Biotech

A helpful biotech starter pack needs one regulatory process guide, one translational science lens, and one open computational toolkit people can actually learn from. That mix reminds the team that evidence, operations, and computation all need owners.

FDA and NIH material give the operating frame; scverse and related open tooling show how modern analysis work is actually being done. That combination is useful because it keeps the science and the operational path in the same conversation. The central debates are about how much platform optionality to preserve, when to narrow around a lead program, and what evidence threshold deserves clinical acceleration. Those questions are best answered with cash runway, operations, and regulator expectations in the room.

The tools that keep proving useful usually support literature and prior-art discovery tools, clinical operations planning systems, and regulatory and documentation workflows without making the underlying work harder to understand. When you bookmark something, write down why it earned the slot.

Three sources worth opening side by side:
- FDA drug development and approval process: fda.gov/drugs/development-approval-process-drugs
A grounding document for the path from development to review and approval.
- Addgene protocols: addgene.org/protocols/
Practical wet-lab documentation that is genuinely useful for day-to-day work.
- scvi-tools: github.com/scverse/scvi-tools
Open source probabilistic tooling for single-cell and spatial omics work.
- NIH video archive: youtube.com/@NIH/videos
Webinars and talks that help keep the science connected to real public research practice.