Advisory Board
Co-Chairs: Angela Koehler, Andrew W. Lo
Academics
- Dimitris Bertsimas
- Sangeeta Bhatia
- Emery Brown
- Iain Cheeseman
- Lauren Foster
- Rupinder Grewal
- Robert Langer
- Douglas Lauffenburger
- Harvey Lodish
- Lesley Millar-Nicholson
- Phillip Sharp
Industry
- Noubar Afeyan, Flagship Pioneering
- Anthony Bogachev, BridgeBio Pharma
- Neil Kumar, BridgeBio Pharma
- Judy Lewent, Merck (retired)
- Gary Pisano, Flagship Pioneering
- Jackson Randal, BridgeBio Pharma
- Ali Satvat, KKR
Curriculum
Certificate Requirements: One foundational Sloan graduate-level course including a project-based component and three electives determined by field-specific departments, including one action-learning course.
Foundational Course: 15.S13 Special Seminar in Management (Fall Term)
The foundational CATAPULT course is organized as a hub-and-spokes model. The first half of the semester forms the common “hub”: five shared sessions focused on management, institutional, and professional issues that arise in translational work across STEM fields. In the second half of the semester, students choose a domain-specific “spoke” consisting of five focused sessions followed by a shared wrap-up session at the end.
Units: 3-0-6
Schedule: Tuesdays 4:00–7:00pm plus weekly recitations
Location: 34-101
Faculty: Andrew W. Lo
Fall 2026 Preliminary Syllabus
**Sloan bidding not required. Enrollment is by Permission of Instructor by completing a short application here.
H1 CATAPULT Hub
Class 1: STEM Career Paths and Core Skills for SuccessClass 2: Writing and Delivering STEM Topics Effectively
Class 3: Creating and Managing Your IP in Academic Settings and Navigating Conflicts of Interest
Class 4: Managing Scientific and Commercial Collaborations
Class 5: Dealing with People, Failure, and Success
H2 CATAPULT Bio Spoke
Class 6: Introduction to Career Paths in the Life SciencesClass 7: Drug Development 101
Class 8: Device, Biomarker, and Diagnostic Development 101
Class 9: Valuing Biomedical Assets
Class 10: How to Start a Biotech Company If You Must
Class 11: The Future of Translation: Course Wrap-Up and Next Steps
Eligibility Requirement(s) and Electives
Students may select their department below to view eligibility requirement(s) and the current list of pre-approved electives as determined by participating departments and fields of study. Core course requirements within participating PhD programs and departments will generally satisfy the elective requirement. In addition to the pre-approved electives listed below, students may petition to count other relevant courses toward the elective requirement.
Eligibility Requirement(s)
- Completion of qualifying exam
- Completion of qualifying exam
- Completion of qualifying exam
- Completion of qualifying exam
- Completion of qualifying exam
- Completion of preliminary exam
- Consent from thesis committee
- Completion of qualifying exam
- Completion of qualifying exam
- Completion of qualifying exam
- Completion of qualifying exam
- Completion of qualifying exam
- Completion of qualifying exam
- Completion of qualifying exam
Pre-approved Electives
- 5.64 Advances in Interdisciplinary Science in Human Health and Disease
- 5.54 Advances in Chemical Biology
- 5.49 Chemical Microbiology
- IDS.C57 Optimization Methods
- 2.156 Artificial Intelligence and Machine Learning for Engineering Design
- IDS.344 Applied Category Theory for Engineering Design
- 6.3952 AI, Decision Making, and Society
- IDS.C85 Interactive Data Visualization and Society
- IDS.522 Mapping and Evaluating New Energy Technologies
- 15.814 Marketing Innovation
