Using Tiny-TIM Dissolution and In Silico Simulation to Accelerate Oral Product Development of a BCS Class II Compound

Area of Science:

• Pharmacokinetics and Drug Delivery
• Biopharmaceutics

Background:

• Oral drug delivery, while preferred, suffers from high pharmacokinetic variability.
• Changes in particle size, formulation, or manufacturing affect dissolution and absorption, particularly for BCS Class II compounds.

Purpose of the Study:

• To establish in vitro-in vivo correlations (IVIVC) using tiny-TIM dissolution data and in silico pharmacokinetic models.
• To predict oral bioavailability and food effects for an investigational drug substance.

Main Methods:

• Utilized tiny-TIM in vitro dissolution data and an in silico pharmacokinetic model.
• Established Level C IVIVC between in vivo AUC and in vitro dissolved amount (fasted/fed states).
• Established Level A IVIVC between in vivo fraction absorbed and tiny-TIM bioaccessibility (fasted/fed states).

Main Results:

• Successful establishment of Level C and Level A IVIVCs.
• tiny-TIM dissolution accurately predicted the positive food effect observed in clinical studies.
• The predictive models showed consistency with clinical findings.

Conclusions:

• IVIVC models using tiny-TIM data can reliably predict oral bioavailability and food effects.
• These predictive models hold potential to minimize animal and human studies.
• The approach can accelerate the overall drug development process.