Expert Opinion on Drug Discovery最新文献

Targeting fibroimmune remodeling in androgenetic alopecia: emerging opportunities for RNA-based drug discovery. 针对雄激素性脱发的纤维免疫重塑：基于rna的药物发现的新机会。

IF 7.3 2区医学

Expert Opinion on Drug Discovery Pub Date : 2026-10-15 DOI: 10.1080/17460441.2026.2749519

In Guk Park, Leegu Song, Jayhyun Cho, Minsoo Noh, Jong-Hyuk Sung

{"title":"Targeting fibroimmune remodeling in androgenetic alopecia: emerging opportunities for RNA-based drug discovery.","authors":"In Guk Park, Leegu Song, Jayhyun Cho, Minsoo Noh, Jong-Hyuk Sung","doi":"10.1080/17460441.2026.2749519","DOIUrl":"https://doi.org/10.1080/17460441.2026.2749519","url":null,"abstract":"Introduction: Current treatments for androgenetic alopecia (AGA) primarily suppress androgen signaling or stimulate hair growth. Recent single-cell and spatial transcriptomic studies identify fibroimmune remodeling as a potential source of new AGA targets.Areas covered: This review integrates transcriptomic and mechanistic evidence linking androgen-responsive fibroblasts, immune-cell recruitment, and extracellular matrix remodeling, in male and female pattern hair loss. Herein, the authors assessed published human scalp, cell and animal studies of JAK/STAT, TGF-β, CXCL12-CXCR4/ACKR3, and DKK3-CKAP4, and evaluated RNA therapeutic modalities and delivery barriers. Literature was identified primarily through PubMed in the last 20 years.Expert opinion: Fibroimmune remodeling should be viewed as a complementary, rather than alternative, framework to androgen biology. The most promising drug discovery strategy is to identify molecularly defined patient subsets and locally inhibit nodal mediators that couple fibroblast activation to inflammation and matrix remodeling. RNA therapeutics are well suited to otherwise difficult-to-drug intracellular targets, but progress will require human spatial validation, rigorous target prioritization, reproducible delivery, and pharmacodynamic biomarkers demonstrating restoration of the regenerative follicular niche.","PeriodicalId":12267,"journal":{"name":"Expert Opinion on Drug Discovery","volume":" ","pages":"1-12"},"PeriodicalIF":7.3,"publicationDate":"2026-10-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149192277","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

Current applications of isothermal titration calorimetry for lead optimization. 等温滴定量热法在铅优化中的应用现状。

IF 7.3 2区医学

Expert Opinion on Drug Discovery Pub Date : 2026-10-14 DOI: 10.1080/17460441.2026.2746971

Huiyang Hu, Martin Guerrero, Yuping Bao

{"title":"Current applications of isothermal titration calorimetry for lead optimization.","authors":"Huiyang Hu, Martin Guerrero, Yuping Bao","doi":"10.1080/17460441.2026.2746971","DOIUrl":"https://doi.org/10.1080/17460441.2026.2746971","url":null,"abstract":"Introduction: Isothermal titration calorimetry (ITC) is a valuate technique for drug lead optimization by providing a complete thermodynamic profile of ligand-target interactions. ITC further provides mechanistic insights into binding by distinguishing enthalpy and entropy for improved binding affinity and selectivity.Area covered: This review focuses on ITC applications in thermodynamic and kinetic information informed lead optimization using representative examples. Here, ITC's roles in optimizing binding affinity, selectivity, and binding mechanisms were emphasized. Practical considerations, current limitations, and emerging opportunities for integrating ITC with structural biology and computational approaches are also discussed. The literature was identified through searches of Web of Science and Google Scholar using keywords related to isothermal titration calorimetry, drug lead optimization, and thermodynamics-guided medicinal chemistry (2018-2026) with the inclusion of earlier literature on ITC fundamentals.Expert opinion: ITC has been evolving from a specialized biophysical method into a central platform for lead optimization. Beyond thermodynamic parameters, recent advancements, including kinetic ITC, microfluidic ITC, and enhanced data analysis, have significantly expanded its capabilities. The greatest impact of ITC is achieved when integrated with structural, computational, and biological approaches, enabling a comprehensive understanding of molecular recognition and facilitating the development of drug candidates with enhanced potency, selectivity, and favorable binding mechanisms.","PeriodicalId":12267,"journal":{"name":"Expert Opinion on Drug Discovery","volume":" ","pages":"1-17"},"PeriodicalIF":7.3,"publicationDate":"2026-10-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149180373","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

