Expert Opinion on Drug Discovery最新文献_第2页

Models of depression for preclinical drug discovery and development: an update of the literature. 抑郁症的临床前药物发现和开发模型：文献更新。

IF 7.3 2区医学

Expert Opinion on Drug Discovery Pub Date : 2026-10-01 Epub Date: 2026-08-19 DOI: 10.1080/17460441.2026.2716135

Pavlina Pavlidi, Dimitrios Kalampokis, Ifigeneia Ioannidi, Kalliopi Skourti, Ioannis Sotiropoulos, Katerina Antoniou, Christina Dalla, Nikolaos Kokras

{"title":"Models of depression for preclinical drug discovery and development: an update of the literature.","authors":"Pavlina Pavlidi, Dimitrios Kalampokis, Ifigeneia Ioannidi, Kalliopi Skourti, Ioannis Sotiropoulos, Katerina Antoniou, Christina Dalla, Nikolaos Kokras","doi":"10.1080/17460441.2026.2716135","DOIUrl":"10.1080/17460441.2026.2716135","url":null,"abstract":"Introduction: Depression is a heterogeneous and multifactorial condition with substantial unmet therapeutic need. Despite significant research, current pharmacotherapies remain limited in efficacy and onset, reflecting an incomplete understanding of underlying pathophysiology. Animal models have therefore been central to dissecting biological mechanisms and enabling antidepressant drug discovery.Area covered: This review provides a synthesis of animal models of depression, including stress paradigms, developmental and genetic models, neuroendocrine manipulations, immune-based, metabolic and hormone-related models. PubMed was searched from database inception to March 2026 using depression-, species-, and model-specific terms. Each paradigm is evaluated in terms of face, construct, and predictive validity, with emphasis on relevance to drug discovery. Converging evidence across models highlights shared pathophysiological domains, including HPA axis dysregulation, neuroinflammation, monoaminergic and glutamatergic imbalance, and impaired neuroplasticity.Expert opinion: No single model captures the complexity of depression; thus, reliance on isolated paradigms may contribute to translational failure. Future progress will depend on multimodal and endophenotype-driven approaches that align biological mechanisms with defined subtypes (e.g. inflammation-associated, hormone-sensitive, or stress-related depression). Integration of animal models with human-relevant data and sex-informed experimental design will advance precision psychiatry, improving predictive validity of preclinical antidepressant discovery.","PeriodicalId":12267,"journal":{"name":"Expert Opinion on Drug Discovery","volume":" ","pages":"1067-1096"},"PeriodicalIF":7.3,"publicationDate":"2026-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148790348","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Advances in the emerging field of epi-informatics in drug discovery: roads taken and future prospects. 药物发现中外源性信息学新兴领域的进展：已采取的道路和未来展望。

IF 7.3 2区医学

Expert Opinion on Drug Discovery Pub Date : 2026-10-01 Epub Date: 2026-09-02 DOI: 10.1080/17460441.2026.2727574

