How to draft CRO quotes faster with pricing checks and sponsor access controls

Where quote time actually goes

A request for quote rarely arrives in your format. One sponsor sends a two-line email asking for a kinase panel, while another attaches a spreadsheet of forty compounds with salt forms and concentrations. Requests from sourcing marketplaces come with their own fields. Somebody has to work out what is being asked before anyone can price it.

In many preclinical CROs that somebody is a business development manager working with a scientist. BD owns the relationship and the price. The scientist decides whether the design makes sense, which assay format fits, how many animals a study needs and what the sponsor forgot to mention. For catalog work such as single-point kinase screening or a standard mouse PK study, the mapping is routine. For a custom efficacy model or a GLP toxicology package it takes real thought.

The arithmetic is quick. The time goes into reading the request, matching each line to a catalog service, pulling the right price tier, writing assumptions and exclusions, and drafting questions back to the sponsor. Every hour a study director spends on a quote is an hour taken from a study.

Sourcing marketplaces set their own expectations on speed. Scientist.com advertises an average of 1.5 days from request to statement of work on its platform, a vendor claim, and Science Exchange offers sponsors one master services agreement covering thousands of providers. Sponsors who buy through those channels compare quotes side by side. Full proposals take longer. A 2018 Clinical Leader column on outsourcing said CROs typically need 10 to 20 business days to do a good job on an RFP, although it was written about clinical work.

What to automate and what to keep with people

A workable rule: let the agent do what a new BD coordinator could do with your catalog and price book in front of them, and keep anything that needs a scientist's judgment or a commercial decision.

The judgment calls are easy to name. A sponsor asking for a 14-day study may need recovery groups it did not mention, and any quoted start date has to fit the vivarium schedule. The agent's job on these is to state the question plainly and route the quote to the right person. It should never pick an answer just to make the quote look complete.

GLP or non-GLP is a quoting decision

One line on the request changes the whole quote. Under 21 CFR Part 58, a nonclinical laboratory study is an in vivo or in vitro experiment that studies a test article prospectively to determine its safety. The definition excludes "basic exploratory studies carried out to determine whether a test article has any potential utility". Kinase profiling and most efficacy pharmacology usually sit outside GLP. A repeat-dose toxicology study meant to support an IND sits inside it.

Inside GLP, the quote has to carry what the study will need: a study director, QA inspections, a protocol with the elements 58.120 lists, a final report with the contents 58.185 requires, and archiving under 58.190. Those costs are real and easy to leave out of a quote put together in a hurry. The agent can check every GLP request against a list of these line items and flag any that are missing. A person still confirms the study type with the sponsor whenever the request is unclear.

The same check works in the other direction. A request that asks for GLP on a discovery assay usually deserves a question back before anyone prices it, and the agent can draft that question too.

Controls that protect your sponsors and your margin

Confidentiality is the first thing to get right. A quote library holds compound names, targets, dose levels and prices for every sponsor you have worked with. An agent that searches the whole library for a similar past quote can copy one sponsor's details into another sponsor's proposal. Confidentiality here comes from your confidential disclosure agreements and master services agreements, and a slip like that breaks them.

We restrict retrieval by sponsor before the model sees anything, so the agent draws only on this sponsor's past work and on templates you have anonymized. We test for cross-sponsor disclosure as one of the acceptance criteria. The other controls are about pricing and commitments:

• The price book is the only source of prices, and every quote line cites the catalog item and price tier it came from.
• Discounts above a threshold you set and custom work route to business development for approval.
• Any change to study design, species, group size or assay format routes to a scientist.
• The agent never commits to a start date. It shows the scheduling data it can see, and a person commits.
• Every draft and approval is logged, so you can show a sponsor how a quote was put together.

Where the FDA draft guidance on AI fits

In January 2025 FDA published a draft guidance, "Considerations for the Use of Artificial Intelligence to Support Regulatory Decision-Making for Drug and Biological Products". It is still a draft, marked not for implementation. Its scope section says it "does not address the use of AI models (1) in drug discovery or (2) when used for operational efficiencies (e.g., internal workflows, resource allocation, drafting/writing a regulatory submission) that do not impact patient safety, drug quality, or the reliability of results from a nonclinical or clinical study."

Drafting a quote sits in the operational category. It touches no study data, and a person approves every price and design choice before the quote goes out. On our reading, that keeps quote drafting outside the draft guidance as written. If you later use the same agent on report drafting or data checks, the line moves, because those steps sit closer to the reliability of study results. The draft may become relevant wherever AI produces information that supports regulatory decisions, such as results from a nonclinical study. This is general information, not legal advice, so confirm applicability with your regulatory and legal teams.

Worked example: what the hours look like

This is an illustrative example with assumed numbers, not a client result. Take a discovery and DMPK CRO that receives 15 requests for quote a week. Today each one takes about 2 hours of combined time, most of it from BD and a scientist. That is 1,800 minutes, or 30 staff hours a week.

Now assume 9 of the 15 are routine, such as catalog panels or standard PK designs. With the agent drafting, BD and a scientist spend about 30 minutes between them reviewing and approving each one, so 270 minutes. The other 6 are custom, and we count them at the full 2 hours, another 720 minutes, even though the agent will usually save some time on those as well. Total time falls to 990 minutes, or 16.5 hours, which gives back 13.5 staff hours a week. The split between scientist and BD time depends on who reviews each draft.

Speed is the second number to watch. Routine quotes that go out the same day instead of later in the week can show up in your win rate before they show up in hours. Your ratio of routine to custom requests matters more than anything else here. If most of your requests are custom in vivo or GLP packages, the routine share may be closer to a third and the saving smaller, so count a real week before you trust any estimate.

Starting small with quotes

Pull last month's requests for quote and the quotes that went out. Tag each request as routine or custom and note roughly how long it took. Check that your catalog and price book are current, because an agent working from an old price book will produce wrong quotes faster. Then run an agent against copies of those requests with nothing going to sponsors, and compare its drafts with what your team actually sent.

That comparison is the core of the acceptance criteria we agree before we build. We scope one workflow with you and write down the tests it has to pass, such as the share of routine quotes approved without rework and zero content from another sponsor. Then we build it in your own Microsoft or AWS cloud tenant in two weeks. You pay $10,000 only after every criterion passes, and running it afterwards is optional, from $1,200 a month.

Common questions