搜索结果：European journal of drug metabolism and pharmacokinetics

When the Editor of the British Journal of Clinical Pharmacology commissioned this article he probably expected a scholarly step-by-step account of the development of our discipline. He also asked that the review should consider current difficulties and future prospects. A period of reflection and some background literature searches soon convinced this author that a comprehensive account would be so lengthy and take so long to research thoroughly that it was more likely to be complete for the 80th anniversary of the British Pharmacological Society (BPS) than the 75th. So this is a personal account by someone who has lived and worked through just under 50 years of the 75 years the Editor wanted to cover. To minimize personal bias I have sought advice from a substantial number of those who have been leaders in the development of the discipline. Their names are listed at the end of the article. I am profoundly grateful to all of them and if I have misrepresented their views here and there I hope that they will forgive me. For the many very active participants I have not mentioned I plead the exigencies of time and page space. The article contains no references because there would have been hundreds, but it does include many names, so those who want to know more can use Google and Medline. At the conclusion of the article I have tried to address some of the rather pessimistic views about the future of clinical pharmacology that are current in many academic circles. They are views that I understand but do not entirely share. From the standpoint of someone who now works in industry, the challenges and opportunities for clinical pharmacologists are greater than they have ever been, but a vibrant academic clinical pharmacology community is essential for the practice of clinical medicine and the training of physicians as well as an important source of ideas for industry. At the very end of this article I have put forward some possible solutions to the current problems. To overseas readers they may seem rather UK oriented, but I believe that similar concepts, adapted to local circumstances, could be applied more widely. 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Timely and comprehensive analyses of causes of death stratified by age, sex, and location are essential for shaping effective health policies aimed at reducing global mortality. The Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2023 provides cause-specific mortality estimates measured in counts, rates, and years of life lost (YLLs). GBD 2023 aimed to enhance our understanding of the relationship between age and cause of death by quantifying the probability of dying before age 70 years (70q0) and the mean age at death by cause and sex. This study enables comparisons of the impact of causes of death over time, offering a deeper understanding of how these causes affect global populations. GBD 2023 produced estimates for 292 causes of death disaggregated by age-sex-location-year in 204 countries and territories and 660 subnational locations for each year from 1990 until 2023. We used a modelling tool developed for GBD, the Cause of Death Ensemble model (CODEm), to estimate cause-specific death rates for most causes. We computed YLLs as the product of the number of deaths for each cause-age-sex-location-year and the standard life expectancy at each age. Probability of death was calculated as the chance of dying from a given cause in a specific age period, for a specific population. Mean age at death was calculated by first assigning the midpoint age of each age group for every death, followed by computing the mean of all midpoint ages across all deaths attributed to a given cause. We used GBD death estimates to calculate the observed mean age at death and to model the expected mean age across causes, sexes, years, and locations. The expected mean age reflects the expected mean age at death for individuals within a population, based on global mortality rates and the population's age structure. Comparatively, the observed mean age represents the actual mean age at death, influenced by all factors unique to a location-specific population, including its age structure. As part of the modelling process, uncertainty intervals (UIs) were generated using the 2·5th and 97·5th percentiles from a 250-draw distribution for each metric. Findings are reported as counts and age-standardised rates. Methodological improvements for cause-of-death estimates in GBD 2023 include a correction for the misclassification of deaths due to COVID-19, updates to the method used to estimate COVID-19, and updates to the CODEm modelling framework. This analysis used 55 761 data sources, including vital registration and verbal autopsy data as well as data from surveys, censuses, surveillance systems, and cancer registries, among others. For GBD 2023, there were 312 new country-years of vital registration cause-of-death data, 3 country-years of surveillance data, 51 country-years of verbal autopsy data, and 144 country-years of other data types that were added to those used in previous GBD rounds. The initial years of the COVID-19 pandemic caused shifts in long-standing rankings of the leading causes of global deaths: it ranked as the number one age-standardised cause of death at Level 3 of the GBD cause classification hierarchy in 2021. By 2023, COVID-19 dropped to the 20th place among the leading global causes, returning the rankings of the leading two causes to those typical across the time series (ie, ischaemic heart disease and stroke). While ischaemic heart disease and stroke persist as leading causes of death, there has been progress in reducing their age-standardised mortality rates globally. Four other leading causes have also shown large declines in global age-standardised mortality rates across the study period: diarrhoeal diseases, tuberculosis, stomach cancer, and measles. Other causes of death showed disparate patterns between sexes, notably for deaths from conflict and terrorism in some locations. A large reduction in age-standardised rates of YLLs occurred for neonatal disorders. Despite this, neonatal disorders remained the leading cause of global YLLs over the period studied, except in 2021, when COVID-19 was temporarily the leading cause. Compared to 1990, there has been a considerable reduction in total YLLs in many vaccine-preventable diseases, most notably diphtheria, pertussis, tetanus, and measles. In addition, this study quantified the mean age at death for all-cause mortality and cause-specific mortality and found noticeable variation by sex and location. The global all-cause mean age at death increased from 46·8 years (95% UI 46·6-47·0) in 1990 to 63·4 years (63·1-63·7) in 2023. For males, mean age increased from 45·4 years (45·1-45·7) to 61·2 years (60·7-61·6), and for females it increased from 48·5 years (48·1-48·8) to 65·9 years (65·5-66·3), from 1990 to 2023. The highest all-cause mean age at death in 2023 was found in the high-income super-region, where the mean age for females reached 80·9 years (80·9-81·0) and for males 74·8 years (74·8-74·9). By comparison, the lowest all-cause mean age at death occurred in sub-Saharan Africa, where it was 38·0 years (37·5-38·4) for females and 35·6 years (35·2-35·9) for males in 2023. Lastly, our study found that all-cause 70q0 decreased across each GBD super-region and region from 2000 to 2023, although with large variability between them. For females, we found that 70q0 notably increased from drug use disorders and conflict and terrorism. Leading causes that increased 70q0 for males also included drug use disorders, as well as diabetes. In sub-Saharan Africa, there was an increase in 70q0 for many non-communicable diseases (NCDs). Additionally, the mean age at death from NCDs was lower than the expected mean age at death for this super-region. By comparison, there was an increase in 70q0 for drug use disorders in the high-income super-region, which also had an observed mean age at death lower than the expected value. We examined global mortality patterns over the past three decades, highlighting-with enhanced estimation methods-the impacts of major events such as the COVID-19 pandemic, in addition to broader trends such as increasing NCDs in low-income regions that reflect ongoing shifts in the global epidemiological transition. This study also delves into premature mortality patterns, exploring the interplay between age and causes of death and deepening our understanding of where targeted resources could be applied to further reduce preventable sources of mortality. We provide essential insights into global and regional health disparities, identifying locations in need of targeted interventions to address both communicable and non-communicable diseases. There is an ever-present need for strengthened health-care systems that are resilient to future pandemics and the shifting burden of disease, particularly among ageing populations in regions with high mortality rates. Robust estimates of causes of death are increasingly essential to inform health priorities and guide efforts toward achieving global health equity. The need for global collaboration to reduce preventable mortality is more important than ever, as shifting burdens of disease are affecting all nations, albeit at different paces and scales. Gates Foundation.

