PEGS Boston Summit 與會者的評價迴響
“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
顯示:

工程組
- Display of Biologics
生物製劑展示 - Engineering Antibodies
抗體工程 - Machine Learning for Protein Engineering
用於蛋白質工程的機器學習

腫瘤組
- Antibodies for Cancer Therapy
用於癌症治療的抗體 - Emerging Targets for Oncology & Beyond
腫瘤學以外的新興目標 - Driving Clinical Success in Antibody-Drug Conjugates
推動抗體藥物偶聯物 (ADC) 在臨床上的成功

多特異性組
- TS: Intro to Multispecific Antibodies
培訓研討會:多特異性抗體簡介 - Advancing Multispecific Antibodies
多特異性抗體研究進展 - Engineering Bispecific and Multifunctional Antibodies
雙特異性抗體與多功能抗體工程

免疫療法組
- Advances in Immunotherapy
免疫療法的進步 - Engineering Cell Therapies
細胞治療工程 - Next-Generation Immunotherapies
下一代免疫療法

表達組
- Difficult-to-Express Proteins
難以表達的蛋白質 - Optimizing Protein Expression
優化蛋白質表達 - Maximizing Protein Production Workflows
最大化蛋白質生產工作流程

分析法組
- ML and Digital Integration in Biotherapeutic Analytics
生物製藥分析中的機器學習和數位整合 - Biophysical Methods
生物物理性手法 - Characterization for Novel Biotherapeutics
新型生物治療藥物的表徵

免疫原性組
- TS: Intro to Immunogenicity
培訓研討會:免疫原性簡介 - Predicting Immunogenicity with AI/ML Tools
使用 AI/ML 工具預測免疫原性 - TS: Bioassay Development and Analysis
培訓研討會:生物測定開發與分析

新興治療學組
- Biologics for Immunology Indications
新興治療學組 - Radiopharmaceutical Therapies
放射性藥物治療 - Next-Generation Immunotherapies
下一代免疫療法

機器學習組
- ML and Digital Integration in Biotherapeutic Analytics
生物製藥分析中的機器學習和數位整合 - Predicting Immunogenicity with AI/ML Tools
使用 AI/ML 工具預測免疫原性 - Machine Learning for Protein Engineering
用於蛋白質工程的機器學習