Gene expression databases for physiologically based pharmacokinetic modeling of humans and animal species.

In drug research, developing a sound understanding of the key mechanistic drivers of pharmacokinetics (PK) for new molecular entities is essential for human PK and dose predictions. Here, characterizing the absorption, distribution, metabolism, and excretion (ADME) processes is crucial for a mechanistic understanding of the drug-target and drug-body interactions. Sufficient knowledge on ADME processes enables reliable interspecies and human PK estimations beyond allometric scaling. The physiologically based PK (PBPK) modeling framework allows the explicit consideration of organ-specific ADME processes. The sum of all passive and active ADME processes results in the observed plasma PK. Gene expression information can be used as surrogate for protein abundance and activity within PBPK models. The absolute and relative expression of ADME genes can differ between species and strains. This is affecting both, the PK and pharmacodynamics and is therefore posing a challenge for the extrapolation from preclinical findings to humans. We developed an automated workflow that generates whole-body gene expression databases for humans and other species relevant in drug development, animal health, nutritional sciences, and toxicology. Solely, bulk RNA-seq data curated and provided by the Swiss Institute of Bioinformatics from healthy, normal, and untreated primary tissue samples were considered as an unbiased reference of normal gene expression. The databases are interoperable with the Open Systems Pharmacology Suite (PK-Sim and MoBi) and enable seamless access to a central source of curated cross-species gene expression data. This will increase data transparency, increase reliability and reproducibility of PBPK model simulations, and accelerate mechanistic PBPK model development in the future.

Muscle to Brain Partitioning as Measure of Transporter-Mediated Efflux at the Rat Blood-Brain Barrier and Its Implementation into Compound Optimization in Drug Discovery.

Movement of xenobiotic substances across the blood-brain barrier (BBB) is tightly regulated by various transporter proteins, especially the efflux transporters P-glycoprotein (P-gp/MDR1) and breast cancer resistance protein (BCRP). Avoiding drug efflux at the BBB is a unique challenge for the development of new central nervous system (CNS) drugs. Drug efflux at the BBB is described by the partition coefficient of unbound drug between brain and plasma (Kp,uu,brain) which is typically obtained from in vivo and often additionally in vitro measurements. Here, we describe a new method for the rapid estimation of the in vivo drug efflux at the BBB of rats: the measurement of the partition coefficient of a drug between brain and skeletal muscle (Kp,brain/muscle). Assuming a closely similar distribution of drugs into the brain and muscle and that the efflux transporters are only expressed in the brain, Kp,brain/muscle, similar to Kp,uu,brain, reflects the efflux at the BBB. The new method requires a single in vivo experiment. For 64 compounds from different research programs, we show the comparability to other approaches used to obtain Kp,uu,brain. P-gp- and BCRP-overexpressing cell systems are valuable in vitro tools for prescreening. Drug efflux at the BBB can be most accurately predicted based on a simple algorithm incorporating data from both in vitro assays. In conclusion, the combined use of our new in vivo method and the in vitro tools allows an efficient screening method in drug discovery with respect to efflux at the BBB.