For more than three decades, the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) has provided a framework to quantify health loss due to diseases, injuries, and associated risk factors. This paper presents GBD 2023 findings on disease and injury burden and risk-attributable health loss, offering a global audit of the state of world health to inform public health priorities. This work captures the evolving landscape of health metrics across age groups, sexes, and locations, while reflecting on the remaining post-COVID-19 challenges to achieving our collective global health ambitions. The GBD 2023 combined analysis estimated years lived with disability (YLDs), years of life lost (YLLs), and disability-adjusted life-years (DALYs) for 375 diseases and injuries, and risk-attributable burden associated with 88 modifiable risk factors. Of the more than 310 000 total data sources used for all GBD 2023 (about 30% of which were new to this estimation round), more than 120 000 sources were used for estimation of disease and injury burden and 59 000 for risk factor estimation, and included vital registration systems, surveys, disease registries, and published scientific literature. Data were analysed using previously established modelling approaches, such as disease modelling meta-regression version 2.1 (DisMod-MR 2.1) and comparative risk assessment methods. Diseases and injuries were categorised into four levels on the basis of the established GBD cause hierarchy, as were risk factors using the GBD risk hierarchy. Estimates stratified by age, sex, location, and year from 1990 to 2023 were focused on disease-specific time trends over the 2010-23 period and presented as counts (to three significant figures) and age-standardised rates per 100 000 person-years (to one decimal place). For each measure, 95% uncertainty intervals [UIs] were calculated with the 2·5th and 97·5th percentile ordered values from a 250-draw distribution. Total numbers of global DALYs grew 6·1% (95% UI 4·0-8·1), from 2·64 billion (2·46-2·86) in 2010 to 2·80 billion (2·57-3·08) in 2023, but age-standardised DALY rates, which account for population growth and ageing, decreased by 12·6% (11·0-14·1), revealing large long-term health improvements. Non-communicable diseases (NCDs) contributed 1·45 billion (1·31-1·61) global DALYs in 2010, increasing to 1·80 billion (1·63-2·03) in 2023, alongside a concurrent 4·1% (1·9-6·3) reduction in age-standardised rates. Based on DALY counts, the leading level 3 NCDs in 2023 were ischaemic heart disease (193 million [176-209] DALYs), stroke (157 million [141-172]), and diabetes (90·2 million [75·2-107]), with the largest increases in age-standardised rates since 2010 occurring for anxiety disorders (62·8% [34·0-107·5]), depressive disorders (26·3% [11·6-42·9]), and diabetes (14·9% [7·5-25·6]). Remarkable health gains were made for communicable, maternal, neonatal, and nutritional (CMNN) diseases, with DALYs falling from 874 million (837-917) in 2010 to 681 million (642-736) in 2023, and a 25·8% (22·6-28·7) reduction in age-standardised DALY rates. During the COVID-19 pandemic, DALYs due to CMNN diseases rose but returned to pre-pandemic levels by 2023. From 2010 to 2023, decreases in age-standardised rates for CMNN diseases were led by rate decreases of 49·1% (32·7-61·0) for diarrhoeal diseases, 42·9% (38·0-48·0) for HIV/AIDS, and 42·2% (23·6-56·6) for tuberculosis. Neonatal disorders and lower respiratory infections remained the leading level 3 CMNN causes globally in 2023, although both showed notable rate decreases from 2010, declining by 16·5% (10·6-22·0) and 24·8% (7·4-36·7), respectively. Injury-related age-standardised DALY rates decreased by 15·6% (10·7-19·8) over the same period. Differences in burden due to NCDs, CMNN diseases, and injuries persisted across age, sex, time, and location. Based on our risk analysis, nearly 50% (1·27 billion [1·18-1·38]) of the roughly 2·80 billion total global DALYs in 2023 were attributable to the 88 risk factors analysed in GBD. Globally, the five level 3 risk factors contributing the highest proportion of risk-attributable DALYs were high systolic blood pressure (SBP), particulate matter pollution, high fasting plasma glucose (FPG), smoking, and low birthweight and short gestation-with high SBP accounting for 8·4% (6·9-10·0) of total DALYs. Of the three overarching level 1 GBD risk factor categories-behavioural, metabolic, and environmental and occupational-risk-attributable DALYs rose between 2010 and 2023 only for metabolic risks, increasing by 30·7% (24·8-37·3); however, age-standardised DALY rates attributable to metabolic risks decreased by 6·7% (2·0-11·0) over the same period. For all but three of the 25 leading level 3 risk factors, age-standardised rates dropped between 2010 and 2023-eg, declining by 54·4% (38·7-65·3) for unsafe sanitation, 50·5% (33·3-63·1) for unsafe water source, and 45·2% (25·6-72·0) for no access to handwashing facility, and by 44·9% (37·3-53·5) for child growth failure. The three leading level 3 risk factors for which age-standardised attributable DALY rates rose were high BMI (10·5% [0·1 to 20·9]), drug use (8·4% [2·6 to 15·3]), and high FPG (6·2% [-2·7 to 15·6]; non-significant). Our findings underscore the complex and dynamic nature of global health challenges. Since 2010, there have been large decreases in burden due to CMNN diseases and many environmental and behavioural risk factors, juxtaposed with sizeable increases in DALYs attributable to metabolic risk factors and NCDs in growing and ageing populations. This long-observed consequence of the global epidemiological transition was only temporarily interrupted by the COVID-19 pandemic. The substantially decreasing CMNN disease burden, despite the 2008 global financial crisis and pandemic-related disruptions, is one of the greatest collective public health successes known. However, these achievements are at risk of being reversed due to major cuts to development assistance for health globally, the effects of which will hit low-income countries with high burden the hardest. Without sustained investment in evidence-based interventions and policies, progress could stall or reverse, leading to widespread human costs and geopolitical instability. Moreover, the rising NCD burden necessitates intensified efforts to mitigate exposure to leading risk factors-eg, air pollution, smoking, and metabolic risks, such as high SBP, BMI, and FPG-including policies that promote food security, healthier diets, physical activity, and equitable and expanded access to potential treatments, such as GLP-1 receptor agonists. Decisive, coordinated action is needed to address long-standing yet growing health challenges, including depressive and anxiety disorders. Yet this can be only part of the solution. Our response to the NCD syndemic-the complex interaction of multiple health risks, social determinants, and systemic challenges-will define the future landscape of global health. To ensure human wellbeing, economic stability, and social equity, global action to sustain and advance health gains must prioritise reducing disparities by addressing socioeconomic and demographic determinants, ensuring equitable health-care access, tackling malnutrition, strengthening health systems, and improving vaccination coverage. We live in times of great opportunity. Gates Foundation and Bloomberg Philanthropies.

Comprehensive, comparable, and timely estimates of demographic metrics-including life expectancy and age-specific mortality-are essential for evaluating, understanding, and addressing trends in population health. The COVID-19 pandemic highlighted the importance of timely and all-cause mortality estimates for being able to respond to changing trends in health outcomes, showing a strong need for demographic analysis tools that can produce all-cause mortality estimates more rapidly with more readily available all-age vital registration (VR) data. The Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) is an ongoing research effort that quantifies human health by estimating a range of epidemiological quantities of interest across time, age, sex, location, cause, and risk. This study-part of the latest GBD release, GBD 2023-aims to provide new and updated estimates of all-cause mortality and life expectancy for 1950 to 2023 using a novel statistical model that accounts for complex correlation structures in demographic data across age and time. We used 24 025 data sources from VR, sample registration, surveys, censuses, and other sources to estimate all-cause mortality for males, females, and all sexes combined across 25 age groups in 204 countries and territories as well as 660 subnational units in 20 countries and territories, for the years 1950-2023. For the first time, we used complete birth history data for ages 5-14 years, age-specific sibling history data for ages 15-49 years, and age-specific mortality data from Health and Demographic Surveillance Systems. We developed a single statistical model that incorporates both parametric and non-parametric methods, referred to as OneMod, to produce estimates of all-cause mortality for each age-sex-location group. OneMod includes two main steps: a detailed regression analysis with a generalised linear modelling tool that accounts for age-specific covariate effects such as the Socio-demographic Index (SDI) and a population attributable fraction (PAF) for all risk factors combined; and a non-parametric analysis of residuals using a multivariate kernel regression model that smooths across age and time to adaptably follow trends in the data without overfitting. We calibrated asymptotic uncertainty estimates using Pearson residuals to produce 95% uncertainty intervals (UIs) and corresponding 1000 draws. Life expectancy was calculated from age-specific mortality rates with standard demographic methods. For each measure, 95% UIs were calculated with the 25th and 975th ordered values from a 1000-draw posterior distribution. In 2023, 60·1 million (95% UI 59·0-61·1) deaths occurred globally, of which 4·67 million (4·59-4·75) were in children younger than 5 years. Due to considerable population growth and ageing since 1950, the number of annual deaths globally increased by 35·2% (32·2-38·4) over the 1950-2023 study period, during which the global age-standardised all-cause mortality rate declined by 66·6% (65·8-67·3). Trends in age-specific mortality rates between 2011 and 2023 varied by age group and location, with the largest decline in under-5 mortality occurring in east Asia (67·7% decrease); the largest increases in mortality for those aged 5-14 years, 25-29 years, and 30-39 years occurring in high-income North America (11·5%, 31·7%, and 49·9%, respectively); and the largest increases in mortality for those aged 15-19 years and 20-24 years occurring in Eastern Europe (53·9% and 40·1%, respectively). We also identified higher than previously estimated mortality rates in sub-Saharan Africa for all sexes combined aged 5-14 years (87·3% higher in GBD 2023 than GBD 2021 on average across countries and territories over the 1950-2021 period) and for females aged 15-29 years (61·2% higher), as well as lower than previously estimated mortality rates in sub-Saharan Africa for all sexes combined aged 50 years and older (13·2% lower), reflecting advances in our modelling approach. Global life expectancy followed three distinct trends over the study period. First, between 1950 and 2019, there were considerable improvements, from 51·2 (50·6-51·7) years for females and 47·9 (47·4-48·4) years for males in 1950 to 76·3 (76·2-76·4) years for females and 71·4 (71·3-71·5) years for males in 2019. Second, this period was followed by a decrease in life expectancy during the COVID-19 pandemic, to 74·7 (74·6-74·8) years for females and 69·3 (69·2-69·4) years for males in 2021. Finally, the world experienced a period of post-pandemic recovery in 2022 and 2023, wherein life expectancy generally returned to pre-pandemic (2019) levels in 2023 (76·3 [76·0-76·6] years for females and 71·5 [71·2-71·8] years for males). 194 (95·1%) of 204 countries and territories experienced at least partial post-pandemic recovery in age-standardised mortality rates by 2023, with 61·8% (126 of 204) recovering to or falling below pre-pandemic levels. There were several mortality trajectories during and following the pandemic across countries and territories. Long-term mortality trends also varied considerably between age groups and locations, demonstrating the diverse landscape of health outcomes globally. This analysis identified several key differences in mortality trends from previous estimates, including higher rates of adolescent mortality, higher rates of young adult mortality in females, and lower rates of mortality in older age groups in much of sub-Saharan Africa. The findings also highlight stark differences across countries and territories in the timing and scale of changes in all-cause mortality trends during and following the COVID-19 pandemic (2020-23). Our estimates of evolving trends in mortality and life expectancy across locations, ages, sexes, and SDI levels in recent years as well as over the entire 1950-2023 study period provide crucial information for governments, policy makers, and the public to ensure that health-care systems, economies, and societies are prepared to address the world's health needs, particularly in populations with higher rates of mortality than previously known. The estimates from this study provide a robust framework for GBD and a valuable foundation for policy development, implementation, and evaluation around the world. Gates Foundation.

