ING116070: a study of the pharmacokinetics and antiviral activity of dolutegravir in cerebrospinal fluid in HIV-1-infected, antiretroviral therapy-naive subjects.

BackgroundDolutegravir (DTG), a once-daily, human immunodeficiency virus type 1 (HIV-1) integrase inhibitor, was evaluated for distribution and antiviral activity in cerebrospinal fluid (CSF).MethodsING116070 is an ongoing, single-arm, open-label, multicenter study in antiretroviral therapy-naive, HIV-1-infected adults. Subjects received DTG (50 mg) plus abacavir/lamivudine (600/300 mg) once daily. The CSF and plasma (total and unbound) DTG concentrations were measured at weeks 2 and 16. The HIV-1 RNA levels were measured in CSF at baseline and weeks 2 and 16 and in plasma at baseline and weeks 2, 4, 8, 12, and 16.ResultsThirteen white men enrolled in the study; 2 withdrew prematurely, 1 because of a non-drug-related serious adverse event (pharyngitis) and 1 because of lack of treatment efficacy. The median DTG concentrations in CSF were 18 ng/mL (range, 4-23 ng/mL) at week 2 and 13 ng/mL (4-18 ng/mL) at week 16. Ratios of DTG CSF to total plasma concentration were similar to the unbound fraction of DTG in plasma. Median changes from baseline in CSF (n = 11) and plasma (n = 12) HIV-1 RNA were -3.42 and -3.04 log10 copies/mL, respectively. Nine of 11 subjects (82%) had plasma and CSF HIV-1 RNA levels <50 copies/mL and 10 of 11 (91%) had CSF HIV-1 RNA levels <2 copies/mL at week 16.ConclusionsThe DTG concentrations in CSF were similar to unbound plasma concentrations and exceeded the in vitro 50% inhibitory concentration for wild-type HIV (0.2 ng/mL), suggesting that DTG achieves therapeutic concentrations in the central nervous system. The HIV-1 RNA reductions were similar in CSF and plasma. Clinical Trials Registration. NCT01499199

Breast cancer growth and metastasis: interplay between cancer stem cells, embryonic signaling pathways and epithelial-to-mesenchymal transition

Induction of epithelial-to-mesenchymal transition (EMT) in cancer stem cells (CSCs) can occur as the result of embryonic pathway signaling. Activation of Hedgehog (Hh), Wnt, Notch, or transforming growth factor-β leads to the upregulation of a group of transcriptional factors that drive EMT. This process leads to the transformation of adhesive, non-mobile, epithelial-like tumor cells into cells with a mobile, invasive phenotype. CSCs and the EMT process are currently being investigated for the role they play in driving metastatic tumor formation in breast cancer. Both are very closely associated with embryonic signaling pathways that stimulate self-renewal properties of CSCs and EMT-inducing transcription factors. Understanding these mechanisms and embryonic signaling pathways may lead to new opportunities for developing therapeutic agents to help prevent metastasis in breast cancer. In this review, we examine embryonic signaling pathways, CSCs, and factors affecting EMT

Global burden of 288 causes of death and life expectancy decomposition in 204 countries and territories and 811 subnational locations, 1990–2021: a systematic analysis for the Global Burden of Disease Study 2021

