OsirisInc

Case studies

Our work,
honestly labelled.

A Medical Affairs launch program worked across twelve workstreams as an illustrative scenario, and two systems we built ourselves. All of it operational, all of it honest about its limits.

About this work

The launch programme is a worked demonstration of our operating model, run end to end on a synthetic dataset. The twelve workstreams, gates and measures are the ones we bring to an engagement; the programme, product, indication and every figure are modelled, and show how the model behaves rather than any client’s results.

Congress Tracker and the Social Listening & Evidence Engine are in-house builds on seeded data. They carry no outcome metrics.

Illustrative scenario · synthetic dataset

Rebuilding a Medical Affairs launch program

Twelve workstreams, each starting from a decision the department could not make.

01 · Strategy

Launch strategy reset

The problem. The draft medical plan contained 47 activities, 14 unranked evidence questions, and no explicit decision rights.

What we did. Facilitated an evidence-and-insights workshop; reduced the plan to five imperatives; cascaded objectives into 18 initiatives; assigned accountable owners and quarterly measures.

Result. 100% of initiatives linked to an imperative; 6 duplicative activities stopped; leadership approved a single 180-day plan.

Artifacts
Annual Medical Plan; objective cascade; RACI; decision log; strategy deck

02 · Insights

Stakeholder prioritization

The problem. Coverage expectations were uniform despite large differences in scientific expertise, patient population, research role, and unmet educational need.

What we did. Scored 36 synthetic experts on scientific relevance, network role, evidence-generation fit, unmet need, and engagement objective; calibrated tiers as a team.

Result. Top-tier coverage increased from 58% to 83%; low-value repeat contacts fell 21%; every priority expert had a documented scientific objective.

Artifacts
Stakeholder map; territory plans; engagement tracker; field dashboard

03 · Insights

Insight-to-action engine

The problem. Field notes were rich but unstructured; themes could not be quantified, validated, or tied to decisions.

What we did. Introduced a controlled taxonomy, confidence score, verbatim/interpretation separation, duplicate handling, and a monthly cross-functional synthesis council.

Result. 48 insights became 4 validated themes; 3 content changes and 1 evidence concept were approved; action aging became visible.

Artifacts
Insight taxonomy; insights log; insight-to-action dashboard; monthly readout

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04 · Evidence

Evidence-gap prioritization

The problem. Twenty-two ideas competed for a constrained evidence budget, often supported by advocacy rather than transparent criteria.

What we did. Ranked six evidence gaps, then scored 10 concepts for patient relevance, scientific value, decision impact, feasibility, time-to-answer, and risk.

Result. Three concepts advanced: natural-history RWE, treatment-pattern study, and patient-burden qualitative work; low-value duplication was avoided.

Artifacts
Evidence gap map; concept scorecard; IEP; evidence investment pitch

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05 · Publications

Publication rescue

The problem. Two congress abstracts and three manuscripts had inconsistent owners, data-cut dates, and author-review assumptions.

What we did. Built a dependency-based publication plan with author agreements, review windows, disclosure checks, and red/amber/green milestone rules.

Result. Critical-path slippage surfaced 10 weeks earlier; four risks received owners; one low-priority manuscript was resequenced.

Artifacts
Publication plan; author tracker; milestone dashboard; congress planner

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06 · External

Advisory-board conversion

The problem. The prior advisory board produced a long transcript but no structured synthesis, prioritization, or accountable follow-through.

What we did. Designed six decision-linked questions; coded notes against evidence, practice, education, and implementation themes; separated individual comments from aggregated interpretation.

Result. Seven insights were validated, six actions assigned, and 83% of actions closed or on track at the 30-day review.

Artifacts
Briefing book; discussion guide; readout deck; action log

07 · Medical information

Medical-information service

The problem. Complex inquiries rose around subpopulation evidence and administration; leaders could see volume but not service risk or recurring content needs.

What we did. Added complexity, topic, channel, escalation, approved-source, response-time, and content-gap fields; established 2-day standard and 5-day complex SLA targets.

Result. Overall on-time response reached 91%; two recurring inquiry clusters triggered new response documents and MSL refreshers.

Artifacts
Inquiry log; SLA dashboard; content-gap trigger; escalation matrix

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08 · People

MSL readiness

The problem. All MSLs completed training, but observed scientific-exchange performance varied and two high-risk modules lacked documented remediation.

What we did. Added knowledge checks, role-play rubrics, observed field certification, coaching plans, and quarterly recertification dates.

