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Zolbetuximab (VYLOY™), a recombinant, chimeric, anti-claudin 18.2 (CLDN18.2) monoclonal antibody (mAb), is being developed by Astellas Pharma Inc. for the treatment of patients with HER2-negative (HER2-), CLDN18.2-positive (CLDN18.2+) advanced gastric or gastroesophageal junction (GEJ) adenocarcinoma and CLDN18.2+ advanced pancreatic adenocarcinoma. In March 2024, zolbetuximab was approved in Japan for the treatment of patients with HER2-, CLDN18.2+ unresectable, advanced/recurrent gastric cancer (the gastric cancer indication includes GEJ cancer). Zolbetuximab is also undergoing regulatory review for HER2-, CLDN18.2+ advanced gastric or GEJ adenocarcinoma in the USA, the EU, China, Australia and several other countries. This article summarizes the milestones in the development of zolbetuximab leading to this first approval for the treatment of patients with CLDN18.2+ gastrointestinal malignancies. [ABSTRACT FROM AUTHOR]

Allergies are one of the diseases whose incidence rates have increased in recent years due to the greenhouse effect and extreme climate change. Therefore, the development of new antiallergic drugs has attracted the interest of researchers in chemistry and pharmacy fields. Dicoumarin is a coumarin derivative with various biological activities, but its antiallergic activity has not been evaluated. In this study, 14 different dicoumarin derivatives were synthesized by diethylamine-catalyzed condensation reactions of 4-hydroxycoumarin with 14 different aldehydes, and they were identified on the basis of their spectral data. The dicoumarin derivatives were subjected to studies on the degranulation of rat basophilic leukemia cells (RBL-2H3 cells) and mouse bone-marrow-derived mast cells (mBMMCs), and some of them showed good inhibitory effects on the degranulation of the two types of mast cells, demonstrating their good antiallergic activity. This study presents a new method of developing new antiallergic drugs. [ABSTRACT FROM AUTHOR]

Simple Summary: Cancer can create a shield of suppressive innate immune cells that stop our body's natural defenses from tumors. VTX-0811 is a new drug that targets these cells and turns them from allies of cancer to fighters against it. Preclinical tests show that it works in the lab on human cells and tumors and is safe and efficacious in animals. The results are promising and pave the way for human trials to see if VTX-0811 can become a new powerful weapon against cancer. Omnipresent suppressive myeloid populations in the tumor microenvironment limit the efficacy of T-cell-directed immunotherapies, become more inhibitory after administration of T-cell checkpoint inhibitors, and are overall associated with worse survival of cancer patients. In early clinical trials, positive outcomes have been demonstrated for therapies aimed at repolarizing suppressive myeloid populations in the tumor microenvironment. We have previously described the key role of P-selectin glycoprotein ligand-1 (PSGL-1) in maintaining an inhibitory state of tumor-associated macrophages (TAMs), most of which express high levels of PSGL-1. Here we describe a novel, first-in-class humanized high-affinity monoclonal antibody VTX-0811 that repolarizes human macrophages from an M2-suppressive phenotype towards an M1 inflammatory phenotype, similar to siRNA-mediated knockdown of PSGL-1. VTX-0811 binds to PSGL-1 of human and cynomolgus macaque origins without inhibiting PSGL-1 interaction with P- and L-Selectins or VISTA. In multi-cellular assays and in patient-derived human tumor cultures, VTX-0811 leads to the induction of pro-inflammatory mediators. RNAseq data from VTX-0811 treated ex vivo tumor cultures and M2c macrophages show similar pathways being modulated, indicating that the mechanism of action translates from isolated macrophages to tumors. A chimeric version of VTX-0811, consisting of the parental murine antibody in a human IgG4 backbone, inhibits tumor growth in a humanized mouse model of cancer. VTX-0811 is exceptionally well tolerated in NHP toxicology assessment and is heading into clinical evaluation after successful IND clearance. [ABSTRACT FROM AUTHOR]

The US FDA's Project Optimus initiative that emphasizes dose optimization prior to marketing approval represents a pivotal shift in oncology drug development. It has a ripple effect for rethinking what changes may be made to conventional pivotal trial designs to incorporate a dose optimization component. Aligned with this initiative, we propose a novel seamless phase II/III design with dose optimization (SDDO framework). The proposed design starts with dose optimization in a randomized setting, leading to an interim analysis focused on optimal dose selection, trial continuation decisions, and sample size re‐estimation (SSR). Based on the decision at interim analysis, patient enrollment continues for both the selected dose arm and control arm, and the significance of treatment effects will be determined at final analysis. The SDDO framework offers increased flexibility and cost‐efficiency through sample size adjustment, while stringently controlling the Type I error. This proposed design also facilitates both accelerated approval (AA) and regular approval in a "one‐trial" approach. Extensive simulation studies confirm that our design reliably identifies the optimal dosage and makes preferable decisions with a reduced sample size while retaining statistical power. [ABSTRACT FROM AUTHOR]

The aging process contributes significantly to the onset of chronic diseases, which are the primary causes of global mortality, morbidity, and healthcare costs. Numerous studies have shown that the removal of senescent cells from tissues extends lifespan and reduces the occurrence of age-related diseases. Consequently, there is growing momentum in the development of drugs targeting these cells. Among them, mTOR and SGLT-2 inhibitors have garnered attention due to their diverse effects: mTOR inhibitors regulate cellular growth, metabolism, and immune responses, while SGLT-2 inhibitors regulate glucose reabsorption in the kidneys, resulting in various beneficial metabolic effects. Importantly, these drugs may act synergistically by influencing senescence processes and pathways. Although direct studies on the combined effects of mTOR inhibition and SGLT-2 inhibition on age-related processes are limited, this review aims to highlight the potential synergistic benefits of these drugs in targeting senescence. [ABSTRACT FROM AUTHOR]

The intricate interplay between cellular senescence and alterations in the gut microbiome emerges as a pivotal axis in the aging process, increasingly recognized for its contribution to systemic inflammation, physiological decline, and predisposition to age‐associated diseases. Cellular senescence, characterized by a cessation of cell division in response to various stressors, induces morphological and functional changes within tissues. The complexity and heterogeneity of senescent cells, alongside the secretion of senescence‐associated secretory phenotype, exacerbate the aging process through pro‐inflammatory pathways and influence the microenvironment and immune system. Concurrently, aging‐associated changes in gut microbiome diversity and composition contribute to dysbiosis, further exacerbating systemic inflammation and undermining the integrity of various bodily functions. This review encapsulates the burgeoning research on the reciprocal relationship between cellular senescence and gut dysbiosis, highlighting their collective impact on age‐related musculoskeletal diseases, including osteoporosis, sarcopenia, and osteoarthritis. It also explores the potential of modulating the gut microbiome and targeting cellular senescence as innovative strategies for healthy aging and mitigating the progression of aging‐related conditions. By exploring targeted interventions, including the development of senotherapeutic drugs and probiotic therapies, this review aims to shed light on novel therapeutic avenues. These strategies leverage the connection between cellular senescence and gut microbiome alterations to advance aging research and development of interventions aimed at extending health span and improving the quality of life in the older population. [ABSTRACT FROM AUTHOR]

