Development of a Whole-Body Physiologically Based Pharmacokinetic Approach to Assess the Pharmacokinetics of Drugs in Elderly Individuals

Pediatric off-label use and nonadherence management for nadolol: A mechanistic PBPK model Incorporating Ontogeny Scaling from Interracial Adults to Children

Nadolol has demonstrated its superior efficacy over other β-blockers in the treatment of specific cardiovascular diseases in children. The clinical development of nadolol for pediatric use was prioritized by Chinese healthcare authorities in May 2023 while there was a lack of clear medication instructions for children. To expedite the pediatric development of nadolol and provide insights into its off-label applications, we developed a physiologically based pharmacokinetic model incorporating mechanistic disposition knowledge. This model integrates key processes of nadolol including P-glycoprotein (P-gp) transporter mediated the absorption of efflux, multidrug and toxin extrusion protein (MATE) 1 transporter and organic cation (OCT) 2 transporter mediated active renal excretion, organic anion transporting polypeptides (OATP) 1A2 mediated transport, along with biliary excretion. The model accurately captured the pharmacokinetic profiles of nadolol in both Western and East Asian populations following a wide dose range (2-160 mg), including the plasma concentration, urine excretion, and drug-drug interactions with the P-gp inhibitor. After our good validation on interracial adult populations, simulations of nadolol pharmacokinetic profiles in the Chinese population were performed by adjusting the liver volume of the Chinese to 0.9 of the Japanese population. Then, with the consideration of physiological changes and plasma protein ontogeny in pediatrics, the nadolol model for pediatrics was also well-verified on several children aged 3 months to 121 months. Accordingly, specific optimal dosages for children across various ages and racial backgrounds with or without obesity were offered by exposure matching with adults. Multiple remedial regimen simulations were also compared to obtain the best nonadherence management in the case of missed dosages, in which resuming a regular dose as soon as possible was the most recommended.

A comprehensive library of lifetime physiological equations for PBK models: Enhancing dietary exposure modeling with mercury as a case study

Dietary risk assessment of food contaminants requires a well-established understanding of the exposure in a heterogeneous population. There are many methods for estimating human exposure to food contaminants, such as intake calculations and internal biomarkers of exposure measured in individuals. However, those methods are expensive, partly invasive, and often provide a momentary exposure snapshot. Physiologically Based Kinetic (PBK) modelling is increasingly used to overcome those challenges that traditional human exposure methods encounter. Still, PBK models are often restricted to certain life stages (e.g., children, adolescents, adults). This study outlines a strategy for implementing nonlinear organ growths in age-specific PBK models to enhance dietary risk assessment from lifetime exposure. To this end, lifetime physiological equations calculating organ growth for both sexes were inventoried from literature and a library was established for 24 organs. We then assessed total lifelong mercury exposure via foodstuff by combining two existing age-specific PBK models for methylmercury (MeHg) and inorganic mercury (iHg) that simulated internal exposure to total mercury, the speciation typically measured in hair and urine. We implemented a set of physiological equations in the PBK model that fitted best the total mercury measured in individuals' organs, hair, and urine from heterogeneous populations. For refined dietary risk assessment, we ultimately estimated total mercury concentration in hair and urine based on i) maximum limits defined by the regulation for MeHg in seafood, ii) the health-based guidance values for MeHg and iHg, and iii) realistic intakes considering French demographic parameters and food consumption data. These exposure scenarios demonstrated that total mercury concentrations in hair and urine estimated from realistic intakes are below critical effect level measures at all ages. The result of this study is the creation of easily accessible tools in Excel and R that facilitate the implementation of physiological equations in Next Generation PBK models.

Physiologically based pharmacokinetic model of brivaracetam to predict the exposure and dose exploration in hepatic impairment and elderly populations

Brivaracetam (BRV) is a new third-generation antiseizure medication for the treatment of focal epileptic seizures. Its use has been increasing among epileptic populations in recent years, but pharmacokinetic (PK) behavior may change in hepatic impairment and the elderly populations. Due to ethical constraints, clinical trials are difficult to conduct and data are limited. This study used PK-Sim® to develop a physiologically based pharmacokinetic (PBPK) model for adults and extrapolate it to hepatic impairment and the elderly populations. The model was evaluated with clinical PK data, and dosage explorations were conducted. For the adult population with mild hepatic impairment, the dose is recommended to be adjusted to 70 % of the recommended dose, and to 60 % for moderate and severe hepatic impairment. For the elderly population with mild hepatic impairment under 80 years old, it is recommended that the dose be adjusted to 60 % of the recommended dose and to 50 % for moderate and severe conditions. The elderly population with hepatic impairment over 80 years old is adjusted to 50 % of the recommended dose for all stages. Healthy elderly do not need to adjust. The BRV PBPK model was successfully developed, studying exposure in hepatic impairment and elderly populations and optimizing dosing regimens.

Application of Physiologically Based Pharmacokinetic Model to Delineate the Impact of Aging and Renal Impairment on Ceftazidime Clearance

The impact of physiological changes during aging on drug disposition has not always been thoroughly assessed in clinical studies. This has left an open question such as how and to what extent patho- and physiological changes in renal function can affect pharmacokinetics in the geriatric population. The objective of this work was to use a physiologically based pharmacokinetic (PBPK) model to quantify the impact of aging and renal impairment (RI) separately and together on ceftazidime pharmacokinetics (PK). The predicted plasma concentrations and PK parameters from the PBPK model were compared to the observed data in individuals of different ages with or without RI (16 independent studies were investigated in this analysis). Apart from clearance in one study, the predicted ceftazidime PK parameters of young adults, elderly, and in individuals with different levels of renal function were within 2-fold of the observed data, and the observed concentrations fell within the 5th-95th prediction interval from the PBPK model simulations. The PBPK model predicted a 1.2-, 1.5-, and 1.8-fold increase in the plasma exposure (AUC) ratio in individuals aged 40, 60, and 70 years old, respectively, with normal renal function for their age compared to 20-year-old individuals with normal renal function. The impact of RI on ceftazidime was predicted to be less marked in older individuals (a 1.04-, 1.43-, and 2.55-fold change in mild, moderate, or severe RI compared to a healthy age-matched control) than in younger individuals (where a 1.47-, 2.03-, and 3.50-fold increase was predicted in mild, moderate, or severe RI compared to a healthy age-matched control). Utilization of the applied population-based PBPK approach allows delineation of the effects of age from renal disease and can better inform future study design and dosing recommendations in clinical study of elderly patients depending on their age and renal function.

Appropriate use of triazolam in elderly patients considering a quantitative benefit-risk assessment based on the pharmacokinetic-pharmacodynamic modeling and simulation approach supported by real-world data

BACKGROUND

Triazolam is a typical drug commonly used in the elderly; however, there have been concerns about its adverse events resulting from age-related changes in physiological function and drug interactions with concomitant drugs. Thus, updated information contributing to the appropriate use based on the latest pharmacokinetic and post-marketing surveillance methods is needed. In this study, we evaluated the appropriate use of triazolam in the elderly by integrating real-world data with a modeling and simulation approach.

METHODS

The occurrence risk of adverse events in the elderly was evaluated using the spontaneous adverse event reporting regulatory databases from Japan and the United States. Information on drug concentrations and reactions was extracted from previous publications to estimate the threshold for plasma triazolam concentrations that cause adverse events. The pharmacokinetic/pharmacodynamic (PK/PD) model was then constructed, and the dose and administration were evaluated in various situations anticipated in medical practice.

RESULTS

Among all prescriptions, 25.4% were prescribed to individuals aged 80 years or above, and 51.8% were for those aged 70 years or above. A majority of cases involved CYP3A-metabolized drug combinations, accounting for 85.6%. Elderly individuals were at a higher risk of developing delirium and fall-fracture. Based on the constructed PK/PD model, the risk of adverse events increased when the plasma concentration of triazolam exceeded the calculated threshold of 0.44 ng/mL at approximately 6 h after administration. Administering 0.125 mg of triazolam, is half the approved dose for the elderly in Japan was deemed appropriate. Moreover, there was a substantial risk of adverse events even at a dosage of 0.0625 mg in combination with a moderate or strong inhibitor of cytochrome P450 3 A.

