Meta-Ranker: Efficient Design of Combination Drug Products for Complex Diseases
IFAC-PapersOnLine(2022)
摘要
Developing multi-targeting combination drug products for complex diseases is necessary to achieve appropriate efficacy benchmarks and translate into meaningful improvements for the patient. Meta-ranker is an algorithm to discover and design novel combinations to advance the leading investigational product candidate based on their effects on an array of phenotypes. Meta-ranker is leveraged during clinical development to elucidate the contribution of individual components to fulfill regulatory requirements for fixed combinations. Here, we detail the algorithm's specific steps, introduce the weight parameter, and highlight potential implications of endogenous metabolic modulators applied as combinations in a liver disease model.
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关键词
Algorithm,Complex diseases,Design,Drug discovery,Endogenous Metabolic Modulators,Fixed combination,Meta-ranker,Phenotype
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