Evidence & development · Hypothetical consulting case

From HER2 to ESR1: the diagnostic can set the launch clock

A drug–diagnostic operating model turns assay availability, testing attrition and turnaround into measurable launch dependencies.

ClarusBIOTECH REVIEW

Read, listen & keep

Narrated by Hermione. Save the audio for offline listening.

Clarus Biotech Review · 10/2/2026 · 3 min read
An assumed precision-oncology patient funnel. Relevant cohort: 4000; Test completed: 2400; Marker eligible: 600; Treatment starts: 420. Patients per year. Entire graphic is hypothetical; categories are sequential, not additive.
Figure 1. Entire graphic is hypothetical; categories are sequential, not additive. Original Clarus quantitative visualization.
View figure data and context
An assumed precision-oncology patient funnel · Patients per year
MeasureValue
Relevant cohort4,000
Test completed2,400
Marker eligible600
Treatment starts420
Browse the research collection

The consulting assignment

A precision-medicine launch begins earlier than the first prescription. It begins when a clinician recognizes whom to test, obtains a usable specimen, receives an interpretable result and acts within the treatment window. That chain belongs in the target product profile and the launch budget. Otherwise the commercial forecast counts biologically eligible patients who never become operationally reachable.

The documented comparator

Herceptin’s original FDA approval was dated September 25, 1998 and specified HER2-overexpressing metastatic breast cancer populations. The historical case links treatment selection to evidence about tumor biology. It does not establish the prevalence, test performance or treatment conversion for today’s unrelated molecular programs. [1]

The current-news bridge

FDA’s September 4, 2026 camizestrant announcement also authorized Guardant360 CDx for ESR1 mutation identification. The more recent example makes serial testing during treatment a concrete workflow question rather than a generic precision-oncology slogan. [2]

Hypothetical client and numerical assumptions

Consider an invented launch region with 4,000 clinically relevant patients annually. Assume 60% receive testing, 25% of tested patients meet the modeled biomarker criterion and 70% of those initiate the hypothetical therapy. This yields 420 starts: 4,000 × 0.60 × 0.25 × 0.70. The assumptions describe a fictional product; they are not HER2 or ESR1 epidemiology.

What the numbers change

Improving test completion from 60% to 75%, with other assumptions fixed, raises starts to 525. That is 105 additional starts, not evidence that promotional activity caused them. A campaign may increase test orders while specimen rejection or delayed interpretation still suppresses completed care. The dashboard must follow completed tests and subsequent decisions, not only awareness.

Assume the intervention costs $300,000 and each additional completed start contributes $5,000 after product-variable costs. The modeled $525,000 contribution less intervention cost leaves $225,000 before fixed overhead. This is an explicit decision sensitivity, not a product margin claim. If only 40 additional starts materialize, contribution is $200,000 and the intervention does not recover its assumed cost.

Diagnostic partners need accountability for invalid results, turnaround, result delivery and clinician training. A study assay and a commercially deployable assay can impose different service dependencies. Even a technically strong test becomes weak infrastructure if nobody owns the handoff from laboratory to prescriber.

Testing improvement: modeled therapy starts. 60% tested: 420; 75% tested: 525; 90% tested: 630. Starts per year. Assumed 4,000 patients, 25% marker positivity and 70% initiation.
Figure 2. Assumed 4,000 patients, 25% marker positivity and 70% initiation.
Figure 2 data — hypothetical sensitivity
ScenarioStarts per year
60% tested420
75% tested525
90% tested630

The next decision gate

Use a 90-day pilot to audit every transition: order, sample, valid result, eligible finding, clinical decision and start. Compare similar sites and preserve rejected specimens in the denominator. Scale the program only when the incremental contribution case survives realistic conversion and service costs; biomarker-specific clinical use remains governed by the applicable authorization.

What to watch next

Expected issue to monitor: the economic value of repeated molecular testing depends on when results can change management. Track missed decision windows rather than assuming every repeat assay adds value.

Consulting scorecard — proposed measures, not observed product results
WorkstreamMeasure to collectDecision use
TestingValid completed tests / relevant cohortDistinguish orders from usable results
TimingResults returned before decision / testsFind losses that shorten the treatment window
AdoptionStarts / marker-eligible patientsAudit handoffs and access constraints

Reporting cutoff: October 1, 2026 Pacific. Later outcomes are not assumed. These tools illustrate decisions; they are not validated clinical, legal or investment prediction models.

Download the assumptions and KPI worksheet (CSV)

EDIT THE HYPOTHETICAL ASSUMPTIONS

Diagnostic-to-start conversion

Hold marker positivity at the fictional 25% used in the article; change the other funnel inputs.

Annual starts420patients

Starts = cohort × tested / 100 × 25% × initiation / 100.

Changing an input explores a scenario; it does not establish an observed result. Inputs stay in this page and are not submitted.

Download worksheet

THE NEXT VALUE INFLECTION

What would change the decision

Use a 90-day pilot to audit every transition: order, sample, valid result, eligible finding, clinical decision and start. Compare similar sites and preserve rejected specimens in the denominator. Scale the program only when the incremental contribution case survives realistic conversion and service costs; biomarker-specific clinical use remains governed by the applicable authorization.

Explore more in Evidence & developmentConnect this perspective to Value Inflection EngineeringVisit BioClarus Consulting

Editorial record

Prepared by Clarus Biotech Review editorial team. Updated 10/2/2026.

Publication relationship: ClarusReview is connected to BioClarus Consulting. No article-specific sponsorship is recorded.

Report a correction
Reading list & subscriptions
CLARUSREVIEW COMMUNITY

Discuss this paper

Open full discussion

Share evidence, ask a question, or offer a professional perspective. Community guidelines

Loading discussion…