Physiologically Based Pharmacokinetic Modelling of Cabotegravir Microarray Patches in Rats and Humans.

Microarray patches (MAPs) are currently under investigation as a self-administered, pain-free alternative used to achieve long-acting (LA) drug delivery. Cabotegravir is a potent antiretroviral that has demonstrated superior results over current pre-exposure prophylaxis (PrEP) regimens. This study aimed to apply physiologically based pharmacokinetic (PBPK) modelling to describe the pharmacokinetics of the dissolving bilayer MAP platform and predict the optimal dosing strategies for a once-weekly cabotegravir MAP. A mathematical description of a MAP was implemented into a PBPK model, and empirical models were utilised for parameter estimation. The intradermal PBPK model was verified against previously published in vivo rat data for intramuscular (IM) and MAP administration, and in vivo human data for the IM administration of LA cabotegravir. The verified model was utilised for the prediction of 300 mg, 150 mg and 75 mg once-weekly MAP administration in humans. Cabotegravir plasma concentrations >4 × protein-adjusted 90% inhibitory concentration (PA-IC90) (0.664 µg/mL) and >8 × PA-IC90 (1.33 µg/mL) were set as targets. The 75 mg, 150 mg and 300 mg once-weekly cabotegravir MAP regimens were predicted to sustain plasma concentrations >4 × PA-IC90, while the 300 mg and 150 mg regimens achieved plasma concentrations >8 × PA-IC90. These data demonstrate the potential for a once-weekly cabotegravir MAP using practical patch sizes for humans and inform the further development of cabotegravir MAPs for HIV PrEP.

Integrating Forward and Reverse Translation in PBPK Modeling to Predict Food Effect on Oral Absorption of Weakly Basic Drugs.

INTRODUCTION: Ketoconazole and posaconazole are two weakly basic broad-spectrum antifungals classified as Biopharmaceutics Classification System class II drugs, indicating that they are highly permeable, but exhibit poor solubility. As a result, oral bioavailability and clinical efficacy can be impacted by the formulation performance in the gastrointestinal system. In this work, we have leveraged in vitro biopharmaceutics and clinical data available in the literature to build physiologically based pharmacokinetic (PBPK) models for ketoconazole and posaconazole, to determine the suitability of forward in vitro-in vivo translation for characterization of in vivo drug precipitation, and to predict food effect. METHODS: A stepwise modeling approach was utilized to derive key parameters related to absorption, such as drug solubility, dissolution, and precipitation kinetics from in vitro data. These parameters were then integrated into PBPK models for the simulation of ketoconazole and posaconazole plasma concentrations in the fasted and fed states. RESULTS: Forward in vitro-in vivo translation of intestinal precipitation kinetics for both model drugs resulted in poor predictions of PK profiles. Therefore, a reverse translation approach was applied, based on limited fitting of precipitation-related parameters to clinical data. Subsequent simulations for ketoconazole and posaconazole demonstrated that fasted and fed state PK profiles for both drugs were adequately recapitulated. CONCLUSION: The two examples presented in this paper show how middle-out modeling approaches can be used to predict the magnitude and direction of food effects provided the model is verified on fasted state PK data.

Evaluating Islatravir Administered Via Microneedle Array Patch for Long-Acting HIV Pre-exposure Prophylaxis Using Physiologically Based Pharmacokinetic Modelling.