BACKGROUND Regular, detailed reporting on population health by underlying cause of death is fundamental for public health decision making. Cause-specific estimates of mortality and the subsequent effects on life expectancy worldwide are valuable metrics to gauge progress in reducing mortality rates. These estimates are particularly important following large-scale mortality spikes, such as the COVID-19 pandemic. When systematically analysed, mortality rates and life expectancy allow comparisons of the consequences of causes of death globally and over time, providing a nuanced understanding of the effect of these causes on global populations. METHODS The Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2021 cause-of-death analysis estimated mortality and years of life lost (YLLs) from 288 causes of death by age-sex-location-year in 204 countries and territories and 811 subnational locations for each year from 1990 until 2021. The analysis used 56 604 data sources, including data from vital registration and verbal autopsy as well as surveys, censuses, surveillance systems, and cancer registries, among others. As with previous GBD rounds, cause-specific death rates for most causes were estimated using the Cause of Death Ensemble model-a modelling tool developed for GBD to assess the out-of-sample predictive validity of different statistical models and covariate permutations and combine those results to produce cause-specific mortality estimates-with alternative strategies adapted to model causes with insufficient data, substantial changes in reporting over the study period, or unusual epidemiology. YLLs were computed as the product of the number of deaths for each cause-age-sex-location-year and the standard life expectancy at each age. As part of the modelling process, uncertainty intervals (UIs) were generated using the 2·5th and 97·5th percentiles from a 1000-draw distribution for each metric. We decomposed life expectancy by cause of death, location, and year to show cause-specific effects on life expectancy from 1990 to 2021. We also used the coefficient of variation and the fraction of population affected by 90% of deaths to highlight concentrations of mortality. Findings are reported in counts and age-standardised rates. Methodological improvements for cause-of-death estimates in GBD 2021 include the expansion of under-5-years age group to include four new age groups, enhanced methods to account for stochastic variation of sparse data, and the inclusion of COVID-19 and other pandemic-related mortality-which includes excess mortality associated with the pandemic, excluding COVID-19, lower respiratory infections, measles, malaria, and pertussis. For this analysis, 199 new country-years of vital registration cause-of-death data, 5 country-years of surveillance data, 21 country-years of verbal autopsy data, and 94 country-years of other data types were added to those used in previous GBD rounds. FINDINGS The leading causes of age-standardised deaths globally were the same in 2019 as they were in 1990; in descending order, these were, ischaemic heart disease, stroke, chronic obstructive pulmonary disease, and lower respiratory infections. In 2021, however, COVID-19 replaced stroke as the second-leading age-standardised cause of death, with 94·0 deaths (95% UI 89·2-100·0) per 100 000 population. The COVID-19 pandemic shifted the rankings of the leading five causes, lowering stroke to the third-leading and chronic obstructive pulmonary disease to the fourth-leading position. In 2021, the highest age-standardised death rates from COVID-19 occurred in sub-Saharan Africa (271·0 deaths [250·1-290·7] per 100 000 population) and Latin America and the Caribbean (195·4 deaths [182·1-211·4] per 100 000 population). The lowest age-standardised death rates from COVID-19 were in the high-income super-region (48·1 deaths [47·4-48·8] per 100 000 population) and southeast Asia, east Asia, and Oceania (23·2 deaths [16·3-37·2] per 100 000 population). Globally, life expectancy steadily improved between 1990 and 2019 for 18 of the 22 investigated causes. Decomposition of global and regional life expectancy showed the positive effect that reductions in deaths from enteric infections, lower respiratory infections, stroke, and neonatal deaths, among others have contributed to improved survival over the study period. However, a net reduction of 1·6 years occurred in global life expectancy between 2019 and 2021, primarily due to increased death rates from COVID-19 and other pandemic-related mortality. Life expectancy was highly variable between super-regions over the study period, with southeast Asia, east Asia, and Oceania gaining 8·3 years (6·7-9·9) overall, while having the smallest reduction in life expectancy due to COVID-19 (0·4 years). The largest reduction in life expectancy due to COVID-19 occurred in Latin America and the Caribbean (3·6 years). Additionally, 53 of the 288 causes of death were highly concentrated in locations with less than 50% of the global population as of 2021, and these causes of death became progressively more concentrated since 1990, when only 44 causes showed this pattern. The concentration phenomenon is discussed heuristically with respect to enteric and lower respiratory infections, malaria, HIV/AIDS, neonatal disorders, tuberculosis, and measles. INTERPRETATION Long-standing gains in life expectancy and reductions in many of the leading causes of death have been disrupted by the COVID-19 pandemic, the adverse effects of which were spread unevenly among populations. Despite the pandemic, there has been continued progress in combatting several notable causes of death, leading to improved global life expectancy over the study period. Each of the seven GBD super-regions showed an overall improvement from 1990 and 2021, obscuring the negative effect in the years of the pandemic. Additionally, our findings regarding regional variation in causes of death driving increases in life expectancy hold clear policy utility. Analyses of shifting mortality trends reveal that several causes, once widespread globally, are now increasingly concentrated geographically. These changes in mortality concentration, alongside further investigation of changing risks, interventions, and relevant policy, present an important opportunity to deepen our understanding of mortality-reduction strategies. Examining patterns in mortality concentration might reveal areas where successful public health interventions have been implemented. Translating these successes to locations where certain causes of death remain entrenched can inform policies that work to improve life expectancy for people everywhere. FUNDING Bill & Melinda Gates Foundation

