MS Artificial Intelligence in Pharma Healthcare
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The MS Artificial Intelligence in Pharma Healthcare at TUF addresses the growing demand for professionals capable of operating at the intersection of technology and healthcare. As digital systems expand across hospitals and the pharmaceutical industry, this program bridges Artificial Intelligence and healthcare principles. Students gain expertise in data analysis, machine learning, digital healthcare systems, and pharmaceutical applications to support diagnostic accuracy, optimize patient care, and accelerate drug development.
Why choose MS Artificial Intelligence in Pharma Healthcare at TUF?
Choosing the MS in Artificial Intelligence in Pharma Healthcare at TUF provides a competitive edge at the intersection of technology, pharmacy, and modern medicine.
- Combine artificial intelligence, pharmaceutical science, and healthcare technologies.
- Practice with machine learning frameworks, computer vision tools, and computational drug models.
- Receive mentorship from expert faculty in computer science, pharmacy, and health domains.
- Learn regulatory guidelines, data privacy rules, and ethical standards for healthcare AI.
- Build a strong foundation for high-demand careers in health-tech, diagnostics, and smart pharma industries.
- Complete research projects focused on solving real-world healthcare and pharmaceutical challenges.
Key Skills You Will Master
Healthcare Data Analysis & Machine Learning
Digital Pharma Solutions
Medical Imaging & Computer Vision
Bioinformatics & Bio-Inspired Computing
AI Strategy & Implementation
Ethics, Safety & Regulatory Compliance
Career Outcomes
- Hospitals & Healthcare Organizations: Managing digital health platforms, diagnostic AI tools, and patient data systems.
- Pharmaceutical Companies & R&D Labs: Applying AI models to accelerate drug discovery, formulation analysis, and clinical trials.
- IT & Health-Tech Companies: Developing AI-driven healthcare products, diagnostic software, and predictive algorithms.
- Universities & Research Institutions: Pursuing academic, analytical, and advanced scientific research roles.
Program Roadmap
Explore courses roadmap in MS Artificial Intelligence in Pharma Healthcare
| Course Code | Course Title | Credit Hours | Category | Prerequisite |
|---|---|---|---|---|
| GEN-700 | ADVANCED RESEARCH METHODOLOGY | 3 (3-0) | - | - |
| AIP-701 | ARTIFICIAL INTELLIGENCE IN PHARMACEUTICAL PRODUCTION AND DISTRIBUTION | 3 (3-0) | - | - |
| ISL-105 | UNDERSTANDING OF HOLY QURAN – I | 1 (0-1) | - | - |
| - | ELECTIVE-I | 3(3-0) | - | - |
| - | ELECTIVE-II | 3(3-0) | - | - |
| Course Code | Course Title | Credit Hours | Category | Prerequisite |
|---|---|---|---|---|
| AIP-702 | ARTIFICIAL INTELLIGENCE: STRATEGIES AND APPLICATIONS | 3 (3-0) | - | - |
| AIP-703 | REGULATION, SAFETY AND ETHICS OF ARTIFICIAL INTELLIGENCE IN PHARMACEUTICALS | 3 (3-0) | - | - |
| ISL-106 | UNDERSTANDING OF HOLY QURAN – II | 1 (0-1) | - | - |
| -- | ELECTIVE – IV | 3(3-0) | - | - |
| -- | ELECTIVE–V | 3(3-0) | - | - |
| Course Code | Course Title | Credit Hours | Category | Prerequisite |
|---|---|---|---|---|
| AIP-721 | AI AND MACHINE LEARNING IN BIOINFORMATICS | 3(3-0) | - | - |
| AIP-722 | FUNDAMENTALS OF ARTIFICIAL INTELLIGENCE | 3(3-0) | - | - |
| AIP-723 | DEEP COMPUTER VISION WITH CONVOLUTIONAL NEURAL NETWORKS | 3(3-0) | - | - |
| AIP-724 | DATA TYPES AND LIFE CYCLE | 3(3-0) | - | - |
| AIP-725 | DATA IN ARTIFICIAL INTELLIGENCE | 3(3-0) | - | - |
| AIP-726 | BIO-INSPIRED COMPUTING | 3(3-0) | - | - |
| AIP-727 | DEVELOPMENT OF NEW DRUGS WITH ARTIFICIAL INTELLIGENCE | 3(3-0) | - | - |
| AIP-728 | MODEL CUSTOMIZATION AND TRAINING WITH TENSORFLOW | 3(3-0) | - | - |
| AIP-729 | PUBLIC HEALTH, EPIDEMIOLOGY | 3(3-0) | - | - |
| AIP-730 | MEDICAL IMAGING AND ARTIFICIAL INTELLIGENCE | 3(3-0) | - | - |
| AIP-731 | MACHINE LEARNING AND PATTERN RECOGNITION | 3(3-0) | - | - |
| AIP-732 | DATA MINING AND EXPLORATION | 3(3-0) | - | - |
| Course Code | Course Title | Credit Hours | Category | Prerequisite |
|---|---|---|---|---|
| AIP-720 | THESIS | 06 | - | - |
Admissions & Eligibility
BS (16 years of education) / Pharm-D or equivalent (Computer Science, IT, AI, Data Science, Pharmacy, Biotechnology, Bioinformatics, Health Sciences) with a minimum CGPA of 2.0/4.0. Requires GRE by NTS or equivalent University entry test with a minimum 50% passing score.
Next Steps
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