Submit a Challenge
Engineering students from across Poland will spend a focused sprint building AI solutions for real pharma problems — submitted by you.
How it works
Submit
Fill in the form below with your problem statement
Review
The organising committee evaluates each submission
Assignment
Selected challenges are assigned to student teams on the day
Sponsors are invited to submit first, but we welcome challenges from anyone in pharma, biotech, medtech, or adjacent fields. The winning team presents at the main conference on October 26–27.
What makes a strong challenge
Four things that separate problems teams can actually solve from ones they can’t.
Teams won’t have access to your systems. Describe what you can share — anonymised records, synthetic data, sample exports, or public sources — and flag any constraints upfront. No data path, no start.
Teams have 4–8 hours. Frame it as a proof-of-concept: „show that X is possible” not „build production-ready X.” The strongest submissions have a narrow, testable core that can be demonstrated end-to-end on the day.
What does a good solution look like? Even a rough rubric — accuracy threshold, output format, processing speed — gives teams a target and judges a basis to evaluate. Vague goals produce vague results.
If the problem lives in a GxP environment, say so. Knowing that a solution must be audit-traceable, or that data provenance matters, shapes how student teams approach it — and makes outcomes more meaningful to you.
Submit your challenge
All required fields must be completed. We’ll confirm receipt and follow up if we have questions.
Ideas and areas to draw from: extracting structured data from CSRs, SOPs or batch records · adverse event detection from unstructured text · mapping submissions to regulatory guidance · anomaly detection in manufacturing data · clinical trial protocol review · SOP deviation or CAPA classification · making clinical trial processes more understandable for patients · helping identify drug interactions from unstructured sources · supply chain analysis to anticipate or respond to medicine shortages.
Questions about submitting a challenge? aiinpharma@ispe.org.pl