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Abstract We report a unique growth of platelet-shaped nanoscale tips of transparent dielectric using femtosecond laser radiation at MHz pulse repetition rate with nitrogen background gas flow under ambient condition. The tips grew with sharp nanoscale apex while their base and lengths are of the order of few hundred nanometers. In the absence of nitrogen, the irradiation leads to nanofibrous structure formation. The collision between the nitrogen gas atoms and the vapor species slows down plume expansion and lead to an increase of nanoparticles size. This prevents the fibrous structure formation and provides appropriate condition for nanoscale tips growth.

Abstract We report the unique growth of nanofibers in silica and borosilicate glass using femtosecond laser radiation at 8 MHz repetition rate and a pulse width of 214 fs in air at atmospheric pressure. The nanofibers are grown perpendicular to the substrate surface from the molten material in laser-drilled microvias where they intertwine and bundle up above the surface. The fibers are few tens of nanometers in thickness and up to several millimeters in length. Further, it is found that at some places nanoparticles are attached to the fiber surface along its length. Nanofiber growth is explained by the process of nanojets formed in the molten liquid due to pressure gradient induced from the laser pulses and subsequently drawn into fibers by the intense plasma pressure. The attachment of nanoparticles is due to the condensation of vapor in the plasma.

In this study the composition of nanostructures generated owing to ablation of crystalline silicon using high repletion rate femtosecond laser under ambient condition is investigated. The web-like silicon fibrous nanostructures are formed in and around the laser irradiated area. Electron Microscopy investigation revealed that the nanostructures are made of nanoparticles of size about 40 nm. In addition Micro-Raman analysis shows that the nanofibrous structures comprises a mixture of amorphous and polycrystalline silicon. X-ray photoelectron spectroscopy analysis reveals the oxidized and un-oxidized elemental states of silicon in the nanostructures. Moreover web-like fibrous nanostructures are generated due to condensation of super saturated vapour and subsequent nucleus growth in the laser induced plasma plume.

The current study was attempted to investigate the effect of melanogenesis and the mechanism behind both hypo and hyperpigmentation by oxidized and non-oxidized Piper betle extracts and on B16F1 melanoma cells. Supplementation with oxidized or non-oxidized Piper betle extracts did not show any significant cytotoxicity (90 % intact cells) in B16F1 melanoma cells. However, the activity of tyrosinase and the levels of lipid peroxidation product (thiobarbituric acid reactive substances), and melanin secretion was significantly decreased with improved antioxidant status after 48 h of incubation with increasing dose (25/35/50 µg/ml) of non-oxidized Piper betle extract in B16F1 melanoma cells. However, slightly decreased antioxidant status with increased melanin content was observed at 72 h (Piper betle extract). The above results indicated that as the duration increased the effect of non-oxidized Piper betle extract on melanin synthesis started to decline. In addition, when oxidized Piper betle extract (35/50 µg/ml) was incubated with B16F1 cells hyperpigmentation was noted within 48 h by enhancing the levels of thiobarbituric acid reactive substances (35 %) and melanin secretion as well as tyrosinase activity (max at 72 h) with lowered tyrosinase inhibitory activity. Taking together that oxidized Piper betle extract might be the reason for the hyperpigmentation and might contribute to various dermal disorders and thus non-oxidized Piper betle extract to be recommended for treating various dermal disorders. [ABSTRACT FROM AUTHOR]

A modification of phase-shifting interferometry is proposed for microsurface profiling of flat surfaces under vibrating conditions. With this technique the required phase shift, achieved by quarter-wave plates and polarizers, is free of errors associated with motion. A nearly common optical-path configuration is achieved, and the effect of environment is reduced. The effect of environment on the optical system is also studied. Moreover, the measurement of phase is instantaneous, which increases the versatility of this technique to measure vibrating objects. Experiments were carried out on a smooth mirror surface excited with high-frequency vibrations, and the technique was found to be immune to vibrations of both high and low frequency. OCIS codes: 120.4570, 120.5050.

