Contact person: Business Client

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Location: New Delhi, India

Budget: Recommended by industry experts

Time to start: As soon as possible

Project description:
"I am building a proof-of-concept platform that shows how artificial intelligence can accelerate early-stage drug discovery in biotechnology and molecular biology. The MVP must let a scientist log in, upload raw protein or gene data, run an automated analysis that predicts promising drug interactions, and then explore those interactions through an interactive molecular viewer.

For the initial demonstration I want to concentrate on cancer-related targets—think p53, KRAS and similar oncogenic proteins—so the workflow has to accept the typical file formats researchers already use and return clear, reproducible affinity scores or other relevant output that a bench scientist could validate.

Key expectations
• Secure data upload and storage
• A back-end model that ingests the sequence or structure and produces drug-binding predictions in reasonable time
• A web interface that turns those predictions into real-time, manipulable 3-D visualizations (rotate, zoom, highlight residues, export images)
• Simple reporting and the ability to download raw results for offline analysis
• Concise technical documentation covering set-up, architecture, and how to extend the target library beyond the cancer focus

The code should be clean, version-controlled, and deployable on a standard cloud stack so I can share the demo with stakeholders. If you have experience uniting bioinformatics tooling with modern AI frameworks and a flair for intuitive front-end visualizations, I’d like to see what you can do." (client-provided description)