Transporter-mediated drug-drug interactions: regulatory guidelines, in vitro and in vivo methodologies and translation, special populations, and the blood-brain barrier.

This review, part of a special issue on drug-drug interactions (DDIs) spearheaded by the International Society for the Study of Xenobiotics (ISSX) New Investigators, explores the critical role of drug transporters in absorption, disposition, and clearance in the context of DDIs. Over the past two decades, significant advances have been made in understanding the clinical relevance of these transporters. Current knowledge on key uptake and efflux transporters that affect drug disposition and development is summarized. Regulatory guidelines from the FDA, EMA, and PMDA that inform the evaluation of potential transporter-mediated DDIs are discussed in detail. Methodologies for preclinical and clinical testing to assess potential DDIs are reviewed, with an emphasis on the utility of physiologically based pharmacokinetic (PBPK) modeling. This includes the application of relative abundance and expression factors to predict human pharmacokinetics (PK) using preclinical data, integrating the latest regulatory guidelines. Considerations for assessing transporter-mediated DDIs in special populations, including pediatric, hepatic, and renal impairment groups, are provided. Additionally, the impact of transporters at the blood-brain barrier (BBB) on the disposition of CNS-related drugs is explored. Enhancing the understanding of drug transporters and their role in drug disposition and toxicity can improve efficacy and reduce adverse effects. Continued research is essential to bridge remaining gaps in knowledge, particularly in comparison with cytochrome P450 (CYP) enzymes.

Comparison of drug-induced liver injury risk between propylthiouracil and methimazole: A quantitative systems toxicology approach.

Propylthiouracil (PTU) and methimazole (MMI), two classical antithyroid agents possess risk of drug-induced liver injury (DILI) with unknown mechanism of action. This study aimed to examine and compare their hepatic toxicity using a quantitative system toxicology approach. The impact of PTU and MMI on hepatocyte survival, oxidative stress, mitochondrial function and bile acid transporters were assessed in vitro. The physiologically based pharmacokinetic (PBPK) models of PTU and MMI were constructed while their risk of DILI was calculated by DILIsym, a quantitative systems toxicology (QST) model by integrating the results from in vitro toxicological studies and PBPK models. The simulated DILI (ALT >2 × ULN) incidence for PTU (300 mg/d) was 21.2%, which was within the range observed in clinical practice. Moreover, a threshold dose of 200 mg/d was predicted with oxidative stress proposed as an important toxic mechanism. However, DILIsym predicted a 0% incidence of hepatoxicity caused by MMI (30 mg/d), suggesting that the toxicity of MMI was not mediated through mechanism incorporated into DILIsym. In conclusion, DILIsym appears to be a practical tool to unveil hepatoxicity mechanism and predict clinical risk of DILI.

Optimization of the betamethasone and dexamethasone dosing regimen during pregnancy: a combined placenta perfusion and pregnancy physiologically based pharmacokinetic modeling approach.