CONCLUSION

Analyzing large-scale databases and existing research publications on PK/PD can practically contribute to optimizing triazolam drug therapy for the elderly in the daily clinical setting.

Physiologically Based Pharmacokinetic Modelling in Critically Ill Children Receiving Anakinra While on Extracorporeal Life Support

BACKGROUND AND OBJECTIVE

Because of the pathophysiological changes associated with critical illness and the use of extracorporeal life support (ECLS) such as continuous renal replacement therapy (CRRT) and extracorporeal membrane oxygenation (ECMO), the pharmacokinetics of drugs are often altered. The objective of this study was to develop a physiologically based pharmacokinetic (PBPK) model for anakinra in children that accounts for the physiological changes associated with critical illness and ECLS technology to guide appropriate pharmacotherapy.

METHODS

A PBPK model for anakinra was first developed in healthy individuals prior to extrapolating to critically ill children receiving ECLS. To account for the impact of anakinra clearance by the dialysis circuit, a CRRT compartment was added to the pediatric PBPK model and parameterized using data from a previously published ex-vivo study. Additionally, an ECMO compartment was added to the whole-body structure to create the final anakinra ECLS-PBPK model. The final model structure was validated by comparing predicted concentrations with observed patient data. Due to limited information in guiding anakinra dosing in this population, in-silico dose simulations were conducted to provide baseline recommendations.

RESULTS

By accounting for changes in physiology and the addition of ECLS compartments, the final ECLS-PBPK model predicted the observed plasma concentrations in an adolescent receiving subcutaneous anakinra. Furthermore, dosing simulations suggest that anakinra exposure in adolescents receiving ECLS is similar to that in healthy counterparts.

CONCLUSION

The anakinra ECLS-PBPK model developed in this study is the first to predict plasma concentrations in a population receiving simultaneous CRRT and ECMO. Dosing simulations provided may be used to inform anakinra use in critically ill children and guide future clinical trial planning.

Naringenin as potent anticancer phytocompound in breast carcinoma: from mechanistic approach to nanoformulations based therapeutics

The bioactive compounds present in citrus fruits are gaining broader acceptance in oncology. Numerous studies have deciphered naringenin's antioxidant and anticancer potential in human and animal studies. Naringenin (NGE) potentially suppresses cancer progression, thereby improving the health of cancer patients. The pleiotropic anticancer properties of naringenin include inhibition of the synthesis of growth factors and cytokines, inhibition of the cell cycle, and modification of several cellular signaling pathways. As an herbal remedy, naringenin has significant pharmacological properties, such as anti-inflammatory, antioxidant, neuroprotective, hepatoprotective, and anti-cancer activities. The inactivation of carcinogens following treatment with pure naringenin, naringenin-loaded nanoparticles, and naringenin combined with anti-cancer agents was demonstrated by data in vitro and in vivo studies. These studies included colon cancer, lung neoplasms, breast cancer, leukemia and lymphoma, pancreatic cancer, prostate tumors, oral squamous cell carcinoma, liver cancer, brain tumors, skin cancer, cervical and ovarian cancers, bladder neoplasms, gastric cancer, and osteosarcoma. The effects of naringenin on processes related to inflammation, apoptosis, proliferation, angiogenesis, metastasis, and invasion in breast cancer are covered in this narrative review, along with its potential to develop novel and secure anticancer medications.

Simulated pharmacokinetics of inhaled caffeine and melatonin from existing products indicate the lack of dosimetric considerations

Numerous commercially available inhalable products claim to improve sleep-wake cycle-related target indications by delivering a wide variety of chemicals like caffeine and melatonin. The resulting exposure-responses from inhaling different doses are unknown and obtaining early understanding of resulting pharmacokinetics is beneficial. This study applied a physiologically based pharmacokinetic modeling approach to predict the inhalation pharmacokinetics of caffeine and melatonin for different target indications related to the sleep-wake cycle. The model predicted rapid systemic delivery of caffeine and melatonin based on airway regional deposition of inhaled aerosol. A low inhaled dose of 1 mg of caffeine resulted in a 72.3-times lower plasma maximal concentration and was predicted to not improve cognitive performance task outcomes compared to oral consumption of coffee containing 80 mg of caffeine. Conversely, 2-mg oral and inhaled doses of melatonin under recommended directions of use result in more than 25.1- and 645-times higher plasma concentrations compared to endogenous melatonin, respectively. The recommended doses for inhalation products for potential improvement in the target indications vary widely. Additional research is needed to evaluate the human pharmacokinetics, efficacy, and safety of inhaled products. Given the lack of assessments, inhaled caffeine and melatonin must be consumed with caution as the toxicological concerns are not known and could outweigh the potential beneficial effects.

The Difficulties of Managing Pain in People Living with Frailty: The Potential for Digital Phenotyping

Pain and frailty are closely linked. Chronic pain is a risk factor for frailty, and frailty is a risk factor for pain. People living with frailty also commonly have cognitive impairment, which can make assessment of pain and monitoring of pain management even more difficult. Pain may be sub-optimally treated in people living with frailty, people living with cognitive impairment and those with both these factors. Reasons for sub-optimal treatment in these groups are pharmacological (increased drug side effects, drug-drug interactions, polypharmacy), non-pharmacological (erroneous beliefs about pain, ageism, bidirectional communication challenges), logistical (difficulty in accessing primary care practitioners and unaffordable cost of drugs), and, particularly in cognitive impairment, related to communication difficulties. Thorough assessment and characterisation of pain, related sensations, and their functional, emotional, and behavioural consequences ("phenotyping") may help to enhance the assessment of pain, particularly in people with frailty and cognitive impairment, as this may help to identify who is most likely to respond to certain types of treatment. This paper discusses the potential role of "digital phenotyping" in the assessment and management of pain in people with frailty. Digital phenotyping is concerned with observable characteristics in digital form, such as those obtained from sensing-capable devices, and may provide novel and more informative data than existing clinical approaches regarding how pain manifests and how treatment strategies affect it. The processing of extensive digital and usual data may require powerful algorithms, but processing these data could lead to a better understanding of who is most likely to benefit from specific and targeted treatments.

Physiologically based pharmacokinetic modeling of apixaban to predict exposure in populations with hepatic and renal impairment and elderly populations

BACKGROUND

Apixaban is a factor Xa inhibitor with a limited therapeutic index that belongs to the family of oral direct anticoagulants. The pharmacokinetic (PK) behavior of apixaban may be altered in elderly populations and populations with renal or hepatic impairment, necessitating dosage adjustments.

METHODS

This study was conducted to examine how the physiologically based pharmacokinetic (PBPK) model describes the PKs of apixaban in adult and elderly populations and to determine the PKs of apixaban in elderly populations with renal and hepatic impairment. After PBPK models were constructed using the reported physicochemical properties of apixaban and clinical data, they were validated using data from clinical studies involving various dose ranges. Comparing predicted and observed blood concentration data and PK parameters was utilized to evaluate the model's fit performance.

RESULTS

Doses should be reduced to approximately 70% of the healthy adult population for the healthy elderly population to achieve the same PK exposure; approximately 88%, 71%, and 89% of that for the elderly populations with mild, moderate, and severe renal impairment, respectively; and approximately 96%, 81%, and 58% of that for the Child Pugh-A, Child Pugh-B, and Child Pugh-C hepatic impairment elderly populations, respectively to achieve the same PK exposure.

CONCLUSION

The findings indicate that the renal and hepatic function might be considered for apixaban therapy in Chinese elderly patients and the PBPK model can be used to optimize dosage regimens for specific populations.

Physiologically based pharmacokinetic modeling of candesartan to predict the exposure in hepatic and renal impairment and elderly populations

Background

Candesartan cilexetil is a widely used angiotensin II receptor blocker with minimal adverse effects and high tolerability for the treatment of hypertension. Candesartan is administered orally as the prodrug candesartan cilexetil, which is wholly and swiftly converted to the active metabolite candesartan by carboxylesterase during absorption in the intestinal tract. In populations with renal or hepatic impairment, candesartan's pharmacokinetic (PK) behavior may be altered, necessitating dosage adjustments.

Objectives

This study was conducted to examine how the physiologically based PK (PBPK) model characterizes the PKs of candesartan in adult and geriatric populations and to predict the PKs of candesartan in elderly populations with renal and hepatic impairment.