Fezolinetant is a non-hormonal selective neurokinin-3 receptor antagonist for the treatment of moderate to severe vasomotor symptoms associated with menopause. The objective of this study was to characterize the pharmacokinetics, mass balance, and metabolism of fezolinetant in postmenopausal women. A single dose of 180 mg 14C-fezolinetant solution was administered to healthy postmenopausal women (n&#x2009;=&#x2009;5) to evaluate mass balance and pharmacokinetics. Quantitative metabolite profiling and metabolite structure elucidation were performed on samples collected from the mass balance study by high performance liquid chromatography with radioactivity detector or liquid chromatography-tandem mass spectrometry analyses. Following a single administration of 14C-fezolinetant, the average recovery of radioactivity was 90.9%, where the majority of radioactivity was recovered in urine (mean: 76.9%) and to a lesser extent in feces (mean: 14.0%). Fezolinetant was well absorbed and primarily metabolized to the hydroxylated metabolite, ES259564, which was eliminated mainly in urine. Fezolinetant accounted for nearly 29% of exposure for total radioactivity in plasma. In addition to the parent drug, only ES259564 was detected as a circulating metabolite and accounted for approximately 52% of total drug-related exposure. Additional minor metabolites (<&#x2009;3.5% of dose for each metabolite) were only detected in urine or feces. Fezolinetant metabolic pathways included hydroxylation of the methyl group of the 3-methyl-1,2,4-thiadiazole moiety (M9, ES259564), further oxidation of M9 to the carboxylic acid metabolite M4, further glucuronidation of the hydroxyl group of M9 to the glucuronide metabolite M5, direct glucuronidation of fezolinetant to the glucuronide M6, and cleavage of the 1,2,4-thiadiazole moiety to the ring-opened metabolite M1. This study successfully characterized the overall pathways of metabolism and excretion of fezolinetant, identified the circulating metabolites, and provided key data to support the development of fezolinetant. Fezolinetant is mainly metabolized to yield ES259564, and primarily excreted into urine as ES259564. In plasma, only fezolinetant and ES259564 were detected, accounting for approximately 81% of total radioactivity, indicating that the majority of circulating drug-related material was quantitatively characterized, with the remaining radioactivity attributable to multiple low-abundance components below the threshold for a major circulating metabolite. EudraCT Number 2017-004911-38.

ES-481 is a potent and selective antagonist of the transmembrane alpha-amino-3-hydroxy-5-methyl-4 isoxazolepropionic acid (AMPA) receptor regulatory protein (TARP)-y8-dependent AMPA receptor being developed for the treatment of drug-resistant epilepsy (DRE). The objective of this study was to determine the pharmacokinetics and tolerability of ES-481 in humans. This study was a Phase 1, first-in-human, single-center, open-label, randomized, sentinel design, ascending dose study of ES-481 to evaluate the pharmacokinetics and tolerability of ES-481 in healthy subjects, with single oral doses ranging from 3 mg to 100 mg. There were 10 dosing cohorts, each comprised of 8 subjects. Within each cohort, 6 subjects were randomized to treatment with ES-481 and 2 subjects were randomized to placebo. In all dosing cohorts, a sentinel pair was dosed first, where 1 subject received ES-481 and 1 subject received a placebo. The sentinel subjects were observed for a minimum of 24 h. If no safety concerns were identified after 24 h, then the remaining 6 subjects in each dosing cohort were administered the investigational product (5 subjects administered ES-481 and 1 subject administered a placebo). In one cohort, only 5 subjects were treated with ES-481. A total of 79 subjects were administered the investigational product (ES-481 or placebo) instead of 80. Blood samples were obtained from each subject up to 48<h post-dose. Following quantification of the concentration of ES-481, pharmacokinetic parameters were derived from plasma concentration-time data using a noncompartmental model. An approximately proportional increase in AUC parameters and Cmax was observed for ES-481 doses of 3 mg, 6 mg, 12 mg, 25 mg, 37 mg, 50 mg, and 62 mg. Following dosing with 75 mg ES-481, 87 mg ES-481, and 100 mg ES-481, plasma ES-481 concentrations did not increase proportionately. The Tmax was observed between 1 h and 4 h post-dose across the dose range examined. Mean (SD) t&#xbd; ranged from 6.456 (2.4379) h to 9.846 (3.8931) h. Mean CL/F was consistent between the treatment groups, with mean values at around 10 L/h. Mean (SD) Vz/F ranged from 83.514 (20.7577) L in the 12-mg ES-481 treatment group, to 163.903 (84.3912) L in the 100-mg ES-481 treatment group. Exploratory dose proportionality analysis revealed that AUC parameters (AUC0-last and AUC0-inf) satisfied the interval criterion. Cmax did not satisfy the criterion for a proportional response to dose. ES-481 doses up to 100 mg were found to be safe and well tolerated. There were no safety findings in this study of concern, and all of the adverse events related to the administration of ES-481 were mild and transient This study describes the pharmacokinetic parameters of ES-481 for the proposed efficacious dose range of 75-100 mg/day of ES-481 for the treatment of DRE.

Physiologically based pharmacokinetic models are increasingly applied in drug development and regulatory submissions. Differences in predictions between software platforms may challenge reproducibility and interpretation of results. We compared two widely used platforms, Simcyp and PK-Sim, using levonorgestrel and ethinylestradiol as model compounds, with parameters sourced from the literature, and implemented the simulations without data fitting. Systematic reconstruction of drug, system, and virtual population models revealed structural and functional differences, including the number of compartments (12 in Simcyp versus 19 in PK-Sim), absorption model options, partition coefficient methods, and enzyme abundances. The clinical relevance of differences was also demonstrated in case of drug-drug interaction (DDI) assessment. Pharmacokinetic (PK) profiles were simulated and area under the curve (AUC) and peak plasma concentration (Cmax) ratios computed for scenarios where ethinylestradiol and levonorgestrel were co-administrated with itraconazole and carbamazepine, the well-established inhibitor and inductor of cytochrome P450 (CYP)-mediated metabolism, respectively. Despite harmonized and consistent inputs, predicted pharmacokinetic metrics diverged and were clinically relevant. For levonorgestrel, Simcyp yielded higher Cmax (1.23 versus 0.59 ng/mL, Cmax ratio: 2.084) and AUC (10.79 versus 6.75 ng/mL/h, AUC ratio: 1.59), while ethinylestradiol results were more consistent (Cmax 0.17 versus 0.13 ng/mL, Cmax ratio: 1.30; AUC 1.04 versus 1.15 ng/mL/h, AUC ratio: 0.90). The most substantial differences were obtained with carbamazepine: The Cmax ratio was 0.78 with Simcyp and 0.61 with PK-Sim, and the AUC ratio was 0.61 with Simcyp and 0.85 with PK-Sim. These findings show that reproducing physiologically based pharmacokinetic (PBPK) models across platforms requires more than inputting identical/consistent parameters: Platform-specific defaults and algorithms substantially influence outcomes, in particular in case no parameter is optimized with observed data. Beside the key role of the PBPK expert in the adequate use of the respective platforms, our results highlight the importance of observed data used for parameter adjustment, when needed, and the key role of ensuring model fitting performances on well qualified data. From a regulatory perspective, extrapolating model qualification between platforms should be approached cautiously. Transparent reporting of assumptions, platform-specific sensitivity analyses, and enhanced collaboration between developers, users, and regulators are essential to ensure reproducibility and credibility of PBPK applications in high-impact contexts such as drug-drug interaction assessment.

