Mahmoud M. Ibrahim , Karen Köhler , Monika Lessl , Michael Gamalinda
{"title":"Enabling research and development innovation in the life sciences: A case study","authors":"Mahmoud M. Ibrahim , Karen Köhler , Monika Lessl , Michael Gamalinda","doi":"10.1016/j.drudis.2025.104325","DOIUrl":"10.1016/j.drudis.2025.104325","url":null,"abstract":"<div><div>Many industries face challenges in driving an innovation strategy that sustains value growth and aligns with the company’s social responsibility. Bayer is in a unique position as a global diversified life science company, with a mission to alleviate hunger and improve health. We propose that research-intensive firms such as Bayer must consider an R&D innovation strategy in addition to a typical product innovation strategy to ensure successful short- and long-term R&D-enabled value creation. To this end, we introduce an R&D technology–product–market innovation framework and apply this framework to a case study involving the Life Science Collaboration (LSC) program, Bayer’s internal multidisciplinary R&D seed fund. In the light of the innovation framework we propose, we show that the LSC’s community-driven decision-making enables broad strategic alignment with business needs while maintaining space for out-of-the-box ideas.</div></div>","PeriodicalId":301,"journal":{"name":"Drug Discovery Today","volume":"30 3","pages":"Article 104325"},"PeriodicalIF":6.5,"publicationDate":"2025-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143583963","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":"Embracing the future of medicine with virtual patients","authors":"Ken Wang , Neil John Parrott , Thierry Lavé","doi":"10.1016/j.drudis.2025.104322","DOIUrl":"10.1016/j.drudis.2025.104322","url":null,"abstract":"<div><div>The adoption of virtual patients promises to revolutionize pharmaceutical R&D and health care through more patient-centric approaches and is driven by integrating innovations in computational approaches, AI, and advanced <em>in vitro</em> human model systems. Virtual patients can create the conditions for faster and more predictive R&D, affecting all drivers of R&D productivity. Virtual patients enable personalized health care, ensuring precise drug dosing and scheduling to maximize efficacy and minimize adverse effects. Numerous concrete examples demonstrate the transformative potential of virtual patients in real-world scenarios, showcasing significant improvements in drug development and clinical outcomes. Despite challenges in data variability, regulatory compliance, and data privacy, virtual patients hold immense potential to transform R&D and clinical practices, driving a new era of personalized and efficient R&D and health care.</div></div>","PeriodicalId":301,"journal":{"name":"Drug Discovery Today","volume":"30 3","pages":"Article 104322"},"PeriodicalIF":6.5,"publicationDate":"2025-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143539644","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}
XiaoYu Yao , Chundi Gao , Changgang Sun , Zhe-Sheng Chen , Jing Zhuang
{"title":"Epigenetic code underlying EGFR-TKI resistance in non-small cell lung cancer: Elucidation of mechanisms and perspectives on therapeutic strategies","authors":"XiaoYu Yao , Chundi Gao , Changgang Sun , Zhe-Sheng Chen , Jing Zhuang","doi":"10.1016/j.drudis.2025.104321","DOIUrl":"10.1016/j.drudis.2025.104321","url":null,"abstract":"<div><div>Non-small-cell lung cancer (NSCLC) is the most common lung cancer subtype, and epidermal growth factor receptor tyrosine kinase inhibitors (EGFR-TKIs) are the core drugs used for its treatment. However, the emergence of drug resistance poses a significant challenge to their clinical efficacy. As a significant role-player in cancer development and maintenance, histone modifications, DNA methylation and noncoding RNA (ncRNA) changes have been proven to play a crucial part in driving EGFR-TKI resistance, which provides promising potential therapeutic targets and biomarkers for overcoming drug resistance. This review delves into the complex epigenetic mechanisms that cause EGFR-TKI resistance and emphasizes the potential of combined epigenetic therapies, aiming to provide better-targeted treatment options for NSCLC patients with NSCLC and drive innovative strategies to overcome the challenges of drug resistance.</div></div>","PeriodicalId":301,"journal":{"name":"Drug Discovery Today","volume":"30 3","pages":"Article 104321"},"PeriodicalIF":6.5,"publicationDate":"2025-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143539645","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}