Design

After developing PBPK models using the reported physicochemical properties of candesartan and clinical data, these models were validated using data from clinical investigations involving various dose ranges.

Methods

Comparing predicted and observed blood concentration data and PK parameters was used to assess the fit performance of the models.

Results

Doses should be reduced to approximately 94% of Chinese healthy adults for the Chinese healthy elderly population; approximately 92%, 68%, and 64% of that of the Chinese healthy adult dose in elderly populations with mild, moderate, and severe renal impairment, respectively; and approximately 72%, 71%, and 52% of that of the Chinese healthy adult dose in elderly populations with Child-Pugh-A, Child-Pugh-B, and Child-Pugh-C hepatic impairment, respectively.

Conclusion

The results suggest that the PBPK model of candesartan can be utilized to optimize dosage regimens for special populations.

Population Pharmacokinetics of Digoxin in Nonagenarian Patients: Optimization of the Dosing Regimen

OBJECTIVE

The aim of this study was to develop a population pharmacokinetic model of digoxin in patients over 90 years old and to propose an equation for adjusting digoxin dose in this population.

METHODS

We included 326 nonagenarian patients admitted to Severo Ochoa University Hospital (Spain) who received digoxin and were under therapeutic drug monitoring. All data were retrospectively collected, and population modeling was performed with non-linear mixed-effect modeling software (NONMEM®). One- and two-compartment models were tested to calculate digoxin clearance (Cl), volume of distribution (Vd), absorption rate constant (Ka), and bioavailability (bioavailable fraction, F). The covariates were evaluated by stepwise covariate model building, and the final model was internally validated by bootstrap analysis with 1000 resamples. External validation was performed with another population of 95 patients with the same characteristics as the modeling group.

RESULTS

The population was 26% males, with a mean age of 93.2 years (90-103 years), mean creatinine 1.11 mg/dL (0.42-3.81 mg/dL), and mean total body weight 61.2 kg (40-100 kg). The pharmacokinetics of digoxin were best described by a one-compartment model (ADVAN2 TRANS2), with first-order conditional estimation with interaction. The covariates with influence on our model were creatinine clearance based on the Cockcroft-Gault equation (CG), serum potassium (K), co-administration of loop diuretics, and sex: Cl/F = 4.55 · (CG/36.4)0.468 · 0.83LD · 1.21SEX; Vd/F = 355 · (K/4.3)-0.849; Ka = 1.22 h-1 [where LD indicates loop diuretics (1 for administered, 0 for otherwise) and SEX indicates patient sex (1 for male, 0 for female)]. Based on our results, we proposed an equation to adjust the digoxin dosing regimen in nonagenarian patients: dose (mg) = 0.144 · (CG/36.4)0.468 · 0.83LD · 1.21SEX.

CONCLUSIONS

The greatest influence on digoxin clearance came from renal function calculated by the Cockcroft-Gault equation. Vd was decreased by K. The model developed showed a precise predictive performance to be applied for therapeutic drug monitoring.

Apixaban and rivaroxaban's physiologically-based pharmacokinetic model validation in hospitalized patients: A first step for larger use of a priori modeling approach at bed side

When used in real-world conditions, substantial interindividual variations in direct oral anticoagulant (DOAC) plasma concentrations are observed for a given dose, leading to a risk of over- or under-exposure and clinically significant adverse events. Physiologically-based pharmacokinetic (PBPK) models could help physicians to tailor DOAC prescriptions in vulnerable patient populations, such as those in the hospital setting. The present study aims to validate prospectively PBPK models for rivaroxaban and apixaban in a large cohort of elderly, polymorbid, and hospitalized patients. In using a model of geriatric population integrating appropriate physiological parameters into models first optimized with healthy volunteer data, observed plasma concentration collected in hospitalized patients on apixaban (n = 100) and rivaroxaban (n = 100) were adequately predicted (ratio predicted/observed area under the concentration curve for a dosing interval [AUCtau ] = 0.97 [0.96-0.99] geometric mean, 90% confidence interval, ratio predicted/observed AUCtau  = 1.03 [1.02-1.05]) for apixaban and rivaroxaban, respectively. Validation of the present PBPK models for rivaroxaban and apixaban in in-patients represent an additional step toward the feasibility of bedside use.

Physiologically based pharmacokinetic (PBPK) modelling of oral drug absorption in older adults - an AGePOP review

The older population consisting of persons aged 65 years or older is the fastest-growing population group and also the major consumer of pharmaceutical products. Due to the heterogenous ageing process, this age group shows high interindividual variability in the dose-exposure-response relationship and, thus, a prediction of drug safety and efficacy is challenging. Although physiologically based pharmacokinetic (PBPK) modelling is a well-established tool to inform and confirm drug dosing strategies during drug development for special population groups, age-related changes in absorption are poorly accounted for in current PBPK models. The purpose of this review is to summarise the current state-of-knowledge in terms of physiological changes with increasing age that can influence the oral absorption of dosage forms. The capacity of common PBPK platforms to incorporate these changes and describe the older population is also discussed, as well as the implications of extrinsic factors such as drug-drug interactions associated with polypharmacy on the model development process. The future potential of this field will rely on addressing the gaps identified in this article, which can subsequently supplement in-vitro and in-vivo data for more robust decision-making on the adequacy of the formulation for use in older adults and inform pharmacotherapy.

Customizable 3D Printed Implants Containing Triamcinolone Acetonide: Development, Analysis, Modification, and Modeling of Drug Release

Three-dimensional-printed customizable drug-loaded implants provide promising opportunities to improve the current therapy options. In this study, we present a modular implant in which shape, dosage, and drug release can be individualized independently of each other to patient characteristics to improve parenteral therapy with triamcinolone acetonide (TA) over three months. This study focused on the examination of release modification via fused deposition modeling and subsequent prediction. The filaments for printing consisted of TA, ethyl cellulose, hypromellose, and triethyl citrate. Two-compartment implants were successfully developed, consisting of a shape-adaptable shell and an embedded drug-loaded network. For the network, different strand widths and pore size combinations were printed and analyzed in long-term dissolution studies to evaluate their impact on the release performance. TA release varied between 8.58 ± 1.38 mg and 21.93 mg ± 1.31 mg over three months depending on the network structure and the resulting specific surface area. Two different approaches were employed to predict the TA release over time. Because of the varying release characteristics, applicability was limited, but successful in several cases. Using a simple Higuchi-based approach, good release predictions could be made for a release time of 90 days from the release data of the initial 15 days (RMSEP ≤ 3.15%), reducing the analytical effort and simplifying quality control. These findings are important to establish customizable implants and to optimize the therapy with TA for specific intra-articular diseases.

Revisiting the in-vitro and in-vivo considerations for in-silico modelling of complex injectable drug products

Complex injectable drug products (CIDPs) have often been developed to modulate the pharmacokinetics along with efficacy for therapeutic agents used for remediation of chronic disorders. The effective development of CIDPs has exhibited complex kinetics associated with multiphasic drug release from the prepared formulations. Consequently, predictability of pharmacokinetic modelling for such CIDPs has been difficult and there is need for advanced complex computational models for the establishment of accurate prediction models for in-vitro-in-vivo correlation (IVIVC). The computational modelling aims at supplementing the existing knowledge with mathematical equations to develop formulation strategies for generation of predictable and discriminatory IVIVC. Such an approach would help in reduction of the burden of effect of hidden factors on preclinical to clinical translations. Computational tools like physiologically based pharmacokinetics (PBPK) modelling have combined physicochemical and physiological properties along with IVIVC characteristics of clinically used formulations. Such techniques have helped in prediction and understanding of variability in pharmacodynamic parameters of potential generic products to clinically used formulations like Doxil®, Ambisome®, Abraxane® in healthy and diseased population using mathematical equations. The current review highlights the important formulation characteristics, in-vitro, preclinical in-vivo aspects which need to be considered while developing a stimulatory predictive PBPK model in establishment of an IVIVC and in-vitro-in-vivo relationship (IVIVR).

