Mohammad Ghazi Vakili, Christoph Gorgulla, Jamie Snider, AkshatKumar Nigam, Dmitry Bezrukov, Daniel Varoli, Alex Aliper, Daniil Polykovsky, Krishna M. Padmanabha Das, Huel Cox III, Anna Lyakisheva, Ardalan Hosseini Mansob, Zhong Yao, Lela Bitar, Danielle Tahoulas, Dora Čerina, Eugene Radchenko, Xiao Ding, Jinxin Liu, Fanye Meng, Feng Ren, Yudong Cao, Igor Stagljar, Alán Aspuru-Guzik, Alex Zhavoronkov
{"title":"Quantum-computing-enhanced algorithm unveils potential KRAS inhibitors","authors":"Mohammad Ghazi Vakili, Christoph Gorgulla, Jamie Snider, AkshatKumar Nigam, Dmitry Bezrukov, Daniel Varoli, Alex Aliper, Daniil Polykovsky, Krishna M. Padmanabha Das, Huel Cox III, Anna Lyakisheva, Ardalan Hosseini Mansob, Zhong Yao, Lela Bitar, Danielle Tahoulas, Dora Čerina, Eugene Radchenko, Xiao Ding, Jinxin Liu, Fanye Meng, Feng Ren, Yudong Cao, Igor Stagljar, Alán Aspuru-Guzik, Alex Zhavoronkov","doi":"10.1038/s41587-024-02526-3","DOIUrl":"https://doi.org/10.1038/s41587-024-02526-3","url":null,"abstract":"<p>We introduce a quantum–classical generative model for small-molecule design, specifically targeting KRAS inhibitors for cancer therapy. We apply the method to design, select and synthesize 15 proposed molecules that could notably engage with KRAS for cancer therapy, with two holding promise for future development as inhibitors. This work showcases the potential of quantum computing to generate experimentally validated hits that compare favorably against classical models.</p>","PeriodicalId":19084,"journal":{"name":"Nature biotechnology","volume":"137 1","pages":""},"PeriodicalIF":46.9,"publicationDate":"2025-01-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142992596","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Sebastian Lobentanzer, Shaohong Feng, Noah Bruderer, Andreas Maier, Cankun Wang, Jan Baumbach, Jorge Abreu-Vicente, Nils Krehl, Qin Ma, Thomas Lemberger, Julio Saez-Rodriguez
{"title":"A platform for the biomedical application of large language models","authors":"Sebastian Lobentanzer, Shaohong Feng, Noah Bruderer, Andreas Maier, Cankun Wang, Jan Baumbach, Jorge Abreu-Vicente, Nils Krehl, Qin Ma, Thomas Lemberger, Julio Saez-Rodriguez","doi":"10.1038/s41587-024-02534-3","DOIUrl":"https://doi.org/10.1038/s41587-024-02534-3","url":null,"abstract":"<p>Generative artificial intelligence (AI) has advanced considerably in recent years, particularly in the domain of language. However, despite its rapid commodification, its use in biomedical research is still in its infancy<sup>1,2</sup>. The two main avenues for using large language models (LLMs) are end-user-ready platforms, which are usually provided by large corporations, and custom solutions developed by individual researchers with programming knowledge. Both use cases have significant limitations. Commercial platforms do not meet the transparency standards required for reproducible research; none are open source, and only a few provide (superficial) scientific descriptions of their algorithms<sup>3</sup>. They are also subject to privacy concerns (reuse of user data) and to considerable commercial pressures. In addition, they are not fully customizable to accommodate a specific research domain or workflow.</p><p>Individual solutions, on the other hand, are not accessible to most biomedical researchers. They require many specialized skills in addition to the researcher’s domain-specific knowledge, such as programming, data management, machine learning knowledge, technical expertise in deployment and frameworking, and management of software versions in a rapidly changing environment. This, in turn, prevents robust and reproducible results owing to the many technical challenges involved. As a result, applications of LLMs in biomedical research are still at the level of individual case studies<sup>2,4</sup>, in contrast to the imaging domain, which boasts several open-source AI frameworks and approved medical devices<sup>1</sup>.</p>","PeriodicalId":19084,"journal":{"name":"Nature biotechnology","volume":"25 1","pages":""},"PeriodicalIF":46.9,"publicationDate":"2025-01-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142992595","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Fresh from the biotech pipeline: FDA approvals settle in 2024, but what next?","authors":"","doi":"10.1038/s41587-025-02555-6","DOIUrl":"https://doi.org/10.1038/s41587-025-02555-6","url":null,"abstract":"After two volatile years, FDA approvals in 2024 settled closer to their 10-year average. Will nominated commissioner Marty Makary shake things up, or maintain a steady ship?","PeriodicalId":19084,"journal":{"name":"Nature biotechnology","volume":"74 1","pages":""},"PeriodicalIF":46.9,"publicationDate":"2025-01-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142990988","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"People","authors":"","doi":"10.1038/s41587-024-02527-2","DOIUrl":"10.1038/s41587-024-02527-2","url":null,"abstract":"Recent moves of note in and around the biotech and pharma industries.","PeriodicalId":19084,"journal":{"name":"Nature biotechnology","volume":"43 1","pages":"148-148"},"PeriodicalIF":33.1,"publicationDate":"2025-01-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142989161","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Five questions with Anastassia Vorobieva","authors":"Michael Francisco","doi":"10.1038/s41587-024-02522-7","DOIUrl":"10.1038/s41587-024-02522-7","url":null,"abstract":"A biophysicist interested in understanding the molecular principles of membrane protein folding and applying them to protein design discusses her nonlinear academic path and the potential societal impact of her research.","PeriodicalId":19084,"journal":{"name":"Nature biotechnology","volume":"43 1","pages":"147-147"},"PeriodicalIF":33.1,"publicationDate":"2025-01-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.nature.com/articles/s41587-024-02522-7.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142989163","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Biotech news from around the world","authors":"","doi":"10.1038/s41587-024-02538-z","DOIUrl":"10.1038/s41587-024-02538-z","url":null,"abstract":"","PeriodicalId":19084,"journal":{"name":"Nature biotechnology","volume":"43 1","pages":"10-10"},"PeriodicalIF":33.1,"publicationDate":"2025-01-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142989339","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"An organoid model with all three pancreatic lineages resembles fetal pancreas","authors":"Iris Marchal","doi":"10.1038/s41587-024-02537-0","DOIUrl":"10.1038/s41587-024-02537-0","url":null,"abstract":"","PeriodicalId":19084,"journal":{"name":"Nature biotechnology","volume":"43 1","pages":"30-30"},"PeriodicalIF":33.1,"publicationDate":"2025-01-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142989341","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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