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Using PBPK to Simulate Target Biopredictive Dissolution Profiles for Long-Acting Injectables - Where to Begin With

Hannah Cleary1,2, Nikoletta Fotaki3, Tim Persoons2,4

  • 1EPSRC-Research Ireland Centre for Doctoral Training in Transformative Pharmaceutical Technologies, School of Pharmacy and Pharmaceutical Sciences, Trinity College Dublin, Dublin, Ireland.

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PubMed
Summary
This summary is machine-generated.

Developing biopredictive dissolution tests for long-acting injectables (LAIs) requires understanding in vivo parameters. Physiologically based pharmacokinetic (PBPK) models simulated slower LAI dissolution, guiding in vitro test development.

Keywords:
bioavailability attributesbiopredictive performance testingdissolution testinglong‐acting injectionpharmacokinetic modeling

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Area of Science:

  • Pharmaceutical Sciences
  • Pharmacokinetics
  • Drug Delivery

Background:

  • Long-acting injectables (LAIs) offer improved medication adherence and sustained drug exposure.
  • Biopredictive in vitro dissolution testing is crucial for LAI formulation development and quality control.
  • Understanding in vivo dissolution mechanisms is essential for developing accurate in vitro tests.

Purpose of the Study:

  • To quantify the impact of in vivo parameters (critical bioavailability attributes) on LAI dissolution.
  • To utilize physiologically based pharmacokinetic (PBPK) models for simulating LAI dissolution profiles.
  • To establish a design space for biopredictive in vitro dissolution testing methods for LAIs.

Main Methods:

  • Developed PBPK models for methylprednisolone acetate LAI.
  • Simulated in vivo dissolution profiles by varying critical bioavailability attributes (particle size, solubility, diffusion layer thickness, diffusion coefficient, depot volume).
  • Compared simulated in vivo dissolution with existing in vitro data.

Main Results:

  • Simulated in vivo dissolution profiles showed significantly slower drug release (80-100% dissolved over 1200 hours) compared to standard in vitro tests (approx. 90% dissolved in 90 minutes).
  • Model performance varied based on the source of attribute values (literature vs. prediction).
  • The study identified key parameters influencing dissolution rate and profile.

Conclusions:

  • In vitro dissolution conditions mimicking low fluid velocities (larger effective particle size, diffusion layer thickness) are needed for biopredictive testing.
  • PBPK modeling with plausible attribute value ranges can simulate target dissolution profiles.
  • This approach aids in developing robust in vitro dissolution test methods for LAI formulations.