Aylin Del Moral-Morales, Erik D Díaz-Dionisio, José L Medina-Franco

{"title":"Advances in the emerging field of epi-informatics in drug discovery: roads taken and future prospects.","authors":"Aylin Del Moral-Morales, Erik D Díaz-Dionisio, José L Medina-Franco","doi":"10.1080/17460441.2026.2727574","DOIUrl":"10.1080/17460441.2026.2727574","url":null,"abstract":"Introduction: Epigenetic drug discovery remains a promising drug discovery strategy that has long been driven by advances in computational approaches. The subfield of epi-informatics, established more than a decade ago, continues to evolve rapidly as emerging machine learning methodologies reshape and expand its applications.Areas covered: The authors provide an updated overview of bioinformatics, chemoinformatics, and machine learning methodologies used to identify, design, and optimize compounds, primarily small-molecules, that modulate epigenetic processes with therapeutic potential. The discussion is based on a comprehensive literature analysis of peer-reviewed literature, encompassing 7,185 unique research articles published between 2000 up to 2025. The article also examines the epigenetic drug discovery landscape by analyzing the most extensively investigated epigenetic targets and emerging research trends.Expert opinion: Epi-informatics has evolved into a distinct interdisciplinary field integrating bioinformatics, chemoinformatics, and artificial intelligence to advance epigenetic drug discovery. Although rapid progress in multi-omics integration, molecular modeling, and generative artificial intelligence is accelerating the identification of drug candidates, future success will depend on high-quality, standardized data, interpretable machine learning models, and rigorous experimental validation that ensure reproducibility. Addressing these challenges will further advance epi-informatics in oncology research and an expanding range of complex diseases.","PeriodicalId":12267,"journal":{"name":"Expert Opinion on Drug Discovery","volume":" ","pages":"1051-1065"},"PeriodicalIF":7.3,"publicationDate":"2026-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148864447","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Bioengineered In vitro bone marrow models of acute myeloid leukemia for novel drug discovery. 用于新药开发的急性髓性白血病生物工程体外骨髓模型。

IF 7.3 2区医学

Expert Opinion on Drug Discovery Pub Date : 2026-10-01 Epub Date: 2026-08-30 DOI: 10.1080/17460441.2026.2723800

Celia Ribes-Balanza, Lucy Clarke, Matthew J Dalby, Hannah Donnelly

{"title":"Bioengineered In vitro bone marrow models of acute myeloid leukemia for novel drug discovery.","authors":"Celia Ribes-Balanza, Lucy Clarke, Matthew J Dalby, Hannah Donnelly","doi":"10.1080/17460441.2026.2723800","DOIUrl":"10.1080/17460441.2026.2723800","url":null,"abstract":"Introduction: Acute myeloid leukemia (AML) is an aggressive hematological malignancy associated with poor prognosis, high rates of chemoresistance and disease relapse. High attrition rates in the drug development pipeline highlight the need for improved modeling strategies that provide more reliable translation from preclinical to clinical outcomes. Bioengineered human cell-based bone marrow models are emerging as promising platforms capable of recapitulating key aspects of disease biology and therapeutic response more faithfully than conventional models.Areas covered: This review discusses advances in bioengineered bone marrow models of AML, including systems capable of reproducing chemoresistance, off-target toxicities, leukemic niche remodeling, and microenvironment-mediated disease mechanisms that are often overlooked by conventional two-dimensional cultures and current animal models. The physical, cellular, and biochemical properties to be considered in next-generation models are also examined. Literature was identified through searches of PubMed, Science Direct, and Google Scholar.Expert opinion: Bioengineered AML bone marrow models have the potential to improve drug development by identifying ineffective compounds earlier and enabling investigation of patient-specific disease heterogeneity. Future progress will depend not only on increasing biological complexity through technologies such as organoids and organ-on-chip systems, but also on rigorous validation against patient data, standardization, scalability, and regulatory acceptance.","PeriodicalId":12267,"journal":{"name":"Expert Opinion on Drug Discovery","volume":" ","pages":"1133-1141"},"PeriodicalIF":7.3,"publicationDate":"2026-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148864452","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Challenges in modeling interstitial cystitis: implications for drug discovery efforts. 模拟间质性膀胱炎的挑战：对药物发现工作的影响。

IF 7.3 2区医学

Expert Opinion on Drug Discovery Pub Date : 2026-10-01 Epub Date: 2026-08-31 DOI: 10.1080/17460441.2026.2726301