Tools to evaluate and accelerate tuberculosis (TB) vaccine development are needed to advance global TB control strategies. Validated human infection studies for TB have the potential to facilitate breakthroughs in understanding disease pathogenesis, identify correlates of protection, develop diagnostic tools, and accelerate and de-risk vaccine and drug development. However, key challenges remain for realizing the clinical utility of these models, which require further discussion and alignment among key stakeholders. In March 2023, the Wellcome Trust and the International AIDS Vaccine Initiative convened international experts involved in developing both TB and bacillus Calmette-Guérin (BCG) human infection studies (including mucosal and intradermal challenge routes) to discuss the status of each of the models and the key enablers to move the field forward. This report provides a summary of the presentations and discussion from the meeting. Discussions identified key issues, including demonstrating model validity, to provide confidence for vaccine developers, which may be addressed through demonstration of known vaccine effects (eg, BCG vaccination in specific populations), and by comparing results from field efficacy and human infection studies. The workshop underscored the importance of establishing safe and acceptable studies in high-burden settings, and the need to validate >1 model to allow for different scientific questions to be addressed as well as to provide confidence to vaccine developers and regulators around use of human infection study data in vaccine development and licensure pathways. [ABSTRACT FROM AUTHOR]

Dose optimization is a critical challenge in drug development. Historically, dose determination in oncology has followed a divergent path from other non-oncology therapeutic areas due to the unique characteristics and requirements in Oncology. However, with the emergence of new drug modalities and mechanisms of drugs in oncology, such as immune therapies, radiopharmaceuticals, targeted therapies, cytostatic agents, and others, the dose-response relationship for efficacy and toxicity could be vastly varied compared to the cytotoxic chemotherapies. The doses below the MTD may demonstrate similar efficacy to the MTD with an improved tolerability profile, resembling what is commonly observed in non-oncology treatments. Hence, alternate strategies for dose optimization are required for new modalities in oncology drug development. This paper delves into the historical evolution of dose finding methods from non-oncology to oncology, highlighting examples and summarizing the underlying drivers of change. Subsequently, a practical framework and guidance are provided to illustrate how dose optimization can be incorporated into various stages of the development program. We provide the following general recommendations: 1) The objective for phase I is to identify a dose range rather than a single MTD dose for subsequent development to better characterize the safety and tolerability profile within the dose range. 2) At least two doses separable by PK are recommended for dose optimization in phase II. 3) Ideally, dose optimization should be performed before launching the confirmatory study. Nevertheless, innovative designs such as seamless II/III design can be implemented for dose selection and may accelerate the drug development program. [ABSTRACT FROM AUTHOR]

An efficient metal‐free DBU catalyzed approach for the construction of biologically significant quaternary carbon centered C‐3 functionalized 2‐oxindole derivatives through vinylogous reaction of 3‐cyano‐4‐methylcoumarins with 3‐arylsulfonyl‐3‐indolyloxindoles has been developed for first time. The developed protocol is simple, cost‐effective, and producing the desired products in good yields, without utilizing potentially harmful chemicals. Moreover, the synthesized 3,3‐disubstituted 2‐oxindole molecules contain established pharmacophors in their structure, i. e. oxindole‐, indole‐ and coumarin‐ moieties, which makes them a valuable candidate for drug development process. [ABSTRACT FROM AUTHOR]

The development of robust and reliable methods for the construction of C(sp2)−C(sp3) bonds is vital for accessing an increased array of structurally diverse scaffolds in drug discovery and development campaigns. While significant advances towards this goal have been achieved using metallaphotoredox chemistry, many of these methods utilise photocatalysts based on precious‐metals due to their efficient redox processes and tuneable properties. However, due to the cost, scarcity, and toxicity of these metals, the search for suitable replacements should be a priority. Here, we show the use of commercially available heterogeneous semiconductor graphitic carbon nitride (gCN) as a photocatalyst, combined with nickel catalysis, for the cross‐coupling between aryl halide and carboxylic acid coupling partners. gCN has been shown to engage in single‐electron‐transfer (SET) and energy‐transfer (EnT) processes for the formation of C−X bonds, and in this manuscript we overcome previous limitations to furnish C−C over C−O bonds using carboxylic acids. A broad scope of both aryl halides and carboxylic acids is presented, and recycling of the photocatalyst demonstrated. The mechanism of the reaction is also investigated. [ABSTRACT FROM AUTHOR]

The influenza virus (IFV) imposes a considerable health and economic burden globally, requiring a comprehensive understanding of its pathogenic mechanisms. Ferroptosis, an iron-dependent lipid peroxidation cell death pathway, holds unique implications for the antioxidant defense system, with possible contributions to inflammation. This exploration focuses on the dynamic interplay between ferroptosis and the host defense against viruses, emphasizing the influence of IFV infections on the activation of the ferroptosis pathway. IFV causes different types of cell death, including apoptosis, necrosis, and ferroptosis. IFV-induced ferroptotic cell death is mediated by alterations in iron homeostasis, intensifying the accumulation of reactive oxygen species and promoting lipid peroxidation. A comprehensive investigation into the mechanism of ferroptosis in viral infections, specifically IFV, has great potential to identify therapeutic strategies. This understanding may pave the way for the development of drugs using ferroptosis inhibitors, presenting an effective approach to suppress viral infections. [ABSTRACT FROM AUTHOR]

Viral infections usually induce the rearrangement of cellular cytoskeletal proteins and organelle membrane structures, thus creating independent compartments [termed replication organelles (ROs)] to facilitate viral genome replication. Within the ROs, viral replicases, including polymerases, helicases, and ligases, play functional roles during viral replication. These viral replicases are pivotal in the virus life cycle, and numerous studies have demonstrated that the viral replicases could be the potential targets for drugs development. Here, we summarize primarily the key replicases within viral ROs and emphasize the advancements of antiviral drugs targeting crucial viral replicases, providing novel insights into the future development of antiviral strategies. [ABSTRACT FROM AUTHOR]

Rationale: Idiopathic pulmonary fibrosis (IPF) is a rare and progressive disease that causes progressive cough, exertional dyspnea, impaired quality of life, and death. Objectives: Bexotegrast (PLN-74809) is an oral, once-daily, investigational drug in development for the treatment of IPF. Methods: This Phase-2a multicenter, clinical trial randomized participants with IPF to receive, orally and once daily, bexotegrast at 40 mg, 80 mg, 160 mg, or 320 mg, or placebo, with or without background IPF therapy (pirfenidone or nintedanib), in an approximately 3:1 ratio in each bexotegrast dose cohort, for at least 12 weeks. The primary endpoint was incidence of treatment-emergent adverse events (TEAEs). Exploratory efficacy endpoints included change from baseline in FVC, quantitative lung fibrosis (QLF) extent (%), and changes from baseline in fibrosis-related biomarkers. Measurements and Main Results: Bexotegrast was well tolerated, with similar rates of TEAEs in the pooled bexotegrast and placebo groups (62/89 [69.7%] and 21/31 [67.7%], respectively). Diarrhea was the most common TEAE; most participants with diarrhea also received nintedanib. Participants who were treated with bexotegrast experienced a reduction in FVC decline over 12 weeks compared with those who received placebo, with or without background therapy. A dose-dependent antifibrotic effect of bexotegrast was observed with QLF imaging, and a decrease in fibrosis-associated biomarkers was observed with bexotegrast versus placebo. Conclusions: Bexotegrast demonstrated a favorable safety and tolerability profile, up to 12 weeks for the doses studied. Exploratory analyses suggest an antifibrotic effect according to FVC, QLF imaging, and circulating levels of fibrosis biomarkers. Clinical trial registered with (NCT04396756). [ABSTRACT FROM AUTHOR]