Aldehyde oxidase (AO) contributes to the clearance of many approved and investigational small molecule drugs, which are often dual substrates of AO and drug-metabolizing enzymes such as cytochrome P450s (CYPs). As such, the lack of established framework for quantitative translation of the clinical pharmacologic correlates of AO-mediated clearance represents an unmet need. This study aimed to evaluate the utility of physiologically based pharmacokinetic (PBPK) modeling in the development of AO and dual AO-CYP substrates. PBPK models were developed for capmatinib, idelalisib, lenvatinib, zaleplon, ziprasidone, and zoniporide, incorporating in vitro functional data from human liver subcellular fractions and human hepatocytes. Prediction of metabolic elimination with/without the additional empirical scaling factors (ESFs) was assessed. Clinical pharmacokinetics, human mass balance, and drug-drug interaction (DDI) studies with CYP3A4 modulators, where available, were used to refine/verify the models. Due to the lack of clinically significant AO-DDIs with known AO inhibitors, the fraction metabolized by AO (fm AO ) was verified indirectly. Clearance predictions were improved by using ESFs (GMFE ≤1.4-fold versus up to fivefold with physiologically-based scaling only). Observed fm i from mass balance studies were crucial for model verification/refinement, as illustrated by capmatinib, where the fm AO (40%) was otherwise underpredicted up to fourfold. Subsequently, independent DDI studies with ketoconazole, itraconazole, rifampicin, and carbamazepine verified the fm CYP3A4 , with predicted ratios of the area under the concentration-time curve (AUCR) within 1.5-fold of the observations. In conclusion, this study provides a novel PBPK-based framework for predicting AO-mediated pharmacokinetics and quantitative assessment of clinical DDI risks for dual AO-CYP substrates within a totality-of-evidence approach., (© 2024 The Author(s). CPT: Pharmacometrics & Systems Pharmacology published by Wiley Periodicals LLC on behalf of American Society for Clinical Pharmacology and Therapeutics.)

With the International Conference on Harmonization of Technical Requirements for Pharmaceuticals for Human Use (ICH) E17 guidelines in effect from 2018, the design of Asia-inclusive multiregional clinical trials (MRCTs) has been streamlined, thereby enabling efficient simultaneous global development. Furthermore, with the recent regulatory reforms in China and its drug administration joining the ICH as a full regulatory member, early participation of China in the global clinical development of novel investigational drugs is now feasible. This would also allow for inclusion of the region in the geographic footprint of pivotal MRCTs leveraging principles of the ICH E5 and E17. Herein, we describe recent case examples of model-informed Asia-inclusive global clinical development in the EMD Serono portfolio, as applied to the ataxia telangiectasia and Rad3-related inhibitors, tuvusertib and berzosertib (oncology), the toll-like receptor 7/8 antagonist, enpatoran (autoimmune diseases), the mesenchymal-epithelial transition factor inhibitor tepotinib (oncology), and the antimetabolite cladribine (neuroimmunological disease). Through these case studies, we illustrate pragmatic approaches to ethnic sensitivity assessments and the application of a model-informed drug development toolkit including population pharmacokinetic/pharmacodynamic modeling and pharmacometric disease progression modeling and simulation to enable early conduct of Asia-inclusive MRCTs. These examples demonstrate the value of a Totality of Evidence approach where every patient's data matter for de-risking ethnic sensitivity to inter-population variations in drug- and disease-related intrinsic and extrinsic factors, enabling inclusive global development strategies and timely evidence generation for characterizing benefit/risk of the proposed dosage in Asian populations., (© 2024 The Author(s). Clinical and Translational Science published by Wiley Periodicals LLC on behalf of American Society for Clinical Pharmacology and Therapeutics.)

Tepotinib is approved for the treatment of patients with non-small-cell lung cancer harboring MET exon 14 skipping alterations. While edema is the most prevalent adverse event (AE) and a known class effect of MET inhibitors including tepotinib, there is still limited understanding about the factors contributing to its occurrence. Herein, we apply machine learning (ML)-based approaches to predict the likelihood of occurrence of edema in patients undergoing tepotinib treatment, and to identify factors influencing its development over time. Data from 612 patients receiving tepotinib in five Phase I/II studies were modeled with two ML algorithms, Random Forest, and Gradient Boosting Trees, to predict edema AE incidence and severity. Probability calibration was applied to give a realistic estimation of the likelihood of edema AE. Best model was tested on follow-up data and on data from clinical studies unused while training. Results showed high performances across all the tested settings, with F1 scores up to 0.961 when retraining the model with the most relevant covariates. The use of ML explainability methods identified serum albumin as the most informative longitudinal covariate, and higher age as associated with higher probabilities of more severe edema. The developed methodological framework enables the use of ML algorithms for analyzing clinical safety data and exploiting longitudinal information through various covariate engineering approaches. Probability calibration ensures the accurate estimation of the likelihood of the AE occurrence, while explainability tools can identify factors contributing to model predictions, hence supporting population and individual patient-level interpretation., (© 2024 The Author(s). Clinical and Translational Science published by Wiley Periodicals LLC on behalf of American Society for Clinical Pharmacology and Therapeutics.)