John A Arnott, Sonia Lobo

{"title":"Challenges in modeling interstitial cystitis: implications for drug discovery efforts.","authors":"John A Arnott, Sonia Lobo","doi":"10.1080/17460441.2026.2726301","DOIUrl":"10.1080/17460441.2026.2726301","url":null,"abstract":"Introduction: Interstitial cystitis/bladder pain syndrome (IC/BPS) is a chronic condition characterized by bladder pain and lower urinary tract symptoms. Despite extensive investigation and numerous therapeutic candidates, few disease-modifying treatments have translated into clinical practice. Evidence indicates that IC/BPS comprises biologically distinct phenotypes, including inflammatory bladder-centric and systemic pain-associated phenotypes, creating challenges for experimental modeling and drug development.Areas covered: Using literature from a structured search of PubMed, Scopus, and Web of Science, this review examines current IC/BPS model systems from a drug discovery perspective, including preclinical, human translational, and computational approaches. The authors evaluate the biological domains captured by existing models, their strengths and limitations, and their influence on therapeutic development. Attention is given to four translational challenges: inadequate representation of disease heterogeneity, reliance on acute injury paradigms for a chronic pain condition, bladder-centric modeling of a multisystem disorder, and limited integration of computational phenotyping. Finally, the authors propose a model-informed framework linking experimental systems with therapeutic mechanisms, patient phenotypes, and clinically relevant endpoints.Expert opinion: Progress in IC/BPS drug discovery will depend on mechanism-driven use of complementary models aligned with defined patient subgroups. Integrating patient phenotyping, biomarkers, computational methods, and back-translation from clinical trial outcomes may improve translational predictability and therapeutic success.","PeriodicalId":12267,"journal":{"name":"Expert Opinion on Drug Discovery","volume":" ","pages":"1097-1114"},"PeriodicalIF":7.3,"publicationDate":"2026-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148864445","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Lymph node models of chronic lymphocytic leukemia for translational evaluation of new drug candidates. 用于新药转化评价的慢性淋巴细胞白血病淋巴结模型。

IF 7.3 2区医学

Expert Opinion on Drug Discovery Pub Date : 2026-09-28 DOI: 10.1080/17460441.2026.2739391

Lucy Clarke, Celia Ribes Balanza, Alison M Michie, Hannah Donnelly

{"title":"Lymph node models of chronic lymphocytic leukemia for translational evaluation of new drug candidates.","authors":"Lucy Clarke, Celia Ribes Balanza, Alison M Michie, Hannah Donnelly","doi":"10.1080/17460441.2026.2739391","DOIUrl":"https://doi.org/10.1080/17460441.2026.2739391","url":null,"abstract":"Introduction: In the past decade, targeted agents have revolutionized the treatment landscape for chronic lymphocytic leukemia (CLL) patients, with life expectancy approaching the age-matched population. Despite this , patients can develop drug-associated toxicities or resistance, highlighting a need for further treatment option development. Conventional 2D models often lack the complexity of CLL to appropriately test new agents and promising therapies can lack translatability to patient disease. However, advanced 3D models are emerging that incorporate CLL microenvironment complexity. These human cell-based systems have the potential to replicate patient disease more faithfully and embed physiologically-relevant understanding at an early stage of the drug discovery and development process.Areas covered: Herein, the authors discuss bioengineered human cell-based models that have and are being developed with ranging complexities which can be tuned to fit study requirements, from scaffold-free models (e.g. spheroids), to bioreactors that mimic blood circulation. These platforms offer the potential for both high-throughput drug screening and an enhanced understanding of CLL biology. Literature was retrieved from searches on Google Scholar.Expert opinion: These bioengineered models collectively offer the potential to enhance drug discovery, minimize attrition in the development pathway and bridge the translational gap. This can ultimately facilitate a more efficient translation of effective treatments toward the clinic.","PeriodicalId":12267,"journal":{"name":"Expert Opinion on Drug Discovery","volume":" ","pages":"1-8"},"PeriodicalIF":7.3,"publicationDate":"2026-09-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149069362","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Strategy-based design for the identification of next generation β-lactam antibiotics that evade resistance from Gram-negative pathogens. 基于策略的新一代β-内酰胺类抗生素的鉴定，以逃避革兰氏阴性病原体的耐药。

IF 7.3 2区医学

Expert Opinion on Drug Discovery Pub Date : 2026-09-27 DOI: 10.1080/17460441.2026.2736532

