MASCC Webinar: Prediction of Oral and Gastrointestinal Mucosal Toxicities

Agenda:

1. Introduction – Paolo Bossi, MD (Chair)
2. The Experience of Nausea and Vomiting: How to Design a Clinical Predictor of a Treatment-Induced Adverse Effect – George Dranitsaris, PhD

Objectives: 

• • Understand the steps in developing toxicity risk prediction tools in oncology, with a focus on nausea and vomiting
  • Illustrate the clinical application of toxicity prediction tools in oncology
  • Demonstrate how toxicity prediction tools can be used to improve the efficiency of clinical trials in oncology

3. Predicting Oral and GI Toxicities in Supportive Oncology: Leveraging Clinical Data to Prevent Nutritional and Pain Consequences – Mellar Davis, MD

 Objectives: 

• • Drug-Related Genetic Risk Assessment: identify DPYD variants associated with 5-FU and capecitabine toxicity UGT1A1 conjugate associated with irinotecan mucositis and diarrhea
  • Individual Genomic Risk Factors: name at least 3 of the 4 categories of individual genetic risks: drug transporters, genes involved in DNA repair, inflammatory signalling pathways, epithelial healing genes
  • Clinical Application: correctly sequence opioid selection as: First line: Morphine (preferred over oxycodone). Second line: Buprenorphine and hydromorphone (preferred over methadone, all three preferred over fentanyl). Contraindicated: Codeine and tramadol (due to CYP2D6 dependence)
  • Treatment Protocol: identify benzylamine as the preferred initial intervention before morphine (where available)

4. Emerging Predictors of Oral and GI Toxicities: From Biological and Microbiome-based Models to AI Models – Akshat Singhal, PhD

Objectives: 

• • Describe the significance of biologically-informed AI models in patient care, including treatment and toxicity prediction
  • Examine a chemotherapy resistance model and discuss methods to extend such models for toxicity prediction

5. Q&A
6. Closing Remarks

Financial support provided by Nestlé Health Science.