Industry Specific Commercialisation Playbook

Industry-Specific Commercialisation Playbook

Purpose

Tailor the commercialisation strategy and expectations by industry: life sciences, deep tech, software, societal/humanities-based innovations.

Based on

the owner's published commercialisation guide (owner, 2025). Chapter "Different Paths by Industry" (pp. 29-34) — case examples Vaccitech/BioNTech, IQM Finland/ArtiQ, DeepMind, the UK's Aspect programme.

• Life sciences: a long (10+ years), expensive, regulated pathway; often partnership/acquisition by a larger player later
• Deep tech: prototype and pilot production stages, specialised equipment, strong IP protection as an advantage
• Software: the fastest cycle, low capital need, often nothing patentable
• Social sciences/humanities: IP-light, "lean spin-out" approach (the UK's Aspect programme)

Method

1. Life sciences (pharma/biotech): expect a 10+ year pathway and significant capital; focus on early-stage evidence (preclinical/Phase 1) and partnership/acquisition later. University equity can justifiably be higher (up to c. 25%).
2. Deep tech / engineering: expect prototype and pilot production stages, specialised equipment and facilities. Strong patent protection is a competitive advantage. Seek deep industry expertise for advisors — a software-background mentor is not enough.
3. Software and digital innovations: the fastest development cycle, low initial capital, often nothing patentable (know-how/copyright/first-mover advantage). University equity is typically lower (≤10%). Speed and continuous iteration are decisive, not the original IP.
4. Social sciences/humanities/"impact" spin-outs: often IP-light, low capital need, fast revenue generation through consulting or a service. "Lean spin-out": minimal initial investment, fast customer interaction, iterative refinement.
5. Identify the regulatory environment early in every industry (FDA/EMA, financial regulation, energy certifications, education sector procurement rules) and secure an experienced advisor.
6. Summarise your own industry "playbook": pharma = patent–prototype– publish–partner (long, capital-intensive); deep tech = patent–prototype– prove in pilots–seek strategic investors; software = build fast–acquire users–pivot–scale; societal = prove impact–seek blended funding (grants + revenue).
7. Study prior spin-outs in your own field — which pathway did they take? (see ../../references/case-studies.md).

Gotchas

• The four archetypes (life sciences, deep tech, software, social science/humanities) are illustrative buckets from the guide's case examples, not an exhaustive taxonomy — a result that straddles two (e.g. an AI-driven diagnostic device) should default to the higher-friction pathway's regulatory and IP assumptions, not the faster one's.
• The equity benchmarks (≤10% software, up to ~25% life sciences) are indicative ranges, not your institution's actual terms — use them as a sanity check on a number the TTO proposes, then confirm the real figure via tto-engagement-strategy and ip-disclosure-and-ownership-check.
• Step 2 explicitly says a software-background mentor is "not enough" for deep tech — satisfying the advisor requirement with whoever's already on the team, rather than someone with the specific industry expertise, misses the point of the step.
• The timelines and cost figures are explicitly indicative (see "does NOT do") — quoting "10+ years" or "fastest cycle" to a funder as a commitment rather than a planning heuristic overstates what the guide's examples actually support.
• Step 7 (study prior spin-outs in your field) only transfers cleanly when the comparison case shares both sub-domain and regulatory regime — a similar-looking spin-out under a different regulator (e.g. FDA vs. EMA) can lead to copying a pathway that doesn't actually apply.

What this skill does NOT do

• Does not perform regulatory classification for you (e.g. EU AI Act classification of an AI system) — use separate regulatory expertise.
• Does not give a precise timeline or cost estimate — the examples are indicative, not guarantees.

Continue from here

• Next in this pack: ../funding-pathway-design/SKILL.md — Build a funding strategy that combines non-dilutive and dilutive funding in the right order, and manage runway.
• Pack's shared guardrails: ../../CLAUDE.md
• Overview of the full journey: ../commercialisation-journey-roadmap/SKILL.md

References

• ../../references/case-studies.md — 7 spin-out examples from different industries and regions
• ../../references/terminology.md — the handbook's glossary
• ../../references/sources.md — the handbook's own source references
• ../../CLAUDE.md — the pack's shared guardrails