BACKGROUND: Antenatal betamethasone and dexamethasone are prescribed to women who are at high risk of premature birth to prevent neonatal respiratory distress syndrome (RDS). The current treatment regimens, effective to prevent neonatal RDS, may be suboptimal. Recently, concerns have been raised regarding possible adverse long-term neurological outcomes due to high fetal drug exposures. Data from nonhuman primates and sheep suggest maintaining a fetal plasma concentration above 1 ng/mL for 48 hours to retain efficacy, while avoiding undesirable high fetal plasma levels. OBJECTIVE: We aimed to re-evaluate the current betamethasone and dexamethasone dosing strategies to assess estimated fetal exposure and provide new dosing proposals that meet the efficacy target but avoid excessive peak exposures. STUDY DESIGN: A pregnancy physiologically based pharmacokinetic (PBPK) model was used to predict fetal drug exposures. To allow prediction of the extent of betamethasone and dexamethasone exposure in the fetus, placenta perfusion experiments were conducted to determine placental transfer. Placental transfer rates were integrated in the PBPK model to predict fetal exposure and model performance was verified using published maternal and fetal pharmacokinetic data. The verified pregnancy PBPK models were then used to simulate alternative dosing regimens to establish a model-informed dose. RESULTS: Ex vivo data showed that both drugs extensively cross the placenta. For betamethasone 15.7±1.7% and for dexamethasone 14.4±1.5%, the initial maternal perfusate concentration reached the fetal circulations at the end of the 3-hour perfusion period. Pregnancy PBPK models that include these ex vivo-derived placental transfer rates accurately predicted maternal and fetal exposures resulting from current dosing regimens. The dose simulations suggest that for betamethasone intramuscular, a dose reduction from 2 dosages 11.4 mg, 24 hours apart, to 4 dosages 1.425 mg, 12 hours apart would avoid excessive peak exposures and still meet the fetal response threshold. For dexamethasone, the dose may be reduced from 4 times 6 mg every 12 hours to 8 times 1.5 mg every 6 hours. CONCLUSION: A combined placenta perfusion and pregnancy PBPK modeling approach adequately predicted both maternal and fetal drug exposures of 2 antenatal corticosteroids (ACSs). Strikingly, our PBPK simulations suggest that drug doses might be reduced drastically to still meet earlier proposed efficacy targets and minimize peak exposures. We propose the provided model-informed dosing regimens are used to support further discussion on an updated ACS scheme and design of clinical trials to confirm the effectiveness and safety of lower doses.

Physiologically-based pharmacokinetic modelling guided dose evaluations of nirmatrelvir/ritonavir in renal impairment for the management of COVID-19.

We aimed to address factors contributing to the pharmacokinetic changes of nirmatrelvir/ritonavir in renal impaired (RI) patients and recommend dosing adjustment via a physiologically-based pharmacokinetic (PBPK) modelling approach. A PBPK model of nirmatrelvir/ritonavir was developed via Simcyp® Simulator. Sensitivity analysis of the influence of hepatic CYP3A4 intrinsic clearance and abundance, as well as hepatic non-CYP3A4 metabolism (other human liver microsomes [HLM] CLint) was performed to evaluate the effects of RI on oral clearance of nirmatrelvir. Other HLM CLint, the most sensitive parameter, was adjusted, and the simulated plasma concentration profiles of nirmatrelvir in severe RI subjects were within the therapeutic index of 292-10 000 ng/mL for dosing regimens of loading doses of 300/100 mg followed by 150/100 mg or 75/100 mg twice daily of nirmatrelvir/ritonavir. Considering that nirmatrelvir is available as a 150 mg tablet, we recommend 300/100 mg followed by 150/100 mg twice daily as the dosing regimen to be investigated in severe RI.

Development of a physiologically based pharmacokinetic model for levetiracetam in patients with renal impairment to guide dose adjustment based on steady-state peak/trough concentrations.

Levetiracetam may cause acute renal failure and myoclonic encephalopathy at high plasma levels, particularly in patients with renal impairment. The aim of this study was to develop a physiologically based pharmacokinetic (PBPK) model to predict levetiracetam pharmacokinetics in Chinese adults with epilepsy and renal impairment and define appropriate levetiracetam dosing regimen.PBPK models for healthy subjects and epilepsy patients with renal impairment were developed, validated, and adapted. Furthermore, we predicted the steady-state trough and peak concentrations of levetiracetam in patients with renal impairment using the final PBPK model, thereby recommending appropriate levetiracetam dosing regimens for different renal function stages. The predicted maximum plasma concentration (Cmax), time to maximum concentration (Tmax), area under the plasma concentration-time curve (AUC) were in agreement (0.8 ≤ fold error ≤ 1.2) with the observed, and the fold error of the trough concentrations in end-stage renal disease (ESRD) was 0.77 - 1.22. The prediction simulations indicated that the recommended doses of 1000, 750, 500, and 500 mg twice daily for epilepsy patients with mild, moderate, severe renal impairment, and ESRD, respectively, were sufficient to achieve the target plasma concentration of levetiracetam.

Prediction of Human Pharmacokinetics of E0703, a Novel Radioprotective Agent, Using Physiologically Based Pharmacokinetic Modeling and an Interspecies Extrapolation Approach.

