Basma Al-Metwali1,2, Hussain Mulla2. 1. School of Pharmacy, De Montfort University, Leicester, UK. 2. Department of Pharmacy, Glenfield Hospital, University Hospitals of Leicester, Leicester, UK.
Abstract
OBJECTIVES: Doses for most drugs are determined from population-level information, resulting in a standard ?one-size-fits-all' dose range for all individuals. This review explores how doses can be personalised through the use of the individuals' pharmacokinetic (PK)-pharmacodynamic (PD) profile, its particular application in children, and therapy areas where such approaches have made inroads. KEY FINDINGS: The Bayesian forecasting approach, based on population PK/PD models that account for variability in exposure and response, is a potent method for personalising drug therapy. Its potential utility is even greater in young children where additional sources of variability are observed such as maturation of eliminating enzymes and organs. The benefits of personalised dosing are most easily demonstrated for drugs with narrow therapeutic ranges such as antibiotics and cytotoxics and limited studies have shown improved outcomes. However, for a variety of reasons the approach has struggled to make more widespread impact at the bedside: complex dosing algorithms, high level of technical skills required, lack of randomised controlled clinical trials and the need for regulatory approval. SUMMARY: Personalised dosing will be a necessary corollary of the new precision medicine initiative. However, it faces a number of challenges that need to be overcome before such an approach to dosing in children becomes the norm.
OBJECTIVES: Doses for most drugs are determined from population-level information, resulting in a standard ?one-size-fits-all' dose range for all individuals. This review explores how doses can be personalised through the use of the individuals' pharmacokinetic (PK)-pharmacodynamic (PD) profile, its particular application in children, and therapy areas where such approaches have made inroads. KEY FINDINGS: The Bayesian forecasting approach, based on population PK/PD models that account for variability in exposure and response, is a potent method for personalising drug therapy. Its potential utility is even greater in young children where additional sources of variability are observed such as maturation of eliminating enzymes and organs. The benefits of personalised dosing are most easily demonstrated for drugs with narrow therapeutic ranges such as antibiotics and cytotoxics and limited studies have shown improved outcomes. However, for a variety of reasons the approach has struggled to make more widespread impact at the bedside: complex dosing algorithms, high level of technical skills required, lack of randomised controlled clinical trials and the need for regulatory approval. SUMMARY: Personalised dosing will be a necessary corollary of the new precision medicine initiative. However, it faces a number of challenges that need to be overcome before such an approach to dosing in children becomes the norm.
Authors: Luca F Roggeveen; Tingjie Guo; Ronald H Driessen; Lucas M Fleuren; Patrick Thoral; Peter H J van der Voort; Armand R J Girbes; Rob J Bosman; Paul Elbers Journal: Front Pharmacol Date: 2020-05-15 Impact factor: 5.810