Elena Peeva , Emma Guttman-Yassky , Yuji Yamaguchi , Brian Berman , Barry Oemar , Jyoti Ramakrishna , Alessio Fasano , Carmella Evans-Molina , Myron Chu , Benjamin Ungar , Percio S. Gulko , Maria Padilla , Roberta Weiss , Arezou Khosroshahi , Patrick M. Brunner , Marguerite Meariman , Michael S. Vincent , Mikael Dolsten
{"title":"Unlocking disease insights to facilitate drug development: Pharmaceutical industry–academia collaborations in inflammation and immunology","authors":"Elena Peeva , Emma Guttman-Yassky , Yuji Yamaguchi , Brian Berman , Barry Oemar , Jyoti Ramakrishna , Alessio Fasano , Carmella Evans-Molina , Myron Chu , Benjamin Ungar , Percio S. Gulko , Maria Padilla , Roberta Weiss , Arezou Khosroshahi , Patrick M. Brunner , Marguerite Meariman , Michael S. Vincent , Mikael Dolsten","doi":"10.1016/j.drudis.2025.104317","DOIUrl":"10.1016/j.drudis.2025.104317","url":null,"abstract":"<div><div>Evolving research landscapes warrant updates in drug development strategy. Collaborations between pharmaceutical industry and academic institutions are crucial for accelerating drug development, leveraging individual expertise in clinical trial conduct and pathophysiological investigations. This review highlights key collaborations between Pfizer and academic institutions in inflammation and immunology research, including dermatology, gastroenterology, rheumatology, and autoimmunity. These collaborations harness and enhance the development of innovative disease models, large clinical databases, registries, and novel clinical trial designs, and open new avenues in disease management to improve patient outcomes.</div></div>","PeriodicalId":301,"journal":{"name":"Drug Discovery Today","volume":"30 3","pages":"Article 104317"},"PeriodicalIF":6.5,"publicationDate":"2025-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143475912","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":"Drugs targeting peroxisome proliferator-activated receptors","authors":"Zhouling Xie, Jiwei Xin, Chuping Huang, Chenzhong Liao","doi":"10.1016/j.drudis.2025.104318","DOIUrl":"10.1016/j.drudis.2025.104318","url":null,"abstract":"<div><div>The year 2024 witnessed the accelerated approvals of two peroxisome proliferator-activated receptor (PPAR) agonists for the treatment of primary biliary cholangitis (PBC). PPARs, including three isoforms (PPARα, PPARγ, and PPARδ), are therapeutic targets generating considerable debate yet also seeing significant advances in their successful targeting. Currently, selective PPAR agonists are used to manage hyperlipidemia, type 2 diabetes mellitus (T2DM), and PBC, and dual/pan-PPAR agonists have been developed to address various disorders. In this review, we summarize the PPAR agonists approved globally, and their pros and cons as therapeutic agents for various diseases, with a particular focus on those agonists marketed since 2010.</div></div>","PeriodicalId":301,"journal":{"name":"Drug Discovery Today","volume":"30 3","pages":"Article 104318"},"PeriodicalIF":6.5,"publicationDate":"2025-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143475906","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}
Arseny Kovyrshin , Lars Tornberg , Jason Crain , Stefano Mensa , Ivano Tavernelli , Anders Broo
{"title":"Prioritizing quantum computing use cases in the drug discovery and development pipeline","authors":"Arseny Kovyrshin , Lars Tornberg , Jason Crain , Stefano Mensa , Ivano Tavernelli , Anders Broo","doi":"10.1016/j.drudis.2025.104323","DOIUrl":"10.1016/j.drudis.2025.104323","url":null,"abstract":"<div><div>Recent innovations in quantum computing hardware and algorithms have raised expectations that practical, real-world applications are within reach. In this context, we explore the potential impact of quantum computing on the drug discovery and development pipeline. Specifically, we discuss use cases from our research programs and outline approaches for prioritizing them based on our assessment of potential benefit from quantum computation. We identify and discuss specific classes of quantum chemistry problems that present challenges for classical computing methods, and where we have made initial efforts to develop and apply quantum computing algorithms. Finally, we offer a perspective on opportunities that will become available as we enter the early-fault tolerant era.