BACKGROUND AND OBJECTIVES: Technologies for long-acting administration of antiretrovirals (ARVs) for the prevention and treatment of HIV are at the forefront of research initiatives aiming to tackle issues surrounding drug adherence with the current standard of once-daily oral administration. Islatravir (ISL) is an emerging ARV that shows promising characteristics for long-acting prevention and treatment both orally as well as through alternative routes of administration. Microneedle array patches (MAPs) are a pain-free and discreet transdermal delivery technology that offer extended-release administration of nanoparticulate drugs. This study aimed to utilise physiologically based pharmacokinetic (PBPK) modelling to predict the pharmacokinetics resulting from ISL administered via MAP and to identify key MAP characteristics required to sustain effective concentrations over extended dosing intervals. METHODS: A PBPK model describing the conversion of ISL to ISL-triphosphate (ISL-TP) and its whole-body disposition was developed and verified against observed clinical data for orally administered ISL in healthy adults. An intradermal PBPK model was integrated with the ISL PBPK model to predict the dose and nanoparticle release rate required for MAP administration strategies capable of achieving a minimum ISL-TP target concentration of 0.05 pmol/106 PBMCs over extended dosing intervals. MAP design was limited to a maximum therapeutic area of 20 cm2 with a dose loading of 4.09 mg/cm2 and a minimum duration of 3 months. Due to the lack of available clinical data, a range of nanoparticle release rates and MAP bioavailability scenarios were simulated to provide an overview of potential clinical outcomes. RESULTS: The ISL PBPK model was successfully verified, with predicted vs observed ratios falling within 0.5-2-fold. ISL MAP doses ranging from 15 to 80 mg were predicted to sustain ISL-TP concentrations above the minimum target concentration at 3, 6 and 12 months after administration. Nanoparticle release rate and MAP bioavailability were found to have a major impact on whether dosing strategies achieved the criteria. Minimum doses of 15 mg and 60 mg with a nanoparticle release rate of 0.0005 h-1 and bioavailability ranging from 25 to 100% were predicted to achieve effective ISL-TP concentrations up to 3 and 6 months, respectively. Doses of 15 mg and 30 mg with a nanoparticle release rate of 0.0005 h-1 were also able to attain the target concentration up to 6 months after MAP administration, albeit with a minimum bioavailability of 75% and 50%, respectively. Furthermore, when simulating a bioavailability of 100%, an 80 mg ISL MAP was predicted to sustain ISL-TP concentrations above the minimum target concentration up to 12 months after administration. CONCLUSIONS: The ISL PBPK model successfully predicted ISL and ISL-TP pharmacokinetics across a range of orally administered regimens. The integrated intradermal PBPK model outlined optimal MAP dose and nanoparticle release rates for effective ISL-TP concentrations up to 12 months, providing justification for further investigation of ISL as a candidate for MAP administration.

PBPK Modelling of Dexamethasone in Patients With COVID-19 and Liver Disease.

The aim of the study was to apply Physiologically-Based Pharmacokinetic (PBPK) modelling to predict the effect of liver disease (LD) on the pharmacokinetics (PK) of dexamethasone (DEX) in the treatment of COVID-19. A whole-body PBPK model was created to simulate 100 adult individuals aged 18-60 years. Physiological changes (e.g., plasma protein concentration, liver size, CP450 expression, hepatic blood flow) and portal vein shunt were incorporated into the LD model. The changes were implemented by using the Child-Pugh (CP) classification system. DEX was qualified using clinical data in healthy adults for both oral (PO) and intravenous (IV) administrations and similarly propranolol (PRO) and midazolam (MDZ) were qualified with PO and IV clinical data in healthy and LD adults. The qualified model was subsequently used to simulate a 6 mg PO and 20 mg IV dose of DEX in patients with varying degrees of LD, with and without shunting. The PBPK model was successfully qualified across DEX, MDZ and PRO. In contrast to healthy adults, the simulated systemic clearance of DEX decreased (35%-60%) and the plasma concentrations increased (170%-400%) in patients with LD. Moreover, at higher doses of DEX, the AUC ratio between healthy/LD individuals remained comparable to lower doses. The exposure of DEX in different stages of LD was predicted through PBPK modelling, providing a rational framework to predict PK in complex clinical scenarios related to COVID-19. Model simulations suggest dose adjustments of DEX in LD patients are not necessary considering the low dose administered in the COVID-19 protocol.

Drug-Drug Interactions in People Living With HIV at Risk of Hepatic and Renal Impairment: Current Status and Future Perspectives.