Background: The aim of this study was to evaluate the association between early postpartum weight change and (1) hospital readmission and (2) 2-week blood pressure trajectory., Methods and Results: This retrospective study cohort included 1365 individuals with a hypertensive disorder of pregnancy enrolled in a postpartum hypertension remote monitoring program. Exposure was percentage weight change from delivery to first weight recorded within 10 days postpartum. We first modeled likelihood of hospital readmission within 8 weeks postpartum using logistic regression adjusting for age, race, insurance, type of hypertensive disorder of pregnancy, early body mass index, gestational weight gain, mode of delivery, and any discharge antihypertensive medications. We then performed case-control analysis additionally matching in a 1:3 ratio on breastfeeding, early body mass index, discharge on antihypertensive medications, and days between weight measurements. Both analytic approaches were repeated, limiting to readmissions attributable to hypertension or heart failure. Finally, we compared blood pressure trajectories over first 2 weeks postpartum. Individuals who did not lose weight in the early postpartum period had more admissions compared with weight loss groups (group 3: 14.1% versus group 2: 5.8% versus group 1: 4.5%). These individuals had 4 times the odds of postpartum readmissions (adjusted odds ratio [aOR], 3.9 [95% CI, 1.8-8.6]) to 7 (aOR, 7.8 [95% CI, 2.3-26.5]) compared with those with the most weight loss. This association strengthened when limited to hypertension or heart failure readmissions. These individuals also had more adverse postpartum blood pressure trajectories, with significant differences by weight change group., Conclusions: Weight change is readily accessible and may identify individuals at high risk for postpartum readmission following a hypertensive disorder of pregnancy who could benefit from targeted interventions.

Project Optimus is a US Food and Drug Administration Oncology Center of Excellence initiative aimed at reforming the dose selection and optimization paradigm in oncology drug development. This project seeks to bring together pharmaceutical companies, international regulatory agencies, academic institutions, patient advocates, and other stakeholders. Although there is much promise in this initiative, there are several challenges that need to be addressed, including multidimensionality of the dose optimization problem in oncology, the heterogeneity of cancer and patients, importance of evaluating long-term tolerability beyond dose-limiting toxicities, and the lack of reliable biomarkers for long-term efficacy. Through the lens of Totality of Evidence and with the mindset of model-informed drug development, we offer insights into dose optimization by building a quantitative knowledge base integrating diverse sources of data and leveraging quantitative modeling tools to build evidence for drug dosage considering exposure, disease biology, efficacy, toxicity, and patient factors. We believe that rational dose optimization can be achieved in oncology drug development, improving patient outcomes by maximizing therapeutic benefit while minimizing toxicity., (© 2023 Emd Serono Research and Development Institute, Inc. Pfizer Inc and The Authors. CPT: Pharmacometrics & Systems Pharmacology published by Wiley Periodicals LLC on behalf of American Society for Clinical Pharmacology and Therapeutics. This article has been contributed to by U.S. Government employees and their work is in the public domain in the USA.)

Brigatinib is an oral anaplastic lymphoma kinase (ALK) inhibitor approved for the treatment of ALK-positive metastatic non-small cell lung cancer. In vitro studies indicated that brigatinib is primarily metabolized by CYP2C8 and CYP3A4 and inhibits P-gp, BCRP, OCT1, MATE1, and MATE2K. Clinical drug-drug interaction (DDI) studies with the strong CYP3A inhibitor itraconazole or the strong CYP3A inducer rifampin demonstrated that CYP3A-mediated metabolism was the primary contributor to overall brigatinib clearance in humans. A physiologically-based pharmacokinetic (PBPK) model for brigatinib was developed to predict potential DDIs, including the effect of moderate CYP3A inhibitors or inducers on brigatinib pharmacokinetics (PK) and the effect of brigatinib on the PK of transporter substrates. The developed model was able to predict clinical DDIs with itraconazole (area under the plasma concentration-time curve from time 0 to infinity [AUC ∞ ] ratio [with/without itraconazole]: predicted 1.86; observed 2.01) and rifampin (AUC ∞ ratio [with/without rifampin]: predicted 0.16; observed 0.20). Simulations using the developed model predicted that moderate CYP3A inhibitors (e.g., verapamil and diltiazem) may increase brigatinib AUC ∞ by ~40%, whereas moderate CYP3A inducers (e.g., efavirenz) may decrease brigatinib AUC ∞ by ~50%. Simulations of potential transporter-mediated DDIs predicted that brigatinib may increase systemic exposures (AUC ∞ ) of P-gp substrates (e.g., digoxin and dabigatran) by 15%-43% and MATE1 substrates (e.g., metformin) by up to 29%; however, negligible effects were predicted on BCRP-mediated efflux and OCT1-mediated uptake. The PBPK analysis results informed dosing recommendations for patients receiving moderate CYP3A inhibitors (40% brigatinib dose reduction) or inducers (up to 100% increase in brigatinib dose) during treatment, as reflected in the brigatinib prescribing information., (© 2024 Takeda Pharmaceuticals. CPT: Pharmacometrics & Systems Pharmacology published by Wiley Periodicals LLC on behalf of American Society for Clinical Pharmacology and Therapeutics.)

