Summary
Large molecule therapeutics have the added complexity of formation of anti-drug antibody (ADA). Consistently confirming the presence of ADA requires a reliable and robust method with decreased impact of drug, soluble drug target, co-drugs, or other interference. In addition, the data from the ADA method should have clinical relevance for treatment of subjects. This course will examine current and evolving methodology to overcome challenges in ADA methods. Issues that will be discussed are developing positive control antibodies for drugs engineered to decrease potential ADA, ADA to drug modifiers, drug and soluble drug target interference, ADA methods for cell and gene therapy drugs, bispecific antibody therapeutics, oligonucleotides, and pre-existing antibodies. This webinar will discuss data analysis using artificial intelligence to reliably calculate cut points. Case studies will be used to highlight challenges and resolutions.
Learning Objectives
- Understanding current regulatory expectations (FDA and EMA Regulatory Expectations)
- Identify potential challenges to ADA methods
- Practical consideration for development of positive controls
- Understanding the complexity of potential interference
- Gain knowledge of new technologies to overcome assay interference
- Implementing a strategy to overcome challenging methods
- Designing ADA methods for modified drugs
- Understanding and targeting domain specificity
- Working with cut point challenges
- Value of in study cut points
- Using AI for robust calculation of cut point
- Practical guides from selected case studies
Key Topics
- Developing appropriate positive controls (pAb vs. mAb)
- Imprecision in ADA methods
- Overcoming drug tolerance
- Matrix interference
- Soluble drug target interference
- Subject co-drug or dietary interference
- ADA to molecule modifiers (PEG)
- Modifying assays for rare disease population cut point
- Clinical relevance of ADA results
- Relevance of pre-existing antibodies
- ADA to cell and gene therapy drug products
- Regulatory perspectives
- Artificial intelligence: tools for cut point calculations
Who should attend?
Laboratory Managers, Lead Scientists, Development Scientists, Validation Scientists, Regulatory Affairs, Clinical Scientists, Quality Assurance, Data Scientists
Our online training experience includes
- Our client zone – a single source for all training materials as well as pre and post-training communication
- Live interactive format via the Zoom platform
- Direct interaction with the trainer
- Q&As, case studies, polls
- Revisit recorded sessions for 7 days
- Training in digital format
- Digital and LinkedIn certificates
Trainers
Mitigating Immunogenicity Risk
Download the full training agenda to reveal complete session details, training takeaways, case studies, daily schedule, special features and full trainer bio.
