PEGS Boston Summit 与会者的评价回响
“I enjoyed my time at PEGS! It was a superb meeting and well organized. I enjoyed most the variety of the program and easy navigation using the app. I think the presence of so many companies and their active engagement in the program make this conference different compared to other conferences.”
“For me, the PEGS conferences are an important and continuous source to develop new ideas for research and product development. Every visit is a deep dive into a world full of science, insights, and ideas I can discuss with so many scientists establishing new collaborations and networks. Based on these interactions and ideas, PEGS has been the beginning for a significant number of new R&D projects in my career.”
2025年 方案
显示:

工程组
- Display of Biologics
生物制剂展示 - Engineering Antibodies
抗体工程 - Machine Learning for Protein Engineering
用于蛋白质工程的机器学习

肿瘤组
- Antibodies for Cancer Therapy
用于癌症治疗的抗体 - Emerging Targets for Oncology & Beyond
肿瘤学以外的新兴目标 - Driving Clinical Success in Antibody-Drug Conjugates
推动抗体药物偶联物 (ADC) 在临床上的成功

多特异性组
- TS: Intro to Multispecific Antibodies
培训研讨会:多特异性抗体简介 - Advancing Multispecific Antibodies
多特异性抗体研究进展 - Engineering Bispecific and Multifunctional Antibodies
双特异性抗体与多功能抗体工程

免疫疗法组
- Advances in Immunotherapy
免疫疗法的进步 - Engineering Cell Therapies
细胞治疗工程 - Next-Generation Immunotherapies
下一代免疫疗法

表达组
- Difficult-to-Express Proteins
难以表达的蛋白质 - Optimizing Protein Expression
优化蛋白质表达 - Maximizing Protein Production Workflows
最大化蛋白质生产工作流程

分析法组
- ML and Digital Integration in Biotherapeutic Analytics
生物制药分析中的机器学习和数位整合 - Biophysical Methods
生物物理性手法 - Characterization for Novel Biotherapeutics
新型生物治疗药物的表征

免疫原性组
- TS: Intro to Immunogenicity
培训研讨会:免疫原性简介 - Predicting Immunogenicity with AI/ML Tools
使用 AI/ML 工具预测免疫原性 - TS: Bioassay Development and Analysis
培训研讨会:生物测定开发与分析

新兴治疗学组
- Biologics for Immunology Indications
新兴治疗学组 - Radiopharmaceutical Therapies
放射性药物治疗 - Next-Generation Immunotherapies
下一代免疫疗法

机器学习组
- ML and Digital Integration in Biotherapeutic Analytics
生物制药分析中的机器学习和数位整合 - Predicting Immunogenicity with AI/ML Tools
使用 AI/ML 工具预测免疫原性 - Machine Learning for Protein Engineering
用于蛋白质工程的机器学习