Clinical Pharmacology & Therapeutics (2004) 75, 376–380; doi: 10.1016/j.clpt.2004.01.007 Interindividual variability in drug metabolism presents a major challenge to optimizing therapy for a particular patient. Much effort has gone into identifying the sources of such variability, and in recent years, attention has focused on possible genetic determinants that alter the expression or function of involved enzymes. With the cytochrome P450 (CYP) superfamily of enzymes, genetic polymorphisms such as those with CYP2C19 and CYP2D6 are well established, but their overall clinical importance is debatable except in limited instances. However, with CYP2C9, there is now considerable evidence that genetic variation may be of more practical significance and importance in optimizing drug therapy. This situation is primarily based on several retrospective studies with warfarin in which drug dosage and adverse events, during both induction and maintenance phases of anticoagulation, have been shown to be associated with the CYP2C9 genotype; the presence of CYP2C9*2 and, to a far greater extent, CYP2C9*3 alleles results in greater difficulty and problems in anticoagulation than in wild-type (CYP2C9*1/*1) homozygotes.1,2,3 Warfarin is mainly prescribed in North America and Asia, whereas acenocoumarol is more commonly used in several European countries. These 2 drugs are structurally related, have a mechanism of action similar to that of vitamin K antagonists, and exhibit a marked difference in dosage requirements (up to 10-fold) and unpredictable interindividual variability in anticoagulation response. Furthermore, their metabolism involves CYP2C9,4,5 from which it might be presumed that in the case of acenocoumarol the genetic variability in this enzyme would, as with warfarin, affect the drug's clinical effect. Indeed, 2 articles6,7 in this issue of the Journal demonstrate this; however, they also indicate that the genetic factor is less important than with warfarin despite the similarities between the 2 drugs. Morin et al6 describe an association between several genetic polymorphisms of the CYP2C9 gene and the immediate anticoagulation response, 24 hours after a single oral dose of acenocoumarol by healthy subjects, as compared with homozygous CYP2C9*1/*1 patients. In addition to coding region variants (CYP2C9*2, CYP2C9*3, and CYP2C9*5), single nucleotide polymorphisms (SNPs) in the −2.1-kb promoter region were also investigated. The haplotype containing the CYP2C9*3 allele was the only one having a statistically significant, albeit limited (14%), contribution to the overall interindividual variability of the anticoagulant response, as measured by a reduction in plasma factor VII activity. Schalekamp et al,7 in contrast, studied patients during their initial 3 to 6 months of anticoagulation therapy and concluded that the CYP2C9*3 allele was associated with a lower stabilization dose and a higher risk of overanticoagulation and that it took longer to reach a state of stabilization. In addition, they also noted that the international normalized ratio (INR) value measured 4 days after initiation of therapy was significantly but modestly higher in CYP2C9*3 carriers. In neither study was anticoagulation associated with the CYP2C9*2 allele. These CYP2C9 genotype–anticoagulant response data are different from those with warfarin, for which both the CYP2C9*2 and CYP2C9*3 alleles have much more pronounced effects.1,2,3 We will comment in brief on this and related issues. Like warfarin, acenocoumarol is administered as a racemic mixture of R- and S-enantiomers. However, there are substantial differences in the pharmacokinetic and pharmacodynamic characteristics between the 2 drugs. With acenocoumarol, the anticoagulation potencies of the R- and S-enantiomers are essentially comparable, as indicated by the area under the effect curve (AUEC) of prothrombin time normalized to the area under the plasma concentration–time curve (AUC) of the respective enantiomers (ie, AUEC/AUC) calculated on the basis of previously reported data.8,9 Furthermore, the mean oral clearance of S-acenocoumarol in homozygous wild-type (CYP2C9*1/*1) subjects is 13-fold greater than that of R-acenocoumarol (19.8 L/h versus 1.56 L/h), and its elimination half-life is far shorter (1.0 hours versus 8.8 hours).10 As a result, the overall anticoagulation response in individuals of this genotype is attributable largely to R-acenocoumarol. By contrast, the anticoagulation activity of the S-enantiomer of warfarin is 3 to 5 times greater than its antipode.11 However, its oral clearance in CYP2C9*1/*1 subjects is only 40% greater than that of R-warfarin (0.25 L/h versus 0.18 L/h),12 and the associated elimination half-life (32 hours versus 43 hours) is sufficiently long to produce an anticoagulant response throughout the usual once-daily dosing interval. Thus the intrinsically more potent S-warfarin is essentially responsible for the anticoagulant responses to racemic warfarin. CYP2C9 is almost exclusively involved in the metabolism of the S-enantiomers of both acenocoumarol and warfarin through 6- and 7-hydroxylations.4,5 On the other hand, other enzymes besides CYP2C9 (eg, CYP1A2, CYP2C19, and CYP3A4) mediate the metabolism of the R-enantiomers of both anticoagulants.4,5 Accordingly, the genetic polymorphisms of CYP2C9 would be predicted to have a greater influence on the metabolism and pharmacodynamic response of warfarin compared with acenocoumarol, and this would be more apparent with CYP2C9*3 than with CYP2C9*2 because of the considerably lower metabolic activity of the former.13 Indeed, patients with the CYP2C9*1/*3 genotype have an approximately 50% lower mean oral clearance of S-acenocoumarol than CYP2C9*1/*1 homozygotes (10.9 L/h versus 19.8 L/h),10 resulting in 2-fold higher steady-state S-acenocoumarol plasma concentrations in such patients relative to those of the homozygous wild-type genotype. The pharmacokinetics of R-acenocoumarol is only modestly affected in CYP2C9*1/*3 heterozygotes10; accordingly, the steady-state concentrations of this enantiomer would be minimally different from those in the CYP2C9*1/*1 genotype, and, therefore, its plasma concentrations would still far exceed (>6-fold) those of the S-enantiomer. Accordingly, the overall anticoagulation effect (INR) in such heterozygotes is attributable to the sum of the plasma concentrations of R- and S-acenocoumarol, but this would be similar or only modestly increased compared with wild-type homozygotes.10 The data of Morin et al6 are consistent with these pharmacokinetic considerations, in that subjects with the CYP2C9*1/*3 genotype showed only a 15% greater INR value and a 53% greater reduction in factor VII coagulant activity at 24 hours after a single oral dose of the drug. In the single CYP2C9*3/*3 homozygote, the increased effects were still quite modest, consistent with the still dominant role of R-acenocoumarol, because it has been estimated that the clearance of the S-enantiomer in such individuals is about 20% of that in homozygous wild-type subjects.10 Nevertheless, Schalekamp et al7 observed that, in patients treated with acenocoumarol for 3 to 6 months, the CYP2C9*3 allele was associated with greater difficulties in empirically determining an optimal anticoagulation dose than in wild-type patients and carriers of the CYP2C9*2 allele. In addition, the stabilized dose requirement for CYP2C9*3 patients was 20% less than in CYP2C9*1/*1 individuals. With warfarin, however, the reduced metabolic activity of the CYP2C9*2 and CYP2C9*3 variants also primarily affects only the S-enantiomer, which in this case is also the isomer responsible for almost all of the anticoagulation effect, especially in patients carrying these mutations. Thus a 50% lower clearance in CYP2C9*1/*3 patients is associated with a 2-fold reduction in warfarin's maintenance dose compared with that in wild-type homozygotes, and even in CYP2C9*2 carriers, the dose is lower.14,15 In CYP2C9*3/*3 homozygotes an even greater dose reduction (5-fold) is required.14,15 Morin et al6 also investigated SNPs in the −2.1-kb 5′-flanking region that putatively might affect CYP2C9 expression. As noted previously,16,17 a number of these were found to be in linkage disequilibrium with common functional SNPs in the coding region, and, therefore, haplotype associations rather than single SNP analyses are, in principle, probably more appropriate for genetic analysis. Morin et al note that just 4 major haplotypes accounted for 97% of the white population; 2 of them were linked with either CYP2C9*2 or CYP2C9*3, and in the case of the latter haplotype, the consequence of the impaired reduction in the encoded enzyme's activity far exceeded any effect on expression, if it was present. In fact, no 5′-flanking region variants through −2.1 kb that up-regulate CYP2C9 expression have yet been identified.16,17 Whether these exist in more distal regions remains to be determined, but such information would possibly provide insights into yet unresolved questions. Fig 1, for example, shows the relationship between the empirically established daily maintenance doses of warfarin and the unbound clearance of S-warfarin obtained in white patients (n = 47) and Japanese patients (n = 126) in our previous studies18,19,20 and in white patients (n = 93) reported by Scordo et al.14 In this figure, variability on the abscissa and ordinate represents that in the pharmacokinetics and pharmacodynamics of warfarin, respectively. Despite significant differences in target INR value (2 to 3 in white patients versus 1.5 to 2.5 in Japanese patients) and body size (76.5 ± 16.6 kg in white patients versus 56.7 ± 11.3 kg in Japanese patients), a significant relationship linked to CYP2C9 genotype exists. Given that the dosing rate reflects clearance at steady state and S-warfarin's clearance is predominantly CYP2C9-mediated, this is not too surprising; that is, patients who require higher doses of warfarin possess greater CYP2C9 activities. However, it is noteworthy that there is considerable variability within the overall pharmacokinetic and pharmacodynamic relationship and within any particular genotype. Similar interindividual variability in the warfarin dosage requirement among CYP2C9*1/*1 homozygous patients, who constitute the majority of all populations studied to date, has also been reported by Daly and King.15 Furthermore, Morin et al6 observed marked differences in acenocoumarol's short-term pharmacodynamic response. Because factors such as age, body size, sex, diet, and vitamin K status do not fully account for such apparently non–CYP2C9-associated variability,6,21,22 this strongly suggests that other, currently unknown environmental determinants or possibly unidentified genetic variants may be involved, especially in the 5′-flanking region or the transcriptional regulatory receptors of the gene.23 These considerations also apply to the significantly greater unbound clearance of S-warfarin in CYP2C9*1/*1 homozygotes of Japanese descent compared with white patients.20 In addition, the possibility of genetically determined variability in the various proteins involved in the anticoagulant effect, such as vitamin K–dependent coagulation factors,24 which may contribute to differences in warfarin and acenocoumarol dosage requirements, is a largely unexplored area with regard to interindividual variability in responsiveness. Relationships between unbound oral clearance (CLpo,u) for S-warfarin and daily doses of warfarin in white (Caucasian; a) and Japanese (b) patients of different genotypes: CYP2C9*1/*1 (open circles), CYP2C9*2 (*1/*2 or *2/*2) (gray circles), CYP2C9*1/*3 (gray triangles), CYP2C9*3/*3 or CYP2C9*2/*3 (black triangles), and CYP2C9*1/*11 (black diamond). Finally, the current reports,6,7 along with additional findings regarding warfarin, acenocoumarol, and other CYP2C9 substrates,25,26,27 clearly indicate that genotype contributes to variability in these drugs' overall pharmacodynamic responses. The critical question, however, is whether this factor is sufficiently determining that knowledge of an individual's CYP2C9 genotype before prescribing a drug dose would lead to improved optimization of therapy, including a reduced risk of bleeding episodes. Given the implied and possibly significant involvement of nongenetic determinants in warfarin's anticoagulant effects (Fig 1 and Verstuyft et al28), for example, the answer to this question is not self-evident. It is even less apparent for acenocoumarol. An appropriately designed, large, multicenter clinical trial will be required to test this hypothesis and could serve as a bellwether study for the future of genetically based, personalized drug therapy involving interindividual variability in drug metabolism. The design, funding, implementation, and evaluation of such a trial, including pharmacoeconomic issues, for drugs such as warfarin and acenocoumarol, whose patents will have expired, will be difficult; the development of alternative and safer anticoagulants such as direct thrombin inhibitors also complicates the issue. In the absence of such a study, there is the possibility that, as with CYP2C19 and CYP2D6, genetically determined variability in CYP2C9 activity may simply remain an interesting scientific phenomenon with limited clinical application except to explain observations in a limited number of situations. None of the authors has financial or personal relationships that could be perceived as conflicts of interest.