From stochastic systems to governed intelligence: a neurosymbolic path for pharma. 从随机系统到受控智能：制药的神经符号路径。

IF 7.3 2区医学

Expert Opinion on Drug Discovery Pub Date : 2026-10-12 DOI: 10.1080/17460441.2026.2744345

Shawn Zheng Kai Tan, Joshua Daniel Valdez, Adam Bohr

{"title":"From stochastic systems to governed intelligence: a neurosymbolic path for pharma.","authors":"Shawn Zheng Kai Tan, Joshua Daniel Valdez, Adam Bohr","doi":"10.1080/17460441.2026.2744345","DOIUrl":"https://doi.org/10.1080/17460441.2026.2744345","url":null,"abstract":"Introduction: Artificial intelligence is being deployed across the pharmaceutical value chain, yet returns have been inconsistent. One of the explanations for this inconsistency is the organizational focus on models rather than the data foundations needed to support reliable use.Areas covered: This Critical Perspective argues that pharma's AI challenge is not primarily model capability, but rather representation and governance. The authors examine why model-centric deployment strategies underdeliver in semantically weak and operationally complex setting. The authors follow this by outlining a semantic reference architecture in which heterogenous enterprise data are organized around explicit semantics while existing operational systems remain largely intact. Within this framework, ontologies function as computational substrates for conceptual clarity, interoperability, and machine reasoning. On this basis, the authors position neurosymbolic AI as a practical deployment model in which neural services provide flexible interpretation and generation, while symbolic substrates ensure semantic coherence with a knowledge base, therefore governing what may be accepted into real workflows.Expert opinion: Durable value from AI in pharma will not come from layering increasingly capable generative models onto poorly governed data environments, nor from relying on human review alone to compensate for weak system design. It will come from operationalizing semantics as infrastructure so that neural outputs are inspectable, verifiable, and accountable before they affect real work.","PeriodicalId":12267,"journal":{"name":"Expert Opinion on Drug Discovery","volume":" ","pages":"1-13"},"PeriodicalIF":7.3,"publicationDate":"2026-10-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149165497","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

Rethinking zebrafish anxiety models in drug discovery and precision psychiatry. 重新思考斑马鱼焦虑模型在药物发现和精确精神病学。

IF 7.3 2区医学

Expert Opinion on Drug Discovery Pub Date : 2026-10-08 DOI: 10.1080/17460441.2026.2743766