E0703, a new steroidal compound optimized from estradiol, significantly increased cell proliferation and the survival rate of KM mice and beagles after ionizing radiation. In this study, we characterize its preclinical pharmacokinetics (PK) and predict its human PK using a physiologically based pharmacokinetic (PBPK) model. The preclinical PK of E0703 was studied in mice and Rhesus monkeys. Asian human clearance (CL) values for E0703 were predicted from various allometric methods. The human PK profiles of E0703 (30 mg) were predicted by the PBPK model in Gastro Plus software 9.8 (SimulationsPlus, Lancaster, CA, USA). Furthermore, tissue distribution and the human PK profiles of different administration dosages and forms were predicted. The 0.002 L/h of CL and 0.005 L of Vss in mice were calculated and optimized from observed PK data. The plasma exposure of E0703 was availably predicted by the CL using the simple allometry (SA) method. The plasma concentration-time profiles of other dosages (20 and 40 mg) and two oral administrations (30 mg) were well-fitted to the observed values. In addition, the PK profile of target organs for E0703 exhibited a higher peak concentration (Cmax) and AUC than plasma. The developed E0703-PBPK model, which is precisely applicable to multiple species, benefits from further clinical development to predict PK in humans.

Systematic review of physiologically based kinetic lactation models for transfer of xenobiotic compounds to milk.

Lactational elimination has been described mathematically for nearly 50 years. Over 40 published articles, containing >50 physiologically based kinetic (PBK) lactation models were included in the systematic review. These PBK models described the lactational elimination of xenobiotic compounds in humans, rats, mice, and dairy cows and goats. A total of 78 compounds have been modelled, ranging from industrial chemicals, pesticides, to pain medication, antibiotics, and caffeine. Few models included several species or compounds, and models were thus generally not translational or generic. Three dairy cow models mechanistically described the intramammary disposition of pharmaceuticals after intramammary administration, including volume changes caused by milking, while empirically describing the remaining pharmacokinetics. The remaining models were semi- or whole body PBK models, describing long-term exposure of environmental pollutants, or short-term exposure of pharmaceuticals. The absolute majority described the disposition to the mammary gland or milk with perfusion limited compartments, but permeability limited models were available as well. With long-term exposure, models often included changes in milk volume and/or consumption by the offspring, and changes in body weight of offspring. Periodic emptying of the mammary gland, as with feeding or milking, was sparsely applied. Rodent models used similar physiological parameters, while values of physiological parameters applied in human models could range widely. When milk composition was included in the models, it most often included the fat content. The review gives an extensive overview of the applied functions and modelling strategies of PBK lactation models.

Integrating Physiologically Based Pharmacokinetic Modeling-Based Forward Dosimetry and in Vitro Bioassays to Improve the Risk Assessment of Organophosphate Esters on Human Health.

The ability to accurately assess the health risks of contaminants is limited by the shortcomings of toxicological standards. Using organophosphate esters (OPEs) as an example, this study attempted to integrate physiologically based pharmacokinetic (PBPK)-based forward dosimetry and in vitro bioassays to assess the likelihood of contaminants inducing biological effects in humans. The total exposure level of OPEs for Chinese residents was 19.5 ± 8.71 ng/kg/day with inhalation being the main exposure pathway. Then, human PBPK models were developed for individual OPEs to predict their steady-state concentrations in human tissues, and the predicted median levels in blood were close to the measurements. The reference doses (RfDs) of OPEs based on in vitro bioassays were comparable to in vivo animal-derived RfDs, demonstrating the reliability of in vitro bioassays. Therefore, the likelihood of OPEs inducing bioactivities in humans (RQin-vitro) was calculated using in vitro toxicity data and OPE levels in human tissues. The RQin-vitros of tris(2-chloroisopropyl) phosphate, tris(1,3-dichloropropyl) phosphate, and triphenyl phosphate (7.68 × 10-5-3.18 × 10-3) were comparable to the risks assessed using traditional RfDs (5.22 × 10-5-1.94 × 10-3), indicating the credibility of the method proposed in this study. This study establishes a new framework to improve the health risk assessment of contaminants without sufficient toxicity data and minimize the need for animal experimentation.