ABSTRACT Dose‐finding studies play a crucial role in drug development by identifying the optimal dose(s) for later studies while considering tolerability. This not only saves time and effort in proceeding with Phase III trials but also improves efficacy. In an era of precision medicine, it is not ideal to assume patient homogeneity in dose‐finding studies as patients may respond differently to the drug. To address this, we propose a personalized dose‐finding algorithm that assigns patients to individualized optimal biological doses. Our design follows a two‐stage approach. Initially, patients are enrolled under broad eligibility criteria. Based on the Stage 1 data, we fit a regression model of toxicity and efficacy outcomes on dose and biomarkers to characterize treatment‐sensitive patients. In the second stage, we restrict the trial population to sensitive patients, apply a personalized dose allocation algorithm, and choose the recommended dose at the end of the trial. Simulation study shows that the proposed design reliably enriches the trial population, minimizes the number of failures, and yields superior operating characteristics compared to several existing dose‐finding designs in terms of both the percentage of correct selection and the number of patients treated at target dose(s). [ABSTRACT FROM AUTHOR]

Background: Conducting traditional wet experiments to guide drug development is an expensive, time-consuming and risky process. Analyzing drug function and repositioning plays a key role in identifying new therapeutic potential of approved drugs and discovering therapeutic approaches for untreated diseases. Exploring drug-disease associations has far-reaching implications for identifying disease pathogenesis and treatment. However, reliable detection of drug-disease relationships via traditional methods is costly and slow. Therefore, investigations into computational methods for predicting drug-disease associations are currently needed. Results: This paper presents a novel drug-disease association prediction method, RAFGAE. First, RAFGAE integrates known associations between diseases and drugs into a bipartite network. Second, RAFGAE designs the Re_GAT framework, which includes multilayer graph attention networks (GATs) and two residual networks. The multilayer GATs are utilized for learning the node embeddings, which is achieved by aggregating information from multihop neighbors. The two residual networks are used to alleviate the deep network oversmoothing problem, and an attention mechanism is introduced to combine the node embeddings from different attention layers. Third, two graph autoencoders (GAEs) with collaborative training are constructed to simulate label propagation to predict potential associations. On this basis, free multiscale adversarial training (FMAT) is introduced. FMAT enhances node feature quality through small gradient adversarial perturbation iterations, improving the prediction performance. Finally, tenfold cross-validations on two benchmark datasets show that RAFGAE outperforms current methods. In addition, case studies have confirmed that RAFGAE can detect novel drug-disease associations. Conclusions: The comprehensive experimental results validate the utility and accuracy of RAFGAE. We believe that this method may serve as an excellent predictor for identifying unobserved disease-drug associations. [ABSTRACT FROM AUTHOR]

As a class of biologically active molecules with significant immunomodulatory and anti-inflammatory effects, anti-inflammatory peptides have important application value in the medical and biotechnology fields due to their unique biological functions. Research on the identification of anti-inflammatory peptides provides important theoretical foundations and practical value for a deeper understanding of the biological mechanisms of inflammation and immune regulation, as well as for the development of new drugs and biotechnological applications. Therefore, it is necessary to develop more advanced computational models for identifying anti-inflammatory peptides. In this study, we propose a deep learning model named DAC-AIPs based on variational autoencoder and contrastive learning for accurate identification of anti-inflammatory peptides. In the sequence encoding part, the incorporation of multi-hot encoding helps capture richer sequence information. The autoencoder, composed of convolutional layers and linear layers, can learn latent features and reconstruct features, with variational inference enhancing the representation capability of latent features. Additionally, the introduction of contrastive learning aims to improve the model's classification ability. Through cross-validation and independent dataset testing experiments, DAC-AIPs achieves superior performance compared to existing state-of-the-art models. In cross-validation, the classification accuracy of DAC-AIPs reached around 88%, which is 7% higher than previous models. Furthermore, various ablation experiments and interpretability experiments validate the effectiveness of DAC-AIPs. Finally, a user-friendly online predictor is designed to enhance the practicality of the model, and the server is freely accessible at http://dac-aips.online. [ABSTRACT FROM AUTHOR]

Abstract\nHIGHLIGHTSCardiovascular diseases (CVDs) cause 30% of deaths each year, and in 2030, around 23.6 million people will die due to CVDs. The major challenge is to obtain molecules with minimal adverse reactions that can prevent and dissolve blood clots. In this context, fibrinolytic enzymes from diverse microorganism sources have been extensively investigated due to their potential to act directly and specifically on the fibrin clot, preventing side effects and performing potential thrombolytic effects. However, most researches focus on the purification and characterization of proteases, with little emphasis on the mechanism of action and pharmacological characteristics, including toxicity assays which are essential to assess safety and side effects. Therefore, this work aims to emphasize the importance of evaluations indicating the toxicological profile of fibrinolytic proteases through in vitro and in vivo tests. Both types of assays contribute as preclinical stage in drug development and are crucial for clinical applications. This scarcity creates arbitrary barriers to further studies. This work should further encourage the development of studies to ensure the safety and effectivity of fibrinolytic proteases.Suggested pre-clinical trials aim to validate more specific methods for fibrinolytic enzymes;Current toxicity standards can be adapted to better assess the profile of fibrinolytic enzymes;The class of fibrinolytic enzymes must be carefully evaluated according to the method of application.Suggested pre-clinical trials aim to validate more specific methods for fibrinolytic enzymes;Current toxicity standards can be adapted to better assess the profile of fibrinolytic enzymes;The class of fibrinolytic enzymes must be carefully evaluated according to the method of application. [ABSTRACT FROM AUTHOR]

Introduced by the Hatch‐Waxman Amendments of 1984, 505(b)(2) applications permit the US Food and Drug Administration to rely, for approval of a new drug application, on information from studies not conducted by or for the applicant and for which the applicant has not obtained a right of reference. This pathway is designed to circumvent the unnecessary duplication of studies already conducted on a previously approved drug. It can lead to a considerably more efficient and expedited route to approval compared to a traditional development path. Model‐informed drug development refers to the utilization of a diverse array of quantitative models in drug development to streamline the decision‐making process. In this approach, diverse quantitative models that integrate knowledge of physiology, disease processes, and drug pharmacology are employed to address drug development challenges and guide regulatory decisions. Integration of these model‐informed approaches into 505(b)(2) regulatory submissions and decision‐making can further expedite the approval of new drugs. This article discusses some applications of model‐informed approaches that were used to support 505(b)(2) drug development and regulatory actions. Specifically, various quantitative models such as population pharmacokinetic and exposure‐response models have been employed to provide evidence of effectiveness, guide dosing in subgroups such as subjects with hepatic or renal impairment, and inform policies. These case study examples collectively underscore the significance of model‐informed approaches in drug development and regulatory decisions associated with 505(b)(2) submissions. [ABSTRACT FROM AUTHOR]

Antifibrotic drug screening requires evaluating the inhibitory effects of drug candidates on fibrotic cells while minimizing any adverse effects on normal cells. It is challenging to create organ-specific vascularized organoids that accurately model fibrotic and normal tissues for drug screening. Our previous studies have established methods for culturing primary microvessels and epithelial cells from adult tissues. In this proof-of-concept study, we used rats as a model organism to create a two-dimensional vascularized liver organoid model that comprised primary microvessels, epithelia, and stellate cells from adult livers. To provide appropriate substrates for cell culture, we engineered ECMs with defined stiffness to mimic the different stages of fibrotic tissues and normal tissues. We examined the effects of two TGFβ signaling inhibitors, A83-01 and pirfenidone, on the vascularized liver organoids on the stiff and soft ECMs. We found that A83-01 inhibited fibrotic markers while promoting epithelial genes of hepatocytes and cholangiocytes. However, it inhibited microvascular genes on soft ECM, indicating a detrimental effect on normal tissues. Furthermore, A83-01 significantly promoted the expression of markers of stem cells and cancers, increasing the potential risk of it being a carcinogen. In contrast, pirfenidone, an FDA-approved compound for antifibrotic treatments, did not significantly affect all the genes examined on soft ECM. Although pirfenidone had minor effects on most genes, it did reduce the expression of collagens, the major components of fibrotic tissues. These results explain why pirfenidone can slow fibrosis progression with minor side effects in clinical trials. In conclusion, our study presents a method for creating vascularized liver organoids that can accurately mimic fibrotic and normal tissues for drug screening. Our findings provide valuable insights into the potential risks and benefits of using A83-01 and pirfenidone as antifibrotic drugs. This method can be applied to other organs to create organ-specific vascularized organoids for drug development. [ABSTRACT FROM AUTHOR]

