Physiologically based pharmacokinetic modelling: a sub-compartmentalized model of tissue distribution

The Utility of Efavirenz-based Prophylaxis Against HIV Infection. A Systems Pharmacological Analysis

Pre-exposure prophylaxis (PrEP) is considered one of the five “pillars” by UNAIDS to reduce HIV transmission. Moreover, it is a tool for female self-protection against HIV, making it highly relevant to sub-Saharan regions, where women have the highest infection burden. To date, Truvada is the only medication for PrEP. However, the cost of Truvada limits its uptake in resource-constrained countries. Similarly, several currently investigated, patent-protected compounds may be unaffordable in these regions. We set out to explore the potential of the patent-expired antiviral efavirenz (EFV) as a cost-efficient PrEP alternative. A population pharmacokinetic model utilizing data from the ENCORE1 study was developed. The model was refined for metabolic autoinduction. We then explored EFV cellular uptake mechanisms, finding that it is largely determined by plasma protein binding. Next, we predicted the prophylactic efficacy of various EFV dosing schemes after exposure to HIV using a stochastic simulation framework. We predicted that plasma concentrations of 11, 36, 1287 and 1486ng/mL prevent 90% sexual transmissions with wild type and Y181C, K103N and G190S mutants, respectively. Trough concentrations achieved after 600 mg once daily dosing (median: 2017 ng/mL, 95% CI:445–9830) and after reduced dose (400 mg) efavirenz (median: 1349ng/mL, 95% CI: 297–6553) provided complete protection against wild-type virus and the Y181C mutant, and median trough concentrations provided about 90% protection against the K103N and G190S mutants. As reduced dose EFV has a lower toxicity profile, we predicted the reduction in HIV infection when 400 mg EFV-PrEP was poorly adhered to, when it was taken “on demand” and as post-exposure prophylaxis (PEP). Once daily EFV-PrEP provided 99% protection against wild-type virus, if ≥50% of doses were taken. PrEP “on demand” provided complete protection against wild-type virus and prevented ≥81% infections in the mutants. PEP could prevent >98% infection with susceptible virus when initiated within 24 h after virus exposure and continued for at least 9 days. We predict that 400 mg oral EFV may provide superior protection against wild-type HIV. However, further studies are warranted to evaluate EFV as a cost-efficient alternative to Truvada. Predicted prophylactic concentrations may guide release kinetics of EFV long-acting formulations for clinical trial design.

Mechanistic framework predicts drug-class specific utility of antiretrovirals for HIV prophylaxis

Currently, there is no effective vaccine to halt HIV transmission. However, pre-exposure prophylaxis (PrEP) with the drug combination Truvada can substantially decrease HIV transmission in individuals at risk. Despite its benefits, Truvada-based PrEP is expensive and needs to be taken once-daily, which often leads to inadequate adherence and incomplete protection. These deficits may be overcome by next-generation PrEP regimen, including currently investigated long-acting formulations, or patent-expired drugs. However, poor translatability of animal- and ex vivo/in vitro experiments, and the necessity to conduct long-term (several years) human trials involving considerable sample sizes (N>1000 individuals) are major obstacles to rationalize drug-candidate selection. We developed a prophylaxis modelling tool that mechanistically considers the mode-of-action of all available drugs. We used the tool to screen antivirals for their prophylactic utility and identify lower bound effective concentrations that can guide dose selection in PrEP trials. While in vitro measurable drug potency usually guides PrEP trial design, we found that it may over-predict PrEP potency for all drug classes except reverse transcriptase inhibitors. While most drugs displayed graded concentration-prophylaxis profiles, protease inhibitors tended to switch between none- and complete protection. While several treatment-approved drugs could be ruled out as PrEP candidates based on lack-of-prophylactic efficacy, darunavir, efavirenz, nevirapine, etravirine and rilpivirine could more potently prevent infection than existing PrEP regimen (Truvada). Notably, some drugs from this candidate set are patent-expired and currently neglected for PrEP repurposing. A next step is to further trim this candidate set by ruling out compounds with ominous safety profiles, to assess different administration schemes in silico and to test the remaining candidates in human trials.