Model-Based Risk Prediction of Rivaroxaban with Amiodarone for Moderate Renal Impaired Elderly Population.

PURPOSE: Increased bleeding risk was found associated with concurrent prescription of rivaroxaban and amiodarone. We previously recommended dose adjustment for rivaroxaban utilizing a physiologically based pharmacokinetic (PBPK) modeling approach. Our subsequent in vitro studies discovered the pivotal involvement of human renal organic anion transporter 3 (hOAT3) in the renal secretion of rivaroxaban and the inhibitory potency of amiodarone. This study aimed to redefine the disease-drug-drug interactions (DDDI) between rivaroxaban and amiodarone and update the potential risks. METHODS: Prospective simulations were conducted with updated PBPK models of rivaroxaban and amiodarone incorporating hOAT3-related parameters. RESULTS: Simulations to recapitulate previously explored DDDI in renal impairment showed a higher bleeding tendency in all simulation scenarios after integrating hOAT3-mediated clearance into PBPK models. Further sensitivity analysis revealed that both hOAT3 dysfunction and age could affect the extent of DDDI, and age was shown to have a more pivotal role on rivaroxaban in vivo exposure. When amiodarone was prescribed along with our recommended dose reduction of rivaroxaban to 10 mg in moderate renal impaired elderly people, it could result in persistently higher rivaroxaban peak concentrations at a steady state. To better manage the increased bleeding risk among such a vulnerable population, a dose reduction of rivaroxaban to 2.5 mg twice daily resulted in its acceptable in vivo exposure. CONCLUSION: Close monitoring of bleeding tendency is essential for elderly patients with moderate renal impairment receiving co-prescribed rivaroxaban and amiodarone. Further dose reduction is recommended for rivaroxaban to mitigate this specific DDDI risk.

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.

Modeled Rat Hepatic and Plasma Concentrations of Chemicals after Virtual Administrations Using Two Sets of in Silico Liver-to-Plasma Partition Coefficients.

The hepatic elimination of chemical substances in pharmacokinetic models requires hepatic intrinsic clearance (CLh,int) parameters for unbound drug in the liver, and these are regulated by the liver-to-plasma partition coefficients (Kp,h). Both Poulin and Theil and Rodgers and Rowland have proposed in silico expressions for Kp,h for a variety of chemicals. In this study, two sets of in silico Kp,h values for 14 model substances were assessed using experimentally reported in vivo steady-state Kp,h data and time-dependent virtual internal exposures in the liver and plasma modeled by forward dosimetry in rats. The Kp,h values for 14 chemicals independently calculated using the primary Poulin and Theil method in this study were significantly correlated with those obtained using the updated Rodgers and Rowland method and with reported in vivo steady-state Kp,h data in rats. When pharmacokinetic parameters were derived based on individual in vivo time-dependent data for diazepam, phenytoin, and nicotine in rats, the modeled liver and plasma concentrations after intravenous administration of the selected substrates in rats using two sets of in silico Kp,h values were mostly similar to the reported time-dependent in vivo internal exposures. Similar results for modeled liver and plasma concentrations were observed with input parameters estimated by machine-learning systems for hexobarbital, fingolimod, and pentazocine, with no reference to experimental pharmacokinetic data. These results suggest that the output values from rat pharmacokinetic models based on in silico Kp,h values derived from the primary Poulin and Theil model would be applicable for estimating toxicokinetics or internal exposure to substances.

Comparison of the predictive accuracy of the physiologically based pharmacokinetic (PBPK) model and population pharmacokinetic (PPK) model of vancomycin in Japanese patients with MRSA infection.

