Integrating statistical genetics with nonlinear fixed effect pharmacokinetic models to advance high-throughput personalized drug therapy

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Pharmacogenetics in pharmacokinetics (PGPK) studies the relationship between variations in DNA sequence on ADME processes and other drug-related outcomes. The European Medicine Agency (EMA) has formally acknowledged the importance of PGPK in a reflection paper in 2007. For example, they recommend the testing of polymorphisms in UGT1A1 and TPMT, which encode enzymes involved in the disposition of irinotecan and mercaptopurine, respectively. In HIV antiretroviral therapy, the CYP2B6 G516T heterozygote and rare homozygote have been found to have 1.4 and 3 times higher concentrations of efavirenz whereas Plasma levels of atazanavir (recently developed protease inhibitor) were shown to be 2.8 and 3.5 higher in patients with the common homozygote than in heterozygotes or rare homozygotes for the MDR1 C3435T variant.About 30 years ago, nonlinear mixed effects (NLME) models were introduced to the biomedical field and have substantially improved the information learned from preclinical and clinical pharmacokinetic (PK) trials. Indeed, NLME models allow quantification of parameters influencing the complex physiological processes underlying the dose-response relationship. Recently the NLME modelling community has shown a growing interest in multiple single nucleotide polymorphisms (SNPs) analyses. However, the nonlinear structure of the PK models and the potential of association from each SNP to one or more physiological parameters represent great statistical and computational challenges. This research project aims at bridging the gap between the analysis of PK data and the growing body of genetics information by integrating the cutting-edge methods developed in genetic statistics into the NLME framework required to handle pharmacokinetic profiles. The computational burden, robustness and power of the statistical methods under study will be assessed on the basis of simulations (aims 1 and 2). Further the statistical developments will be applied to the analysis of PGPK studies performed in both public and industrial projects (aim 3).This research project will be conducted by Dr. Julie Bertrand under the supervision of Pr. David Balding and involves multiple public and industrial collaborations including the University College London (UCL) in the UK, the French National Agency of research in AIDS (ANRS) in France and the pharmaceutical company Servier in France.