Like other monoclonal antibodies, immune checkpoint inhibitors may be immunogenic in some patients, potentially affecting pharmacokinetics (PKs) and clinical outcomes. In post hoc analyses, we characterized antidrug antibody (ADA) development with avelumab monotherapy in patients with metastatic Merkel cell carcinoma (mMCC) from the JAVELIN Merkel 200 trial (first-line [1L; N = 116] and second-line or later [≥2L; N = 88] cohorts) or with advanced urothelial carcinoma (aUC) from the JAVELIN Bladder 100 (1L maintenance [N = 350]) and JAVELIN Solid Tumor (≥2L [N = 249]) trials. Treatment-emergent ADAs developed in a numerically higher proportion of patients with aUC (1L maintenance, 19.1%; ≥2L, 18.1%) versus mMCC (1L, 8.2%; ≥2L, 8.9%); incidences within tumor types were similar by line of therapy. In PK analyses, numerically lower avelumab trough concentration and higher baseline clearance were observed in treatment-emergent ADA+ versus ADA- subgroups; however, differences were not clinically relevant. Numerical differences in overall survival, progression-free survival, or objective response rate by ADA status were observed; however, no clinically meaningful trends were identified. Proportions of patients with treatment-emergent adverse events (TEAEs; any grade or grade 3/4), serious TEAEs, TEAEs leading to treatment discontinuation, or infusion-related reactions were similar, with overlapping 80% confidence intervals between ADA subgroups. Efficacy and safety observations were similar in subgroups defined by early development of ADA+ status during treatment. In conclusion, no meaningful differences in PKs, efficacy, and safety were observed between subgroups of avelumab-treated patients with different ADA status. Overall, these data suggest that ADAs are not relevant for treatment decisions with avelumab., (© 2024 The Authors. Clinical and Translational Science published by Wiley Periodicals LLC on behalf of American Society for Clinical Pharmacology and Therapeutics.)

Several investigational agents are under evaluation in systemic lupus erythematosus (SLE) clinical trials but quantitative frameworks to enable comparison of their efficacy to reference benchmark treatments are lacking. To benchmark SLE treatment effects and identify clinically important covariates, we developed a model-based meta-analysis (MBMA) within a latent variable model framework for efficacy end points and SLE composite end point scores (BILAG-based Composite Lupus Assessment and Systemic Lupus Erythematosus Responder Index) using aggregate-level data on approved and investigational therapeutics. SLE trials were searched using PubMed and www.clinicaltrials.gov for treatment name, SLE and clinical trial as search criteria that resulted in four data structures: (1) study and investigational agent, (2) dose and regimen, (3) baseline descriptors, and (4) outcomes. The final dataset consisted of 25 studies and 81 treatment arms evaluating 16 different agents. A previously developed (K Goteti et al. 2022) SLE latent variable model of data from placebo arms (placebo + standard of care treatments) was used to describe aggregate SLE end points over time for the various SLE placebo and treatment arms in a Bayesian MBMA framework. Continuous dose-effect relationships using a maximum effect model were included for anifrolumab, belimumab, CC-220 (iberdomide), epratuzumab, lulizumab pegol, and sifalimumab, whereas the remaining treatments were modeled as discrete dose effects. The final MBMA model was then used to benchmark these compounds with respect to the maximal efficacy on the latent variable compared to the placebo. This MBMA illustrates the application of latent variable models in understanding the trajectories of composite end points in chronic diseases and should enable model-informed development of new investigational agents in SLE., (© 2023 EMD Serono Inc. CPT: Pharmacometrics & Systems Pharmacology published by Wiley Periodicals LLC on behalf of American Society for Clinical Pharmacology and Therapeutics.)