INTRODUCTION: The latest therapeutic drug monitoring guidelines for vancomycin (VCM) recommend that area under the concentration-time curve is estimated based on model-informed precision dosing and used to evaluate efficacy and safety. Therefore, we predicted VCM concentrations in individual methicillin-resistant Staphylococcus aureus-infected patients using existing a physiologically based pharmacokinetic (PBPK) model and 1- and 2-compartment population pharmacokinetic (PPK) models and confirmed and verified the accuracy of the PBPK model in estimating VCM concentrations with the PPK model. METHODS: The subjects of the study are 20 patients, and the predicted concentrations were evaluated by comparing the observed and predicted trough and peak values of VCM concentrations for individual patients. RESULTS: The results showed good correlation between the observed and predicted trough and peak concentrations of VCM was observed generally in the PBPK model, R2 values of 0.72, 0.62, and 0.40 with trough values of 0.49, 0.40, and 0.34 with peak values for PBPK model, 1-compartment, and 2-compartment model, respectively. CONCLUSIONS: Although the performance of the PBPK model is not as predictive as the PPK model, generally similar predictive trends were obtained, suggesting that it may be a valuable tool for rapid and accurate prediction of AUC for VCM.

Translational physiologically-based pharmacokinetic model for ocular disposition of monoclonal antibodies.

We have previously published a PBPK model comprising the ocular compartment to characterize the disposition of monoclonal antibodies (mAbs) in rabbits. While rabbits are commonly used preclinical species in ocular research, non-human primates (NHPs) have the most phylogenetic resemblance to humans including the presence of macula in the eyes as well as higher sequence homology. However, their use in ocular research is limited due to the strict ethical guidelines. Similarly, in humans the ocular samples cannot be collected except for the tapping of aqueous humor (AH). Therefore, we have translated this rabbit model to monkeys and human species using literature-reported datasets. Parameters describing the tissue volumes, physiological flows, and FcRn-binding were obtained from the literature, or estimated by fitting the model to the data. In the monkey model, the values for the rate of lysosomal degradation for antibodies (Kdeg), intraocular reflection coefficients (σaq, σret, σcho), bidirectional rate of fluid circulation between the vitreous chamber and the aqueous chamber (QVA), and permeability-surface area product of lens (PSlens) were estimated; and were found to be 31.5 h-1, 0.7629, 0.6982, 0.9999, 1.64 × 10-5 L/h, and 4.62 × 10-7 L/h, respectively. The monkey model could capture the data in plasma, aqueous humor, vitreous humor and retina reasonably well with the predictions being within twofold of the observed values. For the human model, only the value of Kdeg was estimated to fit the model to the plasma pharmacokinetics (PK) of mAbs and was found to be 24.4 h-1 (4.14%). The human model could also capture the ocular PK data reasonably well with the predictions being within two- to threefold of observed values for the plasma, aqueous and vitreous humor. Thus, the proposed framework can be used to characterize and predict the PK of mAbs in the eye of monkey and human species following systemic and intravitreal administration. The model can also facilitate the development of new antibody-based therapeutics for the treatment of ocular diseases as well as predict ocular toxicities of such molecules following systemic administration.

Physiologically based pharmacokinetic model to predict drug-drug interactions with the antibody-drug conjugate enfortumab vedotin.

Enfortumab vedotin is an antibody-drug conjugate (ADC) comprised of a Nectin-4-directed antibody and monomethyl auristatin E (MMAE), which is primarily eliminated through P-glycoprotein (P-gp)-mediated excretion and cytochrome P450 3A4 (CYP3A4)-mediated metabolism. A physiologically based pharmacokinetic (PBPK) model was developed to predict effects of combined P-gp with CYP3A4 inhibitor/inducer (ketoconazole/rifampin) on MMAE exposure when coadministered with enfortumab vedotin and study enfortumab vedotin with CYP3A4 (midazolam) and P-gp (digoxin) substrate exposure. A PBPK model was built for enfortumab vedotin and unconjugated MMAE using the PBPK simulator ADC module. A similar model was developed with brentuximab vedotin, an ADC with the same valine-citrulline-MMAE linker as enfortumab vedotin, for MMAE drug-drug interaction (DDI) verification using clinical data. The DDI simulation predicted a less-than-2-fold increase in MMAE exposure with enfortumab vedotin plus ketoconazole (MMAE geometric mean ratio [GMR] for maximum concentration [Cmax], 1.15; GMR for area under the time-concentration curve from time 0 to last quantifiable concentration [AUClast], 1.38). Decreased MMAE exposure above 50% but below 80% was observed with enfortumab vedotin plus rifampin (MMAE GMR Cmax, 0.72; GMR AUClast, 0.47). No effect of enfortumab vedotin on midazolam or digoxin systemic exposure was predicted. Results suggest that combination enfortumab vedotin, P-gp, and a CYP3A4 inhibitor may result in increased MMAE exposure and patients should be monitored for potential adverse effects. Combination P-gp and a CYP3A4 inducer may result in decreased MMAE exposure. No exposure change is expected for CYP3A4 or P-gp substrates when combined with enfortumab vedotin.ClinicalTrials.gov identifier Not applicable.