Remimazolam, an ultrashort-acting benzodiazepine, has emerged as a promising sedative agent for procedural sedation and general anesthesia. It combines the favorable properties of traditional benzodiazepines with a rapid onset and offset of action, largely due to its unique metabolism via hepatic carboxylesterases rather than cytochrome P450 enzymes. This metabolism allows for predictable pharmacokinetics, reducing the risk of prolonged sedation and drug accumulation, particularly in patients with hepatic or renal impairment. Clinically, remimazolam demonstrates non-inferiority to midazolam and propofol, with advantages including a lower incidence of hypotension and respiratory depression. Multiple randomized controlled trials have shown its efficacy in various procedural settings, including endoscopy and bronchoscopy, with high procedural success rates and faster recovery times compared to midazolam. Additionally, remimazolam is reversible with flumazenil, further enhancing its safety profile. Pharmacokinetic studies indicate a rapid distribution phase, a short terminal half-life of approximately 37-53 min, and a clearance rate significantly higher than midazolam. Pharmacodynamic analyses confirm dose-dependent sedation effects, making remimazolam suitable for tailored sedation levels across patient populations. Special population studies suggest minimal impact of age, renal function, or mild-to-moderate hepatic impairment on drug disposition. However, rare cases of anaphylaxis and re-sedation following flumazenil administration have been reported. Given its rapid onset, predictable clearance, and favorable safety profile, remimazolam represents a valuable alternative to existing sedatives in procedural and anesthetic applications. Further research is warranted to explore its long-term safety, expanded clinical applications, and potential role in high-risk populations.

Landiolol, an ultra-short-acting &#x3b2;-blocker, is commonly used to manage tachyarrhythmias, including critically ill patients requiring renal replacement therapy (RRT). Pharmacokinetic (PK) data for landiolol in these patients are lacking. This study aimed to evaluate the PK and dialytic clearance of landiolol and its metabolite, M1, in septic shock patients receiving RRT, with the goal of guiding dosing optimization to ensure safe and effective treatment in this high-risk population. This pre-defined PK sub-study was embedded within the Landi-SEP trial, which randomized patients with septic shock and persistent tachycardia to receive standard care or standard care with landiolol. Patients from two centers undergoing RRT were included in the sub-study. PK parameters, including dialytic and total clearance and area under the concentration-time curve (AUC), were determined based on plasma concentrations of landiolol and M1. Pharmacodynamic data, including heart rate (HR) and blood pressure (BP), were assessed concurrently. Six patients were included in the final analysis. Mean dialytic clearance was 39.3&#xa0;mL/min for landiolol and 42.3&#xa0;mL/min for M1. Dialysis accounted for 2.4% of total landiolol clearance and 50.9% of M1 clearance. HR and BP remained stable throughout the sub-study and no adverse events related to hypotension or bradycardia were reported. Dialysis minimally affected landiolol clearance but removed a substantial proportion of M1. These exploratory data align with current dosing recommendations in patients with renal impairment and suggest that no dose adjustment is required during RRT. Individualized dosing and hemodynamic monitoring remain essential. EU Clinical Trial Register; EudraCT Number: 2017-002138-22.