Physiologically based pharmacokinetic modeling of levetiracetam to predict the exposure in hepatic and renal impairment and elderly populations

Levetiracetam (LEV) is an anti-epileptic drug approved for use in various populations. The pharmacokinetic (PK) behavior of LEV may be altered in the elderly and patients with renal and hepatic impairment. Thus, dosage adjustment is required. This study was conducted to investigate how the physiologically-based PK (PBPK) model describes the PKs of LEV in adult and elderly populations, as well as to predict the PKs of LEV in patients with renal and hepatic impairment in both populations. The whole-body PBPK models were developed using the reported physicochemical properties of LEV and clinical data. The models were validated using data from clinical studies with different dose ranges and different routes and intervals of administration. The fit performance of the models was assessed by comparing predicted and observed blood concentration data and PK parameters. It is recommended that the doses be reduced to ~70%, 60%, and 45% of the adult dose for the mild, moderate, and severe renal impairment populations and ~95%, 80%, and 57% of the adult dose for the Child Pugh-A (CP-A), Child Pugh-B (CP-B), and Child Pugh-C (CP-C) hepatic impairment populations, respectively. No dose adjustment is required for the healthy elderly population, but dose reduction is required for the elderly with organ dysfunction accordingly, on a scale similar to that of adults. A PBPK model of LEV was successfully developed to optimize dosing regimens for special populations.

Pharmacists' knowledge, perceptions and practices regarding frailty: A cross-sectional survey across practice settings in Canada

Background

Data on Canadian pharmacists' knowledge and perceptions about frailty in older adults and its assessment in pharmacy practice are scarce.

Methods

A cross-sectional survey of 349 Canadian pharmacists was conducted to evaluate pharmacists' knowledge, perceptions and practices regarding frailty. Descriptive analyses summarized responses by practice setting, and a multivariable logistic regression model examined associations between respondent characteristics and the likelihood of assessing frailty.

Results

Most respondents were female (70%), aged ≤34 years (47%), Canadian graduates (83%), from Ontario/Quebec (51%) and from urban centres (58%). Although a significant proportion agreed it is important for pharmacists to know (80%) and assess (56%) patient frailty status, only 36% reported assessing frailty in practice. Respondents exclusively practising in a community pharmacy were significantly less likely to agree that it is important for a pharmacist to know or assess frailty status and to report assessing it. Factors associated with a greater likelihood of assessment included positive beliefs about the importance of knowing a patient's frailty status and having a greater proportion of older patients with cognitive or functional impairment in practice.

Discussion

Findings suggest that pharmacists generally agree with the importance of understanding frailty as it relates to the appropriate use of medications, but most do not assess it. Further research is needed to identify the barriers to assessing frailty, while guidance is needed on which of the available screening tools can best be integrated into a clinical pharmacy practice.

Conclusion

There is an opportunity to improve pharmaceutical care for older adults by providing pharmacists the means and resources to assess frailty in practice.

An Overview of Physiologically-Based Pharmacokinetic Models for Forensic Science

A physiologically-based pharmacokinetic (PBPK) model represents the structural components of the body with physiologically relevant compartments connected via blood flow rates described by mathematical equations to determine drug disposition. PBPK models are used in the pharmaceutical sector for drug development, precision medicine, and the chemical industry to predict safe levels of exposure during the registration of chemical substances. However, one area of application where PBPK models have been scarcely used is forensic science. In this review, we give an overview of PBPK models successfully developed for several illicit drugs and environmental chemicals that could be applied for forensic interpretation, highlighting the gaps, uncertainties, and limitations.

In-Depth Analysis of Physiologically Based Pharmacokinetic (PBPK) Modeling Utilization in Different Application Fields Using Text Mining Tools

In the past decade, only a small number of papers have elaborated on the application of physiologically based pharmacokinetic (PBPK) modeling across different areas. In this review, an in-depth analysis of the distribution of PBPK modeling in relation to its application in various research topics and model validation was conducted by text mining tools. Orange 3.32.0, an open-source data mining program was used for text mining. PubMed was used for data retrieval, and the collected articles were analyzed by several widgets. A total of 2699 articles related to PBPK modeling met the predefined criteria. The number of publications per year has been rising steadily. Regarding the application areas, the results revealed that 26% of the publications described the use of PBPK modeling in early drug development, risk assessment and toxicity assessment, followed by absorption/formulation modeling (25%), prediction of drug-disease interactions (20%), drug-drug interactions (DDIs) (17%) and pediatric drug development (12%). Furthermore, the analysis showed that only 12% of the publications mentioned model validation, of which 51% referred to literature-based validation and 26% to experimentally validated models. The obtained results present a valuable review of the state-of-the-art regarding PBPK modeling applications in drug discovery and development and related fields.

Predictive performance and verification of physiologically based pharmacokinetic model of propylthiouracil

Background: Propylthiouracil (PTU) treats hyperthyroidism and thyroid crisis in all age groups. A variety of serious adverse effects can occur during clinical use and require attention to its pharmacokinetic and pharmacodynamic characteristics in various populations.

Objective: To provide information for individualized dosing and clinical evaluation of PTU in the clinical setting by developing a physiologically based pharmacokinetic (PBPK) model, predicting ADME characteristics, and extrapolating to elderly and pediatric populations.

Methods: Relevant databases and literature were retrieved to collect PTU’s pharmacochemical properties and ADME parameters, etc. A PBPK model for adults was developed using PK-Sim® software to predict tissue distribution and extrapolated to elderly and pediatric populations. The mean fold error (MFE) method was used to compare the differences between predicted and observed values to assess the accuracy of the PBPK model. The model was validated using PTU pharmacokinetic data in healthy adult populations.

Result: The MFE ratios of predicted to observed values of AUC0-t, Cmax, and Tmax were mainly within 0.5 and 2. PTU concentrations in various tissues are lower than venous plasma concentrations. Compared to healthy adults, the pediatric population requires quantitative adjustment to the appropriate dose to achieve the same plasma exposure levels, while the elderly do not require dose adjustments.

Conclusion: The PBPK model of PTU was successfully developed, externally validated, and applied to tissue distribution prediction and special population extrapolation, which provides a reference for clinical individualized drug administration and evaluation.

Patient-specific in vitro drug release testing coupled with in silico PBPK modeling to forecast the in vivo performance of oral extended-release levodopa formulations in Parkinson's disease patients

Biorelevant in vitro release models are valuable analytical tools for oral drug development but often tailored to gastrointestinal conditions in 'average' healthy adults. However, predicting in vivo performance in individual patients whose gastrointestinal conditions do not match those of healthy adults would be of great value for optimizing oral drug therapy for such patients. This study focused on establishing patient-specific in vitro and in silico models to predict the in vivo performance of levodopa extended-release products in Parkinsońs disease patients. Current knowledge on gastrointestinal conditions in these patients was incorporated into model development. Relevant in vivo pharmacokinetic data and patient-specific in vitro release data from a novel in vitro test setup were integrated into patient-specific physiologically-based pharmacokinetic models. AUC, c_max and t_max of the computed plasma profiles were calculated using PK-Sim®. For the products studied, levodopa plasma concentration-time profiles modeled using this novel approach compared far better with published average plasma profiles in Parkinsońs disease patients than those derived from in vitro release data obtained from the 'average' healthy adult setup. Although further work is needed, results of this study highlight the importance of addressing patient-specific gastrointestinal conditions when aiming to predict drug release in such specific patient groups.

Physiologically based pharmacokinetic (PBPK) modeling of flurbiprofen in different CYP2C9 genotypes

The aim of this study was to establish the physiologically based pharmacokinetic (PBPK) model of flurbiprofen related to CYP2C9 genetic polymorphism and describe the pharmacokinetics of flurbiprofen in different CYP2C9 genotypes. PK-Sim® software was used for the model development and validation. A total of 16 clinical pharmacokinetic data for flurbiprofen in different CYP2C9 genotypes, dose regimens, and age groups were used for the PBPK modeling. Turnover number (k_cat) of CYP2C9 values were optimized to capture the observed profiles in different CYP2C9 genotypes. In the simulation, predicted fraction metabolized by CYP2C9, fraction excreted to urine, bioavailability, and volume of distribution were similar to previously reported values. Predicted plasma concentration-time profiles in different CYP2C9 genotypes were visually similar to the observed profiles. Predicted AUC_inf in CYP2C9*1/*2, CYP2C9*1/*3, and CYP2C9*3/*3 genotypes were 1.44-, 2.05-, and 3.67-fold higher than the CYP2C9*1/*1 genotype. The ranges of fold errors for AUC_inf, C_max, and t_1/2 were 0.84-1.00, 0.61-1.22, and 0.74-0.94 in development and 0.59-0.98, 0.52-0.97, and 0.61-1.52 in validation, respectively, which were within the acceptance criterion. Thus, the PBPK model was successfully established and described the pharmacokinetics of flurbiprofen in different CYP2C9 genotypes, dose regimens, and age groups. The present model could guide the decision-making of tailored drug administration strategy by predicting the pharmacokinetics of flurbiprofen in various clinical scenarios.