</div></div>","PeriodicalId":301,"journal":{"name":"Drug Discovery Today","volume":"30 3","pages":"Article 104323"},"PeriodicalIF":6.5,"publicationDate":"2025-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143584050","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":"PK/PD modeling of targeted protein degraders: Charting new waters and navigating the shallows","authors":"Robin T.U. Haid , Andreas Reichel","doi":"10.1016/j.drudis.2025.104311","DOIUrl":"10.1016/j.drudis.2025.104311","url":null,"abstract":"<div><div>The development of targeted protein degraders has picked up considerable steam recently, with interest stoked further by the first compounds entering Phase III studies. To keep up with leading biotech start-up firms, big pharma has been keen to venture into this new field, bringing along experienced crews of drug hunters. At their disposal, they find a burgeoning body of literature on pharmacokinetics/pharmacodynamics (PK/PD) models tailor-made for this new therapeutic modality. However, this ocean of opportunities might seem daunting even to veteran scientists. Here, we provide orientation and direction for researchers to find the approach best suited for their respective questions.</div></div>","PeriodicalId":301,"journal":{"name":"Drug Discovery Today","volume":"30 3","pages":"Article 104311"},"PeriodicalIF":6.5,"publicationDate":"2025-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143389760","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}
Rumana Ferdushi , Dohyeon Kim , Dinesh Kumar Sriramulu , Yoonho Hwang , Keunwan Park , Jaehong Key
{"title":"Computational insights into fucoidan–receptor binding: Implications for fucoidan-based targeted drug delivery","authors":"Rumana Ferdushi , Dohyeon Kim , Dinesh Kumar Sriramulu , Yoonho Hwang , Keunwan Park , Jaehong Key","doi":"10.1016/j.drudis.2025.104315","DOIUrl":"10.1016/j.drudis.2025.104315","url":null,"abstract":"<div><div>Fucoidan, a polysaccharide from seaweed, holds promise as a drug delivery system and immune modulator; however, its exact mechanism of action remains unclear. As various carbohydrates play key roles in immune responses by binding to carbohydrate-binding proteins like lectins, fucoidan is hypothesized to interact with immune receptors, potentially driving its anticancer activities. However, structural variability, extraction-induced heterogeneity, and weak binding affinities pose challenges to research. Computational tools offer valuable insights into fucoidan–receptor interactions, addressing these challenges and enabling the design of more effective therapies. This review examines fucoidan’s therapeutic activities, drug delivery potential, and receptor interactions, emphasizing computational approaches to advance immune modulation and anticancer applications using carbohydrate polymers.</div></div>","PeriodicalId":301,"journal":{"name":"Drug Discovery Today","volume":"30 3","pages":"Article 104315"},"PeriodicalIF":6.5,"publicationDate":"2025-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143472011","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}
Lishi Lin , Merel J.J. Lucassen , Vincent van der Noort , Toine C.G. Egberts , Jos H. Beijnen , Alwin D.R. Huitema
{"title":"The feasibility of using real world data as external control arms in oncology trials","authors":"Lishi Lin , Merel J.J. Lucassen , Vincent van der Noort , Toine C.G. Egberts , Jos H. Beijnen , Alwin D.R. Huitema","doi":"10.1016/j.drudis.2025.104324","DOIUrl":"10.1016/j.drudis.2025.104324","url":null,"abstract":"<div><div>Before real world data (RWD)-derived external control arms (ECAs) can be applied in clinical trials within the field of oncology, it must be determined whether these ECAs can function as appropriate and reliable control arms. This review provides an overview of studies in which RWD-derived ECAs were constructed and compared to a randomized clinical trial (RCT) arm. RWD-derived ECAs had similar survival outcomes as the RCT arm of comparison in six of the eight included studies. Therefore, when performing RCTs is not feasible, RWD-derived ECAs can act as control arms in single-arm clinical trials, provided that suitable RWD sources are used and suitable methodological decisions are made.</div></div>","PeriodicalId":301,"journal":{"name":"Drug Discovery Today","volume":"30 3","pages":"Article 104324"},"PeriodicalIF":6.5,"publicationDate":"2025-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143584052","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}