Integrated PK/PD Modeling Relates Smoothened Inhibitor Biomarkers to The Heterogeneous Intratumor Disposition of Cetuximab in Pancreatic Cancer Tumor Models

Therapeutic antibodies have shown little efficacy in the treatment of pancreatic ductal adenocarcinomas (PDAC). Tumor desmoplasia, hypovascularity, and poor perfusion result in insufficient tumor cell exposure, contributing to treatment failure. Smoothened inhibitors of hedgehog signaling (sHHi) increase PDAC tumor permeability, perfusion, and drug delivery, and provide a tool to develop a quantitative, mechanistic understanding as to how the temporal dynamics of tumor priming can impact intratumor distribution of monoclonal antibodies (mAb). A linked pharmacokinetic (PK)/pharmacodynamic (PD) model was developed to integrate the plasma and tumor PK of a sHHi priming agent with its effects upon downstream stromal biomarkers Gli1, hyaluronic acid, and interstitial fluid pressure in PDAC patient-derived xenograft (PDX) tumors. In parallel, in situ tumor concentrations of cetuximab (CTX: anti-epidermal growth factor receptor; EGFR) were quantified as a marker for tumor delivery of mAb or antibody-drug conjugates. A minimal, physiologically-based pharmacokinetic (mPBPK) model was constructed to link sHHi effects upon mechanistic effectors of tumor barrier compromise with the intratumor distribution of CTX, and CTX occupancy of EGFR in tumors. Integration of the mPBPK model of mAb deposition and intratumor distribution with the PK/PD model of tumor responses to priming not only identified physiological parameters that are critical for tumor antibody distribution, but also provides insight into dosing regimens that could achieve maximal tumor disposition of therapeutic antibodies under conditions of transient PDAC tumor permeability barrier compromise that mechanistically-diverse tumor priming strategies may achieve.

Effects of mercury exposure on fetal body burden and its association with infant growth

Several studies have been conducted among South Korean to investigate effects of high blood mercury (Hg) levels. In this study fetal body burden of Hg in 344 pregnant women were estimated using a physiologically-based pharmacokinetic model (PBPK) and its associative effects on the growth of infants were analyzed. The association between cord blood Hg and growth variables at birth was analyzed based on parameters such as the sex of the newborn, living area, maternal age group, gestation day, maternal body mass index . We investigated the effects of Hg on infant growth through follow-ups, using a non-linear mixed model. The mean Hg levels in maternal and cord blood were 4.47 μg/L and 7.35 μg/L, respectively. Among the subjects, the corresponding fetal body burden for Methylmercury ranged between 26.3-86.9 mg. Cord blood Hg levels positively correlated with length at birth. Furthermore, the high cord blood group showed greater growth rates compared to the low cord blood group. Therefore, we suggest that pregnant women should make efforts to mitigate exposures to Hg, specifically from diet. Further research is suggested to investigate the relationship between the follow-up growth of the infants and Hg levels, considering fish consumption, diet information, and other environmental pollutants.

Application of physiologically-based pharmacokinetic models for therapeutic proteins and other novel modalities

The past two decades have seen diversification of drug development pipelines and approvals from traditional small molecule therapies to alternative modalities including monoclonal antibodies, engineered proteins, antibody drug conjugates (ADCs), oligonucleotides and gene therapies. At the same time, physiologically-based pharmacokinetic (PBPK) models for small molecules have seen increased industry and regulatory acceptance.This review focusses on the current status of the application of PBPK models to these newer modalities and give a perspective on the successes, challenges and future directions of this field.There is greatest experience in the development of PBPK models for therapeutic proteins, and PBPK models for ADCs benefit from prior experience for both therapeutic proteins and small molecules. For other modalities, the application of PBPK models is in its infancy.Challenges are discussed and a common theme is lack of availability of physiological and experimental data to characterise systems and drug parameters to enable a priori prediction of pharmacokinetics. Furthermore, sufficient clinical data are required to build confidence in developed models.The PBPK modelling approach provides a quantitative framework for integrating knowledge and data from multiple sources and can be built on as more data becomes available.