Despite the advancement of antiretroviral therapy (ART) for the treatment of human immunodeficiency virus (HIV), drug-drug interactions (DDIs) remain a relevant clinical issue for people living with HIV receiving ART. Antiretroviral (ARV) drugs can be victims and perpetrators of DDIs, and a detailed investigation during drug discovery and development is required to determine whether dose adjustments are necessary or coadministrations are contraindicated. Maintaining therapeutic ARV plasma concentrations is essential for successful ART, and changes resulting from potential DDIs could lead to toxicity, treatment failure, or the emergence of ARV-resistant HIV. The challenges surrounding DDI management are complex in special populations of people living with HIV, and often lack evidence-based guidance as a result of their underrepresentation in clinical investigations. Specifically, the prevalence of hepatic and renal impairment in people living with HIV are between five and 10 times greater than in people who are HIV-negative, with each condition constituting approximately 15% of non-AIDS-related mortality. Therapeutic strategies tend to revolve around the treatment of risk factors that lead to hepatic and renal impairment, such as hepatitis C, hepatitis B, hypertension, hyperlipidemia, and diabetes. These strategies result in a diverse range of potential DDIs with ART. The purpose of this review was 2-fold. First, to summarize current pharmacokinetic DDIs and their mechanisms between ARVs and co-medications used for the prevention and treatment of hepatic and renal impairment in people living with HIV. Second, to identify existing knowledge gaps surrounding DDIs related to these special populations and suggest areas and techniques to focus upon in future research efforts.

Predicting Drug-Drug Interactions between Rifampicin and Ritonavir-Boosted Atazanavir Using PBPK Modelling.

OBJECTIVES: The aim of this study was to simulate the drug-drug interaction (DDI) between ritonavir-boosted atazanavir (ATV/r) and rifampicin (RIF) using physiologically based pharmacokinetic (PBPK) modelling, and to predict suitable dose adjustments for ATV/r for the treatment of people living with HIV (PLWH) co-infected with tuberculosis. METHODS: A whole-body DDI PBPK model was designed using Simbiology 9.6.0 (MATLAB R2019a) and verified against reported clinical data for all drugs administered alone and concomitantly. The model contained the induction mechanisms of RIF and ritonavir (RTV), the inhibition effect of RTV for the enzymes involved in the DDI, and the induction and inhibition mechanisms of RIF and RTV on the uptake and efflux hepatic transporters. The model was considered verified if the observed versus predicted pharmacokinetic values were within twofold. Alternative ATV/r dosing regimens were simulated to achieve the trough concentration (Ctrough) clinical cut-off of 150 ng/mL. RESULTS: The PBPK model was successfully verified according to the criteria. Simulation of different dose adjustments predicted that a change in regimen to twice-daily ATV/r (300/100 or 300/200 mg) may alleviate the induction effect of RIF on ATV Ctrough, with > 95% of individuals predicted to achieve Ctrough above the clinical cut-off. CONCLUSIONS: The developed PBPK model characterized the induction-mediated DDI between RIF and ATV/r, accurately predicting the reduction of ATV plasma concentrations in line with observed clinical data. A change in the ATV/r dosing regimen from once-daily to twice-daily was predicted to mitigate the effect of the DDI on the Ctrough of ATV, maintaining plasma concentration levels above the therapeutic threshold for most patients.

In vitro assessment of the potential for dolutegravir to affect hepatic clearance of levonorgestrel.