This analysis aimed to quantify tumor dynamics in patients receiving either bintrafusp alfa (BA) or pembrolizumab, by population pharmacokinetic (PK)-pharmacodynamic modeling, and investigate clinical and molecular covariates describing the variability in tumor dynamics by pharmacometric and machine-learning (ML) approaches. Data originated from two clinical trials in patients with biliary tract cancer (BTC; NCT03833661) receiving BA and non-small cell lung cancer (NSCLC; NCT03631706) receiving BA or pembrolizumab. Individual drug exposure was estimated from previously developed population PK models. Population tumor dynamics models were developed for each drug-indication combination, and covariate evaluations performed using nonlinear mixed-effects modeling (NLME) and ML (elastic net and random forest models) approaches. The three tumor dynamics' model structures all included linear tumor growth components and exponential tumor shrinkage. The final BTC model included the effect of drug exposure (area under the curve) and several covariates (demographics, disease-related, and genetic mutations). Drug exposure was not significant in either of the NSCLC models, which included two, disease-related, covariates in the BA arm, and none in the pembrolizumab arm. The covariates identified by univariable NLME and ML highly overlapped in BTC but showed less agreement in NSCLC analyses. Hyperprogression could be identified by higher tumor growth and lower tumor kill rates and could not be related to BA exposure. Tumor size over time was quantitatively characterized in two tumor types and under two treatments. Factors potentially related to tumor dynamics were assessed using NLME and ML approaches; however, their net impact on tumor size was considered as not clinically relevant., (© 2023 Merck KGaA and The Authors. CPT: Pharmacometrics & Systems Pharmacology published by Wiley Periodicals LLC on behalf of American Society for Clinical Pharmacology and Therapeutics.)

Metastatic lung cancers are considered one of the most clinically significant malignancies, comprising about 40% of deaths caused by cancers. Detection of lung cancer metastasis prior to symptomatic relapse is critical for timely diagnosis and clinical management. The onset of cancer metastasis is indicated by the manifestation of tumor-shed signatures from the primary tumor in peripheral circulation. A subset of this population, characterized as the metastasis-initiating stem cells, are capable of invasion, tumor initiation, and propagation of metastasis at distant sites. In this study, we have developed a SERS-functionalised L-MISC (Lung-Metastasis Initiating Stem Cells) nanosensor to accurately capture the trace levels of metastatic signatures directly from patient blood. We investigated the signatures of cancer stem cell enriched heterogenous population of primary and metastatic lung cancer cells to establish a metastatic profile unique to lung cancer. Multivariate statistical analyses revealed statistically significant differences in the molecular profiles of healthy, primary, and metastatic cell populations. The single-cell sensitivity of L-MISC nanosensor enabled a label-free detection of MISCs with high sensitivity and specificity. By employing a robust machine learning model, our diagnostic methodology can accurately detect metastatic lung cancer from not more than 5 μl of blood. A pilot validation of our study was carried out using clinical samples for the prediction of metastatic lung cancers resulting in 100% diagnostic sensitivity. The L-MISC nanosensor is a potential tool for highly rapid, non-invasive, and accurate diagnosis of lung cancer metastasis., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2023 Elsevier B.V. All rights reserved.)

Purpose: The effectiveness of a dexamethasone (DEX)-free regimen for chemotherapy-induced nausea and vomiting (CINV) prophylaxis in patients receiving highly emetogenic chemotherapy (HEC) is not known., Methods: This was a double-blind, phase III trial designed to show the noninferiority of a DEX-free regimen (olanzapine, palonosetron, and fosaprepitant [OPF]) compared with the DEX-containing regimen (olanzapine, palonosetron, and DEX [OPD]). Chemotherapy-naïve patients age 18-80 years receiving single-day HEC were randomly assigned 1:1 to receive either the OPD regimen or the OPF regimen. The primary objective was to compare complete response (CR) rates for vomiting during the overall period (start of chemotherapy to 120 hours). Secondary objectives included CR for vomiting during the acute period (0-24 hours) and delayed period (24-120 hours), CR for nausea, and comparison of toxicities and patient-reported outcomes., Results: Three hundred forty-six patients received the study interventions, 174 in the OPD arm and 172 in the OPF arm. The DEX-free OPF arm had significantly higher CR rates for vomiting compared with the DEX-containing OPD arm in acute (94.7% v 85.6%; P < .004), delayed (81.9% v 50.5%; P < .001), and overall (79.6% v 48.8%; P < .001) periods. For nausea, CR rates in the OPF arm were higher in delayed (53.4% v 39.6%; P = .009) and overall (50.5% v 39.1%; P = .031) periods but not in the acute period (77.9% v 81.6%; P = .39). Fatigue ( P = .009) and drowsiness ( P = .002) were more in the OPF arm in the acute period and insomnia ( P < .001) in the OPD arm in the overall period., Conclusion: This study shows that a DEX-free OPF regimen is efficacious and should be considered a standard option for acute and delayed CINV prophylaxis for HEC.