SPEAKERS

CASE STUDY DAY 2

Recent Advances in Maximising Clinical Trials Recruitment Predictability

The advanced analytics statistical methodology for modelling and forecasting patient recruitment is proposed. It allows forecasting recruitment at different levels (site/country/region) and re-projecting and optimally adjusting recruitment using interim data and Bayesian technique. The technique for optimal selecting sites/countries at the design stage to complete recruitment in time with a given confidence accounting for cost/time constraints is also presented.
Further developments to forecasting event counts in event-driven trials accounting for ongoing recruitment are also discussed.

• Modelling and forecasting recruitment at different levels
• Optimal trial design accounting for countries/cost/time constraints
• Data-driven interim re-projecting and optimal adjustment of recruitment
• Forecasting event counts in event-driven trials

CASE STUDY DAY 2

Clinical Trial Transparency and Patient Centricity

Clinical Trial Transparency has been improved over the past years. However, in terms of patient centricity, there is still much room for improvement: Although clinical trial results have been published for quite some time, this has mostly been done using scientific language not easy to understand for patients or other laypersons. Patient centricity requires the translation of clinical trial result into a language that can be understood by a non-scientific audience. Article 37 of the EU Clinical Trial Regulation has implemented this requirement and sponsors need to set up new processes to comply.

CASE STUDY DAY 1

Co-Creating Win-Win Success

The success of clinical trials begins with understanding what 'great' looks like from a participant’s perspective, in addition to a regulatory perspective. The two are now united in advice from the EMA and FDA both, and as such engaging disease experience experts (aka 'patients') from the get-go is a must.

• Co-creating R&D: An example on a partnership for change
• How related engagement may look like
• How win-win outcome may look like

CASE STUDY DAY 1

How Data-Driven Approaches Can Complement the Business Recruitment Efforts

How advanced analytics and emerging technologies can enable the business to achieve the recruitment goals? How real-world data can contribute in that direction and support the business to identify eligible patients on certain indication and geographies?

• Machine learning for protocol feasibility
• Predictive analytics to identify the high performing sites
• RWD + in-house data + new data: Will they provide new insights and support the decision-making?
• Challenges and opportunities in adopting AA techniques throughout the recruitment

CASE STUDY DAY 1

Challenges and Uncertainties from Patient Perspectives

In this presentation the speaker will focus on the topics connected with
his Editorial and some others which focus on patient perspective in relation
to patient enrolment and retention in clinical studies.

• COVID-19 vaccine, patient safety
• Challenges and uncertainties
• Patient recruitment and retention in clinical studies