Artificial Intelligence for Drug Development

AI for Drug Development, Master’s

Degree Offered

MS

Program Description

The role of artificial intelligence (AI) in drug development is transformative, enhancing the capabilities of pharmaceutical leaders and researchers. The key focus of this 30-credit MS program will be on AI-enabled Predictive Analytics. As manual analysis of expanding patient data becomes impractical, AI emerges as a powerful tool to augment existing methodologies. It has already revolutionized drug development, treatment optimization, and patient care. In drug development, AI technologies like natural language processing and machine learning play a crucial role in accelerating processes. The AI for Drug Development Program aims to equip professionals with a comprehensive understanding of AI's applications, limitations, and opportunities in pharmaceuticals. Participants explore techniques across various stages, from setting drug development strategy to clinical trial optimization, empowering them to effectively leverage AI for more efficient drug development.

Learning Outcomes

After completing this degree, the graduate will be able to:

1. Develop a deep understanding of artificial intelligence (AI) and machine learning (ML) principles and their applications in drug development.
2. Acquire advanced knowledge of drug development to effectively apply AI in these areas.
3. Gain proficiency in data analytics and bioinformatics techniques for analyzing large-scale biological and clinical data sets.
4. Learn to integrate AI-driven approaches into preclinical and clinical development processes, including patient selection and trial design.
5. Develop skills in regulatory intelligence specific to AI applications in drug development.
6. Collaborate with industry partners on real-world projects to gain practical experience in applying AI to drug development challenges.
7. Cultivate leadership and communication skills to effectively convey AI-driven insights to interdisciplinary teams and stakeholders.
8. Explore ethical and societal implications of AI in drug development, including privacy, bias, and transparency.
9. Prepare for diverse career paths in pharmaceutical industry, academia, regulatory agencies, and AI-driven healthcare startups.
   
   

 

Program Admission

Applications are accepted for fall and spring admission dates. All candidates applying for admission must meet the minimum qualifications and standards established by the Graduate School, which are outlined in the Admissions section of this catalog. A letter of interest including personal goals, resume/CV, and one letter of recommendation are required.

Admission to this program is selective. A U.S. bachelor’s degree or its equivalent from a non-U.S. educational institution is required. No specific undergraduate course of study is required or recommended. The Graduate Record Examination (GRE) is not required. International applicants must provide acceptable results of the Test of English as a Foreign Language (TOEFL) or the International English Language Testing System (IELTS) exam. 

Degree Requirements

Required Courses

AIDD 601	Introduction to Drug Development	3
AIDD 602	AI Methodology I	4
AIDD 603	AI Methodology II	4
AIDD 604	Drug Development Strategy	4
AIDD 605	Application of AI/ML to Pharmacovigilance	4
AIDD 606	Precision Medicine	4
AIDD 607	Optimizing Clinical Research	4
PHAR 758	SPECIAL TOPICS (PROJECT)	1 TO 7
Total Credit Hours:		30

Students will take 3 Credits of PHAR 758

Details are given in the Course Descriptions part of this catalog.