A Physiologically Based Pharmacokinetic and Pharmacodynamic Model of the CYP3A4 Substrate Felodipine for Drug-Drug Interaction Modeling

The antihypertensive felodipine is a calcium channel blocker of the dihydropyridine type, and its pharmacodynamic effect directly correlates with its plasma concentration. As a sensitive substrate of cytochrome P450 (CYP) 3A4 with high first-pass metabolism, felodipine shows low oral bioavailability and is susceptible to drug–drug interactions (DDIs) with CYP3A4 perpetrators. This study aimed to develop a physiologically based pharmacokinetic/pharmacodynamic (PBPK/PD) parent–metabolite model of felodipine and its metabolite dehydrofelodipine for DDI predictions. The model was developed in PK-Sim^® and MoBi^® using 49 clinical studies (94 plasma concentration–time profiles in total) that investigated different doses (1–40 mg) of the intravenous and oral administration of felodipine. The final model describes the metabolism of felodipine to dehydrofelodipine by CYP3A4, sufficiently capturing the first-pass metabolism and the subsequent metabolism of dehydrofelodipine by CYP3A4. Diastolic blood pressure and heart rate PD models were included, using an E_max function to describe the felodipine concentration–effect relationship. The model was tested in DDI predictions with itraconazole, erythromycin, carbamazepine, and phenytoin as CYP3A4 perpetrators, with all predicted DDI AUC_last and C_max ratios within two-fold of the observed values. The model will be freely available in the Open Systems Pharmacology model repository and can be applied in DDI predictions as a CYP3A4 victim drug.

Determining the Effects of Chronic Kidney Disease on Organic Anion Transporter1/3 Activity Through Physiologically Based Pharmacokinetic Modeling

BACKGROUND AND OBJECTIVE

The renal excretion of drugs via organic anion transporters 1 and 3 (OAT1/3) is significantly decreased in patients with renal impairment. This study uses physiologically based pharmacokinetic models to quantify the reduction in OAT1/3-mediated secretion of drugs throughout varying stages of chronic kidney disease.

METHODS

Physiologically based pharmacokinetic models were constructed for four OAT1/3 substrates in healthy individuals: acyclovir, meropenem, furosemide, and ciprofloxacin. Observed data from drug-drug interaction studies with probenecid, a potent OAT1/3 inhibitor, were used to parameterize the contribution of OAT1/3 to the renal elimination of each drug. The models were then translated to patients with chronic kidney disease by accounting for changes in glomerular filtration rate, kidney volume, renal blood flow, plasma protein binding, and hematocrit. Additionally, a relationship was derived between the estimated glomerular filtration rate and the reduction in OAT1/3-mediated secretion of drugs based on the renal extraction ratios of ƿ-aminohippuric acid in patients with varying degrees of renal impairment. The relationship was evaluated in silico by evaluating the predictive performance of each final model in describing the pharmacokinetics (PK) of drugs across stages of chronic kidney disease.

RESULTS

OAT1/3-mediated renal excretion of drugs was found to be decreased by 27-49%, 50-68%, and 70-96% in stage 3, stage 4, and stage 5 of chronic kidney disease, respectively. In support of the parameterization, physiologically based pharmacokinetic models of four OAT1/3 substrates were able to adequately characterize the PK in patients with different degrees of renal impairment. Total exposure after intravenous administration was predicted within a 1.5-fold error and 85% of the observed data points fell within a 1.5-fold prediction error. The models modestly under-predicted plasma concentrations in patients with end-stage renal disease undergoing intermittent hemodialysis. However, results should be interpreted with caution because of the limited number of molecules analyzed and the sparse sampling in observed chronic kidney disease pharmacokinetic studies.

CONCLUSIONS

A quantitative understanding of the reduction in OAT1/3-mediated excretion of drugs in differing stages of renal impairment will contribute to better predictive accuracy for physiologically based pharmacokinetic models in drug development, assisting with clinical trial planning and potentially sparing this population from unnecessary toxic exposures.

Drug Distribution in Brain and Cerebrospinal Fluids in Relation to IC50 Values in Aging and Alzheimer's Disease, Using the Physiologically Based LeiCNS-PK3.0 Model

Background

Very little knowledge exists on the impact of Alzheimer’s disease on the CNS target site pharmacokinetics (PK).

Aim

To predict the CNS PK of cognitively healthy young and elderly and of Alzheimer’s patients using the physiologically based LeiCNS-PK3.0 model.

Methods

LeiCNS-PK3.0 was used to predict the PK profiles in brain extracellular (brain_ECF) and intracellular (brain_ICF) fluids and cerebrospinal fluid of the subarachnoid space (CSF_SAS) of donepezil, galantamine, memantine, rivastigmine, and semagacestat in young, elderly, and Alzheimer’s patients. The physiological parameters of LeiCNS-PK3.0 were adapted for aging and Alzheimer’s based on an extensive literature search. The CNS PK profiles at plateau for clinical dose regimens were related to in vitro IC₅₀ values of acetylcholinesterase, butyrylcholinesterase, N-methyl-D-aspartate, or gamma-secretase.

Results

The PK profiles of all drugs differed between the CNS compartments regarding plateau levels and fluctuation. Brain_ECF, brain_ICF and CSF_SAS PK profile relationships were different between the drugs. Aging and Alzheimer’s had little to no impact on CNS PK. Rivastigmine acetylcholinesterase IC₅₀ values were not reached. Semagacestat brain PK plateau levels were below the IC₅₀ of gamma-secretase for half of the interdose interval, unlike CSF_SAS PK profiles that were consistently above IC_50.

Conclusion

This study provides insights into the relations between CNS compartments PK profiles, including target sites. CSF_SAS PK appears to be an unreliable predictor of brain PK. Also, despite extensive changes in blood-brain barrier and brain properties in Alzheimer’s, this study shows that the impact of aging and Alzheimer’s pathology on CNS distribution of the five drugs is insignificant.

Supplementary Information

The online version contains supplementary material available at 10.1007/s11095-022-03281-3.

Physiologically-based pharmacokinetic modeling of dextromethorphan to investigate interindividual variability within CYP2D6 activity score groups

This study provides a whole‐body physiologically‐based pharmacokinetic (PBPK) model of dextromethorphan and its metabolites dextrorphan and dextrorphan O‐glucuronide for predicting the effects of cytochrome P450 2D6 (CYP2D6) drug‐gene interactions (DGIs) on dextromethorphan pharmacokinetics (PK). Moreover, the effect of interindividual variability (IIV) within CYP2D6 activity score groups on the PK of dextromethorphan and its metabolites was investigated. A parent‐metabolite‐metabolite PBPK model of dextromethorphan, dextrorphan, and dextrorphan O‐glucuronide was developed in PK‐Sim and MoBi. Drug‐dependent parameters were obtained from the literature or optimized. Plasma concentration‐time profiles of all three analytes were gathered from published studies and used for model development and model evaluation. The model was evaluated comparing simulated plasma concentration‐time profiles, area under the concentration‐time curve from the time of the first measurement to the time of the last measurement (AUC_last) and maximum concentration (C_max) values to observed study data. The final PBPK model accurately describes 28 population plasma concentration‐time profiles and plasma concentration‐time profiles of 72 individuals from four cocktail studies. Moreover, the model predicts CYP2D6 DGI scenarios with six of seven DGI AUC_last and seven of seven DGI C_max ratios within the acceptance criteria. The high IIV in plasma concentrations was analyzed by characterizing the distribution of individually optimized CYP2D6 k_cat values stratified by activity score group. Population simulations with sampling from the resulting distributions with calculated log‐normal dispersion and mean parameters could explain a large extent of the observed IIV. The model is publicly available alongside comprehensive documentation of model building and model evaluation.