Sunitinib malate is used to treat advanced renal cell carcinoma, gastrointestinal stromal, and pancreatic tumors. Wide variability in drug exposure is reported for both sunitinib and its active metabolite (SU12662). This review aimed to summarize reported population pharmacokinetics studies of sunitinib and to identify the factors affecting the pharmacokinetics of sunitinib and SU12662. A systematic search was undertaken using Scopus, Web of Science, and PubMed databases following Preferred Reporting Items for Systematic Reviews and Meta-analyses (PRISMA) guidelines. Studies were included in the review if population pharmacokinetic modeling approach was used for sunitinib and/or SU12662 in adult and/or pediatric population. Data quality was assessed using the percent compliance rate of each study. A total of 1820 articles were retrieved, and subsequently, 14 studies that met the inclusion criteria were included in the systematic review. Most of the studies reported two-compartment model with first-order absorption and elimination to describe sunitinib and SU12662. Body surface area, age, sex, ethnicity, tumor type, and ABCB1 and ABCG2 genotype were the significant covariates that affected the pharmacokinetics of sunitinib and SU12662. According to the published data from the reported studies, various covariates alter sunitinib and SU12662 exposure and thus have the potential to influence the clinical outcome of sunitinib treatment. Predictive performance assessment of these published models should be performed before implementing these models during the routine clinical practice. The summarized significant covariates affecting pharmacokinetics (PK) of sunitinib and SU12662 will facilitate model-informed precision dosing of sunitinib therapy in a clinical setting.

Newly approved drugs expand our therapeutic armamentarium, but augment the potential for drug–drug interactions. These can be broadly categorized into pharmaceutical (physicochemical, usually occurring ex vivo), pharmacokinetic (PK) or pharmacodynamic (PD). Importantly a drug–drug interaction that primarily causes a change in PK will consequently cause a secondary alteration in its pharmacodynamics. The literature has a plethora of human drug–drug interaction studies with widely differing designs, addressing the existence and possible clinical importance of specific potential drug–drug interactions. Most drug–drug interaction studies in humans compare drug substrate (D) concentrations with and without the interacting drug (I), thus focusing on the pharmacokinetic type of interaction. There are many study designs used for this purpose, which include: (i) a parallel group design (D in one group of subjects and D + I in another), (ii) a randomized crossover with a washout period (e.g. D followed by D + I, or D + I followed by D) and (iii) a one-sequence crossover (e.g. D always followed by D + I or the reverse). Several drug dosing regimen combinations for a drug substrate and interacting drug can be used: single dose/single dose, single dose/multiple dose, multiple dose/single dose and multiple dose/multiple dose. The selection of which one of these to use, or an alternative study design, depends on factors which relate specifically to the drug substrate and the interacting drug. These should include (i) acute or chronic use of D and/or I, (ii) safety aspects, including whether a drug is likely to have a narrow therapeutic concentration range, (iii) the pharmacokinetic and pharmacodynamic properties of both the drug substrate and the interacting drug and (iv) assessment of drug metabolizing enzyme inhibition (which in the case of reversible inhibitors typically equilibrates rapidly) as well as induction (which typically occurs over several days). The inhibiting/inducing drugs and the drug substrates should be dosed so that the exposures to both drugs are appropriate to their clinical use, including the highest doses likely to be used clinically [1]. In this issue of the Journal we publish several papers describing drug–drug interaction studies, and a cadre of papers that highlight the value of careful clinical observation and investigation in a single clinical case, which draws attention to potential, but previously undefined or poorly defined, drug–drug interactions. Derks et al. [2] studied the potential interaction between the cholesteryl ester transfer protein inhibitor dalcetrapib (900 mg) and the cholesterol absorption inhibitor ezetemibe (10 mg) in a randomized, open-label, three-period, three-treatment crossover study in 27 healthy men who took dalcetrapib, dalcetrapib plus ezetimibe or ezetimibe alone, each for 7 days with a 7–14 day washout period between treatments. The pharmacokinetic profiles of each drug were determined on day 7 of each treatment. Based on the least mean squares ratios for AUC and Cmax ezetimibe had no significant effect on dalcetrapib pharmacokinetics, while dalcetrapib slightly reduced the AUC and Cmax of ezetimibe. The plasma lipid profile effects were similar for all treatments, except that dalcetripib plus ezetimibe produced a greater reduction in LDL-C. While this study did not reveal a clinically significant pharmacokinetic interaction between the agents, it was a relatively short-term study and was not performed in patients taking these agents, where the findings could be different. A number of reports to agencies in Canada and Europe of increased warfarin anticoagulant effects in patients concomitantly taking oseltamivir prompted Davies et al. [3] to undertake a randomized, non-placebo controlled, two-way crossover study of 22 patients with chronic cardiac or vascular conditions who were taking stable doses of warfarin (INR 2.0–3.5 for 2 weeks). They were randomized to concomitant oseltamivir 75 mg twice daily for 4.5 days or warfarin alone, with a 4–8 day washout between treatments. The pharmacokinetics of R (+) and S (−) warfarin and oseltamivir were studied. Anticoagulant effects were studied by calculating the area under the effect concentration curve (AUEC(0,96 h)), the observed maximum increase in INR from baseline, the decrease from baseline in Factor VIIa, and the change in vitamin K1 concentrations. Oseltamivir caused minor or no significant changes in R (+) or S (−) warfarin pharmacokinetics and no changes in pharmacodynamics. The duration of oseltamivir treatment in the study, while appropriate for influenza treatment, may not be long enough for patients with severe H1N1 infection. The authors also point out that the influenza virus infection can produce cytokines (e.g. interferons) which could have altered warfarin CYP450 mediated metabolism in the reported cases. Egerer et al. [4] undertook a randomized, two-cohort, placebo-controlled study and investigated the effect of the NK1 antagonist aprepitant (an antiemetic) on the pharmacokinetics of high-dose melphalan in 30 patients with multiple myeloma. Aprepitant is a moderate inhibitor of CYP450 and may inhibit drug transporter proteins. It was given orally (125 mg) 1 h before intravenous melphalan (100 mg m−2). Melphalan concentrations were measured by LC-MS-MS. Melphalan Cmax, AUC and plasma clearance were the same with aprepitant and placebo. Thus, 125 mg of aprepitant given orally 1 h before the melphalan infusion did not alter the disposition of melphalan. Monte et al. [5] describe a 19-year-old man who took an overdose of an antitussive agent containing dextromethorphan (estimated dose ingested 1440 mg) and the H1-receptor antagonist chlorphenamine (estimated dose ingested 192 mg). He developed the serotonin syndrome (as diagnosed on clinical Hunter criteria) [6] and made a good recovery. A literature review revealed three cases of overdoses in which solely dextromethorphan and chlorphenamine (including that reported in this paper) had been ingested and in which serotonin syndrome developed. Chlorphenamine has been reported to be a serotonin re-uptake inhibitor (at least as potent as dextromethorphan) [7] and a weak inhibitor of the CYP2D6 (Ki approximately 11 µm) [8] the major metabolizing enzyme for dextromethorphan. The authors sensibly suggest that in patients who take a combined overdose of dextromethorphan and chlorphenamine, the development of serotonin syndrome should be considered a potential complication. Heine et al. [9] describe a patient with non-small cell lung cancer who, while taking erlotinib, developed gastrointestinal symptoms, culminating in haemorrhage from a gastric ulcer. Initially the gastrointestinal symptoms were treated with antacids and then with the proton pump inhibitor pantoprazole intravenously for 2 days and then orally for 5 days. Erlotinib plasma Cmin (trough) concentrations were reduced during high dose intravenous pantoprazole therapy compared with baseline, but rose into the putative therapeutic range when pantoprazole was used orally in a lower dose. The proposed mechanism for this observation is reduced absorption of erlotinib (pKa 5.4) when stomach pH is increased. Clearly, further studies are needed to confirm the potential interaction between pantoprazole and erlotinib and to define its dose-dependency. There is a controversy in an evolving literature concerning the putative effect of proton pump inhibitors (e.g. omeprazole) in impairing the metabolic activation of clopidogrel and compromising its antiplatelet effects [10, 11]. A recent paper in our sister Journal by Zahno et al. [12] described the effects of different CYP450 inhibitors on the two-step bioactivation of clopidogrel to its active metabolite R-130964 in human liver microsomes and the antiplatelet effects of clopidogrel. The conversion of clopidogrel to its active metabolite (R-130964) is a two-step CYP450-dependent process. At clopidogrel concentrations over 10 µm, CYP3A4 is mainly responsible for clopidogrel metabolic activation, whereas CYP2C19 contributes mainly at clopidogrel concentrations of 10 µm and below. Clopidogrel itself inhibited CYP2C19 at concentrations greater than 10 µm. The CYP2C19 inhibitor lansoprazole inhibited clopidogrel biotransformation at clopidogrel concentrations of 10 µm and below. It is difficult to interpret these data from a clinical perspective, because the Cmax of clopidogrel after 75 to 150 mg oral doses is only 0.1–0.15 µm (3–5 ng ml−1) [13] posing the question of what the corresponding range of clopidogrel concentrations in hepatocyte cytoplasm is in the environment of the CYP enzymes. It appears that only a prospective randomized placebo controlled trial will settle this debate. The panoply of study designs outlined above may be used to generate definitive data on in vivo drug–drug interactions, but, not surprisingly, there is no one single optimal study design. The suggested study designs using healthy volunteers may not be optimal for investigational or approved drugs, particularly when small numbers of subjects are studied where the drug–drug interaction only occurs in a few susceptible individuals [14]. Moreover, drug–drug interaction studies in appropriate patient populations have higher relevance and accuracy, providing they are feasible and can be conducted safely. Well documented case reports play a definite role in informing and guiding well-controlled further studies. In vitro studies, particularly for CYP450-mediated interactions, can be helpful in estimating the likely magnitude of any interaction and understanding its mechanism. The incidence of drug–drug interactions in clinical therapeutics will continue to increase and challenge prescribers; as well as drawing the interest of clinical pharmacologists.