OBJECTIVES: The World Health Organization recommends that all countries adopt dolutegravir-based antiretroviral therapy as the preferred regimen for all individuals living with HIV. Levonorgestrel is a commonly used hormonal contraceptive, which undergoes drug-drug interactions with some antiretrovirals, but the potential interaction between dolutegravir and levonorgestrel has not been examined. We aimed to evaluate cytochrome P450 (CYP)-mediated levonorgestrel metabolism and quantify the effects of dolutegravir on levonorgestrel apparent intrinsic clearance (CLint.app. ) and CYP gene expression. METHODS: In vitro CYP-mediated CLint.app. of levonorgestrel was quantified using a recombinant human CYP (rhCYP) enzyme system. A primary human hepatocyte model of drug metabolism was used to assess the effects of dolutegravir on (1) levonorgestrel CLint.app. , using liquid chromatography-tandem mass spectrometry, and (2) the expression of specific CYP enzymes, using quantitative real-time polymerase chain reaction. RESULTS: Levonorgestrel clearance was mediated by multiple rhCYPs, including rhCYP3A4. Under control conditions, levonorgestrel CLint.app. was 22.4 ± 5.0 µL/min/106  hepatocytes. Incubation with 43.1 nM of unbound dolutegravir elevated levonorgestrel CLint.app. to 31.4 ± 7.8 µL/min/106  hepatocytes (P = 0.168), while 142.23 nM increased levonorgestrel CLint.app. to 37.0 ± 2.9 µL/min/106  hepatocytes (P = 0.012). Unbound dolutegravir ≥ 431 nM induced expression of CYP3A4 (≥ two-fold) in a dose-dependent manner, while 1.44 µM of unbound dolutegravir induced CYP2B6 expression 2.2 ± 0.3-fold (P = 0.0004). CONCLUSIONS: In summary, this in vitro study suggests that dolutegravir has the potential to increase hepatic clearance of levonorgestrel by inducing both CYP3A and non-CYP3A enzymes. The observed in vitro dolutegravir-levonorgestrel drug-drug interaction should be further examined in clinical studies.

Clinical Data Combined With Modeling and Simulation Indicate Unchanged Drug-Drug Interaction Magnitudes in the Elderly.

Age-related comorbidities and consequently polypharmacy are highly prevalent in the elderly, resulting in an increased risk for drug-drug interactions (DDIs). The effect of aging on DDI magnitudes is mostly uncertain, leading to missing guidance regarding the clinical DDI management in the elderly. Clinical data obtained in aging people living with HIV ≥ 55 years, who participated in the Swiss HIV Cohort Study, demonstrated unchanged DDI magnitudes with advanced aging for four studied DDI scenarios. These data plus published data for midazolam in the presence of clarithromycin and rifampicin in elderly individuals assessed the predictive potential of the used physiologically-based pharmacokinetic (PBPK) model to simulate DDIs in the elderly. All clinically observed data were generally predicted within the 95% confidence interval of the PBPK simulations. The verified model predicted subsequently the magnitude of 50 DDIs across adulthood (20-99 years) with 42 scenarios being only verified in adults aged 20-50 years in the absence of clinically observed data in the elderly. DDI magnitudes were not impacted by aging regardless of the involved drugs, DDI mechanism, mediators of DDIs, or the sex of the investigated individuals. The prediction of unchanged DDI magnitudes with advanced aging were proofed by 17 published, independent DDIs that were investigated in young and elderly subjects. In conclusion, this study demonstrated by combining clinically observed data with modeling and simulation that aging does not impact DDI magnitudes and thus, clinical management of DDIs can a priori be similar in aging men and women in the absence of severe comorbidities.

Effect of ageing on antiretroviral drug pharmacokinetics using clinical data combined with modelling and simulation.

AIMS: The impact of ageing on antiretroviral pharmacokinetics remains uncertain, leading to missing dosing recommendations for elderly people living with human immunodeficiency virus (HIV: PLWH). The objective of this study was to investigate whether ageing leads to clinically relevant pharmacokinetic changes of antiretrovirals that would support a dose adjustment based on the age of the treated PLWH. METHODS: Plasma concentrations for 10 first-line antiretrovirals were obtained in PLWH ≥55 years, participating in the Swiss HIV Cohort Study, and used to proof the predictive performance of our physiologically based pharmacokinetic (PBPK) model. The verified PBPK model predicted the continuous effect of ageing on HIV drug pharmacokinetics across adulthood (20-99 years). The impact of ethnicity on age-related pharmacokinetic changes between whites and other races was statistically analysed. RESULTS: Clinically observed concentration-time profiles of all investigated antiretrovirals were generally within the 95% confidence interval of the PBPK simulations, demonstrating the predictive power of the modelling approach used. The predicted decline in drug clearance drove age-related pharmacokinetic changes of antiretrovirals, resulting in a maximal 70% [95% confidence interval: 40%, 120%] increase in antiretrovirals exposure across adulthood. Peak concentration, time to peak concentration and apparent volume of distribution were predicted to be unaltered by ageing. There was no statistically significant difference of age-related pharmacokinetic changes between studied ethnicities. CONCLUSION: Dose adjustment for antiretrovirals based on the age of male and female PLWH is a priori not necessary in the absence of severe comorbidities considering the large safety margin of the current first-line HIV treatments.

