Quantitative prediction of human pharmacokinetic responses to drugs via fluidically coupled vascularized organ chips

Abstract

Analyses of drug pharmacokinetics (PKs) and pharmacodynamics (PDs) performed in animals are often not predictive of drug PKs and PDs in humans, and in vitro PK and PD modelling does not provide quantitative PK parameters. Here, we show that physiological PK modelling of first-pass drug absorption, metabolism and excretion in humans-using computationally scaled data from multiple fluidically linked two-channel organ chips-predicts PK parameters for orally administered nicotine (using gut, liver and kidney chips) and for intravenously injected cisplatin (using coupled bone marrow, liver and kidney chips). The chips are linked through sequential robotic liquid transfers of a common blood substitute by their endothelium-lined channels (as reported by Novak et al. in an associated Article) and share an arteriovenous fluid-mixing reservoir. We also show that predictions of cisplatin PDs match previously reported patient data. The quantitative in-vitro-to-in-vivo translation of PK and PD parameters and the prediction of drug absorption, distribution, metabolism, excretion and toxicity through fluidically coupled organ chips may improve the design of drug-administration regimens for phase-I clinical trials.

Fig. 1.. Development of a first pass multi-Organ Chip platform.

(a) Diagrammatic representations (bottom) of the Gut, Liver, and Kidney Chips containing apical parenchymal and basal vascular compartments separated by a porous matrix-coated membrane, as well as how they are fluidically linked to each other and to the AV Reservoir; photographs of the Organ Chips are shown at the top. Red arrows indicate medium flow path and direction; box with ‘I’ indicates sites where fluid was transferred by the automated liquid handling instrument between the AV Reservoir and input reservoirs of the channels of the different chips, as well as between the output and input reservoirs of different Chips. (b) Schematic of the multi-compartment reduced order (MCRO) in silico model of an individual Organ Chip. All organ chips have similar barrier configuration composed of horizontally stacked compartments with volume V shown schematically: Lower wall of the PDMS device (basal package), medium in the vascular channel (basal medium), endothelium (Endo), thin porous PDMS layer (membrane), epithelium (Epi), medical in the parenchymal channel (apical medium), and upper wall of the PDMS device (apical package). All organ devices are represented with similar mathematical equations based on drug mass balance in between the compartments, calculated for the drug flux J in between the compartments and Q, the volumetric medium flow to give the drug concentration C. Each organ device is further discretized into three axial zones (proximal, central, distal), creating a two-dimensional and less computationally demanding model to simulate a specific drug concentration over time. (c) Schematic of the first passage multi-Organ Chip linked system, where the organ-specific parenchymal epithelial cell layers of the Gut, Liver and Kidney Chips are represented by a drug-specific set of parameters for passive permeability, efflux, and metabolism determined experimentally in single Organ Chip studies and then calibrated for the linked Organ Chip platform. The direction of flow and the percentage of input flow distributions from other Organ Chips vs. the AV Reservoir are also indicated in the diagram.

Fig. 2. Mass spectrometry data and DMPK model of first pass multi-Organ Chip platform

Graphs showing nicotine levels measured over time by MS within the apical and basal channels of the linked Gut, Liver and Kidney Chips, as well as in the AV Reservoir, when nicotine was continuously infused through the lumen of the Gut chip at a dose of 396±16 μM for 84 hrs followed by a 56 hrs wash-out period (white bars) compared with predictions of the computational DMPK model (black bars). Values are also shown for the nicotine breakdown product, cotinine, in samples from the effluent of the epithelial channel of the Liver Chip (data are pooled from 3 separated experiments; error bars indicate standard deviation).

Fig. 3.. In vitro-to-in vivo translation (IVIVT) of human pharmacokinetic (PK) parameters for nicotine using the multi-Organ Chip first pass platform.

(a) Graph showing the oral dose (~400 μM) of nicotine infused into the upper parenchymal channel of the Gut Chip (gray shaded area) and nicotine levels measured in the AV Reservoir over time in the real experimental system with discrete linkages every 12 hrs and package loss into the PDMS (gray solid line) versus computational DMPK model predictions of nicotine levels in which the same results were simulated as a continuous flow system with (black solid line) or without (dashed line) package loss. (b) Predictions of nicotine levels in the AV Reservoir using the same computational DMPK model as shown in a with a clinical nicotine dose of 16.15 μM and 30 min infusion (gray shaded area) compared with the same results were simulated as a continuous flow system with (black solid line) or without (dashed line) package loss. The blue line shows that the in silico multi-Organ Chip IVIVT platform made PK predictions for nicotine that much more closely match that rapid PK dynamics of human blood nicotine values using a continuous flow simulation after it was optimized for physiological differences in cell mass and blood flow between the different organs in vivo, drug loss into the chip material, and the geometry of endothelial channels to mimic drug transport. (c) Schematics comparing the actual relative Organ Chip channel volumes, flow rates, and geometries shown in cross-section in the linked multi-Organ system (top) and the scaled values for these properties used for the IVIVT simulations (bottom). (d) Graph showing that changes in nicotine blood concentrations over time predicted by the optimized, scaled, in silico multi-Organ Chip IVIVT platform for three different oral doses (different colored dashed lines) closely match previously published blood nicotine levels measured in human patients receiving orally administered nicotine in the form of nicotine gum (blue; same curve as the blue curve in b shown at different scale), pouched snus (black) or loose snus (green) at three different doses (4, 9, and 13-16 mg, respectively). Similar results were obtained in two separate studies, each with three independent fluidically linked multi-Organ Chip systems.

Fig. 4.. Prediction of cisplatin PK and pharmacodynamic (PD) parameters using the multi-Organ Chip IVIVT platform.

(a) Diagram showing the fluidic coupling path of the Bone Marrow, Liver and Kidney Chips linked to the AV Reservoir in the multi-Organ Chip platform used to study cisplatin PK. Red arrows indicate medium flow path and direction; box with ‘I’ indicates sites where fluid was transferred by the automated liquid handling instrument between the AV Reservoir and input reservoirs of the channels of the different chips, as well as between the output and input reservoirs of different Chips. Cisplatin (160 μM) was continuously infused into the AV reservoir for 24 hrs to simulate intravenous infusion followed by a 48 hrs wash-out period. (b) Cisplatin concentrations measured over time in medium samples collected from the effluent of each chip and the AV reservoir using MS (white bars) compared with predictions of the optimized scaled DMPK model (black bars) (error bars indicate standard deviation). (c) Graph showing that changes in cisplatin concentrations in blood over time predicted by the optimized, scaled, multi-Organ Chip IVIVT platform for either 1 (black) or 3 (blue) hour infusion periods (dotted lines) closely match previously published measurements of blood cisplatin levels measured in human patients who received cisplatin injected intravenously over these times (solid lines) (similar results were obtained in three replicate experiments). (d-g) Cisplatin infusion in the multi-Organ Chip platform resulted in suppression of total neutrophil (d) and erythroid (e) cell numbers in the Bone Marrow chip, as determined by FACS analysis (error bars indicate standard error of the mean), without significantly altering (f) albumin production in the Liver Chip, shown as albumin secretion normalized to control chips, thus, recapitulating cisplatin PD in vitro. (g) Western blot analysis also revealed that cisplatin increased OCT2 and decreased Pgp levels in Kidney Chips compared to controls (similar results were obtained in 2 different experiments; GAPDH is shown as a loading control).