IVIVC & Transport Models MCQs With Answer

Introduction: IVIVC & Transport Models MCQs With Answer is a focused quiz set designed for M.Pharm students preparing for Advanced Biopharmaceutics & Pharmacokinetics (MIP 201T). These questions emphasize in vitro–in vivo correlation (IVIVC) principles, deconvolution/convolution techniques, regulatory acceptance criteria, and mechanistic transport models including diffusion, permeability, and matrix release kinetics. The quiz blends theoretical concepts (Wagner–Nelson, Loo–Riegelman, Fick’s laws, Korsmeyer–Peppas, Higuchi) with practical considerations (sink conditions, biorelevant media, scaling, validation metrics) to strengthen problem-solving and exam readiness. Each item includes a clear correct answer to aid revision and deeper understanding.

Q1. What is the primary definition of an in vitro–in vivo correlation (IVIVC)?

• A statistical correlation between two in vitro analytical methods
• A predictive relationship between in vitro dissolution and in vivo pharmacokinetic response
• A method to directly measure drug permeability in human intestine
• A guideline for selecting dissolution apparatus

Correct Answer: A predictive relationship between in vitro dissolution and in vivo pharmacokinetic response

Q2. Which IVIVC level represents a point-to-point relationship between in vitro dissolution and in vivo absorption rate?

• Level B
• Level C
• Level A
• Level D

Correct Answer: Level A

Q3. Which deconvolution method is appropriate to obtain the full in vivo input function for a drug exhibiting two-compartment plasma kinetics?

• Wagner–Nelson method
• Loo–Riegelman method
• Higuchi numerical transform
• Korsmeyer–Peppas fitting

Correct Answer: Loo–Riegelman method

Q4. The Wagner–Nelson method for deconvolution assumes which pharmacokinetic disposition?

• Nonlinear saturable elimination
• Two-compartment linear kinetics
• One-compartment linear kinetics
• Physiologically based multi-compartmental model

Correct Answer: One-compartment linear kinetics

Q5. Which requirement is essential for application of the Loo–Riegelman method?

• The drug must have negligible first-pass metabolism
• Plasma profile must be describable by a two-compartment model
• Dissolution must follow Higuchi kinetics
• Permeability must be zero-order

Correct Answer: Plasma profile must be describable by a two-compartment model

Q6. According to regulatory guidance for IVIVC validation, the commonly cited acceptance criterion for mean absolute percent prediction error (PE) for AUC and Cmax in internal validation is:

• Mean absolute PE ≤5% for both AUC and Cmax
• Mean absolute PE ≤10% for both AUC and Cmax
• Mean absolute PE ≤20% for AUC and ≤30% for Cmax
• No specific numeric criterion is provided

Correct Answer: Mean absolute PE ≤10% for both AUC and Cmax

Q7. Which definition best describes “sink conditions” in dissolution testing?

• The dissolved drug concentration remains below a defined fraction (often ≤10%) of its saturation solubility in the medium
• The dissolution medium is saturated with drug at all times
• The dissolution medium has zero ionic strength
• The drug concentration reaches steady state immediately

Correct Answer: The dissolved drug concentration remains below a defined fraction (often ≤10%) of its saturation solubility in the medium

Q8. Which of Fick’s laws describes steady-state flux across a membrane?

• Fick’s zeroth law
• Fick’s first law
• Fick’s second law
• Fick–Henry law

Correct Answer: Fick’s first law

Q9. Apparent permeability (Papp) measured in Caco-2 or PAMPA assays is commonly expressed in which units?

• mg/L
• cm/s
• mol/L
• mL/min

Correct Answer: cm/s

Q10. The Higuchi model is best applied to describe release from which system?

• Immediate-release oral solution
• Diffusion-controlled planar or matrix systems under pseudo-steady-state conditions
• Enzyme-mediated prodrug activation in plasma
• Zero-order osmotic pump release exclusively

Correct Answer: Diffusion-controlled planar or matrix systems under pseudo-steady-state conditions

Q11. In the Korsmeyer–Peppas empirical model (Mt/M∞ = k t^n), what does the exponent n represent?

• The rate constant only
• The release exponent that indicates the drug release mechanism
• The solubility of the drug in the medium
• The porosity of the dissolution apparatus

Correct Answer: The release exponent that indicates the drug release mechanism

Q12. Deconvolution in IVIVC is primarily used to estimate which in vivo quantity?

• Apparent permeability across Caco-2 monolayers
• Fraction of dose absorbed (input function) versus time
• Solubility of the drug in gastric fluid
• The in vitro dissolution apparatus speed

Correct Answer: Fraction of dose absorbed (input function) versus time

Q13. Convolution in pharmacokinetics is used to:

• Transform a nonlinear model into linear form
• Predict plasma concentration-time profiles by combining an in vivo input function with a disposition (unit impulse) function
• Directly measure intestinal permeability in vivo
• Calculate dissolution efficiency from in vitro data

Correct Answer: Predict plasma concentration-time profiles by combining an in vivo input function with a disposition (unit impulse) function

Q14. When establishing an IVIVC between in vitro dissolution time and in vivo absorption time, a common empirical scaling approach is to use:

• Linear time scaling (multiplicative factor to map in vitro to in vivo time)
• Change the API chemical structure
• Replace the drug with a prodrug in in vitro tests
• Ignore dissolution and use permeability only

Correct Answer: Linear time scaling (multiplicative factor to map in vitro to in vivo time)

Q15. IVIVC development has been most successful for which Biopharmaceutics Classification System (BCS) category?

• BCS I (high solubility, high permeability)
• BCS II (low solubility, high permeability)
• BCS III (high solubility, low permeability)
• BCS IV (low solubility, low permeability)

Correct Answer: BCS II (low solubility, high permeability)

Q16. Presence of enterohepatic recirculation in a drug’s PK profile affects deconvolution by:

• Having no effect and deconvolution remains straightforward
• Creating multiple absorption peaks that complicate direct deconvolution and may require mechanistic compartmental modeling
• Only altering the dissolution rate in vitro
• Eliminating the need for deconvolution because bioavailability is 100%

Correct Answer: Creating multiple absorption peaks that complicate direct deconvolution and may require mechanistic compartmental modeling

Q17. Which statistical criterion is commonly used to compare different compartmental models and penalize model complexity?

• Coefficient of variation (CV)
• Akaike Information Criterion (AIC)
• Student’s t-test
• Higuchi index

Correct Answer: Akaike Information Criterion (AIC)

Q18. The unstirred water layer adjacent to a biological membrane affects measured permeability by:

• Acting as a resistance in series with membrane diffusion, thereby decreasing apparent permeability
• Increasing solubility of the drug
• Eliminating the need to consider partition coefficient
• Only influencing active transport mechanisms

Correct Answer: Acting as a resistance in series with membrane diffusion, thereby decreasing apparent permeability

Q19. To improve IVIVC predictability, which in vitro dissolution strategy is usually recommended?

• Use non-physiological solvents exclusively (e.g., 100% ethanol)
• Employ biorelevant dissolution media and hydrodynamics that simulate gastrointestinal conditions
• Reduce sampling times to a single time point
• Use a fixed pH 7.4 buffer for all drugs regardless of site of absorption

Correct Answer: Employ biorelevant dissolution media and hydrodynamics that simulate gastrointestinal conditions

Q20. Which transport model conceptually describes passive transmembrane movement as partitioning into the membrane followed by diffusion across it?

• Carrier-mediated Michaelis–Menten model
• Partition–diffusion (lipid partitioning) model
• Zero-order convective flux model
• Facilitated transport model

Correct Answer: Partition–diffusion (lipid partitioning) model

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