Assessing Liver Effects of Cannabidiol and Valproate Alone and in Combination Using Quantitative Systems Toxicology

In clinical trials of cannabidiol (CBD) for the treatment of seizures in patients with Dravet syndrome, Lennox-Gastaut syndrome, and tuberous sclerosis complex, elevations in serum alanine aminotransferase (ALT) > 3× the upper limit of normal were observed in some patents, but the incidence was much greater in patients who were receiving treatment with valproate (VPA) before starting CBD. To explore potential mechanisms underlying this interaction, we used DILIsym, a quantitative systems toxicology model, to predict ALT elevations in a simulated human population treated with CBD alone, VPA alone, and when CBD dosing was starting during treatment with VPA. We gathered in vitro data assessing the potential for CBD, the two major CBD metabolites, and VPA to cause hepatotoxicity via inhibition of bile acid transporters, mitochondrial dysfunction, and production of reactive oxygen species (ROS). Physiologically-based pharmacokinetic models for CBD and VPA were used to predict liver exposure. DILIsym simulations predicted dose-dependent ALT elevations from CBD treatment and this was predominantly driven by ROS production from the parent molecule. DILIsym also predicted VPA treatment to cause ALT elevations which were transient when mitochondrial biogenesis was incorporated into the model. Contrary to the clinical experience, simulation of 2 weeks treatment with VPA prior to introduction of CBD treatment did not predict an increase of the incidence of ALT elevations relative to CBD treatment alone. We conclude that the marked increased incidence of CBD-associated ALT elevations in patients already receiving VPA is unlikely to involve the three major mechanisms of direct hepatotoxicity.

Quantitative systems toxicology (QST) reproduces species differences in PF-04895162 liver safety due to combined mitochondrial and bile acid toxicity

Many compounds that appear promising in preclinical species, fail in human clinical trials due to safety concerns. The FDA has strongly encouraged the application of modeling in drug development to improve product safety. This study illustrates how DILIsym, a computational representation of liver injury, was able to reproduce species differences in liver toxicity due to PF-04895162 (ICA-105665). PF-04895162, a drug in development for the treatment of epilepsy, was terminated after transaminase elevations were observed in healthy volunteers (NCT01691274). Liver safety concerns had not been raised in preclinical safety studies. DILIsym, which integrates in vitro data on mechanisms of hepatotoxicity with predicted in vivo liver exposure, reproduced clinical hepatotoxicity and the absence of hepatotoxicity observed in the rat. Simulated differences were multifactorial. Simulated liver exposure was greater in humans than rats. The simulated human hepatotoxicity was demonstrated to be due to the interaction between mitochondrial toxicity and bile acid transporter inhibition; elimination of either mechanism from the simulations abrogated injury. The bile acid contribution occurred despite the fact that the IC50 for bile salt export pump (BSEP) inhibition by PF-04895162 was higher (311 µmol/L) than that has been generally thought to contribute to hepatotoxicity. Modeling even higher PF-04895162 liver exposures than were measured in the rat safety studies aggravated mitochondrial toxicity but did not result in rat hepatotoxicity due to insufficient accumulation of cytotoxic bile acid species. This investigative study highlights the potential for combined in vitro and computational screening methods to identify latent hepatotoxic risks and paves the way for similar and prospective studies.

Spatio-Temporal Regulation of Rac1 Mobility by Actin Islands

Rho GTPases play important roles in many aspects of cell migration, including polarity establishment and organizing actin cytoskeleton. In particular, the Rho GTPase Rac1 has been associated with the generation of protrusions at leading edge of migrating cells. Previously we showed the mobility of Rac1 molecules is not uniform throughout a migrating cell (Hinde E et. al. PNAS 2013). Specifically, the closer a Rac1 molecule is to the leading edge, the slower the molecule diffuses. Because actin-bound Rac1 diffuses slower than unbound Rac1, we hypothesized that regions of high actin concentration, called "actin islands", act as diffusive traps and are responsible for the non-uniform diffusion observed in vivo. Here, in silico model simulations demonstrate that equally spaced actin islands can regulate the time scale for Rac1 diffusion in a manner consistent with data from live-cell imaging experiments. Additionally, we find this mechanism is robust; different patterns of Rac1 mobility can be achieved by changing the actin islands' positions or their affinity for Rac1.