Introduction: Currently, the development of new antiviral drugs against COVID-19 remains of significant importance. In traditional Chinese medicine, the herb Euphorbia fischeriana Steud is often used for antiviral treatment, yet its therapeutic effect against the COVID-19 has been scarcely studied. Therefore, this study focuses on the roots of E. fischeriana Steud, exploring its chemical composition, antiviral activity against COVID-19, and the underlying basis of its antiviral activity. Methods: Isolation and purification of phytochemicals from E. fischeriana Steud. The elucidation of their configurations was achieved through a comprehensive suite of 1D and 2D NMR spectroscopic analyses as well as X-ray diffraction. Performed cytopathic effect assays of SARS-CoV-2 using Vero E6 cells. Used molecular docking to screen for small molecule ligands with binding to SARSCoV-2 RdRp. Microscale thermophoresis (MST) was used to determine the dissociation constant Kd. Results: Ultimately, nine new ent-atisane-type diterpenoid compounds were isolated from E. fischeriana Steud, named Eupfisenoids A-I (compounds 1-9). The compound of 1 was established as a C-19-degraded ent-atisane-type diterpenoid. During the evaluation of these compounds for their antiviral activity against COVID-19, compound 1 exhibited significant antiviral activity. Furthermore, with the aid of computer virtual screening and microscale thermophoresis (MST) technology, it was found that this compound could directly bind to the RNA-dependent RNA polymerase (RdRp, NSP12) of the COVID-19, a key enzyme in virus replication. This suggests that the compound inhibits virus replication by targeting RdRp. Discussion: Through this research, not only has our understanding of the antiviral components and material basis of E. fischeriana Steud been enriched, but also the potential of atisane-type diterpenoid compounds as antiviral agents against COVID-19 has been discovered. The findings mentioned above will provide valuable insights for the development of drugs against COVID-19. [ABSTRACT FROM AUTHOR]

Cannabinoid subtype 1 receptors (CB1Rs) are an important class of G proteincoupled receptors (GPCRs) belonging to the endocannabinoid system. CB1Rs play a crucial modulatory role in the functioning of other neurotransmitter systems and are involved in a wide range of physiological functions and dysfunctions; thus, they are considered one of the most important targets for drug development, as well as diagnostic purposes. Despite this, only a few molecules targeting this receptor are available on the pharmaceutical market, thus emphasizing the need to gain a deeper understanding of the complex activation pathways of CB1Rs and how they regulate diseases. As part of this review, we provide an overview of pharmacological and imaging tools useful for detecting CB1Rs. Herein, we summarize the derivations of cannabinoids and terpenoids with fluorescent compounds, radiotracers, or photochromic motifs. CB1Rs' molecular probes may be used in vitro and, in some cases, in vivo for investigating and exploring the roles of CB1Rs together with the starting point for the development of CB1R-targeted drugs. [ABSTRACT FROM AUTHOR]

Intra-Target Microdosing (ITM), integral to Phase 0 clinical studies, offers a novel approach in drug development, effectively bridging the gap between preclinical and clinical phases. This methodology is especially relevant in streamlining early drug development stages. Our research utilized a Physiologically Based Pharmacokinetic (PBPK) model and Monte Carlo simulations to examine factors influencing the effectiveness of ITM in achieving target engagement. The study revealed that ITM is capable of engaging targets at levels akin to systemically administered therapeutic doses for specific compounds. However, we also observed a notable decrease in the probability of success when the predicted therapeutic dose exceeds 10 mg. Additionally, our findings identified several critical factors affecting the success of ITM. These encompass both lower dissociation constants, higher systemic clearance and an optimum abundance of receptors in the target organ. Target tissues characterized by relatively low blood flow rates and high drug clearance capacities were deemed more conducive to successful ITM. These insights emphasize the necessity of taking into account each drug's unique pharmacokinetic and pharmacodynamic properties, along with the physiological characteristics of the target tissue, in determining the suitability of ITM. [ABSTRACT FROM AUTHOR]

PBX1 is a transcription factor that can promote the occurrence of various tumors and play a reg-ulatory role in tumor growth, metastasis, invasion, and drug resistance. Furthermore, a variant generated by fusion of E2A and PBX1, E2A-PBX1, has been found in 25% of patients with childhood acute lymphoblastic leukemia. Thus, PBX1 is a potential therapeutic target for many cancers. Here, we describe the structure of PBX1 and E2A-PBX1 as well as the molecular mecha-nisms whereby these proteins promote tumorigenesis to provide future research directions for developing new treatments. We show that PBX1 and E2A-PBX1 induce the development of highly malignant and difficult-to-treat solid and blood tumors. The development of specific drugs against their targets may be a good therapeutic strategy for PBX1-related cancers. Furthermore, we strongly recommend E2A-PBX1 as one of the genes for prenatal screening to reduce the incidence of childhood hematological malignancies. [ABSTRACT FROM AUTHOR]

In recent years, significant advancements have been made in molecular generation algorithms aimed at facilitating drug development, and molecular diversity holds paramount importance within the realm of molecular generation. Nonetheless, the effective quantification of molecular diversity remains an elusive challenge, as extant metrics exemplified by Richness and Internal Diversity fall short in concurrently encapsulating the two main aspects of such diversity: quantity and dissimilarity. To address this quandary, we propose Hamiltonian diversity, a novel molecular diversity metric predicated upon the shortest Hamiltonian circuit. This metric embodies both aspects of molecular diversity in principle, and we implement its calculation with high efficiency and accuracy. Furthermore, through empirical experiments we demonstrate the high consistency of Hamiltonian diversity with real-world chemical diversity, and substantiate its effects in promoting diversity of molecular generation algorithms. Our implementation of Hamiltonian diversity in Python is available at: https://github.com/HXYfighter/HamDiv. Scientific contribution We propose a more rational molecular diversity metric for the community of cheminformatics and drug development. This metric can be applied to evaluation of existing molecular generation methods and enhancing drug design algorithms. [ABSTRACT FROM AUTHOR]

