Archives: Agenda

• Changing how researchers select potential patients for better success rates
• How to improve drug efficacy and patient safety before it’s too late
• Back to square one: Differentiating with simpler, patient-centric protocols and optimised study design
• Avoiding disappointing results by implementing the right technology tools to advance your trial
• Lessons learned to mitigate trial failures

Moderator: Sumeet Ambarkhane, Chief Medical Officer, Pathios Therapeutics

• Evolving Regulatory Environment: Significant regulatory reforms across Latin American countries aiming to align with international standards (e.g., ICH guidelines)
• Opportunities Arising from Regulatory Changes: Faster approval timelines enabling quicker trial initiation
• Role of Vendors in Fostering Opportunities: Need for vendors to adapt to local regulatory nuances and evolving compliance requirements
• Turning to Latin America for a genetically diverse population, valuable for global clinical research, but also understanding the need for culturally sensitive patient engagement strategies to improve recruitment and retention

• Improving the sense of security to reduce unnecessary suffering and distress for patients
• Understanding the different types of patients and their individual response behaviours
• Being hyper aware of cultural differences and biases to ensure sensitivity and effective outcomes for all
• Sharing best practice on effective strategies with case studies and examples to help reduce patient drop out rate

• An overview of CAR-T trial trends in Oncology
• How we can apply regulatory, design, logistical and operational lessons learned to the new wave of CAR-T trials in the rare disease space

• Challenges in securing initial funding/additional financing
• Expense associated with drug development
• Loss of new pharmaceutical technologies and cutting-edge compounds
• Impact on patients in need of options

• Design and implementation of an automated Data Management pipeline that standardizes key processes and reduces manual workload across studies
• Lessons learned from developing and deploying the Data Management pipeline across multiple clinical studies
• How automation and reproducible pipelines are shaping the future of Data Management and Clinical Data Science