Drug Discovery Today最新文献

Wnt signaling plays key roles in the initiation, progression, and therapy resistance of various cancers. No drugs targeting this pathway are currently available, and several candidates have failed because they affected healthy tissues such as bone and intestine. It is necessary, therefore, to develop efficient and safe Wnt pathway inhibitors that act selectively on tumors. The targeting of individual FZD receptor proteins that initiate Wnt pathways is a promising approach to the development of selective inhibitors. In this review, we summarize the physiological and pathological roles of each of ten FZDs and describe diverse selective biologics that have been developed to target them. Antibodies, designer proteins, peptides, nanobodies, and aptamers are being studied for their potential as selective, efficient, and safe anti-Wnt treatments that could be used to combat specific cancers and other pathologies.

Systemic sclerosis (SSc) is an autoimmune disease characterized by vascular abnormalities, immune dysregulation, and progressive fibrosis of the skin and internal organs. Oxidative stress is thought to be a potential initiating factor in SSc vasculopathy, with sustained reactive oxygen species (ROS) production implicated in disease progression and tissue fibrosis. Immunosuppressants have been used to treat SSc, and there are still unmet clinical needs. This review highlights newly validated and investigational therapies targeting ROS-driven immune and cytokine pathways, which have key roles in the initiation and progression of SSc-related vasculopathy and fibrosis.

Leishmaniasis, a neglected tropical disease caused by Leishmania parasites, affects >12 million people globally. Conventional chemotherapy is plagued by drug resistance, systemic toxicity and high cost, creating an urgent need for novel therapeutic strategies. Photothermal therapy and photodynamic therapy with or without synergistic pharmacotherapy have emerged as highly promising alternatives, especially useful in drug-resistant cutaneous leishmaniasis. These methods rely on localized hyperthermia and/or reactive oxygen species (ROS) generated by nanoparticles under light to selectively eradicate the thermosensitive parasites. This review critically examines recent advances in photoactive nanoparticle-based therapy of leishmaniasis. We discuss the intrinsic efficacy of photothermal agents and photosynthesizers such as gold and graphene oxide nanoparticles. Furthermore, we highlight the evolution of the field toward sophisticated, next-generation strategies designed to enhance specificity and efficacy. These include the antibody-targeted delivery of nanoparticles to infected macrophages and the development of combinatorial nanoplatforms that synergize photothermal ablation or photodynamically generated ROS, with controlled drug release, enabling a multimodal attack.

Digital twins can revolutionize drug development and personalized care by accelerating timelines, reducing costs and failure rates, and potentially improving the safety and efficacy of new therapies. In this review, we explore different applications of digital twins across the pharmaceutical value chain, from target discovery and preclinical research to clinical trials, regulatory review, manufacturing and post-market clinical practice. Key challenges, however, remain in data integration, model reliability, regulatory acceptance and data privacy. Overcoming these barriers will require innovation, transparency and collaborative efforts across the healthcare ecosystem to fully realize digital twin potential for patients, healthcare providers and the pharmaceutical industry.

Ultra-large virtual screening (ULVS) enables systematic evaluation of hundreds of millions to billions of compounds for hit discovery. This review surveys recent ULVS strategies spanning structure-based, ligand-based, pharmacophore-based, fragment-based and hybrid workflows, often augmented by machine learning (ML) and deep learning. Platforms such as VirtualFlow, RosettaVS, Deep Docking and V-SYNTHES have delivered chemically novel, experimentally validated hits across diverse target classes, including G-protein-coupled receptors and protein-protein interfaces. Despite these successes, challenges remain in scoring accuracy, resource efficiency and generalizability. Future ULVS will increasingly emphasize selective, adaptive exploration through ML-guided prioritization, fragment-based enumeration and synthesis-aware library design.

A prolonged QT interval is a risk factor for developing torsades de pointes - a potentially fatal drug-related ventricular arrhythmia. The in vitro hERG assay plays a relevant part in this context, presenting predictive value for anticipating the arrhythmogenic potential of new drugs. However, its value for predicting clinical outcomes remains a matter of debate. This review article addresses the several milestones in the field, highlighting the International Council for Harmonization (ICH) S7B and E14 guidelines, and the comprehensive in vitro proarrhythmia assay (CiPA), as well as the current limitations and future challenges.

Open-source statistical software development is increasingly the preferred solution for leveraging new statistical methods in the pharmaceutical industry. However, with a long history of relying on licensed analysis software, there are philosophical and organizational barriers to overcome. In particular, the sustainability, reliability, usability, and feasibility of maintaining open-source statistical software long-term must be ensured. Here, we describe the open-source revolution that is emerging in the pharmaceutical industry and how it facilitates greater scaling of innovative analytical methods in statistics. We discuss challenges to open-source software adoption and propose mitigation strategies. Furthermore, we illustrate the potential for open-source software development with examples of successful projects, which highlight the roles of cross-company collaboration, career paths, education, and community building.

Humanized liver mouse models are constructed by engrafting primary human hepatocytes into immunodeficient mouse livers, thereby reconstructing human-specific metabolic and transport pathways and significantly improving the prediction of pharmacokinetics, drug interactions and hepatotoxicity. These models have been widely applied to MASLD/MASH, fibrosis, hepatocellular carcinoma and viral hepatitis research but remain constrained by the absence of intestinal CYP3A4 expression and functional immune compartments. Emerging approaches, including dual humanization, non-parenchymal cell supplementation, vascularized 3D bioprinting and application of patient-derived hepatocytes, combined with advanced in vitro and computational platforms, further strengthen translational fidelity, reduce R&D attrition and expand the scope for modeling complex metabolism-related diseases.