Omar Abdelmotaleb, Anneliese Schneider, Christian Gassner, Stephan Märsch, Christian Klein
{"title":"The impact of CD3 affinity-attenuation on T cell engaging bispecific antibodies: is it really that simple?","authors":"Omar Abdelmotaleb, Anneliese Schneider, Christian Gassner, Stephan Märsch, Christian Klein","doi":"10.1080/17460441.2025.2522088","DOIUrl":"https://doi.org/10.1080/17460441.2025.2522088","url":null,"abstract":"<p><strong>Introduction: </strong>The first generation of approved T cell engagers (TCEs) showing promising efficacy in hematological and solid tumors relies on high binding affinity to CD3. Treatment of tumors with TCEs has been clinically associated with toxicities related to cytokine release syndrome (CRS). In addition to clinical strategies to mitigate CRS, antibody engineering efforts have been undertaken to generate TCEs with optimized therapeutic index. Strategies pursued in this context include affinity attenuation of CD3 binding arm, to achieve potent tumor cell killing with minimal cytokine secretion.</p><p><strong>Areas covered: </strong>A literature search was conducted to identify peer-reviewed articles related to CD3 affinity and T cell engagers. Here, we provide an overview of the current state and recent developments in CD3 affinity-attenuation, both preclinically and clinically, with a focus on the challenges of developing TCEs with attenuated affinity to CD3 as well as identifying possible areas of improvement.</p><p><strong>Expert opinion: </strong>CD3 affinity reduction can effectively lower cytokine levels preclinically; however, it is crucial to consider all factors influencing the mode of action of TCEs. Prioritizing the use of the most translatable preclinical models is essential to identify the right candidates for further development.</p>","PeriodicalId":12267,"journal":{"name":"Expert Opinion on Drug Discovery","volume":" ","pages":"1-7"},"PeriodicalIF":6.0,"publicationDate":"2025-06-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144474415","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}
{"title":"Advances in the application of NMR to the study of GPCRs and ligand-GPCR interactions.","authors":"Olga A Alimowska, Afnan Khan, R Scott Prosser","doi":"10.1080/17460441.2025.2515045","DOIUrl":"10.1080/17460441.2025.2515045","url":null,"abstract":"<p><strong>Introduction: </strong>GPCRs are targeted by nearly one-third of FDA-approved drugs and are therefore of great interest in drug discovery pursuits. Nuclear magnetic resonance (NMR) builds upon our understanding of the structural biology of GPCRs by helping to identify dynamic facets of ligand engagement, activation, and G protein coupling, often through the identification of an ensemble.</p><p><strong>Areas covered: </strong>The basic facets of NMR spectroscopy and relaxation experiments (e.g. CPMG, WaterLOGSY, STD) are described as they pertain to the study of structure activity relationships (SAR), ligand-fragment interaction dynamics, and fragment-based drug discovery. This article is based on literature searches that have utilized ISI Web of Knowledge, MEDLINE, and Google Scholar.</p><p><strong>Expert opinion: </strong>The structural biology of GPCRs and their associated complexes are rapidly advancing, particularly via cryoEM techniques which provide high-resolution structures and additional insights into minor states represented into the ensemble. Nevertheless, there is still an important niche for NMR methods to capture in terms of the delineation of detailed and physiologically representative ensembles of functional states and their associated dynamics.</p>","PeriodicalId":12267,"journal":{"name":"Expert Opinion on Drug Discovery","volume":" ","pages":"1-17"},"PeriodicalIF":6.0,"publicationDate":"2025-06-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144247220","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}
Stefanie K Menzies, Rohit N Patel, Stuart Ainsworth
{"title":"Practical progress towards the development of recombinant antivenoms for snakebite envenoming.","authors":"Stefanie K Menzies, Rohit N Patel, Stuart Ainsworth","doi":"10.1080/17460441.2025.2495943","DOIUrl":"10.1080/17460441.2025.2495943","url":null,"abstract":"<p><strong>Introduction: </strong>Snakebite envenoming is a neglected tropical disease that affects millions globally each year. In recent years, research into the potential production of recombinant antivenoms, formulated using mixtures of highly defined anti-toxin monoclonal antibodies, has rapidly moved from a theoretical concept to demonstrations of practical feasibility.