Clinical and Translational Science最新文献

The suitability of the endogenous 6-hydroxymelatonin/melatonin urinary metabolic ratio as a surrogate for the paraxanthine/caffeine ratio to predict cytochrome P450 1A2 (CYP1A2) activity was assessed in this study. Twelve healthy volunteers completed four study sessions spread over 1 month (including overnight urine collection with first morning voids collected separately). Except for the third session, volunteers were asked to abstain from methylxanthine-containing beverages and foods at least 24 h before urine collection. At the end of urine collection, subjects were given a caffeinated beverage and capillary blood samples were collected 2 h after the drink administration. A significant linear relationship between the 6-hydroxymelatonin/melatonin ratios from 12-h urine samples and first morning voids was observed (R²  = 0.876, p < 0.0001). In contrast to the paraxanthine/caffeine ratio, consumption of methylxanthine-containing beverages during session three did not significantly influence the 6-hydroxymelatonin/melatonin ratios compared with the other sessions requiring abstinence from caffeine. A larger intra- and interindividual variability in the 6-hydroxymelatonin/melatonin ratios compared with the paraxanthine/caffeine ratio was also observed. A very weak correlation was observed between the paraxanthine/caffeine ratio and both of the endogenous 6-hydroxymelatonin/melatonin ratios (Pearson r < 0.35, p < 0.05). All these results question whether this endogenous metric could adequately reflect CYP1A2 activity or substitute for the probe caffeine. Additional studies with larger study samples are needed to examine this endogenous metric in more details.

The current pediatric mental health crisis is characterized by staggering rates of depression, anxiety, and suicide. Beyond this, first-line pharmacologic interventions for depressive and anxiety disorders in children and adolescents produce variable responses with two in five youths failing to respond. Given the heterogeneity of treatment response in pediatric depressive and anxiety disorders, pharmacodynamic biomarkers are necessary to develop precision therapeutics by identifying clear targets to guide treatment. This mini-review summarizes candidate biomarkers and their development in pediatric mental health conditions. A framework for how these biomarkers may relate to safety, efficacy (e.g., surrogates for clinical endpoints), tolerability or target engagement (i.e., drug action) in children and adolescents is also presented. Taken together, accumulating data suggest that, in children and adolescents with myriad psychiatric disorders, pharmacodynamic biomarkers could facilitate developing drugs with well-defined targets in specific populations, could inform treatment decisions, and hasten patients' recovery.

Odronextamab is a fully-human IgG4-based CD20xCD3 bispecific antibody that binds to CD3 on T cells and CD20 on B cells, triggering T-cell-mediated cytotoxicity independent of T-cell-receptor recognition. Adequate safety, tolerability, and encouraging durable complete responses have been observed in an ongoing first-in-human (FIH) study of odronextamab in patients with relapsed/refractory (R/R) B-cell non-Hodgkin lymphoma (B-NHL; NCT02290951). We retrospectively evaluated the pharmacokinetic, pharmacodynamic, and antitumor characteristics of odronextamab in a series of in vitro/in vivo preclinical experiments, to assess their translational value to inform dose escalation for the FIH study. Half-maximal effective concentration values from in vitro cytokine release assays (range: 0.05-0.08 mg/L) provided a reasonable estimate of odronextamab concentrations in patients associated with cytokine release at a 0.5 mg dose (maximum serum concentration: 0.081 mg/L) on week 1/day 1, which could therefore be used to determine the week 1 clinical dose. Odronextamab concentrations resulting in 100% inhibition of tumor growth in a Raji xenograft tumor mouse model (1-10 mg/L) were useful to predict efficacious concentrations in patients and inform dose-escalation strategy. Although predicted human pharmacokinetic parameters derived from monkey data overestimated projected odronextamab exposure, they provided a conservative estimate for FIH starting doses. With step-up dosing, the highest-tested weekly odronextamab dose in patients (320 mg) exceeded the 1 mg/kg single dose in monkeys without step-up dosing. In conclusion, combination of odronextamab in vitro cytokine data, efficacious concentration data from mouse tumor models, and pharmacokinetic evaluations in monkeys has translational value to inform odronextamab FIH study design in patients with R/R B-NHL.

