Correction to “Recommended approaches for integration of population pharmacokinetic modelling with precision dosing in clinical practice”

Berezowska, M, Hayden, IS, Brandon, AM, et al. Recommended approaches for integration of population pharmacokinetic modelling with precision dosing in clinical practice. Br J Clin Pharmacol. 2025; 91(4): 1064-1079. 10.1111/bcp.16335

In Section 7 (“Outlook for MIPD”), the citation to reference 115 in the phrase “hybridising NLME and ML models to improve upon MAP parameter estimates” was incorrect. This should have referred to a different publication authored by the same group.

The corrected sentence should read:

“Several proof-of-concept works have successfully demonstrated replacing popPK models with ML models for PK parameter prediction [143], hybridising NLME and ML models to improve upon MAP parameter estimates [new reference], using ML algorithms to accelerate NLME model development [144] and creating more realistic synthetic PK data by use of ML [145].”

The newly cited reference is:

Hughes JH, Keizer RJ. A hybrid machine learning/pharmacokinetic approach outperforms maximum a posteriori Bayesian estimation by selectively flattening model priors. CPT Pharmacometrics Syst Pharmacol. 2021; 10: 1150–1160. https://doi.org/10.1002/psp4.12684

We apologize for this error.