Computational Models for Clinical Applications in Personalized Medicine—Guidelines and Recommendations for Data Integration and Model Validation

The future development of personalized medicine depends on a vast exchange of data from different sources, as well as harmonized integrative analysis of large-scale clinical health and sample data. Computational-modelling approaches play a key role in the analysis of the underlying molecular processes and pathways that characterize human biology, but they also lead to a more profound understanding of the mechanisms and factors that drive diseases; hence, they allow personalized treatment strategies that are guided by central clinical questions. However, despite the growing popularity of computational-modelling approaches in different stakeholder communities, there are still many hurdles to overcome for their clinical routine implementation in the future. Especially the integration of heterogeneous data from multiple sources and types are challenging tasks that require clear guidelines that also have to comply with high ethical and legal standards. Here, we discuss the most relevant computational models for personalized medicine in detail that can be considered as best-practice guidelines for application in clinical care. We define specific challenges and provide applicable guidelines and recommendations for study design, data acquisition, and operation as well as for model validation and clinical translation and other research areas.

Analysis of the Reactivity of Aspirin and Clopidogrel and Its Influencing Factors in Patients with Coronary Heart Disease at High Altitude

Objective

To evaluate the efficacy of dual-antiplatelet treatment (DAPT) in patients with coronary heart disease (CHD) at high altitude by using thrombelastogram (TEG) and to analyze the related biochemical factors affecting drug reactivity.

Methods

Totally 118 CHD patients who admitted to the Qinghai People's Hospital from September 2019 to September 2020 were enrolled in the group. Those people have lived in Qinghai for a long time. Seven days after DAPT, venous blood was collected on an empty stomach in the early morning of the next day; blood routine, coagulation function, and biochemical items were tested. Thrombelastogram (TEG) was used to draw curves to calculate platelet, coagulation and fibrinolysis functions, and drug inhibition rate. Patients were divided into the aspirin resistance (AR) group, clopidogrel resistance (CR) group, dual-antiplatelet drug resistance (DAR) group, and drug-sensitive group according to different inhibition rates. The drug efficacy was analyzed, and the clinical data, biochemical indexes, and TEG parameters of each group were compared to identify the risk factors of drug resistance.

Results

Those 118 CHD patients at high altitude were incorporated into the study, ranging from 38 to 84 years of age, including 81 males (68.64%) and 37 females (31.36%). The platelet function and coagulation-fibrinolysis function were detected by TEG, and MA_THROMBI, MA_ADP, and MA_AA were higher than the reference range. There were 82 cases (69.49%) of drug resistance, 36 cases (32.53%) of drug sensitivity, 17 cases (14.41%) of AR alone, and 16 cases (12.71%) of CR alone. There was no significant difference in age, gender, BMI, oxygen saturation, TG, GFR, and history of diabetes and hypertension between ACS and CCS groups (P > 0.05). PLT and FIB in the ACS group were higher than those in the CCS group, and the difference was statistically significant (P < 0.05). In addition, MA_THROMBIN, MA_FIBRIN, E, A, A30, and coagulation composite index were also higher than those in the CCS group, with a statistically significant difference (P < 0.05). Univariate analysis and logistic regression analysis suggested that age, HbA1c, FBG, and diabetes were the main factors of drug resistance.

Conclusion

Antiplatelet drugs aspirin and clopidogrel resistance are associated with increased age, elevated HbA1c and FBG, and diabetes. Therefore, it is necessary to take reasonable treatment measures based on the actual situation of patients.

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 (C_trough) 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 C_trough, with > 95% of individuals predicted to achieve C_trough 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 C_trough of ATV, maintaining plasma concentration levels above the therapeutic threshold for most patients.

Supplementary Information

The online version contains supplementary material available at 10.1007/s40262-021-01067-1.

Age-Related Change in Hepatic Clearance Inferred from Multiple Population Pharmacokinetic Studies: Comparison with Renal Clearance and Their Associations with Organ Weight and Blood Flow

OBJECTIVE

This study aimed to examine the magnitude of age-related change in hepatic clearance by integrating the data of multiple drugs and to compare this with renal clearance, considering associations with age-related changes in organ weight and blood flow.

METHODS

The results of multiple population pharmacokinetic analyses that detected age-related clearance changes in hepatically eliminated drugs were collected. The relationship between hepatic clearance of the unbound drug and age was then analyzed using the nonlinear least-squares method, adjusting for interdrug differences. The obtained change in hepatic clearance was compared with age-related changes in liver weight and hepatic blood flow in Japanese and Westerners. For comparison, the changes in renal clearance were analyzed similarly.

RESULTS

In total, 18 drugs were analyzed. The hepatic unbound clearance decreased by 32% at age 80 years and by 40% at age 90 years, compared with age 40 years, suggesting that it decreased by 0.80% per year with aging. The rate of the decrease was consistent with decreases in hepatic weight per person or blood flow per person, regardless of ethnicity and sex. Since age-related change in body weight varied somewhat by sex or ethnicity, hepatic weight per body weight was less consistent to account for age-related change in hepatic clearance. As for an index of renal clearance, the changes in inulin clearance with age were similar to those in renal blood flow, with a decrease of 0.97% per year from the age of 40 years.

CONCLUSIONS

Hepatic clearance consistently decreased by 0.80% per year from the age of 40 years, with aging for multiple drugs analyzed in this study. Changes in organ weight and blood flow are considered to be primarily responsible for the age-related changes in hepatic and renal clearance.

A Physiological Approach to Pharmacokinetics in Chronic Kidney Disease

The conventional approach to approximating the pharmacokinetics of drugs in patients with chronic kidney disease (CKD) only accounts for changes in the estimated glomerular filtration rate. However, CKD is a systemic and multifaceted disease that alters many body systems. Therefore, the objective of this exercise was to develop and evaluate a whole-body mechanistic approach to predicting pharmacokinetics in patients with CKD. Physiologically based pharmacokinetic models were developed in PK-Sim v8.0 (www.open-systems-pharmacology.org) to mechanistically represent the disposition of 7 compounds in healthy human adults. The 7 compounds selected were eliminated by glomerular filtration and active tubular secretion by the organic cation transport system to varying degrees. After a literature search, the healthy adult models were adapted to patients with CKD by numerically accounting for changes in glomerular filtration rate, kidney volume, renal perfusion, hematocrit, plasma protein concentrations, and gastrointestinal transit. Literature-informed interindividual variability was applied to the physiological parameters to facilitate a population approach. Model performance in CKD was evaluated against pharmacokinetic data from 8 clinical trials in the literature. Overall, integration of the CKD parameterization enabled exposure predictions that were within 1.5-fold error across all compounds and patients with varying stages of renal impairment. Notable improvement was observed over the conventional approach to scaling exposure, which failed in all but 1 scenario in patients with advanced CKD. Further research is required to qualify its use for first-in-CKD dose selection and clinical trial planning for a wider selection of renally eliminated compounds, including those subject to anion transport.

Data-driven personalization of a physiologically based pharmacokinetic model for caffeine: A systematic assessment

Physiologically based pharmacokinetic (PBPK) models have been proposed as a tool for more accurate individual pharmacokinetic (PK) predictions and model‐informed precision dosing, but their application in clinical practice is still rare. This study systematically assesses the benefit of using individual patient information to improve PK predictions. A PBPK model of caffeine was stepwise personalized by using individual data on (1) demography, (2) physiology, and (3) cytochrome P450 (CYP) 1A2 phenotype of 48 healthy volunteers participating in a single‐dose clinical study. Model performance was benchmarked against a caffeine base model simulated with parameters of an average individual. In the first step, virtual twins were generated based on the study subjects' demography (height, weight, age, sex), which implicated the rescaling of average organ volumes and blood flows. The accuracy of PK simulations improved compared with the base model. The percentage of predictions within 0.8‐fold to 1.25‐fold of the observed values increased from 45.8% (base model) to 57.8% (Step 1). However, setting physiological parameters (liver blood flow determined by magnetic resonance imaging, glomerular filtration rate, hematocrit) to measured values in the second step did not further improve the simulation result (59.1% in the 1.25‐fold range). In the third step, virtual twins matching individual demography, physiology, and CYP1A2 activity considerably improved the simulation results. The percentage of data within the 1.25‐fold range was 66.15%. This case study shows that individual PK profiles can be predicted more accurately by considering individual attributes and that personalized PBPK models could be a valuable tool for model‐informed precision dosing approaches in the future.