Parkinson’s disease (PD) and dementia with Lewy bodies (DLB) share underlying neuropathology. Despite overlapping biology, therapeutic development has been approached separately for these clinical syndromes and there remains no treatment to slow, stop or prevent progression of clinical symptoms and development disability for people living with PD or DLB. Recent advances in biomarker tools, however, have paved new paths for biologic definition and staging of PD and DLB under a shared research framework. Patient-centered research funding organizations see the opportunity for a novel biological staging system for PD and DLB to accelerate and increase success of therapeutic development for the patient communities they serve. Amid growing momentum in the field to develop biological definitions for these neurodegenerative diseases, 7 international nonprofit organizations focused on PD and DLB came together to drive multistakeholder discussion and input on a biological staging system for research. The impact of these convenings to date can be seen in changes incorporated into a proposed biological staging system and growing alignment within the field to rapidly apply new scientific knowledge and biomarker tools to inform clinical trial design. In working together, likeminded nonprofit partners who were initially catalyzed by the significant potential for a biological staging system also realized the power of a shared voice in calling the field to action and have since worked together to establish a coalition to advance precompetitive progress and reduce hurdles to developing better treatments for PD, DLB and biologically related disorders. Plain Language Summary. Disease-focused nonprofit organizations serve to speed new treatments for patients through research funding and advocacy. In the Parkinson’s disease (PD) and dementia with Lewy bodies (DLB) fields, several international nonprofit organizations came together to facilitate multistakeholder input on a new biological staging system for research. Stakeholders gathered included researchers, clinicians, drug developers, regulatory agencies, additional nonprofits, and people affected by PD and DLB. This example, fueled by a shared perspective that new drug development tools will improve clinical trials and get better treatments to patients sooner, serves as a model for continued collaborations across the PD and DLB fields. A new, international coalition of nonprofit organizations has emerged to support advancement of treatments to slow, stop, and one day prevent PD, DLB and related disorders, in part, by facilitating future multistakeholder collaborations. [ABSTRACT FROM AUTHOR]

Why does a beneficial treatment effect on a longitudinal biomarker not translate into overall treatment benefit on survival, when the biomarker is in fact a prognostic factor of survival? In a recent exploratory data analysis in oncology, we were faced with this seemingly paradoxical result. To address this problem, we applied a theoretically principled methodology called dynamic path analysis, which allows us to perform mediation analysis with a longitudinal mediator and survival outcome. The aim of the analysis is to decompose the total treatment effect into a direct treatment effect and an indirect treatment effect mediated through a carefully constructed mediation path. The dynamic nature of the underlying methodology enables us to describe how these effects evolve over time, which can add to the mechanistic understanding of the underlying processes. In this paper, we present a detailed description of the dynamic path analysis framework and illustrate its application to survival mediation analysis using simulated and real data. The use case analysis provides clarity on the specific exploratory question of interest while the methodology generalizes to a wide range of applications in drug development where time‐to‐event is the primary clinical outcome of interest. [ABSTRACT FROM AUTHOR]

The study of drug–target interaction plays an important role in the process of drug development. The subject of DTI forecasting has advanced significantly in the last several years, yielding numerous significant research findings and methodologies. Heterogeneous data sources provide richer information and comprehensive perspectives for drug–target interaction prediction, so many existing methods rely on heterogeneous networks, and graph embedding technology becomes an important technology to extract information from heterogeneous networks. These approaches, however, are less concerned with potential noisy information in heterogeneous networks and more focused on the extent of information extraction in those networks. Based on this, a potential DTI predictive network model called FBRWPC is proposed in this paper. It uses a fine-grained similarity selection program to first integrate similarity on similar networks and then a bidirectional random walk graph embedding learning method with restart to obtain an updated drug target interaction matrix. Through the use of similarity selection and fine-grained selection similarity integration, the framework can effectively filter out the noise present in heterogeneous networks and enhance the model's prediction performance. The experimental findings demonstrate that, even after being split up into four distinct types of data sets, FBRWPC can still retain great prediction performance, a sign of the model's resilience and good generalization. [ABSTRACT FROM AUTHOR]

The emergence of drug‐resistant viruses and novel strains necessitates the rapid development of novel antiviral therapies. This need was particularly demanding during the COVID‐19 pandemic. While de novo drug development is a time‐consuming process, repurposing existing approved medications offers a more expedient approach. In our prior in silico screening of the DrugBank database, fidaxomicin emerged as a potential SARS‐CoV‐2 papain‐like protease inhibitor. This study extends those findings by investigating fidaxomicin‘s antiviral properties in vitro. Our results support further exploration of fidaxomicin as a therapeutic candidate against SARS‐CoV‐2, given its promising in vitro antiviral activity and favorable safety profile. [ABSTRACT FROM AUTHOR]

DABMA is a chemical molecule optimized from the parent compound ABMA and exhibits broad‐spectrum antipathogenic activity by modulating the host's endolysosomal and autophagic pathways. Both DABMA and ABMA inhibit severe acute respiratory syndrome coronavirus 2 (SARS‐CoV‐2) in a cellular assay, which further expands their anti‐pathogen spectrum in vitro. However, their precise mechanism of action has not yet been resolved. TMEM175 is a newly characterized endolysosomal channel which plays an essential role in the homeostasis of endosomes and lysosomes as well as organelle fusion. Here, we show that DABMA increases the endosomal TMEM175 current through organelle patch clamping with an EC50 of 17.9 μm. Depletion of TMEM175 protein significantly decreases the antitoxin activity of DABMA and affects its action on acidic‐ and Rab7‐positive endosomes as well as on endolysosomal trafficking. Thus, TMEM175 is necessary for DABMA's activity and may represent a druggable target for the development of anti‐infective drugs. Moreover, DABMA, as an activator of the TMEM175 channel, may be useful for the in‐depth characterization of the physiological and pathological roles of this endolysosomal channel. [ABSTRACT FROM AUTHOR]

Chromobox (CBX) 2, a member of the CBX protein family and a crucial component of the polycomb repressive complex (PRC), exerts significant influence on the epigenetic regulation of tumorigenesis, including glioma. However, the precise role of CBX2 in glioma has remained elusive. In our study, we observed a substantial upregulation of CBX2 expression in glioma, which displayed a strong correlation with pathological grade, chemoresistance, and unfavorable prognosis. Through a series of in vivo and in vitro experiments, we established that heightened CBX2 expression facilitated glioma cell proliferation and bolstered resistance to chemotherapy. Conversely, CBX2 knockdown led to a significant inhibition of glioma cell growth and a reduction in chemoresistance. Notably, our investigation uncovered the underlying mechanism by which CBX2 operates, primarily by inhibiting PTEN transcription and activating the AKT/mTOR signalling pathway. Conversely, silencing CBX2 curtailed cell proliferation and attenuated chemoresistance by impeding the activation of the PTEN/AKT/mTOR signalling pathway. Delving deeper into the molecular intricacies, we discovered that CBX2 can recruit EZH2 and modulate the trimethylation of histone H3 lysine 27 (H3K27me3) levels on the PTEN promoter, effectively suppressing PTEN transcription. Our research unveils a comprehensive understanding of how CBX2 impacts the tumorigenesis, progression, chemoresistance, and prognosis of glioma. Furthermore, it presents CBX2 as a promising therapeutic target for drug development and clinical management of glioma. [ABSTRACT FROM AUTHOR]

Background: Colorectal cancer is influenced by several factors such as unhealthy habits and genetic factors. C1QB has been linked to a number of malignancies. However, uncertainty surrounds the connection between C1QB and CRC. Therefore, this study aimed to explore a bidirectional causal relationship of C1QB as a drug target in CRC through Mendelian randomization (MR) analysis. Methods: The GWASs for C1QB and CRC were obtained from the Integrative Epidemiology Unit Open GWAS database. There were five strategies to investigate MR. Sensitivity analysis was carried out via tests for heterogeneity, horizontal pleiotropy and leave-one-out effects to evaluate the dependability of the MR analysis results. Furthermore, colocalization analysis of C1QB and CRC, protein-protein interaction network and drug prediction according to exposure factors as well as phenotype scanning were performed. Results: The results of forward MR analysis demonstrated that C1QB was a risk factor for CRC (OR = 1.104, p = 0.033). However, we did not find a causal relationship between CRC and C1QB (reverse MR). Rs294180 and rs291985 corresponded to the same linkage interval and had the potential to influence C1QB and CRC, respectively. The PPI results demonstrated that C1QB interacted with 10 genes (C1QA, C1QC, C1R, C1S, C2, C4A, C4B, CALR, SERPING1, and VSIG4). Additionally, 21 medications were predicted to match C1QB. Molecular docking data, including for benzo(a)pyrene, 1-naphthylisothiocyanate, calcitriol and medroxyprogesterone acetate, revealed excellent binding for drugs and proteins. Moreover, we identified 29 diseases that were associated with C1QB and related medicines via disease prediction and intersection methods. As a therapeutic target for CRC, phenotypic scanning revealed that C1QB does not significantly affect weight loss, liver cirrhosis, or nonalcoholic fatty liver disease, but might have protective impacts on ovarian cancer and melanoma. Conclusion: The results highlight a causal relationship between C1QB and CRC and imply an oncogenic role for C1QB in CRC, as potential drug targets. Drugs designed to target C1QB have a greater chance of success in clinical trials and are expected to help prioritize CRC drug development and reduce drug development costs. That provided a theoretical foundation and reference for research on CRC and C1QB in MR. [ABSTRACT FROM AUTHOR]