</p><p><strong>Areas covered: </strong>This article examines the significant practical advancements in transitioning recombinant antivenoms from concept to potential clinical translation. The authors have based their review on literature obtained from Google Scholar and PubMed between September and November 2024. Coverage includes the development and validation of recombinant antivenom antibody discovery strategies, the characterization of the first broadly neutralizing toxin class antibodies, and recent translational proof-of-concept experiments.</p><p><strong>Expert opinion: </strong>The transition of recombinant antivenoms from a 'concept' to the current situation where high-throughput anti-venom mAb discovery is becoming routine, accompanied by increasing evidence of their broad neutralizing capacity <i>in</i> <i>vivo</i>, has been extraordinary. It is now important to build on this momentum by expanding the discovery of broadly neutralizing mAbs to encompass as many toxin classes as possible. It is anticipated that key demonstrations of whether recombinant antivenoms can match or surpass existing conventional polyvalent antivenoms in terms of neutralizing scope and capacity will be achieved in the next few years.</p>","PeriodicalId":12267,"journal":{"name":"Expert Opinion on Drug Discovery","volume":" ","pages":"799-819"},"PeriodicalIF":6.0,"publicationDate":"2025-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143974503","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}
{"title":"A comprehensive update on the application of high-throughput fluorescence imaging for novel drug discovery.","authors":"Michael Ronzetti, Anton Simeonov","doi":"10.1080/17460441.2025.2499123","DOIUrl":"10.1080/17460441.2025.2499123","url":null,"abstract":"<p><strong>Introduction: </strong>High-throughput fluorescence imaging (HTFI) is revolutionizing drug discovery by enabling rapid and precise detection of biological targets and cellular processes. Recent advances in fluorescence imaging technologies now provide unprecedented sensitivity, resolution, and throughput. Integration of artificial intelligence (AI) and machine learning (ML) into HTFI workflows significantly enhances data processing, aiding in hit identification, pattern recognition, and mechanistic understanding.</p><p><strong>Areas covered: </strong>This review outlines recent technological developments, integration strategies, and emerging applications of HTFI. It emphasizes HTFI's role in phenotypic screening, especially for complex diseases such as cancer, neurodegenerative disorders, and viral infections. Additionally, it highlights advances in 3D culture systems, organoids, and organ-on-a-chip technologies, which facilitate physiologically relevant testing, improved predictive accuracy, and translational potential, alongside innovative molecular probes and biosensors.</p><p><strong>Expert opinion: </strong>Despite its advancements, HTFI faces ongoing challenges, including data standardization, integration with multi-omics approaches, and scalability of advanced models. However, recent progress in organoid and 3D modeling technologies has enhanced the physiological relevance of HTFI assays, complemented by sophisticated AI and ML-driven data analysis techniques.</p>","PeriodicalId":12267,"journal":{"name":"Expert Opinion on Drug Discovery","volume":" ","pages":"785-797"},"PeriodicalIF":6.0,"publicationDate":"2025-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12105877/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143994776","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Evaluating AutoGrow4 - an open-source toolkit for semi-automated computer-aided drug discovery.","authors":"Davide Bassani, Matteo Pavan, Stefano Moro","doi":"10.1080/17460441.2025.2499122","DOIUrl":"10.1080/17460441.2025.2499122","url":null,"abstract":"<p><strong>Introduction: </strong>Drug discovery is a long and expensive process characterized by a high failure rate. To make this process more rational and efficient, scientists always look for new and better ways to design novel ligands for a target of interest. Among different approaches, de novo ones gained popularity in the last decade, thanks to their ability to efficiently explore the chemical space and their increasing reliability in generating high-quality compounds. Autogrow4 is open-source software for de novo drug design that generates ligands for a given target by exploiting a combination of a genetic algorithm and molecular docking calculations.</p><p><strong>Areas covered: </strong>In the present paper, the authors dissect this program's usefulness and limitations in generating new compounds from a pharmacodynamic and pharmacokinetic perspective. Specifically, this article examines all reported applications of the Autogrow code in the literature (as retrieved from the Scopus database) from the release of its first version in 2009 to the present.</p><p><strong>Expert opinion: </strong>In the hands of an expert molecular modeler, Autogrow4 is a useful tool for de novo ligand design. Its modular and open-source codebase offers many protocol customization features. The main downsides are limited control over the pharmacokinetic features of generated ligands and the bias toward high molecular weight compounds.</p>","PeriodicalId":12267,"journal":{"name":"Expert Opinion on Drug Discovery","volume":" ","pages":"711-720"},"PeriodicalIF":6.0,"publicationDate":"2025-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143993254","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}