Application of a dual mechanistic approach to support bilastine dose selection for older adults

The objective of this study was to evaluate bilastine dosing recommendations in older adults and overcome the limitation of insufficient data from phase I studies in this underrepresented population. This was achieved by integrating bilastine physicochemical, in vitro and in vivo data in young adults and the effect of aging in the pharmacology by means of two alternative approaches: a physiologically‐based pharmacokinetic (PBPK) model and a semi‐mechanistic population pharmacokinetic (Senescence) model. Intestinal apical efflux and basolateral influx transporters were needed in the PBPK model to capture the observations from young adults after single i.v. (10 mg) and p.o. (20 mg) doses, supporting the hypothesis of involvement of gut transporters on secretion. The model was then used to extrapolate the pharmacokinetics (PKs) to elderly subjects considering their specific physiology. Additionally, the Senescence model was develop starting from a published population PK) model, previously applied for pediatrics, and incorporating declining functions on different physiological systems and changes in body composition with aging. Both models were qualified using observed data in a small group of young elderlies (N = 16, mean age = 68.69 years). The PBPK model was further used to evaluate the dose in older subjects (mean age = 80 years) via simulation. The PBPK model supported the hypothesis that basolateral influx and apical efflux transporters are involved in bilastine PK. Both, PBPK and Senescence models indicated that a 20 mg q.d. dose is safe and effective for geriatrics of any age. This approach provides an alternative to generate supplementary data to inform dosing recommendations in under‐represented groups in clinical trials.

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 [C_max], time to C_max [t_max], 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 C_max, t_max 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.

Development of a physiologically based pharmacokinetic (PBPK) population model for Chinese elderly subjects

Aims

This study aims to develop and verify a physiologically based pharmacokinetic (PBPK) population model for the Chinese geriatric population in Simcyp.

Methods

Firstly, physiological information for the Chinese geriatric population was collected and later employed to develop the Chinese geriatric population model by recalibration of corresponding physiological parameters in the Chinese adult population model available in Simcyp (i.e., Chinese healthy volunteer model). Secondly, drug‐dependent parameters were collected for six drugs with different elimination pathways (i.e., metabolized by CYP1A2, CYP3A4 or renal excretion). The drug models were then developed and verified by clinical data from Chinese adults, Caucasian adults and Caucasian elderly subjects to ensure that drug‐dependent parameters are correctly inputted. Finally, the tested drug models in combination with the newly developed Chinese geriatric population model were applied to simulate drug concentration in Chinese elderly subjects. The predicted results were then compared with the observations to evaluate model prediction performance.

Results

Ninety‐eight per cent of predicted AUC, 95% of predicted C_max, and 100% of predicted CL values were within two‐fold of the observed values, indicating all drug models were properly developed. The drug models, combined with the newly developed population model, were then used to predict pharmacokinetics in Chinese elderly subjects aged 60–93. The predicted AUC, C_max, and CL values were all within two‐fold of the observed values.

Conclusion

The population model for the Chinese elderly subjects appears to adequately predict the concentration of the drug that was metabolized by CYP1A2, CYP3A4 or eliminated by renal clearance.

Contribution of Uptake and Efflux Transporters to Oral Pharmacokinetics of Furosemide

Furosemide is a widely used diuretic for treating excessive fluid accumulation caused by disease conditions like heart failure and liver cirrhosis. Furosemide tablet formulation exhibits variable pharmacokinetics (PK) with bioavailability ranging from 10 to almost 100%. To explain the variable absorption, we integrated the physicochemical, in vitro dissolution, permeability, distribution, and the elimination parameters of furosemide in a physiologically-based pharmacokinetic (PBPK) model. Although the intravenous PBPK model reasonably described the observed in vivo PK data, the reported low passive permeability failed to capture the observed data after oral administration. To mechanistically justify this discrepancy, we hypothesized that transporter-mediated uptake contributes to the oral absorption of furosemide in conjunction with passive permeability. Our in vitro results confirmed that furosemide is a substrate of intestinal breast cancer resistance protein (BCRP), multidrug resistance-associated protein 4 (MRP4), and organic anion transporting polypeptide 2B1 (OATP2B1), but it is not a substrate of P-glycoprotein (P-gp) and MRP2. We then estimated the net transporter-mediated intestinal uptake and integrated it into the PBPK model under both fasting and fed conditions. Our in vitro data and PBPK model suggest that the absorption of furosemide is permeability-limited, and OATP2B1 and MRP4 are important for its permeability across intestinal membrane. Further, as furosemide has been proposed as a probe substrate of renal organic anion transporters (OATs) for assessing clinical drug-drug interactions (DDIs) during drug development, the confounding effects of intestinal transporters identified in this study on furosemide PK should be considered in the clinical transporter DDI studies.

Physiologically Based Pharmacokinetic Models of Probenecid and Furosemide to Predict Transporter Mediated Drug-Drug Interactions

Purpose

To provide whole-body physiologically based pharmacokinetic (PBPK) models of the potent clinical organic anion transporter (OAT) inhibitor probenecid and the clinical OAT victim drug furosemide for their application in transporter-based drug-drug interaction (DDI) modeling.

Methods

PBPK models of probenecid and furosemide were developed in PK-Sim®. Drug-dependent parameters and plasma concentration-time profiles following intravenous and oral probenecid and furosemide administration were gathered from literature and used for model development. For model evaluation, plasma concentration-time profiles, areas under the plasma concentration–time curve (AUC) and peak plasma concentrations (C_max) were predicted and compared to observed data. In addition, the models were applied to predict the outcome of clinical DDI studies.

Results

The developed models accurately describe the reported plasma concentrations of 27 clinical probenecid studies and of 42 studies using furosemide. Furthermore, application of these models to predict the probenecid-furosemide and probenecid-rifampicin DDIs demonstrates their good performance, with 6/7 of the predicted DDI AUC ratios and 4/5 of the predicted DDI C_max ratios within 1.25-fold of the observed values, and all predicted DDI AUC and C_max ratios within 2.0-fold.

Conclusions

Whole-body PBPK models of probenecid and furosemide were built and evaluated, providing useful tools to support the investigation of transporter mediated DDIs.

Supplementary Information

The online version contains supplementary material available at 10.1007/s11095-020-02964-z.

Investigating the Effect of Aging on the Pharmacokinetics and Tumor Delivery of Nanomaterials using Mathematical Modeling

The application of nanomedicine for diagnosis and treatment of cancer has immense potential, but has witnessed only limited clinical success, in part due to insufficient understanding of the role of nanomaterial properties and physiological variables in governing nanoparticle (NP) pharmacology. Here, we present a multiscale mathematical model to examine the effects of physiological changes associated with patient age on the pharmacokinetics and tumor delivery efficiency of NPs. We show that physiological changes due to aging prolong the residence of NPs in the systemic circulation, thereby improving passive accumulation of NPs in tumors.Clinical Relevance - Understanding the effect of inter-individual variability on the pharmacological behavior of nanomaterials will improve their clinical translatability.

A workflow to build PBTK models for novel species

Physiology-based pharmacokinetic and toxicokinetic (PBPK/TK) models allow us to simulate the concentration of xenobiotica in the plasma and different tissues of an organism. PBPK/TK models are therefore routinely used in many fields of life sciences to simulate the physiological concentration of exogenous compounds in plasma and tissues. The application of PBTK models in ecotoxicology, however, is currently hampered by the limited availability of models for focal species. Here, we present a best practice workflow that describes how to build PBTK models for novel species. To this end, we extrapolated eight previously established rabbit models for several drugs to six additional mammalian species (human, beagle, rat, monkey, mouse, and minipig). We used established PBTK models for these species to account for the species-specific physiology. The parameter sensitivity in the resulting 56 PBTK models was systematically assessed to rank the relevance of the parameters on overall model performance. Interestingly, more than 80% of the 609 considered model parameters showed a negligible sensitivity throughout all models. Only approximately 5% of all parameters had a high sensitivity in at least one of the PBTK models. This approach allowed us to rank the relevance of the various parameters on overall model performance. We used this information to formulate a best practice guideline for the efficient development of PBTK models for novel animal species. We believe that the workflow proposed in this study will significantly support the development of PBTK models for new animal species in the future.