Pharmacokinetics of Novel Furoxan/Coumarin Hybrids in Rats Using LC-MS/MS Method and Physiologically Based Pharmacokinetic Model.

Novel furoxan/coumarin hybrids were synthesized, and pharmacologic studies showed that the compounds displayed potent antiproliferation activities via downregulating both the phosphatidylinositide 3-kinase (PI3K) pathway and the mitogen-activated protein kinase (MAPK) pathway. To investigate the preclinical pharmacokinetic (PK) properties of three candidate compounds (CY-14S-4A83, CY-16S-4A43, and CY-16S-4A93), liquid chromatography, in tandem with the mass spectrometry LC-MS/MS method, was developed and validated for the simultaneous determination of these compounds. The absorption, distribution, metabolism, and excretion (ADME) properties were investigated in in vitro studies and in rats. Meanwhile, physiologically based pharmacokinetic (PBPK) models were constructed using only in vitro data to obtain detailed PK information. Good linearity was observed over the concentration range of 0.01−1.0 µg/mL. The free drug fraction (fu) values of the compounds were less than 3%, and the clearance (CL) values were 414.5 ± 145.7 mL/h/kg, 2624.6 ± 648.4 mL/h/kg, and 500.6 ± 195.2 mL/h/kg, respectively. The predicted peak plasma concentration (Cmax) and the area under the concentration-time curve (AUC) were overestimated for the CY-16S-4A43 PBPK model compared with the experimental ones (fold error > 2), suggesting that tissue accumulation and additional elimination pathways may exist. In conclusion, the LC-MS/MS method was successively applied in the preclinical PK studies, and the detailed information from PBPK modeling may improve decision-making in subsequent new drug development.

In Silico and In Vivo Pharmacokinetic Evaluation of 84-B10, a Novel Drug Candidate against Acute Kidney Injury and Chronic Kidney Disease.

Acute kidney injury (AKI) and chronic kidney disease (CKD) have become public health problems due to high morbidity and mortality. Currently, drugs recommended for patients with AKI or CKD are extremely limited, and candidates based on a new mechanism need to be explored. 84-B10 is a novel 3-phenylglutaric acid derivative that can activate the mitochondrial protease, Lon protease 1 (LONP1), and may protect against cisplatin-induced AKI and unilateral ureteral obstruction- or 5/6 nephrectomy [5/6Nx]-induced CKD model. Preclinical studies have shown that 84-B10 has a good therapeutic effect, low toxicity, and is a good prospect for further development. In the present study, the UHPLC-MS/MS method was first validated then applied to the pharmacokinetic study and tissue distribution of 84-B10 in rats. Physicochemical properties of 84-B10 were then acquired in silico. Based on these physicochemical and integral physiological parameters, a physiological based pharmacokinetic (PBPK) model was developed using the PK-Sim platform. The fitting accuracy was estimated with the obtained experimental data. Subsequently, the validated model was employed to predict the pharmacokinetic profiles in healthy and chronic kidney injury patients to evaluate potential clinical outcomes. Cmax in CKD patients was about 3250 ng/mL after a single dose of 84-B10 (0.41 mg/kg), and Cmax,ss was 1360 ng/mL after multiple doses. This study may serve in clinical dosage setting in the future.

Development and Evaluation of Amorphous Solid Dispersion of Riluzole with PBPK Model to Simulate the Pharmacokinetic Profile.

