BP101T Practical Experiments & Viva Questions
Comprehensive practical laboratory experiments and frequently asked oral viva voce questions with model answers for Basics of Python Programming for Pharmaceutical Sciences (BP101T) following PCI 2026 academic standards.
🔬 Prescribed Laboratory Practical Experiments
Practical 1: Python IDE Setup and Basic Arithmetic Solvers
Objective: Install Python 3 and configure VS Code. Write programs to solve basic pharmaceutical dilution equations (C1V1 = C2V2).
Practical 2: Pediatric Posology Dosage Calculators
Objective: Implement Young's, Dilling's, Clark's, and Fried's rules as automated command-line and interactive dosage solvers.
Practical 3: Pharmacokinetic Concentration-Time Curve Plotting
Objective: Use Matplotlib to plot Cp vs t data, calculate AUC using trapezoidal rule, and annotate Cmax and Tmax.
Practical 4: Tablet Weight Variation and Statistical QC
Objective: Write a Pandas program to evaluate 20 tablet weights against Indian Pharmacopoeia percentage deviation limits.
High-Yield Oral Viva Voce Questions & Model Answers
What is the key advantage of Python over C/C++ for pharmacy students?
Python has a simple, readable syntax and extensive scientific libraries (NumPy, SciPy, Matplotlib) that allow rapid mathematical modeling without low-level memory management.
How do you convert string input from input() to float for dosage calculation?
By wrapping the input in float(), e.g., adult_dose = float(input('Enter adult dose in mg: ')).
What is similarity factor f2 in dissolution profile comparison?
f2 is a logarithmic reciprocal square root transformation of sum of squared error and is used to measure the similarity in percentage dissolution between reference and test batches (values between 50-100 indicate equivalence).