Tissue-nonspecific alkaline phosphatase (TNAP) hydrolyzes and inactivates inorganic pyrophosphate (PPi), a potent inhibitor of calcification; therefore, TNAP inhibition is a potential target to treat ectopic calcification. These two first-in-human studies evaluated safety, tolerability, pharmacokinetics (PKs), and pharmacodynamics (PDs) of single (SAD) and multiple-ascending doses (MAD) of DS-1211, a TNAP inhibitor. Healthy adults were randomized 6:2 to DS-1211 or placebo, eight subjects per dose cohort. SAD study subjects received one dose of DS-1211 (range, 3-3000 mg) or placebo, whereas MAD study subjects received DS-1211 (range, 10-300 mg) once daily, 150 mg twice daily (b.i.d.), or placebo for 10 days. Primary end points were safety and tolerability. PK and PD assessments included plasma concentrations of DS-1211, alkaline phosphatase (ALP) activity, and TNAP substrates (PPi, pyridoxal 5'-phosphate [PLP], and phosphoethanolamine [PEA]). A total of 56 (DS-1211: n = 42; placebo: n = 14) and 40 (DS-1211: n = 30; placebo: n = 10) subjects enrolled in the SAD and MAD studies, respectively. In both studies, adverse events were mild or moderate and did not increase with dose. PKs of DS-1211 were linear up to 100 mg administered as a single dose and 150 mg b.i.d. administered as a multiple-dose regimen. In multiple dosing, there was minimal accumulation of DS-1211. Increased DS-1211 exposure correlated with dose-dependent ALP inhibition and concomitant increases in PPi, PLP, and PEA. In two phase I studies, DS-1211 appeared safe and well-tolerated. Post-treatment PD assessments were consistent with exposure-dependent TNAP inhibition. These data support further evaluation of DS-1211 for ectopic calcification diseases.

Randomized controlled trials (RCTs) remain the gold standard to evaluate clinical interventions, producing the highest level of evidence while minimizing potential bias. Inadequate recruitment is a commonly encountered problem that undermines the completion and generalizability of RCTs-and is even more challenging when enrolling amidst a pandemic. Here, we reflect on our experiences with virtual recruitment of non-hospitalized patients in the United States for ColCorona, an international, multicenter, randomized, placebo-controlled coronavirus disease 2019 (COVID-19) drug trial. Recruitment challenges during a pandemic include constraints created by shelter-in-place policies and targeting enrollment according to national and local fluctuations in infection rate. Presenting a study to potential participants who are sick with COVID-19 and may be frightened, overwhelmed, or mistrusting of clinical research remains a challenge. Strategies previously reported to improve recruitment include transparency, patient and site education, financial incentives, and person-to-person outreach. Active measures taken during ColCorona to optimize United States recruitment involved rapid expansion of sites, adjustment of recruitment scripts, assessing telephone calls versus text messages for initial contact with participants, institutional review board-approved financial compensation, creating an infrastructure to systematically identify potentially eligible patients, partnering with testing sites, appealing to both self-interest and altruism, and large-scale media efforts with varying degrees of success.

Recently, we reported the phase II portion of the adaptive phase II/III PANAMO trial exploring potential benefit and safety of selectively blocking C5a with the monoclonal antibody vilobelimab (IFX-1) in patients with severe coronavirus disease 2019 (COVID-19). The potent anaphylatoxin C5a attracts neutrophils and monocytes to the infection site, causes tissue damage by oxidative radical formation and enzyme releases, and leads to activation of the coagulation system. Results demonstrated that C5a inhibition with vilobelimab was safe and secondary outcomes appeared in favor of vilobelimab. We now report the pharmacokinetic/pharmacodynamic (PK/PD) analysis of the phase II study. Between March 31 and April 24, 2020, 30 patients with severe COVID-19 pneumonia confirmed by real-time polymerase chain reaction were randomly assigned 1:1 to receive vilobelimab plus best supportive care or best supportive care only. Samples for measurement of vilobelimab, C3a and C5a blood concentrations were taken. Vilobelimab predose (trough) drug concentrations in plasma ranged from 84,846 to 248,592 ng/ml (571 to 1674 nM) with a geometric mean of 151,702 ng/ml (1022 nM) on day 2 and from 80,060 to 200,746 ng/ml (539 to 1352 nM) with a geometric mean of 139,503 ng/ml (939 nM) on day 8. After the first vilobelimab infusion, C5a concentrations were suppressed in the vilobelimab group (median 39.70 ng/ml 4.8 nM, IQR 33.20-45.55) as compared to the control group (median 158.53 ng/ml 19.1 nM, IQR 60.03-200.89, p = 0.0006). The suppression was maintained on day 8 (p = 0.001). The current PK/PD analysis shows that vilobelimab efficiently inhibits C5a in patients with severe COVID-19.

