Compound ranking based on a new mathematical measure of effectiveness using time course data from cell-based assays

Area of Science:

• Pharmacology
• Cell Biology
• Toxicology

Background:

• The half maximal inhibitory concentration (IC₅₀) has limitations for large-scale cytotoxicity studies, especially with multiple exposure times.
• Existing methods struggle to comprehensively assess compound toxicity across diverse conditions.

Purpose of the Study:

• To propose a new, robust method for measuring drug effectiveness and cellular toxicity.
• To enable automated analysis and ranking of compounds based on their toxic effects on live cells.
• To provide a statistically sound alternative to IC₅₀ for cytotoxicity and growth promotion studies.

Main Methods:

• Developed a novel effectiveness measure comparing cell growth rates in the presence of a compound versus DMSO alone.
• Integrated all tested exposure times into a single, comparable effectiveness metric.
• Utilized linear regression for automated analysis and statistical testing of compound toxicity.

Main Results:

• The new approach measures a wider spectrum of toxicity compared to IC₅₀.
• Demonstrated the method's utility by ranking 24 novobiocin analogs by cytotoxicity against 18 cancer and 1 normal cell line.
• The method allows for an automated decision rule to identify significantly toxic compounds.

Conclusions:

• The proposed method offers a superior alternative to IC₅₀ for cytotoxicity screening and compound ranking.
• This approach facilitates automated, statistically validated assessment of drug toxicity and effectiveness.
• It is also applicable to identifying compounds that promote cell growth, serving as an alternative to EC₅₀ calculations.