Physiologically Based Pharmacokinetic Modelling to Identify Pharmacokinetic Parameters Driving Drug Exposure Changes in the Elderly.

BACKGROUND: Medication use is highly prevalent with advanced age, but clinical studies are rarely conducted in the elderly, leading to limited knowledge regarding age-related pharmacokinetic changes. OBJECTIVE: The objective of this study was to investigate which pharmacokinetic parameters determine drug exposure changes in the elderly by conducting virtual clinical trials for ten drugs (midazolam, metoprolol, lisinopril, amlodipine, rivaroxaban, repaglinide, atorvastatin, rosuvastatin, clarithromycin and rifampicin) using our physiologically based pharmacokinetic (PBPK) framework. METHODS: PBPK models for all ten drugs were developed in young adults (20-50 years) following the best practice approach, before predicting pharmacokinetics in the elderly (≥ 65 years) without any modification of drug parameters. A descriptive relationship between age and each investigated pharmacokinetic parameter (peak concentration [Cmax], time to Cmax [tmax], area under the curve [AUC], clearance, volume of distribution, elimination-half-life) was derived using the final PBPK models, and verified with independent clinically observed data from 52 drugs. RESULTS: The age-related changes in drug exposure were successfully simulated for all ten drugs. Pharmacokinetic parameters were predicted within 1.25-fold (70%), 1.5-fold (86%) and 2-fold (100%) of clinical data. AUC increased progressively by 0.9% per year throughout adulthood from the age of 20 years, which was explained by decreased clearance, while Cmax, tmax and volume of distribution were not affected by human aging. Additional clinical data of 52 drugs were contained within the estimated variability of the established age-dependent correlations for each pharmacokinetic parameter. CONCLUSION: The progressive decrease in hepatic and renal blood flow, as well as glomerular filtration, rate led to a reduced clearance driving exposure changes in the healthy elderly, independent of the drug.

Repository Describing an Aging Population to Inform Physiologically Based Pharmacokinetic Models Considering Anatomical, Physiological, and Biological Age-Dependent Changes.

BACKGROUND: Aging is characterized by anatomical, physiological, and biological changes that can impact drug kinetics. The elderly are often excluded from clinical trials and knowledge about drug kinetics and drug-drug interaction magnitudes is sparse. Physiologically based pharmacokinetic modeling can overcome this clinical limitation but detailed descriptions of the population characteristics are essential to adequately inform models. OBJECTIVE: The objective of this study was to develop and verify a population database for aging Caucasians considering anatomical, physiological, and biological system parameters required to inform a physiologically based pharmacokinetic model that included population variability. METHODS: A structured literature search was performed to analyze age-dependent changes of system parameters. All collated data were carefully analyzed, and descriptive mathematical equations were derived. RESULTS: A total of 362 studies were found of which 318 studies were included in the analysis as they reported rich data for anthropometric parameters and specific organs (e.g., liver). Continuous functions could be derived for most system parameters describing a Caucasian population from 20 to 99 years of age with variability. Areas with sparse data were identified such as tissue composition, but knowledge gaps were filled with plausible qualified assumptions. The developed population was implemented in Matlab® and estimated system parameters from 1000 virtual individuals were in accordance with independent observed data showing the robustness of the developed population. CONCLUSIONS: The developed repository for aging subjects provides a singular specific source for key system parameters needed for physiologically based pharmacokinetic modeling and can in turn be used to investigate drug kinetics and drug-drug interaction magnitudes in the elderly.

Analysis of Clinical Drug-Drug Interaction Data To Predict Magnitudes of Uncharacterized Interactions between Antiretroviral Drugs and Comedications.