Pre-exposure prophylaxis (PrEP) is a novel, promising strategy to halt HIV transmission. PrEP with Truvada can substantially decrease the risk of infection. However, individuals often inadequately adhere to the once-daily regimen and the drug is expensive. These shortcomings may be overcome by next-generation PrEP compounds, including long-acting formulations. However, poor translatability of animal- and ex vivo/in vitro experiments, and difficulties in conducting long-term trials involving considerable sample sizes (N > 1000 individuals) make drug-candidate selection and optimization of administration schemes costly and often infeasible. We developed a simulation tool that mechanistically considers the mode-of-action of all antivirals. We used the tool to screen all available antivirals for their prophylactic utility and identified lower bound effective concentrations for designing PrEP dosing regimen in clinical trials. We found that in vitro measured drug potency may over-predict PrEP potency, for all antiviral classes except reverse transcriptase inhibitors. We could rule out a number of antivirals for PrEP repurposing and predicted that darunavir, efavirenz, nevirapine, etravirine and rilpivirine provide complete protection at clinically relevant concentrations. Further trimming of this candidate set by compound-safety and by assessing different implementation schemes is envisaged.

Hybrid stochastic framework predicts efficacy of prophylaxis against HIV: An example with different dolutegravir prophylaxis schemes

To achieve the 90-90-90 goals set by UNAIDS, the number of new HIV infections needs to decrease to approximately 500,000 by 2020. One of the 'five pillars' to achieve this goal is pre-exposure prophylaxis (PrEP). Truvada (emtricitabine-tenofovir) is currently the only medication approved for PrEP. Despite its advantages, Truvada is costly and requires individuals to adhere to the once-daily regimen. To improve PrEP, many next-generation regimen, including long-acting formulations, are currently investigated. However, pre-clinical testing may not guide candidate selection, since it often fails to translate into clinical efficacy. On the other hand, quantifying prophylactic efficacy in the clinic is ethically problematic and requires to conduct long (years) and large (N>1000 individuals) trials, precluding systematic evaluation of candidates and deployment strategies. To prioritize- and help design PrEP regimen, tools are urgently needed that integrate pharmacological-, viral- and host factors determining prophylactic efficacy. Integrating the aforementioned factors, we developed an efficient and exact stochastic simulation approach to predict prophylactic efficacy, as an example for dolutegravir (DTG). Combining the population pharmacokinetics of DTG with the stochastic framework, we predicted that plasma concentrations of 145.18 and 722.23nM prevent 50- and 90% sexual transmissions respectively. We then predicted the reduction in HIV infection when DTG was used in PrEP, PrEP 'on demand' and post-exposure prophylaxis (PEP) before/after virus exposure. Once daily PrEP with 50mg oral DTG prevented 99-100% infections, and 85% of infections when 50% of dosing events were missed. PrEP 'on demand' prevented 79-84% infections and PEP >80% when initiated within 6 hours after virus exposure and continued for as long as possible. While the simulation framework can easily be adapted to other PrEP candidates, our simulations indicated that oral 50mg DTG is non-inferior to Truvada. Moreover, the predicted 90% preventive concentrations can guide release kinetics of currently developed DTG nano-formulations.

Drug Distribution to Human Tissues: Prediction and Examination of the Basic Assumption in In Vivo Pharmacokinetics-Pharmacodynamics (PK/PD) Research

