How do I use this resource?
Join our community by creating a free and safe PubPub Account:
https://academicentrepreneurship.pubpub.org/resources
Then, participate in this dynamic eBook and community. Update, annotate, comment, download, upload videos and podcasts and share chapters to your own digital spaces and networks.

Academic Entrepreneurship for Medical and Health Scientists, is a free open education resource that can be used asynchronously in courses, workshops, pilot grant programs, and by individuals.

Who is an academic entrepreneur?
Faculty, staff, or students turning observations in the laboratory, clinic, and community into interventions that improve the health of individuals and the public and seeking to:

- patent and/or license their work
- spin-out or spin-in ventures based on evidence
- collaborate with industry to realize impact

5 Primary Domains: Over 500 pages of content

- Academia
- People
- Ideation
- IP/Regulation
- Finance

How do I use this book at my institution?
If you identify faculty teaching biomedical entrepreneurship at your institution (classes, workshops, etc.), we can reach out, assist with suggesting chapters relevant to their syllabus if interested, and provide optional tracking data so they can view their students’ access/use of the material. Contact us! https://www.med.upenn.edu/apps/faculty/index.php/g275/p12240

I want to contribute!
This is a living e-book which is publicly available and licensed with creative commons. It has potential for frequent updates and we welcome contributions from new authors. Contact us! https://www.med.upenn.edu/apps/faculty/index.php/g275/p12240

Other Formats:
Are you a visual learner? Try our interactive Prezi: https://www.bit.ly/AcadEnt

This course teaches the design of contemporary information systems for biological and medical data. Examples are chosen from biology and medicine to illustrate complete life cycle information systems, beginning with data acquisition, following to data storage and finally to retrieval and analysis. Design of appropriate databases, client-server strategies, data interchange protocols, and computational modeling architectures. Students are expected to have some familiarity with scientific application software and a basic understanding of at least one contemporary programming language (e.g. C, C++, Java, Lisp, Perl, Python). A major term project is required of all students. This subject is open to motivated seniors having a strong interest in biomedical engineering and information system design with the ability to carry out a significant independent project.
This course was offered as part of the Singapore-MIT Alliance (SMA) program as course number SMA 5304.

This presentation focuses on the current and novel approaches used to develop drugs in the treatment of obesity. We’ll introduce the student to the physiological regulation of appetite and satiety in relation to meals, then we’ll provide an short overview of the previous and current treatment on the market for the treatment of obesity and finally we’ll describe some of the promising novel approaches pursued for future treatment.

Course responsible: Associate Professor Signe Sørensen Torekov, MD Nicolai Wewer Albrechtsen & Professor Jens Juul Holst

This presentation provides an overview of the existing treatment available for treatment of obesity. Genetic studies have revealed that the genes contributing to development of obesity is mainly located in the brain, therefore it would be logical to tro to target the brain when pursuing drugs for the treatment of obesity. However it’s not that simple.

Course responsible: Associate Professor Signe Sørensen Torekov, MD Nicolai Wewer Albrechtsen & Professor Jens Juul Holst

This resource is a video abstract of a research paper created by Research Square on behalf of its authors. It provides a synopsis that's easy to understand, and can be used to introduce the topics it covers to students, researchers, and the general public. The video's transcript is also provided in full, with a portion provided below for preview:

"Over the past few decades, the pharmaceutical industry has shifted its focus to areas of high unmet need Such as treating cancer and rare diseases For many of these conditions, traditional approaches to clinical trial design fall short The transition therefore calls for innovative clinical and regulatory strategies that can deliver new drugs fast Advanced digital technologies now offer unprecedented opportunities to improve drug development and, by extension, patients’ lives These include capturing patient-reported outcomes facilitating accelerated regulatory approval pathways analyzing real-world data and using intelligent analytics solutions While the tools and practices for unlocking the potential of innovation abound pharma is only in the early stages of adapting them at scale Aligning the needs of patients, providers, payers, and regulators will require biopharma organizations to adapt and evolve And leveraging digital tools, data, and analytics could help them get there Lee e.."

The rest of the transcript, along with a link to the research itself, is available on the resource itself.

Healthcare Finance (15.482x) provides students with the background, resources, and framework to influence the healthcare industry. Topics include applying financial techniques such as portfolio theory, securitization, and option pricing to biomedical contexts to develop more efficient funding structures to reduce financial risks, lower the cost of capital, and bring more life-saving therapies to patients faster.
As part of the Open Learning Library, this course is free to use. You have the option to sign up and enroll if you want to track your progress, or you can view and use all the materials without enrolling.

This half-semester course introduces computational thinking through applications of data science, artificial intelligence, and mathematical models using the Julia programming language. This Spring 2020 version is a fast-tracked curriculum adaptation to focus on applications to COVID-19 responses.
See the MIT News article Computational Thinking Class Enables Students to Engage in Covid-19 Response

This course addresses the scientific basis for the development of new drugs. The first half of the semester begins with an overview of the drug discovery process, followed by fundamental principles of pharmacokinetics, pharmacodynamics, metabolism, and the mechanisms by which drugs cause therapeutic and toxic responses. The second half of the semester applies those principles to case studies and literature discussions of current problems with specific drugs, drug classes, and therapeutic targets.

This learning tool will guide students through the process of understanding real-world applications of drug delivery and how drug delivery is applied to treating infectious diseases. Students using this module should find success in self-directed learning, though they may use additional resources in the community, the guidance of teachers, the advice of scientists or biomedical professionals at DDF, or the knowledge presented in scientific literature to help them achieve their goal; though this module should provide most of the tools they will need for guidance.

This course focuses on early-stage biotechnology companies with particular emphasis on understanding the underlying science, technology, and disease targets—together with the application of novel business structures and financing methods—to facilitate drug discovery, clinical development, and greater patient access to new therapies.   
The course was created for MITx as a collaboration between the Whitehead Institute and the Sloan School of Management and is now archived on the Open Learning Library (OLL), which is free to use. You have the option to sign up and enroll in each module if you want to track your progress, or you can view and use all the materials without enrolling.