Nur Sabrina Abdul Basit, Maxine Min Chien Yap, Ying Kai Mah, Satoshi Ogawa

{"title":"Rethinking zebrafish anxiety models in drug discovery and precision psychiatry.","authors":"Nur Sabrina Abdul Basit, Maxine Min Chien Yap, Ying Kai Mah, Satoshi Ogawa","doi":"10.1080/17460441.2026.2743766","DOIUrl":"https://doi.org/10.1080/17460441.2026.2743766","url":null,"abstract":"Introduction: Anxiety disorders are among the most prevalent psychiatric conditions worldwide, yet the development of novel anxiolytic therapies remains limited by poor translational success and the complexity of anxiety neurobiology. Zebrafish (Danio rerio) have emerged as a valuable vertebrate model bridging high-throughput in vitro screening and mammalian preclinical studies by combining whole-organism physiology with scalable phenotypic screening.Areas covered: This review evaluates advances in zebrafish models for anxiolytic drug discovery, focusing on features supporting their construct and predictive validity. Larval zebrafish enable high-throughput behavioral and imaging-based screening, whereas adults provide more complex behavioral phenotypes and translational validation. Genetically engineered models, automated behavioral tracking, functional imaging, and molecular profiling further support mechanism-based drug discovery. A targeted search of PubMed/MEDLINE, Web of Science, and Scopus identified current and foundational studies on zebrafish anxiety models, neurobiology, behavioral assays, and drug discovery.Expert opinion: Integration of behavioral phenotyping with genetics, multi-omics, functional imaging, and artificial intelligence could transform zebrafish from a screening organism into an integrated platform for precision psychiatry and personalized neuropsychopharmacological drug discovery, and improving translation across experimental scales. Zebrafish are best positioned as an efficient intermediate translational model that accelerates mechanism-based anxiolytic discovery while complementing, rather than replacing, mammalian preclinical studies.","PeriodicalId":12267,"journal":{"name":"Expert Opinion on Drug Discovery","volume":" ","pages":"1-15"},"PeriodicalIF":7.3,"publicationDate":"2026-10-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149135648","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

Organoids in drug discovery and development: emerging technologies to transition beyond animal models. 药物发现和开发中的类器官：超越动物模型的新兴技术。

IF 7.3 2区医学

Expert Opinion on Drug Discovery Pub Date : 2026-10-05 DOI: 10.1080/17460441.2026.2742992

Jolene Phelps, Amanda Orr, Stephanie M Willerth

{"title":"Organoids in drug discovery and development: emerging technologies to transition beyond animal models.","authors":"Jolene Phelps, Amanda Orr, Stephanie M Willerth","doi":"10.1080/17460441.2026.2742992","DOIUrl":"https://doi.org/10.1080/17460441.2026.2742992","url":null,"abstract":"Introduction: High translational failure rates and ethical concerns surrounding animal models are driving the development of technologies to improve the drug development process. Organoids, three-dimensional self-organizing structures derived from stem cells, provide scalable, human-relevant platforms that recapitulate aspects of native tissue architecture and physiology with the potential to enhance predictive assessment of drug efficacy and toxicity.Areas covered: This review evaluates the potential for organoids to complement and, where scientifically feasible, reduce or eliminate animal testing. It highlights advancements and enabling technologies, including bioprinting, organ-on-chip, bioreactors, and machine learning, that support increasing organoid complexity and physiological relevance. Furthermore, it explores evolving regulatory frameworks and industry adoption while discussing practical challenges and ethical complexities to inform future development. The literature was surveyed up to August 2026 through PubMed and ClinicalTrials.gov, with industry reports retrieved through Google search.Expert opinion: The future of drug discovery lies in a strategic transition toward human-relevant systems. Organoid technologies provide value across stages of drug development, from high-throughput screening and mechanistic studies to predicting patient-specific treatment response, while reducing reliance on animal testing and supporting increased patient safety and efficiency. However, challenges in standardization, morphological complexity, heterogeneity, and cellular maturation currently limit their broad application.","PeriodicalId":12267,"journal":{"name":"Expert Opinion on Drug Discovery","volume":" ","pages":"1-26"},"PeriodicalIF":7.3,"publicationDate":"2026-10-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149106511","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

Using molecular modeling and QSAR-based design strategies for advancing the development of therapeutic solute carrier 6 (SLC6) transporter ligands. 利用分子建模和基于qsar的设计策略推进治疗性溶质载体6 （SLC6）转运体配体的开发。

IF 7.3 2区医学

Expert Opinion on Drug Discovery Pub Date : 2026-10-04 DOI: 10.1080/17460441.2026.2742988