Despite their high potential for drug-drug interactions (DDI), clinical DDI studies of antiretroviral drugs (ARVs) are often lacking, because the full range of potential interactions cannot feasibly or pragmatically be studied, with some high-risk DDI studies also being ethically difficult to undertake. Thus, a robust method to screen and to predict the likelihood of DDIs is required. We developed a method to predict DDIs based on two parameters: the degree of metabolism by specific enzymes, such as CYP3A, and the strength of an inhibitor or inducer. These parameters were derived from existing studies utilizing paradigm substrates, inducers, and inhibitors of CYP3A to assess the predictive performance of this method by verifying predicted magnitudes of changes in drug exposure against clinical DDI studies involving ARVs. The derived parameters were consistent with the FDA classification of sensitive CYP3A substrates and the strength of CYP3A inhibitors and inducers. Characterized DDI magnitudes (n = 68) between ARVs and comedications were successfully quantified, meaning 53%, 85%, and 98% of the predictions were within 1.25-fold (0.80 to 1.25), 1.5-fold (0.66 to 1.48), and 2-fold (0.66 to 1.94) of the observed clinical data. In addition, the method identifies CYP3A substrates likely to be highly or, conversely, minimally impacted by CYP3A inhibitors or inducers, thus categorizing the magnitude of DDIs. The developed effective and robust method has the potential to support a more rational identification of dose adjustment to overcome DDIs, being particularly relevant in an HIV setting, given the treatment's complexity, high DDI risk, and limited guidance on the management of DDIs.

The biological challenges and pharmacological opportunities of orally administered nanomedicine delivery.

INTRODUCTION: Nano-scale formulations are being developed to improve the delivery of orally administered medicines, and the interactions between nanoformulations and the gastrointestinal luminal, mucosal and epithelial environment is currently being investigated. The mucosal surface of the gastrointestinal tract is capable of trapping and eliminating large particles and pathogens as part of the natural defences of the body, it is becoming clearer that nanoformulation properties such as particle size, charge, and shape, as well as mucous properties such as viscoelasticity, thickness, density, and turn-over time are all relevant to these interactions. However, progress has been slow to utilise this information to produce effective mucous-penetrating particles. Areas covered: This review focuses on delivery method of nanomedicines both into and across the gastrointestinal mucosal surface, and aims to summarise the biological barriers that exist to successful oral nanomedicine delivery and how these barriers may be investigated and overcome. Expert commentary: Despite successes in the laboratory, no nanotechnology-enabled products are currently in clinical use which either specifically target the intestinal mucous surface or cross the epithelial barrier intact. New nanomedicine-based treatments of local diseases (intestinal cancer, inflammation, infection) and systemic diseases are advancing towards clinical use, and offer genuine opportunities to improve therapy.

Elemental and molecular profiling of licit, illicit, and niche tobacco.

The recognition of differences between regulated large-scale mass manufactured products and the uncontrolled cultivation of tobaccos for illicit purposes plays a significant role within identification of provenance. This research highlights X-ray fluorescence and Fourier transform infrared spectroscopy as useful analytical techniques for the rapid identification of tobacco samples of unknown provenance. Identification of key discriminative features within each technique allowed for the development of typical characteristic profiles for each type of tobacco. Analysis using X-ray fluorescence highlights chlorine, potassium, calcium and iron as key elemental indicators of tobacco provenance. Significant levels of chlorine seen within Snüs samples prompted attempts to visualise chlorine containing regions and structures within the sample. Scanning electron microscopy images showed crystalline structures visible within the Snüs tobacco, structures which Energy dispersive X-ray spectroscopy qualitatively confirmed to contain chlorine. Chloride levels within Snüs samples were quantified using ion chromatography with levels found to range between 0.87mgmL(-1) and 1.28mg. Additionally, FTIR indicated that absorbances attributed to carbonyl stretching at 1050-1150cm(-1), alkane bending at 1350-1480cm(-1) and amide I stretching at 1600-1700cm(-1) highlighting a spectral fingerprint region that allowed for the clear differentiation between different types of tobaccos using PCA analysis, but was limited by differentiation between provenance of cigarettes and hand rolled tobacco. X-ray fluorescence and Fourier transform infrared spectroscopy yielded different information with regards tobacco discrimination and provenance, however both methods overall analysis time and cost reduced indicating usefulness as potential handheld analytical techniques in the field.