Impact of route-dependent phase-II gut metabolism and enterohepatic circulation on the bioavailability and systemic disposition of resveratrol in rats and humans: A comprehensive whole body physiologically-based pharmacokinetic modeling

Resveratrol, a natural polyphenolic phytoalexin, is a dietary supplement that improves the outcomes of metabolic, cardiovascular, and other age-related diseases due to its diverse pharmacological activities. Although there have been several preclinical and clinical investigations of resveratrol, the contributions of gut phase-II metabolism and enterohepatic circulation to the oral bioavailability and pharmacokinetics of resveratrol remain unclear. Furthermore, a physiologically-based pharmacokinetic (PBPK) model that accurately describes and predicts the systemic exposure profiles of resveratrol in clinical settings has not been developed. Experimental data were acquired from several perspectives, including in vitro protein binding and blood distribution, in vitro tissue S9 metabolism, in situ intestinal perfusion, and in vivo pharmacokinetics and excretion studies. Using these datasets, an in-house whole-body PBPK model incorporating route-dependent phase-II (glucuronidation and sulfation) gut metabolism and enterohepatic circulation processes was constructed and optimized for chemical-specific parameters. The developed PBPK model aligned with the observed systemic exposure profiles of resveratrol in single and multiple dosing regimens with an acceptable accuracy of 0.538-0.999-fold errors. Furthermore, the model simulations elucidated the substantial contribution of gut first-pass metabolism to the oral bioavailability of resveratrol and suggested differential effects of enterohepatic circulation on the systemic exposure of resveratrol between rats and humans. After partial modification and verification, our proposed PBPK model would be valuable to optimize dosage regimens and predict food-drug interactions with resveratrol-based natural products in various clinical scenarios.

Diagnostic biomarker kinetics: how brain-derived biomarkers distribute through the human body, and how this affects their diagnostic significance: the case of S100B

Blood biomarkers of neurological diseases are often employed to rule out or confirm the presence of significant intracranial or cerebrovascular pathology or for the differential diagnosis of conditions with similar presentations (e.g., hemorrhagic vs. embolic stroke). More widespread utilization of biomarkers related to brain health is hampered by our incomplete understanding of the kinetic properties, release patterns, and excretion of molecules derived from the brain. This is, in particular, true for S100B, an astrocyte-derived protein released across the blood–brain barrier (BBB). We developed an open-source pharmacokinetic computer model that allows investigations of biomarker’s movement across the body, the sources of biomarker’s release, and its elimination. This model was derived from a general in silico model of drug pharmacokinetics adapted for protein biomarkers. We improved the model’s predictive value by adding realistic blood flow values, organ levels of S100B, lymphatic and glymphatic circulation, and glomerular filtration for excretion in urine. Three key variables control biomarker levels in blood or saliva: blood–brain barrier permeability, the S100B partition into peripheral organs, and the cellular levels of S100B in astrocytes. A small contribution to steady-state levels of glymphatic drainage was also observed; this mechanism also contributed to the uptake of organs of circulating S100B. This open-source model can also mimic the kinetic behavior of other markers, such as GFAP or NF-L. Our results show that S100B, after uptake by various organs from the systemic circulation, can be released back into systemic fluids at levels that do not significantly affect the clinical significance of venous blood or salivary levels after an episode of BBB disruption.

Bayesian population physiologically-based pharmacokinetic model for robustness evaluation of withdrawal time in tilapia aquaculture administrated to florfenicol

The antimicrobial residues of aquacultural production is a growing public concern, leading to reexamine the method for establishing robust withdrawal time and ensuring food safety. Our study aims to develop the optimizing population physiologically-based pharmacokinetic (PBPK) model for assessing florfenicol residues in the tilapia tissues, and for evaluating the robustness of the withdrawal time (WT). Fitting with published pharmacokinetic profiles that experimented under temperatures of 22 and 28 °C, a PBPK model was constructed by applying with the Bayesian Markov chain Monte Carol (MCMC) algorithm to estimate WTs under different physiological, environmental and dosing scenarios. Results show that the MCMC algorithm improves the estimates of uncertainty and variability of PBPK-related parameters, and optimizes the simulation of the PBPK model. It is noteworthy that posterior sets generated from temperature-associated datasets to be respectively used for simulating residues under corresponding temperature conditions. Simulating the residues under regulated regimen and overdosing scenarios for Taiwan, the estimated WTs were 12-16 days at 22 °C and 9-12 days at 28 °C, while for the USA, the estimated WTs were 14-18 and 11-14 days, respectively. Comparison with the regulated WT of 15 days, results indicate that the current WT has well robustness and resilience in the environment of higher temperatures. The optimal Bayesian population PBPK model provides effective analysis for determining WTs under scenario-specific conditions. It is a new insight into the increasing body of literature on developing the Bayesian-PBPK model and has practical implications for improving the regulation of food safety.

