Development of a predictive algorithm for the efficacy of half-life extension strategies.

A challenge in development of peptide and protein therapeutics is rapid elimination from the body, necessitating frequent dosing that may lead to toxicities and/or poor patient compliance. To solve this issue, there has been great investment into half-life extension of rapidly eliminated drugs using approaches such as albumin binding, fusion to albumin or Fc, or conjugation to polyethylene glycol. Despite clinical successes of half-life extension products, no clear relationship has been drawn between properties of drugs and the pharmacokinetic parameters of their half-life extended analogues. In this study, non-compartmentally derived pharmacokinetic parameters (half-life, clearance, volume of distribution) were collected for 186 half-life extended drugs and their unmodified parent molecules. Statistical testing and regression analysis was performed to evaluate relationships between pharmacokinetic parameters and a matrix of variables. Multivariate linear regression models were developed for each of the three pharmacokinetic parameters and model predictions were in good agreement with observed data with r