Rivaroxaban is an oral anticoagulant that inhibits thrombin and blocks coagulation cascade through directly inactivating factors Xa. Despite rivaroxaban is widely used for prevention and treatment of venous thrombosis, and its common adverse reactions have been reported, including abnormal coagulation, mucosal hemorrhage, hematuria, and intracranial hemorrhage. To explore potential drivers of individual differences in adverse reactions induced by rivaroxaban, we performed whole-exome sequencing and found that AKR7A3 rs1738023/rs1738025 and ABCA6 rs7212506 are susceptible sites for rivaroxaban-related bleeding in aged patients treated with rivaroxaban. Gene functional annotation and signaling pathway enrichment indicated that homozygous mutations in AKR7A3 and ABCA6 might alter normal rivaroxaban transport and metabolism, and lead to continuous accumulation of activated drugs and toxic substances in vivo. Our results suggested that interindividual differences in bleeding events induced by rivaroxaban may be potentially driven by genetic alterations related to abnormal metabolism and transport of rivaroxaban.

Large, observational genetic studies are commonly used to identify genetic factors associated with diseases and disease-related traits. Such cohorts have not been commonly used to identify genetic predictors of drug dosing or concentrations, perhaps because of the heterogeneity in drug dosing and formulation, and the random timing of blood sampling. We hypothesized that large sample sizes relative to traditional pharmacokinetic studies would compensate for this variability and enable the identification of pharmacogenetic predictors of drug concentrations. We performed a cross-sectional, proof-of-concept association study to replicate the well-established association between metoprolol concentrations and CYP2D6 genotype-inferred metabolizer phenotypes in participants from the Montreal Heart Institute Hospital Cohort undergoing metoprolol therapy. Plasma concentrations of metoprolol and α-hydroxymetoprolol (α-OH-metoprolol) were measured in samples collected randomly regarding the previous metoprolol dose. A total of 999 individuals were included. The metoprolol daily dose ranged from 6.25 to 400 mg (mean 84.3 ± 57.1 mg). CYP2D6-inferred phenotype was significantly associated with both metoprolol and α-OH-metoprolol in unadjusted and adjusted models (all p < 10^-14 ). Models for metoprolol daily dose showed consistent results. Our study suggests that randomly drawn blood samples from biobanks can serve as a new approach to discover genetic associations related to drug concentrations and dosing, with potentially broader implications for genomewide association studies on the pharmacogenomics of drug metabolism.

Inflammatory bowel disease (IBD) is a chronic and relapsing disease with multiple underlying influences and notable heterogeneity among its clinical and response-to-treatment phenotypes. There is no cure for IBD, and none of the currently available therapies have demonstrated clinical efficacies beyond 40%-60%. Data collected about its omics, pathogenesis, and treatment strategies have grown exponentially with time making IBD a prime candidate for artificial intelligence (AI) mediated discovery support. AI can be leveraged to further understand or identify IBD features to improve clinical outcomes. Various treatment candidates are currently under evaluation in clinical trials, offering further approaches and opportunities for increasing the efficacies of treatments. However, currently, therapeutic plans are largely determined using clinical features due to the lack of specific biomarkers, and it has become necessary to step into precision medicine to predict therapeutic responses to guarantee optimal treatment efficacy. This is accompanied by the application of AI and the development of multiscale hybrid models combining mechanistic approaches and machine learning. These models ultimately lead to the creation of digital twins of given patients delivering on the promise of precision dosing and tailored treatment. Interleukin-6 (IL-6) is a prominent cytokine in cell-to-cell communication in the inflammatory responses' regulation. Dysregulated IL-6-induced signaling leads to severe immunological or proliferative pathologies, such as IBD and colon cancer. This mini-review explores multiscale models with the aim of predicting the response to therapy in IBD. Modeling IL-6 biology and generating digital twins enhance the credibility of their prediction.