Artificial Intelligence and Computational Drug Discovery and Development (MS)

The Artificial Intelligence and Computational Drug Discovery and Development (AICD3) Graduate Program is a 1.5 years (5 quarters) program leading to a MS in Artificial Intelligence and Computational Drug Discovery and Development. Students will complete 38 units of didactic courses in the first three quarters, then complete a capstone project in the following two quarters (20 weeks).

Program Description

The program will train students to apply computer science, data science, statistical analysis, machine learning, and other data-driven methods to bolster the discovery and development of new drugs and therapies. The program intends to give students the competitive edge for the most desirable jobs in the biopharmaceutical industry and in academia, both of which increasingly require interdisciplinary training.

The curriculum is carefully designed to ensure mastery in computational approaches spanning systems pharmacology, bioinformatics, physiologic-based pharmacokinetic/pharmacodynamic modeling, and pharmacogenomics, that will pave the way to transformational changes and innovation of drug discovery (e.g., identification of novel targets) and drug development (e.g., virtual human trials). Didactic courses will provide students with in-depth foundational computer science knowledge and advanced computational skills, and cover the latest technological advancements while emphasizing the ethical implications and societal impacts of AI in healthcare.

Capstone Project

The Capstone Project is required for graduation from the AI-CD3 program. It is designed and structured to allow students to gain experience applying learned tools and methodologies to drug discovery and drug development projects in an academic or industry setting. These projects provide experiential training in which students will use the computational skills and tools that they gained in their didactic curriculum in an applied project in either industry or academia. Additionally, the Capstone Project will allow students to deeply explore fields of interest and collaborate with scientists from many disciplines. It concludes with the submission and presentation (poster and oral) of the project.

Admission Requirements

Basic Qualifications

Prospective students must possess a bachelor’s degree from an accredited institution by the time classes commence. Strong computational skills in programming languages, particularly Python, are essential for academic success in the program.

Preferred Degree Backgrounds

Applicants with degrees in the following fields are encouraged to apply:

• Biology, chemistry, biochemistry, bioinformatics
• Computer science, computer engineering, electrical engineering
• Statistics, data science
• Mathematics

These degrees should demonstrate the applicant’s capability for success in technical studies.

Consideration for Non-Technical Degrees

Candidates with degrees outside the mentioned technical fields may still be considered if:

• They’ve undertaken significant relevant coursework with strong focus on STEM concepts.
• They have at least 1-2 years of experience in computational research related to drug discovery and development.
• The admissions committee assesses them as adequately prepared for graduate studies.

Additional Prerequisites

• Minimum GPA: 3.0 out of 4.0.
• Essential courses: calculus, and at least one from the following: biology, chemistry, physiology, or biochemistry.
• A strong foundational understanding of linear algebra is recommended.

Learning Outcomes

The program's learning outcomes revolve around mastering the essential skills and knowledge in AI and computational techniques for drug discovery and development. This includes proficiency in data analysis, understanding of drug design processes, ethical considerations in AI, and the ability to translate theoretical knowledge into practical solutions for real-world challenges.

Degree Requirements

Our program is 1.5 years, full-time, and in-person. It consists of five quarters:

• Three quarters of didactic coursework (43.5 units)
• Two quarters in a capstone project: fieldwork in academic or industry research (6 units)

Core Courses

The plan of study includes the following core courses:

Year 1

Fall Quarter

• AICOMPDRUG 201: Techniques in Drug Discovery (3 units)
• AICOMPDRUG 202: PK/PD Principles (4 units)
• AICOMPDRUG 203: Applied Machine Learning (5 units)
• AICOMPDRUG 223A: AI and ML for Capstone Innovation (4 units)
• BIOSTAT 272: Foundations in Biostatistical Principles and Methods (4 units) Total units: 20

Winter Quarter

• AICOMPDRUG 204: Computation and AI in Drug Discovery and Development (4 units)
• AICOMPDRUG 205: Modeling for Drug Development (4 units)
• AICOMPDRUG 223B: Practical Modules of AI and ML for the Biotech Industry (4 units)
• BIO MD INF 212: Deep Learning for Biological and Clinical Research (5 units) Total units: 17

Spring Quarter

• AICOMPDRUG 206: RWD/RWE Mining and Analysis (4 units)
• AICOMPDRUG 207: Advanced Omics Analysis and Systems Pharmacology (4 units)
• AICOMPDRUG 223C: AI and ML Research Frontiers (3 units)
• GRAD 214: Responsible Conduct of Research and Rigor & Reproducibility (1.5 units) Total units: 12.5 Total units for the program: 49.5

University of California San Francisco

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Overview:

University of California San Francisco (UCSF) is a renowned public research university located in San Francisco, California. It is a leading institution in the fields of health sciences, biomedical research, and patient care. UCSF is known for its commitment to innovation, collaboration, and its dedication to improving human health.

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Services Offered:

UCSF offers a wide range of services to its students, including:

Academic Calendar:

Provides information on academic schedules and important dates.

Career Center:

Assists students with career exploration, job searching, and professional development.

Financial Aid:

Offers financial assistance to eligible students through scholarships, grants, and loans.

General Catalog:

Contains detailed information about academic programs, policies, and resources.

Library:

Provides access to a vast collection of books, journals, databases, and other research materials.

Registrar:

Handles student records, registration, and graduation.

Student Success Guide:

Offers resources and support services to help students succeed academically and personally.

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Student Life and Campus Experience:

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Key Reasons to Study There:

World-Class Faculty:

UCSF boasts a faculty of renowned researchers, clinicians, and educators who are leaders in their fields.

Cutting-Edge Research:

The university is at the forefront of biomedical research, with groundbreaking discoveries and advancements in various areas of health sciences.

Exceptional Patient Care:

UCSF is home to a world-class medical center that provides comprehensive and compassionate care to patients.

Vibrant Campus Community:

UCSF offers a diverse and supportive campus community with a strong emphasis on collaboration and innovation.

Location in San Francisco:

The university's location in San Francisco provides students with access to a vibrant city with numerous cultural, entertainment, and career opportunities.

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Academic Programs:

UCSF offers a wide range of academic programs across its various schools, including:

School of Dentistry:

Offers programs in dentistry, oral health, and dental research.

School of Medicine:

Provides education and training in medicine, biomedical research, and public health.

School of Pharmacy:

Offers programs in pharmacy, pharmaceutical sciences, and drug discovery.

School of Nursing:

Provides education and training in nursing, nursing research, and healthcare leadership.

Graduate Division:

Offers graduate programs in various disciplines, including biomedical sciences, public health, and bioengineering.

Global Health Sciences:

Focuses on global health issues and provides training and research opportunities in this field.

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