Day Two

• Applying large language models to capture and structure real-time toxicity events from clinical data sources, enabling more comprehensive and timely identification of ADC-related adverse events
• Developing a clinically annotated framework for systematic collection of patient samples across clinical trials and standard-of-care settings, supporting integrated analyses of ADC toxicity mechanisms
• Leveraging advanced analytical techniques to characterize toxicity profiles and compare them with analogous sporadic events, enabling deeper mechanistic insights and more informed strategies for toxicity prediction and management

• Developing a clinical algorithm for the early detection of ILD using high-resolution CT imaging and pulmonary function tests, to differentiate between early, reversible pneumonitis and progressive fibrosis, enabling timely intervention to prevent Grade 3-5 events
• Correlating serum biomarkers with the onset and severity of ILD in real-world patient cohorts, to validate a non-invasive monitoring tool for early detection, allowing clinicians to intervene before the onset of debilitating symptoms
• Building a multidisciplinary approach involving oncologists, pulmonologists, and radiologists, to establish standardized guidelines for the management of ILD and the criteria for safe re-challenge, improving patient outcomes and preserving the therapeutic option

The disconnect between observed clinical toxicities and preclinical predictions continues to challenge ADC development and patient management. Treatments that appear tolerable in early studies can lead to unexpected adverse events in patients, complicating dosing decisions and long-term care. Join clinicians, clinical pharmacologists, and translational experts as they explore how to integrate clinical data, PK/PD insights, and real-world evidence to better interpret safety signals and inform treatment strategies by:

• Interpreting clinical safety signals to inform treatment decisions, exploring how systematic analysis of patient-level data can support dose modifications, treatment interruptions, and proactive toxicity management in clinical practice
• Leveraging translational and pharmacokinetic insights to contextualize toxicity risk, examining how physiologically based pharmacokinetic modeling and cross-species data can help clinicians anticipate adverse events, understand variability in patient response, and apply trial learnings to real-world populations
• Applying exposure-response relationships to guide dosing in the clinic, discussing how evolving dose optimization strategies, including those aligned with Project Optimus, can move toward individualized dosing approaches that balance efficacy and safety for different patient subgroups

• Attenuating payload platform toxicities through novel linker design
• Case studies for translatability of glucuronide linker ADC design with different payload classes
• Challenges of ADC toxicity assessment for linker-payloads with novel mechanisms of action

• Characterizing the mechanism of action of NMT inhibitors across tumor models, to understand their potential as highly potent ADC payloads
• Assessing the preliminary clinical safety and antitumor efficacy of Zelenirstat as an oral therapeutic, to establish its therapeutic window and translational potential for payload development
• Evaluating the initial performance of NMT inhibitors as ADC payloads, to determine their effects on targeted cytotoxicity, payload stability, and antitumor activity while minimizing off-target toxicities

• Leveraging a novel receptor-driven internalization mechanism to enable rapid, tumor-specific payload delivery, reducing systemic exposure and off-target toxicity compared to traditional ADCs
• Utilizing PDC architecture to achieve differentiated pharmacokinetics and improved safety profiles, addressing challenges associated with dual payloads and complex ADC formats
• Activating multimodal mechanisms of action to enhance efficacy while enabling safer combination strategies

• Profiling the molecular mechanisms of ADC-induced keratopathy using a human corneal epithelial cell model, to differentiate between payload-driven apoptosis and antibody-mediated inflammation, identifying specific interventions to block each pathway
• Validating a rabbit model for ocular toxicity that correlates with clinical findings for a panel of marketed ADC, to establish a robust non-clinical platform for ranking ocular safety liabilities, enabling confident lead selection for programs with a high risk ofocular tox
• Presenting Phase I/II data on novel prophylactic strategies, such as topical IVIG or targeted corticosteroid regimens, to demonstrate how proactive management can significantly reduce the incidence and severity of ocular adverse events, improving the overall risk-benefit profile for patients

As the ADC field rapidly expands beyond the established topoisomerase-I paradigm into dual-payload constructs, bispecific formats, and entirely novel toxin classes, the safety assessment playbook must evolve. With no historical safety data to rely on and toxicity mechanisms that may be fundamentally different from traditional ADCs, developers face an urgent need to establish new frameworks for predicting and mitigating risk.

Join preclinical safety leaders from biotech and large pharma as they share strategies for de-risking the next generation of ADC innovation by:

• Designing fit-for-purpose toxicology packages for dual-payload ADCs, debating whether standard NHP studies are sufficient to detect additive or synergistic toxicities, and exploring how staggered-dosing studies and payload-selective biomarkers can deconvolute the contribution of each warhead to the overall safety profile
• Assessing the unique liabilities of bispecific and biparatopic formats, discussing how altered binding avidity, internalization kinetics, and tissue distribution create novel safety challenges that require bespoke in vitro and in vivo models to accurately predict clinical risk
• Prioritizing novel payload classes by mechanistic profiling, evaluating how a standardized preclinical safety screening cascade, encompassing human primary cell panels, tissue organoids, and computational modelling, can rapidly identify the most promising payloads with differentiated toxicity profiles before committing to costly IND-enabling studies

• Rationally designing Auristatin S to improve the tolerability of auristatin payloads through the tuning of permeability and bystander activity
• Explaining how Auristatin S maintains key auristatin properties, including strong tubulin binding affinity and induction of immunogenic cell death
• Exploring Auristatin S improved preclinical therapeutic window