Michio Kurosu, Iván Cheng-Sánchez, Mohammad M Aboulwafa, Amro Hanora, Mohamed K El-Ashrey, Ahmad M Abbas, Mahmoud A El Hassab, Moustafa A Tageldein, Francisco Sarabia

{"title":"Strategy-based design for the identification of next generation β-lactam antibiotics that evade resistance from Gram-negative pathogens.","authors":"Michio Kurosu, Iván Cheng-Sánchez, Mohammad M Aboulwafa, Amro Hanora, Mohamed K El-Ashrey, Ahmad M Abbas, Mahmoud A El Hassab, Moustafa A Tageldein, Francisco Sarabia","doi":"10.1080/17460441.2026.2736532","DOIUrl":"https://doi.org/10.1080/17460441.2026.2736532","url":null,"abstract":"Introduction: β-Lactam antibiotics have defined antibacterial chemotherapy for over eight decades and remain indispensable for the treatment of bacterial infections. Despite their clinical success, escalating antimicrobial resistance, particularly among Gram-negative pathogens, continues to impair their efficacy. This challenge has shifted the field from scaffold discovery to strategy-driven innovation aimed at overcoming firmly established resistance mechanisms.Areas covered: This review summarizes the current landscape of β-lactam antibiotic discovery and development, with particular emphasis on strategies designed to overcome resistance in Gram-negative pathogens. The authors discuss recent advances in β-lactam antibiotics and β-lactamase inhibitors, including clinically approved agents, compounds in late-stage clinical development, and emerging approaches targeting resistant pathogens. Furthermore, they highlight the key molecular determinants of resistance that undermine current β-lactam therapies and provide perspectives on emerging opportunities for the development of next-generation β-lactam antibiotics and β-lactamase inhibitors designed to retain activity against multidrug-resistant Gram-negative pathogens.Expert opinion: Strategies to overcome resistance in Gram-negative bacteria have established a robust foundation for the development of next-generation β-lactam antibiotics. The integration of broad-spectrum β-lactamase inhibitors, novel PBP-targeting chemotypes, enhanced outer-membrane permeation, siderophore-mediated drug delivery, and structure-guided medicinal chemistry is expected to produce β-lactam agents with improved efficacy against multidrug-resistant Gram-negative pathogens.","PeriodicalId":12267,"journal":{"name":"Expert Opinion on Drug Discovery","volume":" ","pages":"1-16"},"PeriodicalIF":7.3,"publicationDate":"2026-09-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149069375","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Design considerations for in silico drug discovery platform that can accelerate targeted drug repurposing: a focus on rare, neglected, and emerging diseases. 加速靶向药物再利用的芯片药物发现平台的设计考虑：专注于罕见、被忽视和新出现的疾病。

IF 7.3 2区医学

Expert Opinion on Drug Discovery Pub Date : 2026-09-25 DOI: 10.1080/17460441.2026.2737326

Alan Talevi

{"title":"Design considerations for in silico drug discovery platform that can accelerate targeted drug repurposing: a focus on rare, neglected, and emerging diseases.","authors":"Alan Talevi","doi":"10.1080/17460441.2026.2737326","DOIUrl":"https://doi.org/10.1080/17460441.2026.2737326","url":null,"abstract":"Introduction: Over the past decades, considerable debate has arisen regarding the decline in productivity within the pharmaceutical industry. In this context, drug repurposing has become an increasingly important strategy. Because of its cost- and time-efficient nature, it offers a particularly attractive avenue for identifying therapeutic solutions for rare, neglected, and emerging diseases. However, the implementation of rational drug repurposing strategies in these fields is hindered by data scarcity.Areas covered: The author focuses on the challenge of data availability in the context of rare, emerging, and neglected diseases. Strategies that can be implemented to mitigate these limitations are discussed: open data initiatives, federated learning, data augmentation, data synthesis, and data-centric strategies for AI-guided drug repurposing. Scopus was searched for relevant literature published in the last 10 years.Expert opinion: Drug repurposing increasingly relies on knowledge-based strategies to identify new therapeutic opportunities. The implementation of these approaches depends on the availability of high-quality data. The consolidation of data augmentation and data synthesis technologies as well as open-knowledge and federated learning paradigms could help mitigate some of the data limitations that currently constrain computational drug repurposing. Their impact remains to be established through real-world implementation.","PeriodicalId":12267,"journal":{"name":"Expert Opinion on Drug Discovery","volume":" ","pages":"1-19"},"PeriodicalIF":7.3,"publicationDate":"2026-09-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149037412","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

