Planning
Activation
Engagement
AI & Insights
General
Insights
.png?width=20&height=21&name=Frame%20(1).png){kind=small}
About
Webinar
Stop Guessing, Start Enrolling
A data-driven approach to trial forecasting — and to fixing enrollment before the timeline does it for you.
Most enrollment forecasts are one line on one slide: a target, a curve, and a hope. When sites underperform, that model can't tell you why — or what to do next. In conversation with leaders from CSL Behring and Merck, we'll walk through what a defensible forecast looks like in practice.
Save your seat
Free to attend. Registration closes when the room fills.
Practitioners who defend these forecasts internally
Chris Conklin
Triathlete. Treats enrollment timelines the same way — pace it wrong early and the back half hurts.
Ed White
Loves dogs, trains, planes, and free boats. Ask him about the boats — there is an explanation.
Joseph Kim
Asks the question everyone in the room is already thinking. Collects enrollment horror stories.
Four things a real forecast does that a single curve can't
Use benchmarks that actually apply
How to select comparator studies with predictive value — and how to recognise when a benchmark is quietly setting you up to miss.
Model inputs, not outcomes
Build scenarios from site activation, referral volume, and screen-fail rates instead of back-solving a curve from the date you promised.
Diagnose the delay before you spend
Tell a site problem from a protocol problem from a funnel problem — the three look identical on an enrollment chart and need opposite responses.
Choose interventions in combination
What adding sites, expanding geography, amending criteria, and funding outreach each realistically buy you — and how they interact.
Bring the study that's behind
60 minutes, online. Free to attend.
Reserve my seatCan't make it live? Register anyway and we'll send the recording.
%201.svg)
