of action, engineering principles of controlled release and quantitative understanding of drug transport, chemical and physical characteristics of delivery molecules and assemblies, significance of biodistribution and pharmacokinetic models, toxicity of biomaterials and drugs, and immune responses.

Preference to medical and bioengineering graduate students with first preference given to Bioengineering Scholarly Concentration medical students. Bioengineering is an interdisciplinary field that leverages the disciplines of biology, medicine, and engineering to understand living systems, and engineer biological systems and improve engineering designs and human and environmental health. Students and faculty make presentations during the course. Students expected to make presentations, complete a short paper, read selected articles, and take quizzes on the material.

May be used to prepare for research during a later quarter in 392. Faculty sponsor required. May be repeated for credit.

For Bioengineering graduate students. Previous work in 391 may be required for background; faculty sponsor required. May be repeated for credit.

Bioengineering department labs at Stanford present recent research projects and results. Guest lecturers. Topics include applications of engineering to biology, medicine, biotechnology, and medical technology, including biodesign and devices, molecular and cellular engineering, regenerative medicine and tissue engineering, biomedical imaging, and biomedical computation.

Addressing climate change and environmental/social determinants of health are the next frontiers of innovation and entrepreneurship. In this seminar you will learn about scientific and economic challenges and opportunities in innovating in these areas. Speakers are inspiring entrepreneurs and leaders who are addressing planet and global health challenges through their work. The instructor, Dr. Narges Baniasadi, is a successful serial entrepreneur (co-founder of Bina, acquired by Roche) who now focuses on purposeful entrepreneurship.

Science and engineering researchers often spend days choosing a problem and years solving it. However, the problem initially chosen and subsequent course adjustments made along the project's decision tree, have an outsize influence on its likelihood of success and ultimate impact. This course will establish a framework for choosing problems and navigating a project's decision tree, emphasizing the role of intuition-building exercises and a stepwise analysis of assumptions. No prior knowledge is required.

Launching a company and navigating the complexities of the startup ecosystem can be challenging. This is particularly true in life sciences (e.g., biotech, diagnostics, tools, medtech, synthetic biology, agriculture), where technical risks are compounded with market, regulatory, and financing risks. In this seminar series, we explore the foundational principles behind starting, financing, and building successful startups, with an emphasis on academic spinouts leveraging bioengineering technologies. Guest speakers include experienced entrepreneurs, venture capital investors, senior executives from industry, as well as legal counsel and IP licensing professionals. The series will provide students with the fundamentals required to start conceptualizing their startup idea, ample networking opportunities, and will culminate in a fireside chat with recent PhD/MS graduates who have launched biotech startups. This course is open to MS/PhD/MD/JD/MBA students only. This class has a capacity limit and students must apply to be admitted. The application can be accessed via: https://forms.gle/fu62vHYkVaCNP1hK7

This course provides an overview of cutting-edge advances in biotechnology with a focus on therapeutic, health-related and agricultural topics. We will hear from academic and industrial speakers from a range of areas including novel anti-infectives, AI tools, quantitative microfluidics biotechnology research, new therapies for the treatment of addiction, neurodegenerative diseases like Alzheimer¿s disease, plant bioengineering, immuno-oncology, science journalism, and venture capital investing in biotechnology. This course is designed for students interested in pursuing a career in the biotech industry.

Principles for the design and optimization of new biological systems. Development of new enzymes, metabolic pathways, other metabolic systems, and communication systems among organisms. Example applications include the production of central metabolites, amino acids, pharmaceutical proteins, and isoprenoids. Economic challenges and quantitative assessment of metabolic performance. Pre- or corequisite: CHEMENG 355 or equivalent.

Students register through their affiliated department; otherwise register for CHEMENG 459. For specialists and non-specialists. Sponsored by the Stanford BioX Program. Three seminars per quarter address scientific and technical themes related to interdisciplinary approaches in bioengineering, medicine, and the chemical, physical, and biological sciences. Leading investigators from Stanford and the world present breakthroughs and endeavors that cut across core disciplines. Pre-seminars introduce basic concepts and background for non-experts. Registered students attend all pre-seminars; others welcome. See http://biox.stanford.edu/courses/459.html. Recommended: basic mathematics, biology, chemistry, and physics.

Direct experience with the computational tools used to create simulations of human movement. Lecture/labs on animation of movement; kinematic models of joints; forward dynamic simulation; computational models of muscles, tendons, and ligaments; creation of models from medical images; control of dynamic simulations; collision detection and contact models. Prerequisite: 281, 331A,B, or equivalent.

(Staff)

(Staff)