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Creating Adhesive and Soluble Gradients for Imaging Cell Migration with Fluorescence Microscopy

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Published on: April 4, 2013

Solubility-excipient classification gradient maps.

Alex Avdeef¹, Stefanie Bendels, Oksana Tsinman

¹pION INC, 5 Constitution Way Woburn, MA 01801, USA. aavdeef@pion-inc.com

Pharmaceutical Research

|January 25, 2007

Summary

This study developed a high-throughput assay using excipient classification maps to predict drug solubility. This method aids early screening for drug developability, improving candidate prioritization.

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Area of Science:

Pharmaceutical Sciences
Drug Discovery
Physical Chemistry

Background:

Assessing drug solubility is crucial for pharmaceutical development.
Sparingly soluble drugs present significant formulation challenges.
Existing models like the Henderson-Hasselbalch equation have limitations in predicting complex solubility behavior.

Purpose of the Study:

To evaluate the impact of various excipients on the apparent intrinsic solubility of sparingly soluble drugs.
To develop novel predictive models for drug solubility-pH dependence.
To create a visualization tool for ranking drug-excipient interactions.

Main Methods:

Utilized a high-throughput instrument for over 1,200 UV-based solubility measurements across a pH range of 3-10.
Derived new equations based on the "shift-in-pKa" method to interpret solubility-pH profiles.
Developed an intrinsic solubility-excipient classification gradient map visualization tool.

Main Results:

Excipients significantly influenced the apparent intrinsic solubility of eight model drugs (bases, neutrals, acids).
Ionizable compounds formed aggregates in excipient-free solutions, with specific aggregation patterns observed for mefenamic acid and glibenclamide.
The presence of strong excipients reduced drug aggregation, with notable exceptions.

Conclusions:

A cost-effective, compound-sparing, high-throughput assay for early drug screening is feasible.
The "self-organized" intrinsic solubility-excipient classification gradient maps effectively rank drug candidates for developability.
This approach offers a valuable tool for prioritizing molecules based on their potential for formulation via excipient strategies.