Development of a physiologically-based pharmacokinetic model for ocular disposition of monoclonal antibodies in rabbits

Development of protein therapeutics for ocular disorders, particularly age-related macular degeneration (AMD), is a highly competitive and expanding therapeutic area. However, the application of a predictive and translatable ocular PK model to better understand ocular disposition of protein therapeutics, such as a physiologically-based pharmacokinetic (PBPK) model, is missing from the literature. Here, we present an expansion of an antibody platform PBPK model towards rabbit and incorporate a novel anatomical and physiologically relevant ocular component. Parameters describing all tissues, flows, and binding events were obtained from existing literature and fixed a priori. First, translation of the platform PBPK model to rabbit was confirmed by evaluating the model's ability to predict plasma PK of a systemically administered exogenous antibody. Then, the PBPK model with the new ocular component was validated by estimation of serum and ocular (i.e. aqueous humor, retina, and vitreous humor) PK of two intravitreally administered monoclonal antibodies. We show that the proposed PBPK model is capable of accurately (i.e. within twofold) predicting ocular exposure of antibody-based drugs. The proposed PBPK model can be used for preclinical-to-clinical translation of antibodies developed for ocular disorders, and assessment of ocular toxicity for systemically administered antibody-based therapeutics.

PBPK modeling of CYP3A and P-gp substrates to predict drug-drug interactions in patients undergoing Roux-en-Y gastric bypass surgery

Roux-en-Y gastric bypass surgery (RYGBS) is an effective surgical intervention to reduce mortality in morbidly obese patients. Following RYGBS, the disposition of drugs may be affected by anatomical alterations and changes in intestinal and hepatic drug metabolizing enzyme activity. The aim of this study was to better understand the drug-drug interaction (DDI) potential of CYP3A and P-gp inhibitors. The impacts of RYGBS on the absorption and metabolism of midazolam, acetaminophen, digoxin, and their major metabolites were simulated using physiologically-based pharmacokinetic (PBPK) modeling. PBPK models for verapamil and posaconazole were built to evaluate CYP3A- and P-gp-mediated DDIs pre- and post-RYGBS. The simulations suggest that for highly soluble drugs, such as verapamil, the predicted bioavailability was comparable pre- and post-RYGBS. For verapamil inhibition, RYGBS did not affect the fold-change of the predicted inhibited-to-control plasma AUC ratio or predicted inhibited-to-control peak plasma concentration ratio for either midazolam or digoxin. In contrast, the predicted bioavailability of posaconazole, a poorly soluble drug, decreased from 12% pre-RYGBS to 5% post-RYGBS. Compared to control, the predicted posaconazole-inhibited midazolam plasma AUC increased by 2.0-fold pre-RYGBS, but only increased by 1.6-fold post-RYGBS. A similar trend was predicted for pre- and post-RYGBS inhibited-to-control midazolam peak plasma concentration ratios (2.0- and 1.6-fold, respectively) following posaconazole inhibition. Absorption of highly soluble drugs was more rapid post-RYGBS, resulting in higher predicted midazolam peak plasma concentrations, which was further increased following inhibition by verapamil or posaconazole. To reduce the risk of a drug-drug interaction in patients post-RYGBS, the dose or frequency of object drugs may need to be decreased when administered with highly soluble inhibitor drugs, especially if toxicities are associated with plasma peak concentrations.

Drug dosing during pregnancy-opportunities for physiologically based pharmacokinetic models

Drugs can have harmful effects on the embryo or the fetus at any point during pregnancy. Not all the damaging effects of intrauterine exposure to drugs are obvious at birth, some may only manifest later in life. Thus, drugs should be prescribed in pregnancy only if the expected benefit to the mother is thought to be greater than the risk to the fetus. Dosing of drugs during pregnancy is often empirically determined and based upon evidence from studies of non-pregnant subjects, which may lead to suboptimal dosing, particularly during the third trimester. This review collates examples of drugs with known recommendations for dose adjustment during pregnancy, in addition to providing an example of the potential use of PBPK models in dose adjustment recommendation during pregnancy within the context of drug-drug interactions. For many drugs, such as antidepressants and antiretroviral drugs, dose adjustment has been recommended based on pharmacokinetic studies demonstrating a reduction in drug concentrations. However, there is relatively limited (and sometimes inconsistent) information regarding the clinical impact of these pharmacokinetic changes during pregnancy and the effect of subsequent dose adjustments. Examples of using pregnancy PBPK models to predict feto-maternal drug exposures and their applications to facilitate and guide dose assessment throughout gestation are discussed.