Understanding protein function is pivotal in comprehending the intricate mechanisms that underlie many crucial biological activities, with far-reaching implications in the fields of medicine, biotechnology, and drug development. However, more than 200 million proteins remain uncharacterized, and computational efforts heavily rely on protein structural information to predict annotations of varying quality. Here, we present a method that utilizes statistics-informed graph networks to predict protein functions solely from its sequence. Our method inherently characterizes evolutionary signatures, allowing for a quantitative assessment of the significance of residues that carry out specific functions. PhiGnet not only demonstrates superior performance compared to alternative approaches but also narrows the sequence-function gap, even in the absence of structural information. Our findings indicate that applying deep learning to evolutionary data can highlight functional sites at the residue level, providing valuable support for interpreting both existing properties and new functionalities of proteins in research and biomedicine. Understanding protein function is vital for biomedicine. Here, authors develop a method using statistics-informed graph networks to predict functions from sequences. The method integrates evolutionary couplings and residue communities to improve the accuracy of function annotations for proteins. [ABSTRACT FROM AUTHOR]

Immunometabolism has been an emerging hotspot in the fields of tumors, obesity, and atherosclerosis in recent decades, yet few studies have investigated its connection with rheumatoid arthritis (RA). In principle, intracellular metabolic pathways upstream regulated by nutrients and growth factors control the effector functions of immune cells. Dynamic communication and hypermetabolic lesions of immune cells within the inflammatory synovial microenvironment contributes to the development and progression of RA. Hence, targeting metabolic pathways within immune subpopulations and pathological cells may represent novel therapeutic strategies for RA. Natural products constitute a great potential treasury for the research and development of novel drugs targeting RA. Here, we aimed to delineate an atlas of glycolysis, lipid metabolism, amino acid biosynthesis, and nucleotide metabolism in the synovial microenvironment of RA that affect the pathological processes of synovial cells. Meanwhile, therapeutic potentials and pharmacological mechanisms of natural products that are demonstrated to inhibit related key enzymes in the metabolic pathways or reverse the metabolic microenvironment and communication signals were discussed and highlighted. [ABSTRACT FROM AUTHOR]

Cerebral infarction, also known as ischemic stroke, is caused by various regional blood supply disorders in the brain tissue, leading to ischemic hypoxic lesions and necrosis of the brain tissue and then the corresponding clinical manifestations of neurological loss, which has high mortality and disability. This study comprehensively reviews the potential molecular mechanisms of TRPC6 in neuroprotection in cerebral infarction and provides a summary of TRPC6 as a targeted drug or prognostic biomarker for cerebral infarction patients. We will screen and synthesize evidence about the molecular mechanisms of TRPC6 in cerebral infarction from the current literature to obtain comprehensive knowledge on this topic. In the pathogenesis, neuroinflammation and intracellular calcium accumulation play an important role in the onset and development of cerebral infarction. Transient receptor potential cation channel subfamily C6 (TRPC6) is the main component of calcium store-operated calcium channels. It plays a central role in ischemic cerebrovascular disease by mediating the calcium ion signaling pathway. In this review, evidence on the neuroprotective effects of TRPC6 has been shown, including inhibiting neuroinflammation and inhibiting nerve cell apoptosis, thereby alleviating nerve injury. However, at the same time, TRPC6 promotes inflammation in other organs. Generally, although an increasing number of researches support the protective role of TRPC6 in cerebral infarction, there is still evidence showing that overexpression of TRPC6 increases inflammatory tissue damage in other organs. Therefore, clarifying the molecular mechanism of TRPC6 will help develop targeted drugs or prognostic biomarkers for cerebral infarction to promote and predict neurological function recovery. More evidence to elucidate the molecular mechanism of TRPC6 in cerebral infarction is needed. Enriching TRPC6 in neuroinflammation areas and modifying its cell specificity might be the orientation of drug development that increases the effect of stroke treatment and reduces the impact on other organs. In conclusion, in cerebral infarction, TRPC6 has been proven to alleviate neuroinflammation and inhibit nerve cell apoptosis. However, at the same time, TRPC6 may promote inflammation in other organs. Therefore, the targeting potential of TRPC6 in cerebral infarction needs to be further explored [ABSTRACT FROM AUTHOR]

Background • Asl-us-Soos (Glycyrrhiza glabra L.) has been used as a therapeutic agent in the treatment of respiratory, digestive, and neurological disorders since ancient times in Unani Medicine. Its therapeutic uses have been documented in Unani pharmacopeia, classical textbooks, and manuscripts based on experience in clinical practices. Asl-us-Soos (AS) and its compound preparations are recommended in the treatment of respiratory diseases such as Dhat al-Janb (pleurisy), Dhat al-Ri’a (pneumonia), Jamod us Sadr (pulmonary apoplexy), Diq al-Nafas (asthma), Sil (thiasis), and Diq (pulmonary tuberculosis). Objectives • This review aimed to provide insight into ethno-medicinal uses, pharmacological activities, and phytochemical profile of AS. The review also highlights the prospects in the development of potential drug molecules for various respiratory ailments. Methods • This review is based on a search of authentic Unani classical literature and major databases such as Science Direct, Medline (via PubMed), Google Scholar, Scopus, and Web of Science. The studies published between January 2001 and February 2022 were included in this study. Results • This review found that AS had medicinal uses in various respiratory disorders. Its roots are used as single drug and compound formulations for the treatment of dry cough, bronchial asthma, bronchitis, and pneumonia. In addition, AS contains active phytoconstituents such as glycyrrhizin (glycyrrhizic acid), isoliquiritigenin, glabridin, and licochalcone A. They have been extensively studied using in vitro and in vivo models and were found to exhibit pharmacological effects in pulmonary tuberculosis, pulmonary carcinoma, emphysema, bronchial asthma, pneumonia, and upper respiratory tract infections. Moreover, glycyrrhizin has been found to possess therapeutic potential against COVID-19. Conclusion • This review concludes that AS is a potent anti-tumor, anti-inflammatory, anti-microbial, antioxidant, expectorant, and antitussive drug. This plant could be an important source for the development of new drug compounds for various respiratory diseases. [ABSTRACT FROM AUTHOR]