In the current work, screening of polymers viz. polyacrylic acid (PAA), polyvinyl pyrrolidone vinyl acetate (PVP VA), and hydroxypropyl methyl cellulose acetate succinate (HPMC AS) based on drug-polymer interaction and wetting property was done for the production of a stable amorphous solid dispersion (ASD) of a poorly water-soluble drug Riluzole (RLZ). PAA showed maximum interaction and wetting property hence, was selected for further studies. Solid state characterization studies confirmed the formation of ASD with PAA. Saturation solubility, dissolution profile, and in vivo pharmacokinetic data of the ASD formulation were generated in rats against its marketed tablet Rilutor. The RLZ:PAA ASD showed exponential enhancement in the dissolution of RLZ. Predicted and observed pharmacokinetic data in rats showed enhanced area under curve (AUC) and Cmax in plasma and brain with respect to Rilutor. Furthermore, a physiologically based pharmacokinetic (PBPK) model of rats for Rilutor and RLZ ASD was developed and then extrapolated to humans where physiological parameters were changed along with a biochemical parameter. The partition coefficient was kept similar in both species. The model was used to predict different exposure scenarios, and the simulated data was compared with observed data points. The PBPK model simulated Cmax and AUC was within two times the experimental data for plasma and brain. The Cmax and AUC in the brain increased with ASD compared to Rilutor for humans showing its potential in improving its biopharmaceutical performance and hence enhanced therapeutic efficacy. The model can predict the RLZ concentration in multiple compartments including plasma and liver.

The Extension of the LeiCNS-PK3.0 Model in Combination with the "Handshake" Approach to Understand Brain Tumor Pathophysiology.

Micrometastatic brain tumor cells, which cause recurrence of malignant brain tumors, are often protected by the intact blood-brain barrier (BBB). Therefore, it is essential to deliver effective drugs across not only the disrupted blood-tumor barrier (BTB) but also the intact BBB to effectively treat malignant brain tumors. Our aim is to predict pharmacokinetic (PK) profiles in brain tumor regions with the disrupted BTB and the intact BBB to support the successful drug development for malignant brain tumors. LeiCNS-PK3.0, a comprehensive central nervous system (CNS) physiologically based pharmacokinetic (PBPK) model, was extended to incorporate brain tumor compartments. Most pathophysiological parameters of brain tumors were obtained from literature and two missing parameters of the BTB, paracellular pore size and expression level of active transporters, were estimated by fitting existing data, like a "handshake". Simultaneous predictions were made for PK profiles in extracellular fluids (ECF) of brain tumors and normal-appearing brain and validated on existing data for six small molecule anticancer drugs. The LeiCNS-tumor model predicted ECF PK profiles in brain tumor as well as normal-appearing brain in rat brain tumor models and high-grade glioma patients within twofold error for most data points, in combination with estimated paracellular pore size of the BTB and active efflux clearance at the BTB. Our model demonstrated a potential to predict PK profiles of small molecule drugs in brain tumors, for which quantitative information on pathophysiological alterations is available, and contribute to the efficient and successful drug development for malignant brain tumors.

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.

Investigating the uncertainty of prediction accuracy for the application of physiologically based pharmacokinetic models to animal-free risk assessment of cosmetic ingredients.

Physiologically based pharmacokinetic (PBPK) models are considered useful tools in animal-free risk assessment. To utilize PBPK models for risk assessment, it is necessary to compare their reliability with in vivo data. However, obtaining in vivo pharmacokinetics data for cosmetic ingredients is difficult, complicating the utilization of PBPK models for risk assessment. In this study, to utilize PBPK models for risk assessment without accuracy evaluation, we proposed a novel concept-the modeling uncertainty factor (MUF). By calculating the prediction accuracy for 150 compounds, we established that using in vitro data for metabolism-related parameters and limiting the applicability domain increase the prediction accuracy of a PBPK model. Based on the 97.5th percentile of prediction accuracy, MUF was defined at 10 for the area under the plasma concentration curve and 6 for Cmax. A case study on animal-free risk assessment was conducted for bisphenol A using these MUFs. As this study was conducted mainly on pharmaceuticals, further investigation using cosmetic ingredients is pivotal. However, since internal exposure is essential in realizing animal-free risk assessment, our concept will serve as a useful tool to predict plasma concentrations without using in vivo data.