短期课程
短期课程以教学和互动的形式提供关于特定主题的深入资讯。参加者和讲师之间的一对一互动可以更轻松地涵盖主要演示文稿中可能未涵盖的技术方面。
短期课程仅限线下参加
Sunday, May 11, 2025 2:00 - 5:00 pm
SC1: In silico and Machine Learning Tools for Antibody Design and Developability Predictions
Topics to be covered include:
- Overview of sequence, structure-guided, ML (machine learning) tools for developability and designs
- Overview and demo of various ML tools from Oxford Protein Informatics Group (OPIG)
- Antibody specific language models (Ablang - Olsen et al 2022, Ablang2 - Olsen et al 2024)
- Antibody (and nanobody) structure prediction (ABodyBuilder2) Abanades et al 2023)
- Therapeutic antibody profiling and developability evaluation (TAP - Raybould et al 2019, TAP2 - Raybould et al 2024)
- Antibody sequence optimization with inverse folding (AntiFold - Hummer et al 2023)
- In silico developability assessment - case studies
INSTRUCTOR BIOGRAPHIES:
Mehdi Boroumand, PhD, Associate Principal Data Scientist, Machine Learning, AstraZeneca
Henriette Capel, PhD Student, University of Oxford
Vinodh B. Kurella, PhD, Biotherapeutic Computational Modeler, Takeda Pharmaceuticals, Inc.
Robert Vernon, PhD, Associate Director, Amgen
SC2: Safety & Efficacy of Bispecifics and ADCs
The short course will discuss:
- Bispecific and ADC landscape assessment and unmet medical needs
- Efficacy and safety challenges originating from poorly constructed ADCs
- Five rights of the targets, effector arms, and constructs for attaining the best therapeutic index for bispecifics and ADCs
- Minimizing toxicities of bispecifics and ADCs
- Translational aspects of bispecific and ADC development
INSTRUCTOR BIOGRAPHIES:
Rakesh Dixit, PhD, DABT, President & Founder, Bionavigen Oncology, LLC and Regio Biosciences
SC3: Challenges and Opportunities in Solid Tumor and Autoimmune Disease Therapeutic Innovations
- Identify and develop next-generation immunotherapies for solid tumors and autoimmune diseases
- Analyze the solid tumor microenvironment, discussing successful therapies such as T cell engagers, blocking bispecific antibodies, ADCs, CAR-Ts, Radio ligand therapy and Targeted Protein degraders
- Examines autoimmune disease biology and therapeutic development, integrating approaches like immune target blockade and autoantigen tolerizing.
- Highlights the application of machine learning and generative AI in discovering novel therapeutic targets and expediting therapeutic development.
- Addresses the challenges and provides case examples of cutting-edge therapeutic approaches in both cancer and autoimmune diseases
INSTRUCTOR BIOGRAPHIES:
Tony R. Arulanandam, DVM, PhD, CEO and Founder, Synaptimmune Therapeutics
Tuesday, May 13, 2025 6:30 - 9:00 pm
SC4: Best Practices for Targeting GCPRs, Ion Channels, and Transporters with Monoclonal Antibodies
INSTRUCTOR BIOGRAPHIES:
Ross Chambers, PhD, Vice President, Antibody Discovery, Integral Molecular, Inc.
SC5: Targeting the Target: Aligning Target and Biologic Format Biology to Achieve Desired Outcomes
Topics to be covered
- Introduction to the “components of success paradigm”
- Underlying concepts and examples of one target, multiple functions/outcomes
- How emerging technologies are and could impact
- o Understanding target biology, lead selection and discovery/development paradigm
- o Target space for bispecifics, ADCs and other therapeutic formats/concepts
- Case studies: (i) evaluating functional impact of different mAbs to the same target (target/mAb biology): (ii) designing biologic molecules to develop functional assays to assess novel/emerging target biology and potentially develop novel therapeutics
INSTRUCTOR BIOGRAPHIES:
Tariq Ghayur, PhD, Tariq Ghayur Consulting, LLC; Entrepreneur in Residence, FairJourney Biologics
SC6: Developability of Bispecific Antibodies
Topics to be covered
- Introduction to bispecifics and bispecific formats
- Therapeutic applications of bispecific antibodies
- Developability of bispecifics
- Case study: discovery and development of an FDA-approved bispecific antibody
INSTRUCTOR BIOGRAPHIES:
Nimish Gera, PhD, Vice President, Biologics, Mythic Therapeutics
SC7: Nuts and Bolts of Building a Radiopharmaceutical Therapy Agent
INSTRUCTOR BIOGRAPHIES:
Diane S. Abou, PhD, Principal Radiochemist, Assistant Professor, Mallinckrodt Institute of Radiology, Washington University School of Medicine in St. Louis
* 活动内容有可能不事先告知作更动及调整。
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