Migraine affects up to 11% of children and adolescents, leading to substantial disability through school absenteeism, cognitive impairment, and reduced quality of life. Traditionally, preventive treatment options for this population have been limited to the off-label use of nutraceuticals, antiseizure medications, calcium channel blockers, serotonin modulators, antidepressants, or beta-blockers, with limited efficacy and tolerability data. Monoclonal antibodies targeting the calcitonin gene-related peptide (CGRP) pathway have transformed adult migraine prevention, and fremanezumab is the first in this class to receive regulatory approval for pediatric use. In August 2025, the US Food and Drug Administration approved fremanezumab for the preventive treatment of episodic migraine in patients aged 6-17 years weighing at least 45 kg, based on the pivotal phase three SPACE trial. This randomized, placebo-controlled study demonstrated significant reductions in monthly migraine and headache days, with nearly half of treated participants achieving a &#x2265;50% response rate, and a safety profile consistent with adult data. In this review, we provide an integrated, pediatric-focused synthesis of the pharmacokinetic, pharmacodynamic, and regulatory evidence supporting fremanezumab use in children and adolescents. In particular, we contextualize population pharmacokinetic modeling and pediatric phase 1 data to explain the rationale for weight-based dosing, exposure matching with adults, and the selection of the dosing regimens used in clinical trials and regulatory labeling. Pharmacokinetic analyses indicate that fremanezumab follows a two-compartment model with first-order absorption and a terminal half-life of approximately 30 days in pediatric patients, similar to adults, with body weight as the primary determinant of exposure. Finally, we discuss unresolved issues related to long-term CGRP blockade during growth, including theoretical effects on vascular regulation, bone metabolism, and neurodevelopment. Overall, fremanezumab represents a novel, mechanism-based preventive option for older children and adolescents with episodic migraine, while highlighting the need for continued longitudinal studies to define its long-term safety and optimal role in pediatric migraine management.

The cendakimab (CC-93538, previously RPC4046) phase 3 trial used prefilled syringes (PFS), while the intended commercial product is an autoinjector (AI). This study evaluated the pharmacokinetic (PK) comparability of cendakimab administration by PFS and AI, and at different injection sites. This was a phase 1, single-center, randomized, open-label, single-dose, two-part parallel-group study (NCT05337345) in healthy adults. In part 1, participants were randomized 1:1 to receive cendakimab 360 mg subcutaneously in the abdomen by PFS (treatment A) or AI (treatment B). In part 2, participants were randomized to receive cendakimab 360 mg subcutaneously in either the upper arm (treatment C) or upper thigh area (treatment D) by AI. Analysis of covariance was used to compare the log-transformed area under the curve (AUC) and peak concentration (Cmax) between PFS and AI devices. PK parameters based on cendakimab serum concentration were estimated using noncompartmental analysis and actual PK collection time. Immunogenicity was evaluated via measurement of antidrug antibody (ADA) titer over 105 (&#xb1;&#xa0;2) days after dosing; the impact of ADAs on the safety and PK of cendakimab was evaluated. Overall, 64 and 40 healthy adults were dosed in parts 1 and 2, respectively. In part 1, the geometric least squares mean (LSM) ratios (90% CI) of treatment B versus A were contained within the generally accepted limit of 80-125%; 1.04 (0.90-1.20), 0.98 (0.87-1.12), and 0.99 (0.87-1.12) for Cmax, AUC from time zero extrapolated to infinity (AUC&#x221e;), and AUC from time zero to the time of the last quantifiable concentration (AUCt), respectively. The geometric LSM ratios (90% CI) of treatment C versus B were 1.21 (1.05-1.39), 1.21 (1.07-1.38), and 1.22 (1.08-1.38) for Cmax, AUC&#x221e;, and AUCt, respectively. The geometric LSM ratios (90% CI) of treatment D versus B were 1.23 (1.06-1.41), 1.26 (1.11-1.43), and 1.26 (1.11-1.42) for Cmax, AUC&#x221e;, and AUCt, respectively. Lastly, the geometric LSM ratios (90% CI) of treatment C versus D for Cmax, AUC&#x221e;, and AUCt were contained entirely within 80-125%. In part 1, 43.8% (n&#xa0;=&#xa0;14) of participants receiving treatment A (PFS, abdomen) and 40.6% (n&#xa0;=&#xa0;13) receiving treatment B (AI, abdomen) reported &#x2265;&#xa0;1 adverse event (AE). In part 2, 35.0% (n&#xa0;=&#xa0;7) of participants receiving either treatment C (AI, upper arm) or treatment D (AI, upper thigh) reported &#x2265;&#xa0;1 AE. There were no serious/severe AEs and no discontinuations due to an AE. PK parameters of cendakimab were comparable when using PFS or AI. Cendakimab exposures when administered in the arm or thigh resulted in similar exposure; both were ~&#xa0;20% higher than when administering in the abdomen. Both PFS and AI were well tolerated. ADA status did not impact the PK or safety of cendakimab. GOV: NCT05337345.

The cytochrome P450 (CYP) system plays a central role in drug metabolism and pharmacokinetic variability, influencing drug-drug interaction risk. The newly synthesized 4-propoxy-2-arylquinoline derivatives (MW1-3) are dual inhibitors of epidermal growth factor receptor (EGFR) and focal adhesion kinase (FAK) with potent anticancer activity. This study aimed to assess their potential inhibitory effects on major human CYP enzymes to predict metabolic liabilities and interaction risks. Inhibitory effects of MW1-3 were evaluated against CYP1A2, CYP2A6, CYP2C9, CYP2C19, CYP2D6, CYP2E1, and CYP3A4 using pooled human liver microsomes and probe substrates quantified by validated liquid chromatography with tandem mass spectrometry (LC-MS/MS) and high-performance liquid chromatography-ultraviolet (HPLC-UV) assays. Molecular docking was performed with the seven CYP enzymes to estimate binding affinities and identify possible enzyme-ligand interactions. All the compounds showed negligible inhibition of CYP1A2 with half-maximal inhibitory concentrations (IC50)&#xa0;> 100 &#xb5;M. MW1, MW2, and MW3 strongly inhibited CYP2A6 (IC50 = 0.04, 0.189, and 0.118 &#xb5;M, respectively) and CYP2D6 (IC50 = 0.69, 1.26, and 0.69 &#xb5;M, respectively), while MW3 was also a potent inhibitor of CYP2E1 (IC50 = 0.12 &#xb5;M). MW2 displayed moderate-strong inhibition of CYP3A4 (IC50 = 1.65 &#xb5;M) and CYP2C19 (IC50 = 43.9 &#xb5;M). Docking results complemented in vitro inhibition findings for CYP2D6 and provided structural insights into the binding modes for CYP2C9 and CYP2C19, although modeling did not account for the strong inhibition observed in smaller enzymes like CYP2A6. MW1-3 exhibit selective and differential inhibition profiles toward major CYP enzymes, with CYP2A6, CYP2D6, and CYP2E1 being most affected. These findings provide essential preclinical insights for predicting potential drug-drug interactions and guiding the safe development of these arylquinoline-based anticancer agents.