Physiologically-based pharmacokinetic and pharmacodynamic models for gemcitabine and birinapant in pancreatic cancer xenografts

The anticancer effects of combined gemcitabine and birinapant were demonstrated as synergistic in PANC-1 cells in vitro. In this study, pharmacokinetic information derived from experiments and the literature was utilized to develop full physiologically-based pharmacokinetic (PBPK) models that characterize individual drugs. The predicted intra-tumor drug concentrations were used as the driving force within a linked PBPK/PD model for treatment-mediated changes in tumor volume in a xenograft mouse model. The efficacy of the drug combination in vivo was evaluated mathematically as exhibiting additivity. The network model developed for drug effects in the in vitro cell cultures was applied successfully to link the in vivo tumor drug concentrations with tumor growth inhibition, incorporating more mechanistic features and accounting for disparate drug interaction outcomes in vitro and in vivo.

Improving the clinical management of traumatic brain injury through the pharmacokinetic modeling of peripheral blood biomarkers

Background

Blood biomarkers of neurovascular damage are used clinically to diagnose the presence severity or absence of neurological diseases, but data interpretation is confounded by a limited understanding of their dependence on variables other than the disease condition itself. These include half-life in blood, molecular weight, and marker-specific biophysical properties, as well as the effects of glomerular filtration, age, gender, and ethnicity. To study these factors, and to provide a method for markers’ analyses, we developed a kinetic model that allows the integrated interpretation of these properties.

Methods

The pharmacokinetic behaviors of S100B (monomer and homodimer), Glial Fibrillary Acidic Protein and Ubiquitin C-Terminal Hydrolase L1 were modeled using relevant chemical and physical properties; modeling results were validated by comparison with data obtained from healthy subjects or individuals affected by neurological diseases. Brain imaging data were used to model passage of biomarkers across the blood–brain barrier.

Results

Our results show the following: (1) changes in biomarker serum levels due to age or disease progression are accounted for by differences in kidney filtration; (2) a significant change in the brain-to-blood volumetric ratio, which is characteristic of infant and adult development, contributes to variation in blood concentration of biomarkers; (3) the effects of extracranial contribution at steady-state are predicted in our model to be less important than suspected, while the contribution of blood–brain barrier disruption is confirmed as a significant factor in controlling markers’ appearance in blood, where the biomarkers are typically detected; (4) the contribution of skin to the marker S100B blood levels depends on a direct correlation with pigmentation and not ethnicity; the contribution of extracranial sources for other markers requires further investigation.

Conclusions

We developed a multi-compartment, pharmacokinetic model that integrates the biophysical properties of a given brain molecule and predicts its time-dependent concentration in blood, for populations of varying physical and anatomical characteristics. This model emphasizes the importance of the blood–brain barrier as a gatekeeper for markers’ blood appearance and, ultimately, for rational clinical use of peripherally-detected brain protein.

Electronic supplementary material

The online version of this article (doi:10.1186/s12987-016-0045-y) contains supplementary material, which is available to authorized users.

Population physiologically-based pharmacokinetic model incorporating lymphatic uptake for a subcutaneously administered pegylated peptide

PURPOSE

Physiologically-based pharmacokinetic (PBPK) models provide a rational mechanistic approach for predicting the time course of macromolecules in plasma. Population PBPK models for large molecules necessitate incorporation of lymphatic circulation to mechanistically account for biodistribution. Moreover, characterization of subcutaneous absorption requires consideration of the microvascular transit from the injection site to the systemic circulation. A PBPK model for a pegylated peptide conjugate, previously developed for primates, was modified to describe the lymphatic uptake in a population of humans by incorporation of interindividual variability in the lymphatic circulation and a unique lymphatic drainage compartment (LDC). The model was then used to simulate the time course of the drug in a population of humans and compared to the same drug administered to a group of human subjects participating in a first-in-human study.