- 15.563 Artificial Intelligence for Business
- 15.573 Generative AI for Managers
- 15.572 Analytics Lab: Action Learning Seminar on Analytics, Machine Learning, and the Digital Economy
- 1.818 Sustainable Energy
- 15.561 Digital Revolution: From Foundations to Future Trends
- 1.65 Atmospheric Boundary Layer Flows and Wind Energy
- 1.670 Energy Systems for Climate Change Mitigation
- 1.881 Genomics and Evolution of Infectious Disease
- Any other 12-unit restricted elective that fulfills the Biology PhD curriculum
-
Biological Engineering PhD Course Requirements
Departmental course requirements will satisfy the elective requirements for the CATAPULT certificate. - 1.861 Physics and Engineering of Renewable Energy Systems
- 15.357 Economics of Ideas, Innovation and Entrepreneurship
- 15.355 Engine Lab: Building & Scaling Deep Tech Ventures
- 15.S15 Special Seminar in Management
-
EECS Technical Qualifying Evaluation (TQE) Courses
Courses that fulfill the EECS PhD TQE requirement will fulfill the elective requirements for the CATAPULT certificate. -
Course 15 Electives
Students may also fulfill CATAPULT elective requirements with Sloan-approved electives - HST.962 Medical Product Development and Translational Biomedical Research
- HST.956 Machine Learning for Healthcare
- HST.936/7/8 Global Health Informatics to Improve Quality of Care
- HST.552 Medical Device Design
- 15.784 Operations Lab
- 15.708 Global Organizations Lab
- 15.704 IDEA Lab
- 15.480 Science and Business of Biotechnology
- 15.367 Healthcare Ventures
- 15.363 Strategic Decision Making in Life Science Ventures
- 15.232 Breakthrough Ventures: Effective Business Models in Frontier Markets
- 15.137 Case Studies and Strategies in Drug Discovery and Development
- 7.548 Advances in Biomanufacturing
- HST.953 Clinical Data Learning, Visualization, and Deployments
- 20.201 Fundamentals of Drug Development
- 15.705 Organizations Lab
- 15.482 Healthcare Finance
- 15.399 Entrepreneurship Lab
- 15.390 Entrepreneurship 101: Systematic Approach to New Venture Creation
- 15.371 Innovation Teams
- 10.595 Molecular Design and Bioprocess Development of Immunotherapies
- 15.136 Principles and Practice of Drug Development
- 15.767 Introduction to Healthcare Delivery in the US
- 15.777 Healthcare Lab: Introduction to Healthcare Delivery in the US
- 15.141 Economics and Analytics of Health Care Industries
- HST.090 Cardiovascular Pathophysiology
- HST.160 Genetics in Modern Medicine
- HST.030 Human Pathology
- 2.989 Experiential Learning in Mechanical Engineering
- 3.23 Electrical, Optical, and Magnetic Properties of Materials
- 3.21 Kinetic Processes in Materials
- 3.22 Structure and Mechanics of Materials
- 3.20 Materials at Equilibrium
- 10.65 Chemical Reactor Engineering
- 10.50 Analysis of Transport Phenomena
- 10.40 Chemical Engineering Thermodynamics
- 10.34 Numerical Methods in Chemical Engineering
- 20.420 Principles of Molecular Bioengineering
- 9.015 Molecular and Cellular Neuroscience Core I
- 9.014 Quantitative Methods and Computational Models in Neuroscience
- 9.011 Systems Neuroscience Core I
- 9.012 Cognitive Science
- 8.333 Statistical Mechanics I
- 8.321 Quantum Theory I
- 8.311 Electromagnetic Theory I
- 8.309 Classical Mechanics III
- 6.8710 Computational Systems Biology: Deep Learning in the Life Sciences
- 6.C51 & 20.C51 Modeling with Machine Learning: from Algorithms to Applications & Machine Learning for Molecular Engineering
- 6.8700 Advanced Computational Biology: Genomes, Networks, Evolution
- 7.81 Systems Biology
- 7.51 Principles of Biochemical Analysis
- 7.50 Method and Logic in Molecular Biology