The tissue:plasma partition coefficients (Kp ) are good indicators of the extent of tissue distribution. Therefore, advanced tissue composition-based models were used to predict the Kp values of drugs under in vivo conditions on the basis of in vitro and physiological input data. These models, however, focus on animal tissues and do not challenge the predictions with human tissues for drugs. The first objective of this study was to predict the experimentally determined Kp values of seven human tissues for 26 drugs. In all, 95% of the predicted Kp values are within 2.5-fold error of the observed values in humans. Accordingly, these results suggest that the tissue composition-based model used in this study is able to provide accurate estimates of drug partitioning in the studied human tissues. Furthermore, as the Kp equals to the ratio of total concentration between tissue and plasma, or the ratio of unbound fraction between plasma (fup ) and tissue (fut ), this parameter Kp would deviate from the unity. Therefore, the second objective was to examine the corresponding relationships between fup and fut values experimentally determined in humans for several drugs. The results also indicate that fup may significantly deviate to fut ; the discrepancies are governed by the dissimilarities in the binding and ionization on both sides of the membrane, which were captured by the tissue composition-based model. Hence, this violated the basic assumption in in vivo pharmacokinetics-pharmacodynamics (PK/PD) research, since the free drug concentration in tissue and plasma was not equal particularly for the ionizable drugs due to the pH gradient effect on the fraction of unionized drug in plasma (fuip ) and tissue (fuit ) (i.e., fup × fuip × total plasma concentration = fut × fuit × total tissue concentration, and, hence, the free drug concentration in plasma and tissue differed by fuip/fuit). Therefore, this assumption should be adjusted for the ionized drugs, and, hence, a mathematical correction to the basic assumption of similar free drug concentration in plasma and tissues can be derived from the tissue composition-based model. Note that this assumption will be further challenged in a dynamic in vivo system in a companion manuscript. Overall, this study was a first attempt to predict the in vivo Kp values for specific human tissues by considering separately the effect of fup and fut , with the aim of facilitating the use of physiologically-based PK (PBPK) model in PK/PD studies.

Comparison of in-vivo and in-silico methods used for prediction of tissue: plasma partition coefficients in rat

OBJECTIVES

To use methods from the literature to predict rat tissue:plasma partition coefficients (Kps) and volume of distribution values. Determine which model provides the most accurate predictions to increase confidence in the use of predicted pharmacokinetic parameters in physiologically based pharmacokinetic modelling.

METHODS

Six models were used to predict Kps and four to predict V(ss) for a dataset of 81 compounds in 11 rat tissues, and the predictions were compared with experimentally derived values.

KEY FINDINGS

Kp predictions made by the Rodgers et al. model were the most accurate, with 77% within threefold of experimental values. The Poulin & Theil model was the most accurate for the prediction of V(ss) , with 87% of predictions within threefold.

CONCLUSIONS

This study has shown that in-silico models available in the literature can be used to accurately predict Kp and V(ss) in rat. The Rodgers et al. model has been shown to provide the most accurate Kp predictions, with consistent accuracy across all drug classes and tissues. It was also the most accurate V(ss) predictor when no in-vivo data were used as input. However, transporter systems and other mechanisms that are not yet fully understood need to be incorporated into these types of models in the future to further increase their applicability.

Interspecies scaling in pharmacokinetics: a novel whole-body physiologically based modeling framework to discover drug biodistribution mechanisms in vivo

Drug approval processes require extensive testing and have recently put more emphasis on understanding mechanistic drug action in the body including toxicity and safety.1 Consequently, there is an urgent need in the pharmaceutical industry to develop mechanistic pharmacokinetic (PK) models able to both expedite knowledge gain from experimental trials and, simultaneously, address safety concerns. We previously developed a first principles based whole-body PK model, which incorporated physiological dimensions and drug mass transport. In this follow-up article, we demonstrate how the first principles model in combination with novel physiological scaling laws yields more reliable interspecies and intraspecies extrapolation of drug biodistribution. We show how experimental dose-response data in rats for immunosuppressant cyclosporin are sufficient for predicting the biodistribution of this drug in pigs, monkeys, and humans. The predicted drug concentrations extrapolated by interspecies scaling laws match well with the experimental measurements. These promising results demonstrate that the whole-body PK modeling approach not only elucidates drug mechanisms from a biochemical standpoint, but offers better scaling precision. Better models can substantially accelerate the introduction of drug leads to clinical trials and eventually to the market by offering more understanding of the drug mechanisms, aiding in therapy design, and serving as an accurate dosing tool.