The rapid emergence of small molecule RNA modulator hit discovery: unlocking the potential. 快速出现的小分子RNA调节剂击中发现：释放潜力。

IF 7.3 2区医学

Expert Opinion on Drug Discovery Pub Date : 2026-09-22 DOI: 10.1080/17460441.2026.2736534

Rachel Moore, Alessandro Bonetti, Rhona J Cox, Stefan Geschwindner, Mariacarmela Giurrandino, Sergio Martinez Cuesta, Stefan Schiesser

{"title":"The rapid emergence of small molecule RNA modulator hit discovery: unlocking the potential.","authors":"Rachel Moore, Alessandro Bonetti, Rhona J Cox, Stefan Geschwindner, Mariacarmela Giurrandino, Sergio Martinez Cuesta, Stefan Schiesser","doi":"10.1080/17460441.2026.2736534","DOIUrl":"https://doi.org/10.1080/17460441.2026.2736534","url":null,"abstract":"Introduction: RNA is now recognized as an active regulatory target rather than a passive intermediary, expanding therapeutic opportunities beyond protein-centric drug discovery. Small-molecule RNA modulators offer access to novel target space and new mechanisms to modulate protein targets that are difficult to drug directly, but clinical translation remains limited.Areas covered: This review examines the principal challenges and opportunities in small-molecule RNA-targeted hit discovery: target prioritization based on genetics, structure, and function; mechanisms of modulation beyond splicing, including translation interference and targeted RNA degradation; the persistent gap between RNA structural engagement and functional outcome; hit-finding strategies; and hit-to-lead optimization. Here, the authors discuss how limitations do not lie solely in identifying RNA binders, but in predicting prospectively whether binding to a defined RNA structure will produce a functional consequence.Expert opinion: Progress requires closing the structure-function-druggability loop through in-cell validation and RNA-specific druggability models, deploying targeted RNA degradation to convert silent binders into functional molecules, establishing standardized validation cascades and translational PK/PD frameworks, building RNA-native chemical infrastructure, and training AI on RNA-specific datasets. Pre-competitive infrastructure to generate shared structural and functional data will accelerate the field.","PeriodicalId":12267,"journal":{"name":"Expert Opinion on Drug Discovery","volume":" ","pages":"1-19"},"PeriodicalIF":7.3,"publicationDate":"2026-09-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149024196","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Epidermal growth factor receptor (EGFR)-directed PROTACs: mechanistic validation, mutant selectivity, and translational challenges. 表皮生长因子受体（EGFR）导向的PROTACs：机制验证、突变选择性和翻译挑战。

IF 7.3 2区医学

Expert Opinion on Drug Discovery Pub Date : 2026-09-20 DOI: 10.1080/17460441.2026.2736536

Yash Hegde, Ranjit K Mehta, Mingjia Tan, Theodore S Lawrence, Alexander J Bridges, Mukesh K Nyati

引用次数: 0

Limitations of current drug hybridization strategies and the challenges ahead. 当前药物杂交策略的局限性和未来的挑战。

IF 7.3 2区医学

Expert Opinion on Drug Discovery Pub Date : 2026-09-01 DOI: 10.1080/17460441.2026.2726308

Joana Gil, Tânia S Morais

引用次数: 0