Christine Ann Withers, Amina Mardiyyah Rufai, Aravind Venkatesan, Santosh Tirunagari, Sebastian Lobentanzer, Melissa Harrison, Barbara Zdrazil
{"title":"Natural language processing in drug discovery: bridging the gap between text and therapeutics with artificial intelligence.","authors":"Christine Ann Withers, Amina Mardiyyah Rufai, Aravind Venkatesan, Santosh Tirunagari, Sebastian Lobentanzer, Melissa Harrison, Barbara Zdrazil","doi":"10.1080/17460441.2025.2490835","DOIUrl":"10.1080/17460441.2025.2490835","url":null,"abstract":"<p><strong>Introduction: </strong>The field of Natural Language Processing (NLP) within the life sciences has exploded in its capacity to aid the extraction and analysis of data from scientific texts in recent years through the advancement of Artificial Intelligence (AI). Drug discovery pipelines have been innovated and accelerated by the uptake of AI/Machine Learning (ML) techniques.</p><p><strong>Areas covered: </strong>The authors provide background on Named Entity Recognition (NER) in text - from tagging terms in text using ontologies to entity identification via ML models. They also explore the use of Knowledge Graphs (KGs) in biological data ingestion, manipulation, and extraction, leading into the modern age of Large Language Models (LLMs) and their ability to maneuver complex and abundant data. The authors also cover the main strengths and weaknesses of the many methods available when undertaking NLP tasks in drug discovery. Literature was derived from searches utilizing Europe PMC, ResearchRabbit and SciSpace.</p><p><strong>Expert opinion: </strong>The mass of scientific data that is now produced each year is both a huge positive for potential innovation in drug discovery and a new hurdle for researchers to overcome. Notably, methods should be selected to fit a use case and the data available, as each method performs optimally under different conditions.</p>","PeriodicalId":12267,"journal":{"name":"Expert Opinion on Drug Discovery","volume":" ","pages":"765-783"},"PeriodicalIF":6.0,"publicationDate":"2025-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144001689","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}
{"title":"Use of pharmacokinetic versus pharmacodynamic endpoints to support human dose predictions: implications for rational drug design and early clinical development.","authors":"Rui Li, Tristan S Maurer","doi":"10.1080/17460441.2025.2491670","DOIUrl":"10.1080/17460441.2025.2491670","url":null,"abstract":"<p><strong>Introduction: </strong>The predicted human dose regimen of new chemical entities represents the most holistic and clinically relevant measure of drug-likeness upon which to base decisions in drug design and selection of candidate molecules for further development. Likewise, the predicted human dose regimen for efficacy and safety provides critical insight into clinical development planning. As such, human dose predictions are commonly generated in early stages of research and continually revisited as new data are generated through development.</p><p><strong>Areas covered: </strong>In this work, the authors illustrate scenarios where conventional approaches based on discrete pharmacokinetic metrics are inappropriate and propose a generalizable approach leveraging a predicted average pharmacodynamic effect rather than pharmacokinetic metrics. Preclinical and clinical data of a JAK inhibitor, tofacitinib, were used to illustrate the relative value of this approach to human dose prediction.</p><p><strong>Expert opinion: </strong>Due to the simplicity of implementation, pharmacokinetic-based approaches which target a discrete maximal, average, or minimum concentration have been widely used across the pharmaceutical industry. However, in emphasizing only one point on the overall exposure-time profile, such approaches can be misleading in terms of the expected pharmacodynamic effect. For future projections, the authors recommend using the average pharmacodynamic effect-based approach to calculate human efficacious dose.</p>","PeriodicalId":12267,"journal":{"name":"Expert Opinion on Drug Discovery","volume":" ","pages":"735-744"},"PeriodicalIF":6.0,"publicationDate":"2025-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144062869","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}
