About the Program
The Molecular Pharmacology Training Program is housed in the Department of Chemical and Systems Biology. The MPTP is a multi-departmental program that complements the training received by students in their Ph.D. degree-granting department or interdepartmental program. The MPTP provides training in the area of molecular pharmacology, with a focus on the process of drug discovery and drug development. Our mission is to provide students with expertise in basic biomedical science and an understanding of the steps required to translate their fundamental discoveries into clinical therapies. Our goal is to train future leaders in academic research, biotechnology, science/health policy, and other science-related careers.
We strongly encourage students from diverse backgrounds to apply, including but not limited to women, underrepresented minorities, first-generation students, and individuals with disabilities.
Program Requirements:
- Trainees must attend a one-day workshop and lecture pertaining to rigor and reproducibility that is part of BIOS 200: Foundations in Experimental Biology.
- Trainees are required to attend and present a poster at an annual three-day retreat. After completion of their funding term, they are required to give an oral presentation at the retreat.
- Trainees will present an annual 30-minute talk at a student/faculty research forum.
- Participate in a summer biotech industry internship or a quarter-long clinical shadowing experience with a Stanford physician-scientist.
- Participate in quarterly discussions on responsible conduct, rigor, and reproducibility in research during entire training grant period.
- Trainees meet annually with the MPTP Co-Directors, Dr. James Chen and Dr. Matthew Bogyo to discuss MPTP training experiences, career development goals, and any areas of concern.
- Participate in both annual IDP meetings and annual thesis committee meetings
- Regular meetings with faculty mentor to discuss scientific hypotheses, devise experimental approaches, and help analyze and interpret data.
- Trainees must acknowledge the MPTP T32 training grant in all publications resulting from their graduate work during or following their year(s) of support and must enter these publications into the PMCID database.
Other Program Activities:
MPTP trainees will also have access to faculty and cohort lunches, quarterly lunches with the Directors, various career development and exploration opportunities, including science communication workshops, alumni networking events, and SPARK-funded translational research projects (http://sparkmed.stanford.edu).
Required Courses are:
This course is divided into two 3-week cycles. During the first cycle, students will be developing a 2-page original research proposal, which may be used for NSF or other fellowship applications. In the second cycle, students will work in small teams and will be mentored by faculty to develop an original research project for oral presentation. Skills emphasized include: 1) reading for breadth and depth; 2) developing compelling, creative arguments; 3) communicating with the spoken and written word; 4) working in teams. Important features of the course include peer assessment, interactive joint classes, and substantial face-to-face discussion with faculty drawn from across the Biosciences programs. Shortened autumn quarter class; class meets during weeks 1 through 8 of the quarter.
Advancing a drug from discovery of a therapeutic target to human trials and commercialization. Topics include: high-throughput assay development, compound screening, lead optimization, protecting intellectual property, toxicology testing, regulatory issues, assessment of clinical need, defining the market, conducting clinical trials, project management, and commercialization issues, including approach to licensing and raising capital. Maximum units are available by taking an additional contact hour.
Continuation of CSB 240A. Maximum units are available by taking an additional contact hour. Prerequisite: CSB 240A.
How to identify and approach ethical dilemmas that commonly arise in biomedical research, issues in the practice of research such as in publication and interpretation of data, and issues raised by academic/industry ties. Contemporary debates at the interface of biomedical science and society regarding research on stem cells, bioweapons, genetic testing, human subjects, and vertebrate animals. (We anticipate that most MPTP applicants will have already fulfilled this requirement in the first year).
Statistics Requirement:
Introduction to foundations of rigorous, reproducible research in experimental biology and clinical research. Provides conceptual framework for linking hypotheses to experimental design, quantitative measurement, statistical analysis and assessment of uncertainty. Course combines lecture presentation and discussion of core concepts from statistics and reproducibility with hands-on exposure to best practices for reproducible workflows spanning design, data collection, annotation, analysis and presentation of results. Brief discussion of social, legal, and ethical issues with reproducibility in scientific practice, along with NIH grant requirements. Course provides foundations for future learning in these areas. Examples drawn from multiple areas of experimental biology and clinical research. Target audience: Students in BIOS 200 (Foundations in Experimental Biology), in Biosciences graduate programs or T32 training programs. Prerequisites: None
This course will cover the basic principles and practices underlying rigorous and reproducible biomedical research, both in the clinic and the lab. Approximately 40% of the course will cover the basic scientific and statistical principles, with an emphasis on elements of design and analysis that pose threats to reproducibility; e.g. multiplicity, selective reporting, design effects, non-random assignment, pseudo-replication and handling of outliers. The remainder of the course will focus on computational approaches to ensure that all data, code, and analyses can be captured in a reproducible workflow, to be confirmed and replicated by you in the future, by other members of your team, and by reviewers and other researchers. We will cover how to satisfy FAIR principles, version control, how to create a git repository, utilize Github and how to create a reproducible dataset. Prerequisites: Basic knowledge of R. Recommended (not required): EPI 202 or 261/262, STATS 60, or MS&E 125