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The correlation between a drug's dosage and its impact on a biological system is a cornerstone of pharmacology and toxicology. Conventional dose–response curves, which include graded and quantal relationships, are key to this understanding. Graded dose–response curves depict the spectrum of a biological reaction to different doses within an individual, indicating that as the drug dosage increases, so does the intensity of the response. On the other hand, quantal dose–response...
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An automated fitting procedure and software for dose-response curves with multiphasic features.

Giovanni Y Di Veroli1, Chiara Fornari1, Ian Goldlust1,2

  • 1CRUK Cambridge Institute, University of Cambridge, UK.

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A new multiphasic model and Dr Fit software improve dose-response curve analysis. This approach accurately models complex biological data, outperforming the standard Hill equation in 28% of cancer cell viability cases.

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Area of Science:

  • Pharmacology
  • Computational Biology
  • Biostatistics

Background:

  • Dose-response curves are typically modeled using the classical 4-parameter logistic Hill equation.
  • Complex biological systems can exhibit dose-response curves with multiple inflection points or combined agonist/antagonist effects, which are not adequately described by the standard Hill equation.

Purpose of the Study:

  • To develop a modified, generalized model and an automated fitting procedure for analyzing complex, multiphasic dose-response curves.
  • To provide a robust computational tool for researchers to model diverse dose-response data.

Main Methods:

  • A novel generalized model was proposed to interpret each phase of a dose-response curve as an independent, dose-dependent process.
  • An automated algorithm was developed to generate and rank dose-response models with varying multiphasic features.
  • The algorithm was implemented in the freely available Dr Fit software.

Main Results:

  • The proposed multiphasic model successfully describes complex dose-response curves.
  • Analysis of 11,650 cancer cell viability dose-response curves revealed that 28% were better fitted by a multiphasic model compared to the standard Hill model.
  • The automated fitting procedure effectively handles dose-response data with varying degrees of complexity.

Conclusions:

  • The developed multiphasic modeling approach offers a robust and flexible method for analyzing complex dose-response data.
  • The freely available Dr Fit software empowers researchers across various disciplines to accurately process and interpret their dose-response experiments.
  • This work enhances the understanding of complex pharmacological and biological responses by providing advanced modeling capabilities.