Mirogabalin besylate is a selective &#x3b1;2&#x3b4;-1 ligand approved for diabetic peripheral neuropathic pain. This study evaluated the pharmacokinetic (PK) bioequivalence and safety of generic 5 mg and 10 mg mirogabalin formulations compared with the reference product (Tarlige&#xae;) under both fasting and fed conditions among healthy Chinese volunteers. This pooled analysis comprised two independent, randomized, open-label, two-period crossover trials: one evaluating the 5 mg formulation (24 participants/group) and another evaluating the 10 mg formulation (36 participants/group). Liquid chromatography-tandem mass spectrometry (LC-MS/MS) assays have been validated over ranges of 1.00-200 ng/mL (5-mg study) and 0.50-500 ng/mL (10-mg study) for plasma mirogabalin quantification. Primary endpoints were peak plasma concentration (Cmax), area under the plasma concentration-time curve from time zero to the last quantifiable time point (AUC0-t), and area under the plasma concentration-time curve from time zero to infinity (AUC0-&#x221e;). Bioequivalence was determined if the 90% confidence intervals (CIs) of geometric mean ratios (GMRs) fell within the 80.00-125.00% range, evaluated via analysis of variance (ANOVA) on log-transformed parameters. For the 5 mg formulation, the fasting study demonstrated bioequivalence with a Cmax GMR of 99.10% (90% CI 91.23-107.64), AUC0-t of 99.50% (97.14-101.91), and AUC0-&#x221e; of 99.29% (96.96-101.68). Under fed conditions, Cmax showed higher variability (GMR: 88.61%, 80.48-97.55), while AUC0-t (98.55%, 96.42-100.73) and AUC0-&#x221e; (99.03%, 97.00-101.10) remained within equivalence bounds. The 10 mg formulation exhibited robust bioequivalence in both fasting and fed states: fasting Cmax GMR was 97.07% (91.84-102.60), AUC0-t 100.61% (98.52-102.74), and AUC0-&#x221e; 100.55% (98.61-102.53); fed Cmax was 97.14% (89.64-105.26), AUC0-t 101.04% (99.26-102.86), and AUC0-&#x221e; 100.53% (99.03-102.05). An exploratory analysis of the two dose levels suggested a linear PK for mirogabalin within the 5-10 mg range. The intrasubject variability was generally low (CVW%: 3.76-20.36%), with the 10 mg formulation showing numerically lower variability for Cmax (13.79%) compared with the 5 mg formulation (16.39%) in the fasting state. Adverse event incidence ranged from 13.0% to 25.0% across groups, with no severe events reported. Both generic formulations met bioequivalence criteria to Tarlige&#xae; across studied doses. While both formulations showed acceptable PK profiles, the 10 mg dose exhibited more consistent exposure characteristics, as evidenced by a lower within-subject variability. The PK data are consistent with linear PK for mirogabalin within the studied dose range. Comparable safety profiles support the pharmaceutical equivalence in the studied population. These findings provide critical PK evidence for China's first generic mirogabalin products. ( http://www.chinadrugtrials.org.cn ): 5 mg: CTR20232783; 10 mg: CTR20242717.

Obtaining pharmacokinetic curves is crucial for drug dosage selection, and for assessment of efficacy and adverse effects in clinical practice. The aim of this study was to utilize a minimal physiologically-based pharmacokinetic model to predict concentration-time profiles of cinacalcet hydrochloride, a poorly soluble drug, under fasting and fed conditions, and further to establish correlations between in vivo and in vitro dissolution profiles of cinacalcet hydrochloride. The mPBPK model consisted of six tissue compartments, and an additional compartmental absorption and transit model, incorporating the stomach, seven small intestinal compartments, and the large intestine along with Johnson's equation, was integrated to enable precise calculations of in vivo dissolution. External validations for three dosages showed that the average fold error and the absolute average fold error were all within a two-fold error range, indicating the accuracy and reliability of the established model. Subsequently, the model was used to calculate the in vivo dissolution profile and to establish a correlation with the in vitro dissolution profile (R2&#xa0;=&#xa0;0.991 in fasting conditions and R2&#xa0;=&#xa0;0.991 in fed conditions, both in water medium). Notably, under fasting conditions, this correlation exhibited superior performance compared to convolution, deconvolution, and Wagner-Nelson methods. However, under fed conditions, all four methods demonstrated satisfactory correlations. The mPBPK model can accurately predict the plasma concentration-time curves under both fasted and fed conditions, and provides a new perspective for establishing in vivo-in vitro correlations of drug products such as incomplete in vivo release, sustained/controlled release, and poor absorption.

This study evaluated the pharmacokinetic characteristics, bioequivalence, and safety of propafenone hydrochloride tablets under fasting conditions in healthy Chinese subjects. This was a single-center, randomized, open-label, two-formulation, single-dose study using a four-period fully replicated crossover design. A total of 36 subjects were randomized 1:1 to two sequence groups and received the test (T) or reference (R) formulation in each period. Plasma concentrations of propafenone and its active metabolite, 5-hydroxypropafenone, were quantified using a validated liquid chromatography-tandem mass spectrometry (LC-MS/MS) method. Pharmacokinetic parameters were derived by noncompartmental analysis using Phoenix WinNonlin 7.0. Bioequivalence was assessed using reference-scaled average bioequivalence (RSABE) based on the within-subject standard deviation (SWR) of the reference product for area under the concentration-time curve from time 0 to the last time (AUC0-t), area under the concentration-time curve from time 0 to infinity (AUC0-&#x221e;), and maximum plasma drug concentration (Cmax). Overall, 35 subjects completed the study. After administration of T and R, mean (&#xb1;&#xa0;standard deviation [SD]) propafenone Cmax, AUC0-t, and AUC0-&#x221e; were 52.81&#xb1;70.44 versus 50.11&#xb1;60.96 ng/mL, 174.98&#xb1;220.13 versus 165.25&#xb1;204.39 h/ng/mL, and 184.19&#xb1;222.71 versus 171.31&#xb1;206.53 h/ng/mL, respectively. For 5-hydroxypropafenone, Cmax, AUC0-t, and AUC0-&#x221e; were 68.95&#xb1;42.09 versus 66.55&#xb1;33.52 ng/mL, 234.08&#xb1;150.88 versus 223.33&#xb1;141.50 h/ng/mL, and 241.43&#xb1;151.53 versus 230.11&#xb1;142.83 h/ng/mL, respectively. RSABE analysis indicated that the geometric mean ratios (T/R) for propafenone Cmax, AUC0-t, and AUC0-&#x221e; were 101.04%, 106.27%, and 105.32%, all within the acceptance range of 80.00-125.00%. Under fasting single-dose conditions, the test and reference propafenone hydrochloride tablets met bioequivalence criteria in healthy Chinese subjects.

Focusing on pharmacokinetic-derived individual dose-intensity parameter values (DIPs), we modeled the pharmacokinetics of polyethylene glycol-conjugated asparaginase (PEG-ASNase) in all treatment phases and different trial groups of AIEOP-BFM ALL 2009. Children with acute lymphoblastic leukemia received 1-10 weekly or biweekly repetitive doses (2500&#xa0;U/m2/dose intravenously). A population pharmacokinetic (popPK) model was extended to all phases to describe the pharmacokinetics and the impact of anti-PEG- and anti-asparaginase-antibodies in the German/Czech group (2535 patients, aspartic acid &#x3b2;-hydroxamate (AHA) assay) and validated the model in the Italian group (1603 patients, medac asparaginase activity test (MAAT) assay). DIPs, also for 279 Australian patients, were derived. Allergic reactions and silent inactivation were exclusion criteria. Treatment phase dependency and drug accumulation were modeled by up to -60% lower clearance and -30% lower volume of distribution compared with the first administration in induction. Apart from the impact of high preexisting anti-PEG-antibody levels on clearance in induction, no further impact of antibodies was identified. Independent modelling of the Italian data (conversion factor 1.23/1.42: &#x2264; 600/> 600&#xa0;U/L) confirmed the model. Time above 100&#xa0;U/L correlated to the time-interval between the first and last dose within a phase, whereas the area under the concentration-time curve (AUC) was linked to the cumulative dose showing higher drug accumulation after repetitive doses than expected by linear extrapolation. A popPK model was adapted to all phases and different trial groups integrating asparaginase antibodies as long as they did not lead to silent inactivation or allergic reaction. The model allows strategic development of trial schedules and the calculation of intended or realized individual DIPs. EU clinical trails register; European Union Drug Regulating Authorities Clinical Trials Database (EudraCT) Number 2007-004270-43.