Thy T. Nguyen, Bohan Zhang, Luke Zhong, Xiuyi Liang, Letao Bo
Tislelizumab is a next-generation PD-1 monoclonal antibody developed to overcome the limitations of earlier immune checkpoint inhibitors. By eliminating Fcγ receptor binding, it avoids macrophage-mediated T-cell clearance and enhances the antitumor immune response. Unlike conventional PD-1 inhibitors, tislelizumab binds to PD-1 in a way that more closely mimics the natural PD-L1 interaction, potentially improving efficacy and reducing immune-related toxicity. This review highlights its structural advantages, clinical efficacy across multiple cancers, and recent global regulatory approvals. We also discuss key pharmacokinetic features and current challenges, including the need for predictive biomarkers, immune-related adverse events, and combination therapy strategies. Together, these insights may guide the more effective and safer use of tislelizumab in cancer immunotherapy.
{"title":"Tislelizumab: Structural Innovations and Expanding Clinical Horizons in Next-Generation PD-1 Immunotherapy","authors":"Thy T. Nguyen, Bohan Zhang, Luke Zhong, Xiuyi Liang, Letao Bo","doi":"10.1002/cdt3.70017","DOIUrl":"https://doi.org/10.1002/cdt3.70017","url":null,"abstract":"<p>Tislelizumab is a next-generation PD-1 monoclonal antibody developed to overcome the limitations of earlier immune checkpoint inhibitors. By eliminating Fcγ receptor binding, it avoids macrophage-mediated T-cell clearance and enhances the antitumor immune response. Unlike conventional PD-1 inhibitors, tislelizumab binds to PD-1 in a way that more closely mimics the natural PD-L1 interaction, potentially improving efficacy and reducing immune-related toxicity. This review highlights its structural advantages, clinical efficacy across multiple cancers, and recent global regulatory approvals. We also discuss key pharmacokinetic features and current challenges, including the need for predictive biomarkers, immune-related adverse events, and combination therapy strategies. Together, these insights may guide the more effective and safer use of tislelizumab in cancer immunotherapy.</p>","PeriodicalId":32096,"journal":{"name":"Chronic Diseases and Translational Medicine","volume":"11 3","pages":"173-185"},"PeriodicalIF":0.0,"publicationDate":"2025-08-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/cdt3.70017","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145038003","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Safayet Jamil, Masoud Mohammadnezhad, Abdulrakib Abdulrahim, Faisal Muhammad, Hafiz T. A. Khan
The global burden of diabetes mellitus disproportionately affects low- and middle-income countries (LMICs), where limited healthcare infrastructure hampers timely and effective disease management. Wearable technologies, such as continuous glucose monitors (CGMs), insulin pumps, and fitness trackers, offer a transformative opportunity to bridge care gaps by enabling real-time monitoring, personalized feedback, and improved glycemic control. Evidence shows how wearables enhance patient engagement, support clinical decision-making, and reduce complications. However, significant barriers such as cost, digital illiteracy, poor system integration, and data privacy concerns impede widespread adoption in LMICs. Case studies from Ghana, China, and Ethiopia illustrate these devices' potential and challenges in resource-limited settings. Policy interventions, such as public-private partnerships, subsidies, simplified interfaces, and digital literacy programs, are essential to overcome these obstacles. Furthermore, integrating wearable data into national health systems and leveraging artificial intelligence can improve individualized care and long-term outcomes. As mobile phone use increases in LMICs, coupling wearables with mHealth platforms could further empower self-management. With targeted investments and regulatory support, wearable technologies can be pivotal in advancing equitable, proactive, and data-driven diabetes care across underserved populations.
{"title":"Managing Diabetes One Step at a Time in Low- and Middle-Income Countries: The Promise of Wearable Devices","authors":"Safayet Jamil, Masoud Mohammadnezhad, Abdulrakib Abdulrahim, Faisal Muhammad, Hafiz T. A. Khan","doi":"10.1002/cdt3.70018","DOIUrl":"https://doi.org/10.1002/cdt3.70018","url":null,"abstract":"<p>The global burden of diabetes mellitus disproportionately affects low- and middle-income countries (LMICs), where limited healthcare infrastructure hampers timely and effective disease management. Wearable technologies, such as continuous glucose monitors (CGMs), insulin pumps, and fitness trackers, offer a transformative opportunity to bridge care gaps by enabling real-time monitoring, personalized feedback, and improved glycemic control. Evidence shows how wearables enhance patient engagement, support clinical decision-making, and reduce complications. However, significant barriers such as cost, digital illiteracy, poor system integration, and data privacy concerns impede widespread adoption in LMICs. Case studies from Ghana, China, and Ethiopia illustrate these devices' potential and challenges in resource-limited settings. Policy interventions, such as public-private partnerships, subsidies, simplified interfaces, and digital literacy programs, are essential to overcome these obstacles. Furthermore, integrating wearable data into national health systems and leveraging artificial intelligence can improve individualized care and long-term outcomes. As mobile phone use increases in LMICs, coupling wearables with mHealth platforms could further empower self-management. With targeted investments and regulatory support, wearable technologies can be pivotal in advancing equitable, proactive, and data-driven diabetes care across underserved populations.</p>","PeriodicalId":32096,"journal":{"name":"Chronic Diseases and Translational Medicine","volume":"11 4","pages":"279-283"},"PeriodicalIF":0.0,"publicationDate":"2025-08-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/cdt3.70018","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145652746","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}