Population pharmacokinetic modeling and simulation of maribavir to support dose selection and regulatory approval in adolescents with posttransplant refractory cytomegalovirus

Abstract Maribavir was approved by the US Food and Drug Administration for the treatment of patients aged ≥12 years and weighing ≥35 kg with posttransplant cytomegalovirus infection/disease refractory (with/without resistance) to valganciclovir, ganciclovir, cidofovir, or foscarnet, with an oral dose of 400 mg twice daily. With no pediatric clinical data available and difficulty in trial recruitment, population pharmacokinetic modeling and simulations were conducted to predict the pharmacokinetics and inform maribavir dosing in adolescents

Maribavir: Mechanism of action, clinical, and translational science

Abstract Maribavir is an oral benzimidazole riboside for treatment of post‐transplant cytomegalovirus (CMV) infection/disease that is refractory to prior antiviral treatment (with or without resistance). Through competitive inhibition of adenosine triphosphate, maribavir prevents the phosphorylation actions of UL97 to inhibit CMV DNA replication, encapsidation, and nuclear egress. Maribavir is active against CMV strains with viral DNA polymerase mutations that confer resistance to other CMV antivirals. After oral administration, maribavir is rapidly and highly absorbed (fraction absorbed >90%). The approved dose of 400 mg twice daily (b.i.d.) achieves a steady‐state area under the curve per dosing interval of 128 h*μg/mL and trough concentration of 4.90 μg/mL (13.0 μM). Maribavir is highly bound to human plasma proteins (98%) with a small apparent volume of distribution of 27.3 L. Maribavir is primarily cleared by hepatic CYP3A4 metabolism; its major metabolite, VP44669 (pharmacologically inactive), is excreted in the urine and feces. There is no clinically relevant impact on maribavir pharmacokinetics by age, sex, race/ethnicity, body weight, transplant type, or hepatic/renal impairment status. In phase II dose‐ranging studies, maribavir showed similar rates of CMV viral clearance across 400, 800, or 1200 mg b.i.d. groups, ranging from 62.5–70% in study 202 (NCT01611974) and 74–83% in study 203 (EudraCT 2010–024247‐32). In the phase III SOLSTICE trial (NCT02931539), maribavir 400 mg b.i.d. demonstrated superior CMV viremia clearance at week 8 versus investigator‐assigned treatments, with lower treatment discontinuation rates. Dysgeusia, nausea, vomiting, and diarrhea were commonly experienced adverse events among patients treated with maribavir in clinical trials

Pharmacokinetics of Budesonide Oral Suspension in Children and Adolescents with Eosinophilic Esophagitis

The pharmacokinetic (PK) profile of budesonide oral suspension (BOS) was evaluated during a phase 2, randomized, double-blind, placebo-controlled, dose-ranging study in pediatric patients with eosinophilic esophagitis (EoE)(MPI 101-01/NCT00762073). Non-compartmental methods were used to calculate PK parameters in 37 patients after receiving morning doses of BOS, with volume and dose adjusted for age (low dose: 0.35 or 0.5 mg; high dose: 1.4 or 2.0 mg [2–9 or 10–18 years old, respectively]). Relationships between apparent oral clearance and volume of distribution versus bodyweight and body mass index were also evaluated. Budesonide systemic exposure increased with BOS dose. After oral administration, time to maximum plasma budesonide concentration occurred ~1 hour post-dose and the half-life of budesonide was 3.3–3.5 hours. PK parameters were similar between age groups for low- and high-dose BOS, indicating that volume and dose adjustments for age were appropriate for pediatric patients with EoE. BOS was well tolerated