Martyna Ogos, Marek Bajda

{"title":"Using molecular modeling and QSAR-based design strategies for advancing the development of therapeutic solute carrier 6 (SLC6) transporter ligands.","authors":"Martyna Ogos, Marek Bajda","doi":"10.1080/17460441.2026.2742988","DOIUrl":"https://doi.org/10.1080/17460441.2026.2742988","url":null,"abstract":"Introduction: The SLC6 transporter family serves as an important source of therapeutic targets, particularly in CNS disorders. Although advances in structural biology have rapidly expanded our knowledge of these transporters, rational drug design remains challenging due to their dynamic nature and a highly conserved orthosteric binding pocket. Consequently, in silico methods have become irreplaceable tools in the design of SLC6 inhibitors.Areas covered: This review summarizes computational methods applied to the discovery of SLC6 transporter inhibitors between January 2020 and August 2026. Particular attention is paid to approaches that have enabled the identification of novel chemotypes or helped address key challenges in the rational design of SLC6-targeting drugs, including ligand selectivity, transporter conformational dynamics, or allosteric modulation. The authors identified literature using the search tools PubMed, Embase, and Web of Science.Expert opinion: Future SLC6 drug discovery will likely rely on integrated computational workflows combining LBDD, SBDD, and AI to enable the design of selective and conformation-specific inhibitors. These advances may accelerate early-stage drug discovery by improving hit identification, hopefully facilitating the development of safer and more effective SLC6 inhibitors.","PeriodicalId":12267,"journal":{"name":"Expert Opinion on Drug Discovery","volume":" ","pages":"1-14"},"PeriodicalIF":7.3,"publicationDate":"2026-10-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149105559","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

Incentivizing challenging drug discovery: from reducing failure to quantifying uncertainty. 激励具有挑战性的药物发现：从减少失败到量化不确定性。

IF 7.3 2区医学

Expert Opinion on Drug Discovery Pub Date : 2026-10-01 Epub Date: 2026-09-17 DOI: 10.1080/17460441.2026.2733199

Stefano Moro

{"title":"Incentivizing challenging drug discovery: from reducing failure to quantifying uncertainty.","authors":"Stefano Moro","doi":"10.1080/17460441.2026.2733199","DOIUrl":"10.1080/17460441.2026.2733199","url":null,"abstract":"Introduction: Drug discovery's central difficulty is less the elimination of failure than the measurement of uncertainty. This editorial argues that artificial intelligence (AI) helps mainly by converting unquantifiable uncertainty into measurable, priceable confidence, as one evidence stream among several.Areas covered: It discusses the risk-uncertainty distinction, AI as a new layer in the computational drug-discovery stack, the cumulative nature of confidence (illustrated by KRAS, PCSK9 and the AI-discovered TNIK inhibitor rentosertib), discordant evidence, AI's limitations, and incentive design. Literature was identified from PubMed/MEDLINE, Scopus and Google Scholar to August 2026, with primary sources and trial registries; as an invited editorial, the search was narrative, not systematic.Expert opinion: AI's deepest contribution is epistemic rather than algorithmic: unlikely to lower failure rates markedly, but by making uncertainty measurable it can improve portfolio decisions and render ambitious biology attemptable - given calibration, prospective validation, open negative data, and incentives that reward reducing uncertainty.","PeriodicalId":12267,"journal":{"name":"Expert Opinion on Drug Discovery","volume":" ","pages":"1043-1049"},"PeriodicalIF":7.3,"publicationDate":"2026-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148988766","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

Tumor spheroids versus organoids: defining the more suitable three-dimensional model for cancer research. 肿瘤球体与类器官：定义更适合癌症研究的三维模型。

IF 7.3 2区医学

Expert Opinion on Drug Discovery Pub Date : 2026-10-01 Epub Date: 2026-09-04 DOI: 10.1080/17460441.2026.2726313

