GenAI
GenAI That Works in Pharma
Why build-vs-buy is the GenAI decision that quietly makes or breaks your AI program — and how partnerships outperform internal builds in life sciences.
- 5 pages
- 7 min read
Overview
Every Sponsor, CRO, and biotech now faces the same question about generative AI: build it in-house or partner with a purpose-built platform?
This paper makes the case that for commoditized, regulated work like medical writing, internal builds are hard to scale and maintain — a compliant, usable tool can cost over $1M to build, plus 15–25% of that each year — while specialized partners deliver purpose-built regulatory workflows, embedded quality control, and centralized audit trails without the maintenance burden. It frames an objective make-vs-buy analysis and shows, through a CRO case study, how a partnership accelerated informed consent development.
What’s inside
- 01Executive Summary
- Why internal GenAI development in life sciences is difficult to scale, hard to maintain, and resource-intensive — and why specialized partners deliver broader capabilities and faster time to value.
- 02The Rise of GenAI in Life Sciences
- AI’s momentum across drug discovery, documentation, and regulatory work — and the build-or-partner decision every Sponsor now faces.
- 03The Appeal of Internal GenAI Development
- The honest reasons teams reach for an in-house build: IT influence, subject-matter ownership, customization, and perceived cost savings — and where each one breaks down.
- 04The Hidden Challenges of Going Solo (Table 1)
- Resource reliance, limited use cases, compliance risk and ongoing training, high initial investment, and capacity constraints laid out side by side.
- 05What You Gain When You Partner
- Purpose-built regulatory workflows, rules-based rigor, embedded quality control, configurable platforms, and centralized audit trails you’d otherwise have to build from nothing.
- 06How Strategic Partnerships Deliver Better Results (Table 2)
- Broader capabilities, faster time to value, lower and predictable costs, built-in compliance, and innovation without the maintenance burden.
- 07Case Study: Accelerating Informed Consent Form Development
- How CRO MMS used a GenAI-driven solution to simplify patient-facing language and shorten ICF development cycles — without building a new AI system in-house.
- 08Choose the Path That Moves You Forward
- A pragmatic close on adopting AI the right way: start from strength with proven solutions rather than from scratch.
Who it’s forSponsors, CROs, biotech & pharma leadership, and IT / digital-transformation teams
What you’ll take away
- Understand why internal GenAI builds targeting commoditized processes like medical writing so often deliver neutral or negative ROI over time.
- See the hidden costs of going solo — a compliant, usable GenAI tool in pharma can run over $1M, plus 15-25% of that cost in maintenance every year.
- Learn what’s genuinely hard to replicate without dedicated teams: purpose-built regulatory workflows, embedded QC and review layers, audit trails, and access to cross-company best practices.
- Run an objective Make vs. Buy analysis so the promised savings are measured honestly rather than on metrics that can be manipulated.
- Follow how CRO MMS accelerated informed consent form development through a GenAI partnership instead of building a new system from scratch.
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Inside this guide
- Executive Summary
- The Rise of GenAI in Life Sciences
- The Appeal of Internal GenAI Development
- The Hidden Challenges of Going Solo (Table 1)
- 5 pages
- 7 min read
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Frequently asked questions about GenAI in pharma
Should we build GenAI in-house or partner?
For commoditized, regulated processes like medical writing, building GenAI in pharma from scratch often delivers neutral or negative ROI. A compliant, usable tool can cost over $1M to build, plus 15–25% of that each year to maintain — the paper lays out an objective make-vs-buy analysis.
What’s hard to replicate with an internal GenAI build?
Purpose-built regulatory workflows shaped by ICH guidelines, embedded quality-control and review layers, centralized audit trails, and cross-company best practices — capabilities that are difficult to sustain without fully dedicated teams.
Does partnering mean losing control or customization?
No. Configurable, purpose-built platforms offer customization within compliant guardrails, faster time to value, and predictable costs. The paper includes a CRO case study where a partnership accelerated informed-consent development.
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