← Semester 8
BP803T

Industrial Pharmacy and Facility Design (Theory)

Unit-wise topics with PDF download buttons

Add each topic PDF inside the matching files/unit-X/ folder. The button will download that PDF.
UNIT 1

AI Lifecycle, Validation & Model Auditing

Overview of AI system lifecycle: data collection, preprocessing, modeling, validation, deployment, and monitoring Download PDF
Importance of data quality in healthcare datasets Download PDF
Training vs testing vs validation datasets Download PDF
Cross-validation (conceptual understanding) Download PDF
Model drift and performance degradation, data leakage in modeling Download PDF
Documentation practices: Documentation and reproducibility Download PDF
Basics of model auditing Download PDF
UNIT 2

Regulatory Framework & Explainable AI

Overview of AI in regulatory submissions Download PDF
Explainable AI (XAI) concept Download PDF
Transparency and interpretability Download PDF
Overview of regulatory guidance on AI (EU AI Act, FDA/ CDSCO frameworks) Download PDF
Accountability in automated decision systems Download PDF
Risk-based classification of AI systems Download PDF
UNIT 3

AI in in Pharmacy Automation & Supply Chain

Overview of AI in automated dispensing systems Download PDF
Inventory prediction models Download PDF
Case studies on regression-based demand forecasting, different forecasting methods Download PDF
Medication adherence monitoring systems Download PDF
AI in supply chain risk prediction Download PDF
Predictive analytics in pharmaceutical logistics Download PDF
Advantages, limitations, legal & privacy considerations of AI in pharmacy automation. Download PDF
UNIT 4

AI in in Public Health & Real-World Data Analytics

Overview of real-world data sources (EHR, claims, surveillance systems) Download PDF
Conceptual knowledge of AI in outbreak prediction, Population-level risk modeling Download PDF
Regression models in epidemiology Download PDF
AI in vaccination forecasting Download PDF
Case studies: AI applications in epidemiological trend analysis (e.g. COVID-19 vaccination hesitancy, diabetes prevalence forecasting, antibiotic resistance trends etc.) Download PDF
UNIT 5

Guided Project - Translational AI in Pharmacy Students implement a supervised ML model (regression, logistic regression, or others) using real-world pharmacy data from domains like formulation, pharmacokinetics (PK), ADR detection, quality control (QC), automation, or public health. They validate the model, analyze regulatory implications, identify ethical risks (e.g., bias, privacy), and present a structured AI implementation plan for peer/faculty review. Suggested topics (not exhaustive): ADR prediction system, stability forecasting, demand prediction, QC failure model, disease risk prediction, medication adherence