Hiral Tanna, Shrey Shah

{"title":"Tumor spheroids versus organoids: defining the more suitable three-dimensional model for cancer research.","authors":"Hiral Tanna, Shrey Shah","doi":"10.1080/17460441.2026.2726313","DOIUrl":"10.1080/17460441.2026.2726313","url":null,"abstract":"Introduction: Three-dimensional cell culture systems, such as spheroids and organoids, have emerged as tools for modeling biological processes beyond conventional two-dimensional cultures. Spheroids, formed by self-aggregation of cell lines or primary cells, are simple multicellular structures ideal for drug screening due to their reproducibility and compatibility with high-throughput platforms. Organoids, typically derived from stem cells or patient tissues, develop structures that mimic tissue architecture and genetic features, including tumor heterogeneity.Areas covered: This review examines the fundamental differences between spheroid and organoid models, focusing on their cellular origin, structural features, methods of generation, and applications in tumor research. The authors discuss the advantages and limitations of each system and highlight how experimental goals, scalability requirements, and biological complexity influence model selection. This review is based on structured literature searches of PubMed/MEDLINE, Web of Science, and Google Scholar for articles published between January 1988 and July 2026.Expert opinion: Tumor spheroid models offer practical and scalable solutions to screening and mechanistic studies, while organoids offer biological complexity and better representation of patient-derived disease characteristics. These models improve the physiological relevance of in-vitro studies, help bridge the gap between simplified cell culture systems and in-vivo testing, and reduce dependence on animal model testing.","PeriodicalId":12267,"journal":{"name":"Expert Opinion on Drug Discovery","volume":" ","pages":"1115-1131"},"PeriodicalIF":7.3,"publicationDate":"2026-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148891464","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

Opportunities in drug discovery innovation and the vital role of preclinical research. 药物发现创新的机会和临床前研究的重要作用。

IF 7.3 2区医学

Expert Opinion on Drug Discovery Pub Date : 2026-10-01 Epub Date: 2026-08-29 DOI: 10.1080/17460441.2026.2711718

Werngard Czechtizky

引用次数: 0

Advances in antisense technology for cardiovascular drug discovery: from gene silencing to therapeutics. 心血管药物发现的反义技术进展：从基因沉默到治疗。

IF 7.3 2区医学

Expert Opinion on Drug Discovery Pub Date : 2026-10-01 Epub Date: 2026-08-14 DOI: 10.1080/17460441.2026.2716800

Deung-Dae Park, Anja Bühler, Christian Schöllhorn, Steffen Just

{"title":"Advances in antisense technology for cardiovascular drug discovery: from gene silencing to therapeutics.","authors":"Deung-Dae Park, Anja Bühler, Christian Schöllhorn, Steffen Just","doi":"10.1080/17460441.2026.2716800","DOIUrl":"10.1080/17460441.2026.2716800","url":null,"abstract":"Introduction: Cardiovascular diseases remain a major cause of morbidity and mortality, and many disease-relevant RNA mechanisms remain difficult to address with conventional therapeutic modalities. Antisense oligonucleotides (ASOs) provide a sequence-defined RNA-targeting modality to modulate transcript abundance, splicing, and regulatory RNA function. In cardiovascular drug discovery, however, target complementarity is only the starting point. Translational success requires early alignment between target biology, tissue exposure, and therapeutic index.Areas covered: Based on PubMed and Web of Science searches through June 2026, this review discusses the principles that shape cardiovascular ASO candidate development, with emphasis on mechanism selection, chemical design, and exposure feasibility. Selected examples from lipoprotein-related targets and transthyretin amyloidosis are used to illustrate why target compartment and pharmacodynamic evidence are central to translational decision-making.Expert opinion: The near-term impact of cardiovascular ASO therapeutics is likely to be strongest for targets in accessible compartments, particularly liver-derived mediators with clear links to cardiovascular pathology. Applications requiring direct engagement of cardiovascular tissues, including vascular and myocardial targets, will require evidence that target engagement can be achieved in the relevant cell populations at tolerable exposure levels. Future development should therefore integrate sequence optimization with exposure-informed target qualification and therapeutic-index engineering throughout ASO candidate selection.","PeriodicalId":12267,"journal":{"name":"Expert Opinion on Drug Discovery","volume":" ","pages":"1143-1157"},"PeriodicalIF":7.3,"publicationDate":"2026-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148757450","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