Lumping of physiologically-based pharmacokinetic models and a mechanistic derivation of classical compartmental models

In drug discovery and development, classical compartment models and physiologically based pharmacokinetic (PBPK) models are successfully used to analyze and predict the pharmacokinetics of drugs. So far, however, both approaches are used exclusively or in parallel, with little to no cross-fertilization. An approach that directly links classical compartment and PBPK models is highly desirable. We derived a new mechanistic lumping approach for reducing the complexity of PBPK models and establishing a direct link to classical compartment models. The proposed method has several advantages over existing methods: Perfusion and permeability rate limited models can be lumped; the lumped model allows for predicting the original organ concentrations; and the volume of distribution at steady state is preserved by the lumping method. To inform classical compartmental model development, we introduced the concept of a minimal lumped model that allows for prediction of the venous plasma concentration with as few compartments as possible. The minimal lumped parameter values may serve as initial values for any subsequent parameter estimation process. Applying our lumping method to 25 diverse drugs, we identified characteristic features of lumped models for moderate-to-strong bases, weak bases and acids. We observed that for acids with high protein binding, the lumped model comprised only a single compartment. The proposed lumping approach established for the first time a direct derivation of simple compartment models from PBPK models and enables a mechanistic interpretation of classical compartment models.

Drug-class specific impact of antivirals on the reproductive capacity of HIV

Predictive markers linking drug efficacy to clinical outcome are a key component in the drug discovery and development process. In HIV infection, two different measures, viral load decay and phenotypic assays, are used to assess drug efficacy in vivo and in vitro. For the newly introduced class of integrase inhibitors, a huge discrepancy between these two measures of efficacy was observed. Hence, a thorough understanding of the relation between these two measures of drug efficacy is imperative for guiding future drug discovery and development activities in HIV. In this article, we developed a novel viral dynamics model, which allows for a mechanistic integration of the mode of action of all approved drugs and drugs in late clinical trials. Subsequently, we established a link between in vivo and in vitro measures of drug efficacy, and extract important determinants of drug efficacy in vivo. The analysis is based on a new quantity-the reproductive capacity-that represents in mathematical terms the in vivo analog of the read-out of a phenotypic assay. Our results suggest a drug-class specific impact of antivirals on the total amount of viral replication. Moreover, we showed that the (drug-)target half life, dominated by immune-system related clearance processes, is a key characteristic that affects both the emergence of resistance as well as the in vitro-in vivo correlation of efficacy measures in HIV treatment. We found that protease- and maturation inhibitors, due to their target half-life, decrease the total amount of viral replication and the emergence of resistance most efficiently.

Physiologically-based PK/PD modelling of therapeutic macromolecules

Therapeutic proteins are a diverse class of drugs consisting of naturally occurring or modified proteins, and due to their size and physico-chemical properties, they can pose challenges for the pharmacokinetic and pharmacodynamic studies. Physiologically-based pharmacokinetics (PBPK) modelling has been effective for early in silico prediction of pharmacokinetic properties of new drugs. The aim of the present workshop was to discuss the feasibility of PBPK modelling of macromolecules. The classical PBPK approach was discussed with a presentation of the successful example of PBPK modelling of cyclosporine A. PBPK model was performed with transport of the cyclosporine across cell membranes, affinity to plasma proteins and active membrane transporters included to describe drug transport between physiological compartments. For macromolecules, complex PBPK modelling or permeability-limited and/or target-mediated distribution was discussed. It was generally agreed that PBPK modelling was feasible and desirable. The role of the lymphatic system should be considered when absorption after extravascular administration is modelled. Target-mediated drug disposition was regarded as an important feature for generation of PK models. Complex PK-models may not be necessary when a limited number of organs are affected. More mechanistic PK/PD models will be relevant when adverse events/toxicity are included in the PK/PD modelling.

Defining the role of macrophages in local moxifloxacin tissue concentrations using biopsy data and whole-body physiologically based pharmacokinetic modelling

OBJECTIVES

This study used a whole-body physiologically based pharmacokinetic (WB-PBPK) model for moxifloxacin, plus in vitro and in vivo literature data on its interaction with macrophages, to interpret biopsy results generated from patients undergoing primarily colorectal surgery.

