A medical science liaison working a neurology territory in the mid-Atlantic will typically have between 8 and 12 HCP interactions per week. On a good week, two of those are substantive scientific exchanges with practicing neurologists or academic KOLs: the kind of meetings that require knowing not just the headline efficacy numbers from the flagship trial, but the patient subgroup data from Table 14.3.1, the specific dose adjustment language from Section 2.4 of the prescribing information, and the two-sentence caveat buried on page 38 of the clinical study report that matters when the physician asks about patients with prior biologic exposure.
Getting ready for that meeting takes time. How much time, and where it goes, is the question we have spent a lot of time thinking about at Argon.
The Documents an MSL Searches Before Every KOL Meeting
Before a complex HCP interaction, a well-prepared MSL is typically working from several different document types:
- The current prescribing information, particularly sections covering dosing, warnings, and the clinical studies summary
- The full clinical study report for the pivotal trial, or the trial the physician has published in
- Published reprints of key papers, especially recent ones the KOL may have co-authored
- Standard response documents or medical information letters for anticipated off-label questions
- Competitive landscape documents, particularly if a new trial data readout has come out recently
- CRM notes from prior meetings with this physician
That is six categories of documents before the first page is read. In a mature product portfolio, each category might contain multiple documents. An MSL carrying four products cannot hold all of that in working memory, nor should they be expected to.
Where the Time Actually Goes
The preparation problem is not remembering information. MSLs are trained scientists. A pharmacist or PhD carrying a cardiovascular product knows cardiovascular pharmacology. The problem is that the specific answer to the specific question the physician is likely to ask lives somewhere in a stack of PDFs, and finding it before a Tuesday morning meeting requires knowing which document, which section, and which page.
In practice, that search happens across at least three separate systems. Veeva Vault holds the formally approved product documents. SharePoint or a similar intranet holds training materials, field slides, and internal Q&A documents. Email holds the latest version of the competitive response document a medical director sent two weeks ago. CRM notes are in a fourth system.
None of these systems are indexed together. A question like "What does the label say about dose adjustments for hepatic impairment in patients on concurrent CYP3A4 inhibitors?" requires opening the prescribing information, navigating to the dosing section, cross-referencing the drug interactions section, and then confirming whether the most recent label version is the one you have open. That is a five-minute exercise for someone who knows where to look. It is a fifteen-minute exercise on a bad morning when Veeva is loading slowly and you are not sure whether the label was updated last quarter.
Multiply that across three or four anticipated question areas, add the time to read the physician's most recent publication and connect it to your product data, and a thorough pre-meeting prep for a single complex KOL interaction can take three to four hours. MSLs with heavy call schedules report that prep time is the primary constraint on how many substantive scientific exchanges they can sustain per week.
How Structured Q&A Retrieval Changes the Prep Sequence
The change we built toward at Argon is straightforward in concept: instead of navigating to a document and reading until you find the relevant passage, you ask the question in plain language and the system returns the answer with the exact source citation, section, and page behind it.
An MSL preparing for the hepatic impairment question asks it directly. The answer comes back with the specific language from Section 2.3 of the prescribing information, the table number, and the page. The MSL reads the source passage, confirms the answer is what they expected (or finds an update they did not know about), and moves on.
This is not the same as reading a summary. The citation requirement is the important part. Medical affairs operates in a regulated communication environment: an MSL citing clinical data to a physician needs to be citing what the document actually says, not what a summarization engine inferred it says. Source-grounded retrieval means the passage is surfaced alongside the answer, not instead of it. The MSL still reads the source. The change is that they find it in thirty seconds instead of eight minutes.
A Realistic Scenario
Consider an MSL preparing for a meeting with a hematologist who has been participating in a phase 3 extension study for a drug in the portfolio. The physician's own patient data is informing how she thinks about the product's long-term safety profile, and she is likely to ask detailed questions about the hepatotoxicity signal observed in the extension cohort.
That information lives in the clinical study report addendum, not in the prescribing information or the published papers. The addendum is a 400-page document. Without structured retrieval, finding the hepatotoxicity section, locating the specific grade 3 and grade 4 event rates by treatment arm, and cross-referencing the monitoring guidance takes meaningful time. With structured retrieval, the MSL asks the question directly and receives the table reference and passage, which they then read in the addendum before the meeting.
The prep still requires expert reading and clinical judgment. What changes is how quickly the right passage is in front of the person doing the reading.
What Does Not Change
We want to be clear about the boundary here. Faster retrieval does not replace the scientific judgment an MSL brings to an HCP interaction. The system surfaces the source; the MSL reads it, evaluates whether it answers the physician's likely question, and decides how to frame it within the bounds of the approved indication and company policy. That judgment call is not delegated to software.
Similarly, source-grounded retrieval is a preparation tool, not a real-time conversation assistant. An MSL is not querying a system mid-meeting. The value is in the thirty minutes before the meeting, when the difference between a prepared and an underprepared liaison comes down to how quickly they found the right page in the right document.
The Shape of a Different Preparation Workflow
The MSL teams we work with who have adopted structured retrieval tend to describe a consistent shift in how prep time gets used. Less time navigating to documents and scrolling to relevant sections. More time actually reading the passages that matter, making notes, thinking about how to frame data for a specific physician's clinical context.
One regional medical affairs lead described the shift as changing the prep task from "find the right page" to "think about what to do with the right page." That is the change that has downstream impact on conversation quality, not retrieval speed as an end in itself.
For medical affairs leaders thinking about MSL productivity, the relevant metric is probably not how many meetings per week each liaison attends. It is how many of those meetings are substantive scientific exchanges where the MSL was genuinely prepared at the level of the physician they were meeting. Retrieval speed is a precondition for that kind of preparation. It is not a substitute for it.