METHODS

Organ, blood and lymph masses for the population were sampled from either normal or log-normal distributions. Blood flows were calculated for each organ based on mean organ perfusion per gram of organ tissue and lymphatic flow was set as a fixed fraction of blood flow. Interindividual variability in lymphatic volume was assumed to be similar to that of blood volume. The volume of the LDC was parameterzed as a fraction of the injection volume. Sensitivity analysis was performed to study uncertain parameters and distribution assumptions.

RESULTS

The population generator was capable of simulating a virtual population incorporating the lymphatic circulation. Incorporation of a LDC resulted in similar line shape relative to the observed data and incorporation of anthropometric variability accounted for individual differences in the absorption and elimination phases across all dose cohorts. Line shape was sensitive to the inclusion of LDC while peak and elimination portions of the time course were influenced by the magnitude of variance assumed for blood volume and renal clearance, respectively.

CONCLUSION

Lymphatic circulation can be incorporated into a population PBPK model assuming similar interindividual variability as observed for blood volume. Incorporation of an LDC, where the volume of this transit compartment is proportional to the SC injection volume may be an important mechanistic means of predicting the transit from the SC depot to the systemic circulation.

Physiologically Based Pharmacokinetic Model for Long-Circulating Inorganic Nanoparticles

A physiologically based pharmacokinetic model was developed for accurately characterizing and predicting the in vivo fate of long-circulating inorganic nanoparticles (NPs). This model is built based on direct visualization of NP disposition details at the organ and cellular level. It was validated with multiple data sets, indicating robust inter-route and interspecies predictive capability. We suggest that the biodistribution of long-circulating inorganic NPs is determined by the uptake and release of NPs by phagocytic cells in target organs.

Bayesian evaluation of a physiologically-based pharmacokinetic (PBPK) model of long-term kinetics of metal nanoparticles in rats

Biomathematical modeling quantitatively describes the disposition of metal nanoparticles in lungs and other organs of rats. In a preliminary model, adjustable parameters were calibrated to each of three data sets using a deterministic approach, with optimal values varying among the different data sets. In the current effort, Bayesian population analysis using Markov chain Monte Carlo (MCMC) simulation was used to recalibrate the model while improving assessments of parameter variability and uncertainty. The previously-developed model structure and some physiological parameter values were modified to improve physiological realism. The data from one of the three previously-identified studies and from two other studies were used for model calibration. The data from the one study that adequately characterized mass balance were used to generate parameter distributions. When data from a second study of the same nanomaterial (iridium) were added, the level of agreement was still acceptable. Addition of another data set (for silver nanoparticles) led to substantially lower precision in parameter estimates and large discrepancies between the model predictions and experimental data for silver nanoparticles. Additional toxicokinetic data are needed to further evaluate the model structure and performance and to reduce uncertainty in the kinetic processes governing in vivo disposition of metal nanoparticles.

Species extrapolation of life-stage physiologically-based pharmacokinetic (PBPK) models to investigate the developmental toxicology of ethanol using in vitro to in vivo (IVIVE) methods

To provide useful alternatives to in vivo animal studies, in vitro assays for dose-response assessments of xenobiotic chemicals must use concentrations in media and target tissues that are within biologically-plausible limits. Determining these concentrations is a complex matter, which can be facilitated by applying physiologically-based pharmacokinetic (PBPK) models in an in vitro to in vivo extrapolation (IVIVE) paradigm. We used ethanol (EtOH), a ubiquitous chemical with defined metrics for in vivo and in vitro embryotoxicity, as a model chemical to evaluate this paradigm. A published series of life-stage PBPK models for rats was extended to mice, yielding simulations that adequately predicted in vivo blood EtOH concentrations (BECs) from oral, intraperitoneal, and intravenous routes in nonpregnant and pregnant adult mice. The models were then extrapolated to nonpregnant and pregnant humans, replicating BEC data within a factor of two. The rodent models were then used to conduct IVIVEs for rodent and whole-embryo culture embryotoxicity data (neural tube closure defects, morphological changes). A second IVIVE was conducted for exposure scenarios in pregnant women during critical windows of susceptibility for developmental toxicity, such as the first 6-to-8 weeks (prerecognition period) or mid-to-late pregnancy period, when EtOH consumption is associated with fetal alcohol spectrum disorders. Incorporation of data from human embryonic stem cell studies led to a model-supported linkage of in vitro concentrations with plausible exposure ranges for pregnant women. This effort demonstrates benefits and challenges associated with use of multispecies PBPK models to estimate in vivo tissue concentrations associated with in vitro embryotoxicity studies.