Predictive Pediatric Modeling and Simulation Using Ontogeny Information

Food and Drug Administration submissions of physiologically based pharmacokinetic (PBPK) modeling and simulation of small-molecule drugs document the relevance of pediatric drug development and, in particular, information on dosing strategies in children. The most relevant prerequisite for reliable PBPK-based translation of adult pharmacokinetics of a small molecule to children is knowledge of the drug-specific absorption, distribution, metabolism, and elimination (ADME) processes in adults together with existing information about ontogeny of ADME processes relevant for the drug. All mechanisms driving a drug's clearance are of specific importance. For other drug modalities, our knowledge of ADME processes and ontogeny is still limited. More research is required, for example, to understand why some therapeutic proteins show complex differences in pharmacokinetics between adults and children, whereas other proteins seem to follow simple allometric scaling rules. Ontogeny information originates from various sources, such as (semi)quantitative mRNA expression, in vitro activity data, and deconvolution of in vivo pharmacokinetic data. The workflow for pediatric predictions is well described in several articles documenting successful translation from adults to children. The technical hurdles for PBPK modeling are low. State-of-the-art PBPK modeling software tools provide integrated pediatric translation workflows. For example, PK-Sim and MoBi are freely available as fully transparent open-source software via Open Systems Pharmacology (OSP). With the latest 2019 software release, version 8.0, OSP even provides a fully integrated technical framework for the qualification (and requalification) of any specific intended PBPK use in line with Food and Drug Administration and European Medicines Agency PBPK guidance. Qualification packages for pediatric translation are available on the OSP platform.

Computational Approaches in Preclinical Studies on Drug Discovery and Development

Because undesirable pharmacokinetics and toxicity are significant reasons for the failure of drug development in the costly late stage, it has been widely recognized that drug ADMET properties should be considered as early as possible to reduce failure rates in the clinical phase of drug discovery. Concurrently, drug recalls have become increasingly common in recent years, prompting pharmaceutical companies to increase attention toward the safety evaluation of preclinical drugs. In vitro and in vivo drug evaluation techniques are currently more mature in preclinical applications, but these technologies are costly. In recent years, with the rapid development of computer science, in silico technology has been widely used to evaluate the relevant properties of drugs in the preclinical stage and has produced many software programs and in silico models, further promoting the study of ADMET in vitro. In this review, we first introduce the two ADMET prediction categories (molecular modeling and data modeling). Then, we perform a systematic classification and description of the databases and software commonly used for ADMET prediction. We focus on some widely studied ADMT properties as well as PBPK simulation, and we list some applications that are related to the prediction categories and web tools. Finally, we discuss challenges and limitations in the preclinical area and propose some suggestions and prospects for the future.

Evaluation of the Impacts of Formulation Parameters on the Pharmacokinetics and Bioequivalence of Risperidone Orodispersible Film: a Physiologically Based Pharmacokinetic Modeling Approach

The purpose of this study was to investigate the impacts of the formulation parameters on the pharmacokinetics and bioequivalence of risperidone orodispersible film (ODF) using physiologically based pharmacokinetic model. The pharmacokinetic profiles of two risperidone ODFs, which exhibit different in vitro dissolution, were examined in Beagle dogs after supralingual administration. Subsequently, a physiologically based pharmacokinetic (PBPK) model was constructed to evaluate the in vivo performance of risperidone ODF. The parameter sensitivity analysis (PSA) was used to access the impacts of formulation parameters on the pharmacokinetics of risperidone. Moreover, the validated PBPK model was applied to predict human pharmacokinetic profiles and examine the bioequivalence of these two ODFs. These two ODFs displayed similar risperidone pharmacokinetic profiles in dogs. The parameter sensitivity analysis indicated that the changes in the solubility, particle size, particle density, and diffusion coefficient did not have obvious influence on the in vivo properties of risperidone ODF. Alternation of the in vitro complete dissolution time in water from 15 to 30 min led to a 30% decrease in C_max and 20% of increase in T_max. AUC_0-∞ would be decreased if risperidone was not fully released within 1 h. As both ODFs completely released risperidone within 15 min, the difference in the extent of in vivo absorption, intestinal regional absorption location, and plasma concentration-time curves between these two ODFs was almost negligible. Consequently, a bioequivalence was foreseen in humans. The in vitro cumulative dissolution percentage in water at 15 min was found to be the major determinant on the in vivo properties of risperidone ODF. PBPK modeling appears to be an innovative strategy to guide the development of risperidone ODF.

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.

Assessing Barriers to Adherence with the Use of Dimethyl Fumarate in Multiple Sclerosis

BACKGROUND

Multiple sclerosis (MS) is a chronic, inflammatory, central nervous system demyelinating disease that requires long-term use of disease-modifying therapies (DMT). Patient adherence to DMT is key in reducing the inflammation that leads to relapses and neurodegeneration. Dimethyl fumarate (DMF) poses unique challenges to adherence including being the only twice-daily dosing DMT. Previous research suggests there are direct roles that providers play on improving their patients' adherence rates, such as focusing on the patient-provider relationship, helping put the patient at ease so that they feel understood and respected. Also, route of administration affects adherence in other chronic healthcare conditions. However, the issue of adherence to DMT in MS is more complex than just route of administration, with adverse effects being the main predictor of adherence.

OBJECTIVES

(1) To define various patient specific factors (e.g. fatigue and mood disorders) that affect adherence with DMF and (2) to understand how patients' perceptions of treatment satisfaction (such as effectiveness, convenience, side effects and global satisfaction) and DMFs impact on quality of life (such as social support, activities of daily living, coping) influence adherence.

METHODS

Our study was a prospective, observational measurement of adherence to treatment with DMF in MS patients over 52 weeks. Twenty-five out of thirty-five patients enrolled completed the study. Adverse event (AE) data was reviewed on all participants.

RESULTS

Adherence rates correlated with patient's perceived effectiveness (0.25, p < 0.023) and the level of bothersome symptoms the patient experienced (0.45, p < 0.0001). The majority of new AE onset was reported within 12 weeks of DMF initiation. This is consistent with previously published data with DMF use.

CONCLUSION

Adherence rates are an important factor to be considered when starting patients on DMT. DMF creates its own barriers to adherence with our study highlighting some, including twice-daily dosing and AEs experienced following treatment initiation. Healthcare providers should be aware of these barriers prior to treatment initiation and counsel patients appropriately.

Modelling Age-Related Changes in the Pharmacokinetics of Risperidone and 9-Hydroxyrisperidone in Different CYP2D6 Phenotypes Using a Physiologically Based Pharmacokinetic Approach

PURPOSE

Dose-optimization strategies for risperidone are gaining in importance, especially in the elderly. Based on the genetic polymorphism of cytochrome P 450 (CYP) 2D6 genetically and age-related changes cause differences in the pharmacokinetics of risperidone and 9-hydroxyrisperidone. The goal of the study was to develop physiologically based pharmacokinetic (PBPK) models for the elderly aged 65+ years. Additionally, CYP2D6 phenotyping using metabolic ratio were applied and different pharmacokinetic parameter for different age classes predicted.

METHODS

Plasma concentrations of risperidone and 9-hydroxyrisperidone were used to phenotype 17 geriatric inpatients treated under naturalistic conditions. For this purpose, PBPK models were developed to examine age-related changes in the pharmacokinetics between CYP2D6 extensive metabolizer, intermediate metabolizer, poor metabolizer, (PM) and ultra-rapid metabolizer.

RESULTS

PBPK-based metabolic ratio was able to predict different CYP2D6 phenotypes during steady-state. One inpatient was identified as a potential PM, showing a metabolic ratio of 3.39. About 88.2% of all predicted plasma concentrations of the inpatients were within the 2-fold error range. Overall, age-related changes of the pharmacokinetics in the elderly were mainly observed in Cmax and AUC. Comparing a population of young adults with the oldest-old, Cmax of risperidone increased with 24-44% and for 9-hydroxyrisperidone with 35-37%.

CONCLUSIONS

Metabolic ratio combined with PBPK modelling can provide a powerful tool to identify potential CYP2D6 PM during therapeutic drug monitoring. Based on genetic, anatomical and physiological changes during aging, PBPK models ultimately support decision-making regarding dose-optimization strategies to ensure the best therapy for each patient over the age of 65 years.