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In silico Tools at Early Stage of Pharmaceutical Development: Data Needs and Software Capabilities.

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Summary

Predictive dissolution modeling for immediate-release tablets is feasible in early drug development. Minimal data, including one solubility point and a surfactant model, can yield useful predictions, though buffered media require more data for accuracy.

Keywords:
ADMET predictorDDDPlusdissolutionmodel fittingsimulation

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Area of Science:

  • Pharmaceutical Science
  • Drug Development
  • Computational Chemistry

Background:

  • Early drug development necessitates rapid formulation decisions with limited active pharmaceutical ingredient (API).
  • Accurate prediction of drug release profiles is crucial for formulation platform selection.
  • Simulation software can aid in predicting immediate-release tablet performance.

Purpose of the Study:

  • To evaluate physicochemical parameters for improving simulation accuracy of immediate-release tablets.
  • To assess the minimum data requirements for predictive simulations using DDDPlus™.
  • To develop and validate models for solubility and dissolution prediction.

Main Methods:

  • Simulated dissolution profiles of ritonavir immediate-release tablets using DDDPlus™.
  • Assessed minimum data requirements using ADMET predictor and Chemicalize.
  • Developed a surfactant model for solubility enhancement and evaluated a USP transfer model.

Main Results:

  • One measured data point was sufficient for predictive simulations in DDDPlus™.
  • Simulations showed good agreement with experimental results at pH 1.0 and 6.8, but overestimated release at pH 2.0.
  • A surfactant solubility model improved dissolution predictions in relevant media.

Conclusions:

  • In silico dissolution predictions for immediate-release tablets are achievable with minimal data.
  • For weak bases, multiple solubility data points in buffered media enhance prediction accuracy.
  • Surfactant models are valuable for predicting dissolution in surfactant-containing media, emphasizing the need for measured solubility data.