Meta-Ranker: Efficient Design of Combination Drug Products for Complex Diseases
Shreya Shirodkar, Matthew Russell, Shuran Xing, Arianna Nitzel, Franklin Vairinhos, Manish R. Patel, Irina A. Leaf, Murat Cokol, Karim Azer · IFAC-PapersOnLine · 2022
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.