Dengue, caused by dengue virus (DENV), is now endemic in nearly 100 countries and infection incidence is reported in another 30 countries. Yearly an estimated 400 million cases and 2200 deaths are reported. Effective vaccines against DENV are limited and there has been significant focus on the development of effective antiviral against the disease. The World Health Organization has initiated research programs to prioritize the development and optimization of antiviral agents against several viruses including Flaviviridae. A significant effort has been taken by the researchers to develop effective antivirals against DENV. Several potential small-molecule inhibitors like efavirenz, tipranavir and dasabuvir have been tested against envelope and non-structural proteins of DENV, and are in clinical trials around the world. We recently developed one small molecule, namely 7D, targeting the host PF4-CXCR3 axis. 7D inhibited all 4 serotypes of DENV in vitro and specifically DENV2 infection in two different mice models. Although the development of dengue vaccines remains a high priority, antibody cross reactivity among the serotypes and resulting antibody-dependent enhancement (ADE) of infection are major concerns that have limited the development of effective vaccine against DENV. Therefore, there has been a significant emphasis on the development of antiviral drugs against dengue. This review article describes the rescue effects of some of the small molecule inhibitors to viral/host factors associated with DENV pathogenesis. [ABSTRACT FROM AUTHOR]

Imatinib is an oral molecular targeted therapy that acts as a tyrosine kinase inhibitor. Silkworms present a promising experimental model for elucidating the pharmacokinetic and toxicity profiles of various compounds. This study aimed to establish an experimental paradigm for investigating the pharmacokinetics of imatinib in silkworms. A comparative analysis of imatinib pharmacokinetic parameters across silkworms, humans, mice, and rats revealed similarities in time to maximum concentration (Tmax) and apparent clearance values between silkworms and humans. However, differences in elimination half-life (t1/2) and apparent volume of distribution between silkworms and humans remained within 5- and 4-fold ranges, respectively. Importantly, mice demonstrated pharmacokinetic parameters closer to those of humans than rats during imatinib studies. Additionally, silkworms and mice exhibit similar Tmax and t1/2 values. This study highlights the potential of silkworms as valuable tools for investigating imatinib metabolism in pharmacokinetic studies. Furthermore, it underscores the applicability of silkworms in elucidating the pharmacokinetic parameters of various molecular-targeted drugs, thus facilitating advancements in drug development and evaluation. [ABSTRACT FROM AUTHOR]

Gamma-aminobutyric acid （GABA） is a widely distributed non-protein amino acid. As an inhibitory neurotransmitter, GABA plays an important role in negative regulatory process of vertebrate nervous system, which is essential for maintaining the balance of neuronal stimulation and inhibition. With continued exploration, it was found that GABA in immune system and immune cell development can not be ignored. T cells are important components of lymphocytes and the immune system, and participate in the body's cellular immune response to prevent infection and tumor formation. Evidence in recent years showed that GABA can inhibit T cell activation and proliferation, involve in the development of tumor, diabetes and autoimmune diseases. The development of drugs targeting specific diseases is still far away due to structural heterogeneity of GABA-A receptors. In this review, we will review advances in GABA metabolism, mechanism of action for T cells and its relevance with human diseases. [ABSTRACT FROM AUTHOR]

Pulmonary arterial hypertension (PAH) is a complex pulmonary vascular disease characterized by progressive elevation of mean pulmonary artery pressure resulted from the pathological feature of pulmonary vascular remodeling. Without medical intervention, PAH can eventually lead to right heart failure and death of patients. Up to the present, there are few treatment options for PAH are still mainly function through pulmonary vasodilation. Although these treatments can alleviate symptoms, the prognosis remains poor. In recent years, breakthroughs have been made in understanding the pathogenesis of PAH, thus support the development of new treatment strategies targeting at dysregulation of signaling pathways in PAH. This review focuses on five critical pathways and the relevant drugs those entered phase II clinical trials and discusses their therapeutic potential, so to provide a basis for future research on targeting therapies for PAH patients. [ABSTRACT FROM AUTHOR]

Since its first release in 2016, the Cambridge Structural Database Python application programming interface (CSD Python API) has seen steady uptake within the community that the Cambridge Crystallographic Data Centre serves. This article reviews the history of scripting interfaces, demonstrating the need, and then briefly outlines the technical structure of the API. It describes the reach of the CSD Python API, provides a selected review of its impact and gives some illustrative examples of what scientists can do with it. The article concludes with speculation as to how such endeavours will evolve over the next decade. [ABSTRACT FROM AUTHOR]

The phage display technology is based on the presentation of peptide sequences on the surface of virions of bacteriophages. Its development led to creation of sophisticated systems based on the possibility of the presentation of a huge variability of peptides, attached to one of proteins of bacteriophage capsids. The use of such systems allowed for achieving enormous advantages in the processes of selection of bioactive molecules. In fact, the phage display technology has been employed in numerous fields of biotechnology, as diverse as immunological and biomedical applications (in both diagnostics and therapy), the formation of novel materials, and many others. In this paper, contrary to many other review articles which were focussed on either specific display systems or the use of phage display in selected fields, we present a comprehensive overview of various possibilities of applications of this technology. We discuss an usefulness of the phage display technology in various fields of science, medicine and the broad sense of biotechnology. This overview indicates the spread and importance of applications of microbial systems (exemplified by the phage display technology), pointing to the possibility of developing such sophisticated tools when advanced molecular methods are used in microbiological studies, accompanied with understanding of details of structures and functions of microbial entities (bacteriophages in this case). [ABSTRACT FROM AUTHOR]

There are good reasons to perform a randomized controlled trial (RCT) even in early phases of clinical development. However, the low sample sizes in those settings lead to high variability of the treatment effect estimate. The variability could be reduced by adding external control data if available. For the common setting of suitable subject-level control group data only available from one external (clinical trial or real-world) data source, we evaluate different analysis options for estimating the treatment effect via hazard ratios. The impact of the external control data is usually guided by the level of similarity with the current RCT data. Such level of similarity can be determined via outcome and/or baseline covariate data comparisons. We provide an overview over existing methods, propose a novel option for a combined assessment of outcome and baseline data, and compare a selected set of approaches in a simulation study under varying assumptions regarding observable and unobservable confounder distributions using a time-to-event model. Our various simulation scenarios also reflect the differences between external clinical trial and real-world data. Data combinations via simple outcome-based borrowing or simple propensity score weighting with baseline covariate data are not recommended. Analysis options which conflate outcome and baseline covariate data perform best in our simulation study. [ABSTRACT FROM AUTHOR]

Treatment guidelines for non-small cell lung cancer (NSCLC) vary by several factors including pathological stage, patient candidacy, and goal of treatment. With many therapeutics and even more combinations available in the NSCLC clinician's toolkit, a multitude of questions remain unanswered vis-a-vis treatment optimization. While some studies have begun exploring the interplay among the many pillars of NSCLC treatment—surgical resection, radiotherapy, chemotherapy, and immunotherapy—the vast number of combinations and permutations of different therapy modalities in addition to the modulation of each constituent therapy leaves much to be desired in a field that is otherwise rapidly evolving. Given NSCLC's high incidence and lethality, the experimentation of synergistic benefits that combinatorial treatment may confer presents a ripe target for advancement and increased understanding without the cost and burden of novel drug development. This review introduces, synthesizes, and compares prominent NSCLC therapies, placing emphasis on the interplay among types of therapies and the synergistic benefits some combinatorial therapies have demonstrated over the past several years. [ABSTRACT FROM AUTHOR]