Ray Price, Miguel Ramirez-Moreno, Amber Cooper, Rachita Singh, Yee Ming Khaw, Annastasiah Mudiwa Mhaka, Lovesha Sivanantharajah, Amrit Mudher
{"title":"Are we missing a trick by not exploiting fruit flies in inflammation-led drug discovery for neurodegeneration?","authors":"Ray Price, Miguel Ramirez-Moreno, Amber Cooper, Rachita Singh, Yee Ming Khaw, Annastasiah Mudiwa Mhaka, Lovesha Sivanantharajah, Amrit Mudher","doi":"10.1080/17460441.2025.2498675","DOIUrl":"10.1080/17460441.2025.2498675","url":null,"abstract":"<p><strong>Introduction: </strong>Alzheimer's disease (AD) remains a formidable challenge in neurodegeneration research, with limited therapeutic options despite decades of study. While <i>Drosophila</i> melanogaster has been instrumental in in modeling AD related Tau and amyloid beta toxicity, inflammation, a key driver of AD pathology, remains unexplored in fly models. Given the evolutionary conservation of innate immune pathways between flies and mammals, drosophila presents a powerful yet underutilized tool for inflammation led drug discovery in AD.</p><p><strong>Areas covered: </strong>This perspective highlights the relevance of <i>Drosophila</i> in studying neuroinflammatory processes, including microglial-like glial activation, systemic inflammation and gut-brain axis interactions. It further explores how fly models can be leveraged to screen anti-inflammatory compounds and dissect immune related genetic factors implicated in AD.</p><p><strong>Expert opinion: </strong>By integrating immune modulation in <i>Drosophila</i>-based drug discovery pipeline we can accelerate the identification of novel therapeutic strategies. Fully exploiting the potential of <i>Drosophila</i> in inflammation led drug screening may usher in a new era of AD therapeutics, bridging gaps between fundamental research and translational medicine.</p>","PeriodicalId":12267,"journal":{"name":"Expert Opinion on Drug Discovery","volume":" ","pages":"721-734"},"PeriodicalIF":6.0,"publicationDate":"2025-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144077044","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}
{"title":"Advancing drug discovery with electrophysiological tools for lysosomal and organellar ion channels.","authors":"Niels Fertig, Alexandre Santinho","doi":"10.1080/17460441.2025.2505540","DOIUrl":"10.1080/17460441.2025.2505540","url":null,"abstract":"","PeriodicalId":12267,"journal":{"name":"Expert Opinion on Drug Discovery","volume":" ","pages":"693-697"},"PeriodicalIF":6.0,"publicationDate":"2025-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143975774","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}
{"title":"Momelotinib - a tale of trials, tribulations, transfusion independence, and triumph.","authors":"Ruchi J Desai, Pankit Vachhani, Prithviraj Bose","doi":"10.1080/17460441.2025.2502021","DOIUrl":"10.1080/17460441.2025.2502021","url":null,"abstract":"<p><strong>Introduction: </strong>Momelotinib is a small molecule inhibitor of JAK1, JAK2, and ACVR1 that is approved by the FDA and EMA for adults patients with intermediate/high risk myelofibrosis (MF) and anemia. Inhibition of the JAK-STAT pathway has a well-established role in MF therapy, producing reductions in MF-related symptoms and spleen size. Inhibition of ACVR1 downregulates hepcidin production and improves anemia. The mechanism of action of momelotinib addresses three critical aspects of morbidity in MF, ith both spleen and symptom-directed therapy for both cytopenic and proliferative MF patients.</p><p><strong>Areas covered: </strong>Key milestones in the development of momelotinib and its regulatory approvals are reviewed here. Additionally, the efficacy, safety, and tolerability of momelotinib are discussed. The literature review is based on a comprehensive search of English language, peer-reviewed articles using PubMed and clinical trial information is taken from w ww. ClinicalTrials.gov. Studies from 1 January 2000, through 31 January 2025, were included.</p><p><strong>Expert opinion: </strong>The development of momelotinib represents an important breakthrough in MF therapy with spleen and symptom directed therapy with improvements in anemia and limited myelosuppression, facilitating dose intensity. Current and future research efforts for MF therapy are directed at development of newer, anemia-directed therapies including combinations with momelotinib.</p>","PeriodicalId":12267,"journal":{"name":"Expert Opinion on Drug Discovery","volume":"20 6","pages":"699-709"},"PeriodicalIF":6.0,"publicationDate":"2025-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144127050","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}