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Key Principles for Developing Algorithms in Drug Resistance Classification and Evaluating Treatment Response

This discussion explores critical principles for designing algorithms that classify mutational constellations as "drug resistant" in drug development. It examines the future development of mutational algorithms and phenotypic breakpoints. Additionally, it evaluates the necessary covariates and methodologies for assessing treatment response beyond current standards. The utility of HIV genotypic and phenotypic testing in drug development is also analyzed, alongside the limitations of correlating mutational patterns with clinical outcomes. Finally, it outlines the clinical studies needed to enhance resistance testing's effectiveness.

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Key Principles for Developing Algorithms in Drug Resistance Classification and Evaluating Treatment Response

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  1. Question 1 • For use in drug development what are some important principles for developing algorithms that classify mutational constellations as “drug resistant”? How should mutational algorithms and/or phenotypic breakpoints be developed in the future?

  2. Question 2 • In addition to the covariates and methodology for assessing treatment response included in the DAP what additional covariates or methodologies should be considered when evaluating resistance data?

  3. Question 3 • Do the data presented support the clinical utility of HIV genotypic testing for use in drug development?

  4. Question 4 • Do the data presented support the clinical utility of HIV phenotypic testing for use in drug development?

  5. Question 5 • What are the limitations of the data correlating mutational patterns with clinical outcome?

  6. Question 6 • What additional clinical studies are needed to further define the clinical utility of resistance testing?

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