Aims: Sweet's syndrome is an acute febrile neutrophilic dermatosis first described in 1964 by Robert Douglas Sweet. The pathophysiological mechanism is not fully established; however, several cases of Sweet's syndrome have been reported following drug administration. Methods: To investigate the existence of pharmacovigilance signals between drugs and the occurrence of Sweet's syndrome, we performed a case/non‐case study on reports of 'acute febrile neutrophilic dermatosis' registered in the French pharmacovigilance database. Reporting odds ratio (ROR) with its 95% confidence interval were calculated. Results: Amongthe 994 789 reports recorded in the database, 136 were Sweet's syndrome, of which 50.7% were men and the median age was 59 years (range 15–91). A total of 224 drugs were mentioned as suspects: 21.0% were antibacterials, 19.2% were antineoplastics and 12.1% were immunosuppressants. Median time to onset from drug initiation to the development of Sweet's syndrome was 15 days (range 1–1095). The highest RORs were observed with bortezomib (74.04 [40.8–134.2]), azacitidine (72.14 [29.4–176.9]), perfilgrastim (67.05 [21.2–211.6]), azathioprine (55.46 [34.8–88.4]) and bendamustine (35.84 [11.4–112.8]). Conclusions: Pharmacovigilance signals have been observed between the occurrence of Sweet's syndrome and colony‐stimulating factors, immunosuppressants, antineoplastics and antibiotics. Clinicians should be aware of the potential associations with these drugs and should be encouraged to report any case of drug‐induced Sweet's syndrome. [ABSTRACT FROM AUTHOR]

The objective of the present investigation is to improve the solubility of valsartan and prepare immediate release tablets. To increase the solubility and bioavailability of valsartan, a low-soluble antihypertensive drug, immediate release dosage forms were formulated by a direct compression method using a solid dispersion technique with three different carriers (β-cyclodextrin, polyvinyl pyrrolidone K30 and poloxamer 188) at three different ratios (1:3, 1:4 and 1:5). Nine physical mixtures (PM1–PM9) were prepared and various physical parameters were characterised in in vitro release studies. Out of the prepared physical mixtures, PM8 showed the best results, with 94.2% of the drug dissolving within 30 min. Formulation PM8 solid dispersion further used for the preparation of valsartan immediate release tablets by using sodium starch glycolate superdisintegrant, at different concentrations (3%, 4% and 5%; i.e., IF1, IF2 and IF3 formulations, respectively). The optimised formulation showed friability and disintegration values of 0.456±0.9 and 6.2±0.4 min. Among the three immediate release formulations, IF2, which contains 4% sodium starch glycolate, demonstrated an 84.46% drug release in 30 min and a 99.69% drug release in 1 hr, indicating increased drug solubility. When compared with a valsartan pure drug, the solubility of the solid dispersion increased by 135.06-fold. The results show that the optimised IF2 formulation demonstrated enhanced drug solubility by 135.06-fold, using a solid dispersion technique with poloxamer 188. This can be explained by the conversion of crystalline to an amorphous form of drug, leading to a reduction in the contact angle between the drug and the gastric medium. It can be concluded that poloxamer 188 is a suitable carrier and that use of a physical mixture technique is an applicable method to improve the solubility of valsartan. [ABSTRACT FROM AUTHOR]

The present study was aimed at preparing stable dry adsorbed nanoparticles (DANs) of olanzapine (OLZ) loaded solid lipid nanoparticles (SLNs) for sustained release. OLZ SLNs were prepared by hot melt emulsification and ultrasonication using Precirol ATO 5 (PRE) as a solid lipid, combination of Kolliphor ELP (KELP) and Tween 80 (T80) as surfactants, after optimising formulation and process variables. The SLN system was subjected to evaluation of particle size, zeta potential, entrapment efficiency (EE), in-vitro drug release and ex-vivo intestinal permeability studies using the chicken intestinal segments (jejunum). Further, these SLNs were converted into stable DANs by adsorbing onto a Neusilin US2 (NUS2) and Avicel CL 611 (ACL) carriers using the granulation-evaporative drying method. The DANs were characterised for redispersion properties, in-vitro drug release, thermal behaviour, crystallinity, and morphology. The SLN and DAN had a particle size of 238.0 nm [0.274 polydispersity index (PdI)] and 302.4 [0.494 PdI] respectively. The zeta potentials of SLN and DAN were found to be −29.3 mV and −26.3 mV, respectively. The SLN had 67% EE, and showed a sustained drug release in various media. The highest permeability of SLNs was observed in ex-vivo permeation model compared to the OLZ suspension, indicating that SLNs have the potential to bypass hepatic metabolism. The adsorption of SLNs onto carriers was confirmed by surface morphology. The DAN had good flow properties and sustained drug release similar to that of SLNs. The X-ray diffraction (XRD) patterns and endothermic peaks confirmed the complete encapsulation of actives in lipid matrices. The encapsulating of OLZ in SLNs and converting it into DAN showed a sustained release and adsorption technique that can be used for improving the stability of NLC dispersion. The DANs can be offered in dosage forms such as filling into sachets, capsules and compressed into tablets. [ABSTRACT FROM AUTHOR]

BI 187004, a selective small‐molecule inhibitor of 11β‐hydroxysteroid dehydrogenase‐1 (11β‐HSD1), displayed complex nonlinear pharmacokinetics (PK) in humans. Following nine single oral doses, BI 187004 exhibited nonlinear PK at low doses and linear PK at higher doses. Notably, substantial hepatic 11β‐HSD1 inhibition (50%) was detected in a very low‐dose group, achieving a consistent 70% hepatic enzyme inhibition in subsequent ascending doses without any dose‐dependent effects. The unusual PK and PD profiles of BI 187004 suggest the presence of pharmacological target‐mediated drug disposition (TMDD), arising from the saturable binding of BI 187004 compound to its high‐affinity and low‐capacity target 11β‐HSD1. The non‐intuitive dose, exposure, and response relationship for BI 187004 pose a significant challenge in rational dose selection. This study aimed to construct a TMDD model to explain the complex nonlinear PK behavior and underscore the importance of recognizing TMDD in this small‐molecule compound. Among the various models explored, the best model was a two‐compartment TMDD model with three transit absorption components. The final model provides insights into 11β‐HSD1 binding‐related parameters for BI 187004, including the total amount of 11β‐HSD1 in the liver (estimated to be 8000 nmol), the second order association rate constant (estimated to be 0.102 nM−1h−1), and the first‐order dissociation rate constant (estimated to be 0.11 h−1). Our final population PK model successfully characterized the intricate nonlinear PK of BI 187004 across a wide dose range. This modeling work serves as a valuable reference for the rational selection of the dose regimens for BI 187004's future clinical trials. [ABSTRACT FROM AUTHOR]

The article focuses on the impact of food on oral pharmacokinetics in pediatric drug development. Topics include the challenges posed by ethical constraints on conducting food effect studies in children, the discrepancies in physiological factors influencing drug absorption between adults and children, and the need for physiologically based biopharmaceutics modeling to better predict food effects in pediatric populations.

Over the past decade, there has been an increase in accelerated drug development with successful regulatory approval that has provided rapid access of novel medicines to patients world-wide. This has created the opportunity for the pharmaceutical industry to continuously improve the process of quickly bringing new medicines to patients with unmet medical needs. This can be accomplished through sharing the learnings and advancements in drug development, enhancing regulatory interactions, and collaborating with academics on developing the underlying science to reduce drug development timelines. In this paper, the IQ Consortium – Accelerated Drug Development working group members intend to share recommendations for optimizing strategies that build efficiencies in accelerated pathways for regulatory approval. Information was obtained by surveying member pharmaceutical companies with respect to recent expedited submissions within the past 5 years to gain insights as to which development strategies were successful. The learnings from this analysis are provided, which includes shared learnings in formulation development, stability, analytical methods, manufacturing, and importation testing as well as regulatory considerations. Each of these sections provide a summary illustrating the key data collected as well as a discussion that is aimed to guide pharmaceutical companies on strategies to consider streamlining development activities and expedite the drug to market. [ABSTRACT FROM AUTHOR]