METHODS

A WB-PBPK model was developed using PK-Sim(R) software and refined using observed plasma profiles. The model was assessed by comparing predictions of unbound interstitial concentrations with in vivo data from a microdialysis study.

RESULTS

Incorporating in vitro data on the percentage volume of macrophages in a colorectal resection (8.1%) plus the in vivo kinetic and accumulation potential of moxifloxacin in macrophages into the WB-PBPK model, biopsy concentrations and kinetics were predicted and compared with observed data. The WB-PBPK model accurately described adipose and muscle interstitial unbound concentrations. The predicted biopsy concentrations (including interstitial, intracellular, vascular space and macrophages) were slightly greater than the observed values, although the kinetic (i.e. observed biopsy half-life = 21 hours) was similar to that of moxifloxacin in macrophages (20.8 hours) and thus similar to the predicted biopsy half-life. A reduction in the predicted biopsy concentrations to match the observed data required a decrease in the volume fraction of macrophages from 8.1% to 3.6%.

CONCLUSION

When plasma concentrations are known, WB-PBPK is a method to determine interstitial and intracellular concentrations. In this study, integration of biopsy data with WB-PBPK allowed for generation and testing of hypotheses to determine the reason for the observed biopsy kinetics. This type of translational modelling may lead to a better understanding of the anti-infective pharmacokinetic/pharmacodynamic relationship.

Predicting plasma concentrations of bisphenol A in children younger than 2 years of age after typical feeding schedules, using a physiologically based toxicokinetic model

BACKGROUND

Concerns have recently been raised regarding the safety of potential human exposure to bisphenol A (BPA), an industrial chemical found in some polycarbonate plastics and epoxy resins. Of particular interest is the exposure of young children to BPA via food stored in BPA-containing packaging.

OBJECTIVES

In this study we assessed the age dependence of the toxicokinetics of BPA and its glucuronidated metabolite, BPA-Glu, using a coupled BPA-BPA-Glu physiologically based toxicokinetic (PBTK) model.

METHODS

Using information gathered from toxicokinetic studies in adults, we built a PBTK model. We then scaled the model to children < 2 years of age based on the age dependence of physiologic parameters relevant for absorption, distribution, metabolism, and excretion.

RESULTS

We estimated the average steady-state BPA plasma concentration in newborns to be 11 times greater than that in adults when given the same weight-normalized dose. Because of the rapid development of the glucuronidation process, this ratio dropped to 2 by 3 months of age. Simulation of typical feeding exposures, as estimated by regulatory authorities, showed a 5-fold greater steady-state BPA plasma concentration in 3- and 6-month-olds compared with adults, reflecting both a reduced capacity for BPA metabolism and a greater weight-normalized BPA exposure. Because of uncertainty in defining the hepatic BPA intrinsic clearance in adults, these values represent preliminary estimates.

CONCLUSIONS

Simulations of the differential BPA dosimetry between adults and young children point to the need for more sensitive analytical methods for BPA to define, with greater certainty, the adult hepatic BPA intrinsic clearance, as well as a need for external exposure data in young children.

Whole body physiologically-based pharmacokinetic models: their use in clinical drug development

BACKGROUND

Whole-body physiologically-based pharmacokinetic (WB-PBPK) models mathematically describe an organism as a closed circulatory system consisting of compartments that represent the organs important for compound absorption, distribution, metabolism and elimination.

OBJECTIVES

To review the current state of WB-PBPK model use in the clinical phases of drug development.

METHODS

A qualitative description of the WB-PBPK model structure is included along with a review of the varying methods available for input parameterisation. Current and potential WB-PBPK model application in clinical development is discussed.

CONCLUSIONS

This modelling tool is at present used for small and large molecule drug development primarily as a means to scale pharmacokinetics from animals to humans based on physiology. The pharmaceutical industry is active in employing these models to clinical drug development although the applications in use now are narrow in comparison to the potential. Expanded integration of WB-PBPK models into the drug development process will only be achieved with staff training, managerial will, success stories and regulatory agency openness.