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Build vs Buy — Biotech
Weigh SaaS subscriptions against a custom build for Biotech — see the multi-year total cost of ownership and which path wins.
What this means for Biotech
- R&D timelines are 10-15 years and the cost per approved drug is in the billions — every operating decision is filtered through 'how does this affect time-to-IND, time-to-readout, time-to-NDA'.
- FDA and EMA regulatory readiness is non-negotiable — the IND, the NDA, the BLA, and every clinical trial design has to survive regulator examination, and the documentation infrastructure has to be audit-ready continuously.
- Clinical trial operations are the largest single line of cost — site selection, patient recruitment, monitoring, data management, and trial conduct are operationally intense and the largest leverage on cycle time.
Where it pays to act
- AI for drug discovery and lead optimization — protein structure prediction (AlphaFold-class models), generative chemistry, target identification, and lead optimization that compresses early-discovery timelines.
- AI for clinical trial design and operations — patient recruitment optimization, site selection ML, protocol design support, and trial-monitoring AI that compress the largest single cost line in R&D.
Adjust the inputs to match your Biotech context.
Total cost of ownership
SaaS total (3yr)
₹19.9 L
Custom build total
₹21.8 L
Difference (cheaper to buy)
₹1.89 L
Breakeven
—
What this means
A hybrid path fits best.
For Biotech, the gap is ₹1.89 L over 3 years — close enough that a hybrid approach (buy core, build differentiating layers) often wins.
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Build vs buy — summary
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