A biotech case study should document one of three things: a research partnership, an application of your platform or assay, or a change in lab workflow or throughput. Keep every scientific statement linked to an approved source, attribute every figure to the dataset or person it came from, avoid extrapolating from one partner's result to a general claim, and secure the partner's written approval for naming and quotes. The result is a document a BD lead can send to a prospect scientist without flinching.
Key takeaways
- Scientists are the audience. Write for a reader who will check your numbers, because they will.
- Three story types work: research partnerships, platform or assay applications, and lab workflow and throughput changes.
- One partner's result is one partner's result. Never let it become a general claim about the platform.
- Keep scientific data and attribution linked to approved sources. The source ledger is your friend in a technical review.
- Partner approval covers naming, data citation, quotes, and sometimes publication timing. Ask about all four up front.
Who reads a biotech case study?
Usually a scientist or a scientific leader deciding whether your platform, service, or reagent fits their programme, and often a business development counterpart deciding whether to take the next meeting. Both readers are trained to spot overclaiming. A case study that uses marketing adjectives where a scientist would use a number loses them in the first paragraph.
Write accordingly. State the question the partner was trying to answer, what they did, what they observed, and what it meant for their programme. Attribute everything. Let the reader draw the conclusion.
Which biotech stories make good case studies?
- Research partnership stories. How a collaboration was structured, what each party contributed, what was learned, and where it led. These support BD conversations about future partnerships because they show how you work, not just what you sell.
- Platform and assay application stories. How a partner applied your technology to a specific problem: the sample types, the workflow, the readout, and what the data enabled them to decide. These are the technical proof prospects ask for.
- Lab workflow and throughput stories. How a lab changed its process after adopting your product: validation time, hands-on time, samples per week, turnaround. These are measurable without touching scientific claims about results.
Avoid stories that depend on unpublished efficacy data, that involve investigational products in a way that could be read as promotion, or where the partner's result is still under embargo. Those are not case studies yet; they are future case studies.
How do you keep the science honest?
Four disciplines, applied to every draft.
- Link every scientific statement to an approved source. A publication, a poster, an internal report the partner has cleared, or a dataset the partner has agreed can be cited. If the source is not approved, the statement waits.
- Attribute every figure. "Validation time fell to four weeks on average" needs the measurement period and the record it came from. "The lab director estimates roughly a third less hands-on time" is attributed as an estimate and stays an estimate.
- Do not extrapolate. One partner reducing validation time on four assays is a story about that partner. It is not evidence that your platform reduces validation time. The draft should say the first thing and never imply the second.
- Preserve the partner's own language for their science. If they describe their assay a particular way, use their description. Paraphrasing science introduces errors that a technical reader will catch.
This is the same substantiation discipline that applies to medical device case studies, with the difference that the reviewer is often the partner's own scientific lead rather than your regulatory team.
How do you get a research partner to approve a case study?
Partner approval is where biotech case studies most often stall, because the partner has more to protect than a typical customer: their data, their publication plans, their relationships with other vendors, and sometimes their investors' expectations.
Ask about four things before drafting, not after.
| Question | Why it matters |
|---|---|
| Can the partner be named, or must the story be anonymised? | Many academic and early-stage partners will approve "a mid-size diagnostics lab" but not their name. Knowing this shapes the whole draft. |
| Which data can be cited, and from which source? | Partners often agree to cite published or presented data but not internal results. Get the list in writing. |
| Who approves quotes, and can they be attributed by name or by role? | Institutional communications offices frequently require sign-off on any staff quote. |
| Are there timing constraints? | Embargoes, pending publications, and financing rounds can all delay approval. Better to know now than at final draft. |
With those answered, give the partner a draft where every data point is already attributed and every quote is already marked as pending their approval. Partners approve faster when they can see that nothing has been added to what they supplied.
How should a biotech case study be structured?
- The partner and the question. Who they are (named or described), what programme or problem they were working on, and what they needed to find out or improve.
- Why they chose the platform. What they evaluated, what the deciding factor was. For biotech this is often a side-by-side on the partner's own samples, data compatibility, or support during validation.
- What they did. The workflow, sample types, timeline, and what was hard. Keep the partner's own descriptions of their science.
- What they observed. Attributed data with periods and sources. Qualitative observations attributed to the person.
- What it enabled. The decision or next step the data supported. This is the most useful section for a prospect, and the one most case studies forget.
A pull quote from the partner's scientific lead, approved in writing, usually does more than any amount of copy.
How do BD teams actually use case studies?
Rarely as a PDF attached to a cold email. More often as a one-page brief sent after a first conversation, as a link in a follow-up, as a slide in a partnership deck, and as a LinkedIn document post around a conference. That is why the written story should ship with a sales brief, an email snippet, social excerpts, and a web version, which is what the Complete Case Study Kit delivers. A story that only exists in one format gets used once.
The results guide covers how to collect partner data in a form you can actually cite.
Frequently asked questions
Can a biotech case study cite unpublished data?
Only with the partner's explicit written agreement, and usually only in the form they specify. Many partners restrict case studies to data that has been published or presented. Get the list of citable sources in writing before drafting.
Should a biotech case study name the partner?
Only with written permission. An accurate anonymised description with attributed data is credible to scientific readers and far easier to get approved. Offer the anonymised option early rather than as a fallback.
How technical should a biotech case study be?
As technical as the reader needs to judge whether the application fits their programme, and no more. Keep the partner's own description of their science, state sample types and readouts, and avoid both marketing adjectives and unnecessary methods detail.
Can one partner's result be used to claim the platform works in general?
No. One partner's result is evidence about that partner's application. The case study should describe it precisely and let readers draw their own conclusions. General performance claims need their own substantiation.
Can you produce a biotech case study without interviewing the partner?
Yes, if you have the material: call transcripts, email threads, the partner's own descriptions, and the data they have agreed can be cited. Case Study Works drafts entirely from uploaded material and marks every statement for the partner's review.
A partner story a scientist can read without flinching
Upload the partner's materials and the sources they've cleared. Get a first draft with every data point attributed within two business days of a complete intake.
Written Case Study from $1,495. Complete Case Study Kit $3,495. Pay online, then complete the intake. No calls.