Clinical trial landscape analysis
Inspired by publicly reported work at Novartis
Map clinical trials for a disease (phases, sponsors, countries, delays) from the public trial registry.
The brief
Novartis has written about data42, which brings decades of its clinical trial data together so data scientists can find new insights. Do a public version: pull trials for one disease from the open trial registry, map them by phase, sponsor, country and status, and find which trials stop early or run late. Good looks like: a reproducible data pull from the API, a clean trial table, clear charts, and three findings a research team could use.
Read the case first
What Novartis has said in public about this kind of work, on its own pages:
Make it your own
Study trials that matter in India: tuberculosis, dengue, diabetes or sickle cell disease, and compare trials run in India with the rest of the world. Add the Clinical Trials Registry of India by hand for a sample, if you can.
AITeky has no link with Novartis, which has not reviewed or endorsed this brief. The brief only draws on what the company has published, uses open data rather than its data, and is a learning exercise: don't present your project as Novartis's work or system.
What you will build
- Pull trials for one disease from the ClinicalTrials.gov API
- Clean phases, sponsors, countries and dates
- Map trials by phase, sponsor and country
- Find early stops and delays and their stated reasons
- Write three findings for a research team
Free, open data to build it with
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