Result. Certification rose from 63% to 88%; all remediation had owners and due dates; readiness became evidence-based.

Artifacts
Curriculum map; certification tracker; coaching log; readiness dashboard

09 · Governance

Launch-readiness governance

The problem. Readiness was reported through narrative updates that masked dependencies between people, content, systems, and evidence.

What we did. Created a six-domain scorecard with objective evidence, threshold definitions, milestone owners, and a cross-domain dependency log.

Result. Readiness improved from 61% to 82%; three red dependencies were escalated; the executive committee approved targeted recovery actions.

Artifacts
Launch scorecard; risk register; dependency log; launch-readiness deck

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10 · Operations

Budget reallocation

The problem. The budget view grouped spend by vendor and cost center, making it hard to test whether resources followed strategic priorities.

What we did. Mapped forecast and actuals to objectives, initiative type, evidence gap, geography, and quarter; added committed-versus-flexible categorization.

Result. $420K moved from low-impact events and duplicated vendors into RWE, content remediation, and field capability; forecast variance fell below 5%.

Artifacts
Budget model; capacity view; initiative portfolio; investment memo

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11 · Congress

Congress command center

The problem. Abstracts, scientific exchange plans, expert meetings, booth staffing, intelligence questions, and debrief actions lived in separate trackers.

What we did. Built one milestone plan with workstream owners, dependencies, scientific objectives, coverage map, daily synthesis, and post-congress action capture.

Result. All critical milestones met; 22 insights captured using the common taxonomy; debrief actions assigned within five business days.

Artifacts
Congress planner; coverage grid; daily huddle; congress debrief deck

12 · Leadership

Monthly executive value story

The problem. Leadership reviews overemphasized activity counts, obscuring quality, learning, evidence progress, service, readiness, and risk.

What we did. Balanced the scorecard across reach, quality, insight impact, evidence/publication, medical information, people readiness, budget, and compliance.

Result. The monthly review shifted from reporting to decisions: three risks escalated, two resources reallocated, and four actions closed.

Artifacts
Executive dashboard; narrative KPI commentary; QBR deck; decision log

How it was measured

Eleven KPIs, each with a definition.

Each has a written definition, a threshold and a stated interpretation — so a number moving meant something specific rather than inviting a story.

Measure Target What it is for
Priority expert coverage≥80% monthlyReach, without rewarding raw volume
Engagement quality≥4.0 / 5Preparation, relevance, exchange, outcome, follow-up
Insight action rate≥60%Learning actually converted into decisions
Evidence on track≥80%Portfolio delivery health
Publication on track≥85%Scientific communication execution
Medical information on time≥90%Service reliability against SLA
Advisory actions on track≥80%External engagement follow-through
MSL certified≥85%Capability, not course completion
Launch readiness≥80% at T−3Cross-domain execution
Budget variancewithin ±5%Resource control
Safety routing confirmation100%Process completeness — explicitly not a safety-system metric

The measurement guardrail

No field or insight metric was linked to prescriptions, market share, or individual prescriber behaviour, and no ranking rewarded contact volume absent scientific purpose. Trends prompted a review; they were never allowed to stand as conclusions. Adverse events and product-quality complaints routed immediately through the company’s own process — no dashboard sat between a signal and a report.

In-house prototypes

What we’ve built ourselves.

Two working systems built in-house to show how a governed Medical Affairs workflow holds together end to end. Both run on seeded, non-client data. Neither carries outcome metrics, because neither has a client engagement behind it.

In-house prototype · seeded data

Congress Tracker

The problem. Abstracts, scientific exchange plans, expert meetings, booth staffing, intelligence questions and debrief actions each lived in a separate tracker.

What we built. One milestone plan carrying workstream owners, dependencies, scientific objectives, a coverage map, daily synthesis and post-congress action capture.

Honest limits. Seeded, non-client data. No outcome metrics are claimed for it.

In-house prototype · seeded data

Social Listening & Evidence Engine

The problem. Scientific signal is scattered across public sources with no shared taxonomy, no confidence handling and no path into a decision.

What we built. A retrieval pipeline across public sources, each behind its own fallback chain, with connector status surfaced in the interface.

Honest limits. Counts are per-scan retrieval volumes, not results. No client engagement sits behind it.

Connect with an expert

Tell us where AI is stalling in your Medical Affairs organisation, and we’ll come back with a concrete view of what a governed approach would look like.

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