10 Critical Questions Every Pharma Team Must Answer 6 Months Before a Drug Launch

Six months before a drug launch is when most teams shift into execution mode.

Slide decks get finalized. Sales training ramps up. Messaging is refined.

But in reality, the outcome of your launch is already being shaped — not internally, but in the market.

Physicians are already deciding what they trust. Referral pathways are already determining where patients flow. Health systems are already aligning around treatment protocols.

By the time your therapy reaches its PDUFA date, much of the groundwork for adoption has already been laid.

The difference between a strong launch and a slow one often comes down to whether you can answer these ten questions — clearly, confidently, and with data.

1. Do We Actually Know Who Is Treating Our Patients?

Most teams begin with a specialty lens. Oncology, cardiology, neurology. It’s a logical starting point, but it is not precise enough for modern commercialization.

In oncology especially, physicians within the same specialty can have dramatically different patient mixes. One oncologist may treat a high volume of metastatic cases aligned to your therapy, while another focuses on early-stage disease or entirely different tumor types.

The only reliable way to distinguish between them is through diagnosis-level data. ICD-10 coding exists specifically to capture this clinical nuance (see the Centers for Medicare & Medicaid Services ICD-10 overview)

For example, a company launching a therapy for metastatic colorectal cancer should not be targeting “oncologists in the Midwest.” Instead, they should identify physicians actively billing ICD-10 codes such as C18–C20 and correlate that with treatment activity.

This is where platforms like Alpha Sophia become critical. Rather than relying on specialty labels, teams can identify physicians who are demonstrably treating the relevant patient population. As outlined in Alpha Sophia’s guide on identifying providers using claims data (How to Identify the Right Doctors Using CPT, ICD-10, and Claims Data: A Practical Guide for MedTech and Life Sciences Teams | Alpha Sophia), combining diagnosis and procedure signals creates a far more accurate target list.

2. What Does Our True Addressable Market Actually Look Like?

Most Total Addressable Market (TAM) models are built too early and too loosely. They often include physicians who are adjacent to the indication but not actively treating it.

This leads to inflated expectations and misaligned field efforts.

A more realistic TAM emerges when you anchor it in real-world activity. Research has shown that physician practice patterns vary significantly even within the same specialty and geography (see studies summarized by JAMA Network: https://jamanetwork.com/).

For instance, two cardiologists in the same city may see entirely different patient populations — one focused on interventional procedures, another on chronic disease management.

A more defensible TAM model incorporates:

• ICD-10 diagnosis frequency

• CPT procedure volume

• site-of-care distribution

Alpha Sophia’s perspective on unified provider data (How Unified Provider Data Powers Commercial and Research Use Cases in Pharma, MedTech, and Diagnostics | Alpha Sophia) highlights that the challenge is not lack of data, but connecting these signals into a coherent view.

When you do this, your TAM typically becomes smaller — but far more actionable.

3. Who Are the Real Key Opinion Leaders?

KOL identification is one of the most over-simplified parts of launch planning.

Teams often default to visible indicators:

• publication count

• conference speaking

• academic affiliation

These are valuable, but they do not fully capture influence.

In many markets, the most impactful physicians are not the most visible ones. They are the ones embedded in referral networks and high-volume treatment pathways.

For example, a regional oncologist working within a large multi-site practice may:

• receive referrals from 15+ surrounding physicians

• influence treatment decisions across multiple clinics

• shape informal standards of care locally

That physician may have more real-world impact than a globally recognized academic.

Platforms like Alpha Sophia allow teams to identify these “operational KOLs” by mapping referral networks and clinical activity. This aligns with broader industry thinking around network-based influence in healthcare delivery.

4. How Do Referral Networks Shape Patient Flow?

Healthcare delivery is fundamentally network-driven. Patients rarely move in isolation; they are referred, transferred, and escalated through systems.

Understanding these pathways is essential, particularly in oncology and specialty care.

For example, a patient diagnosed in a community setting may be referred to a tertiary center for treatment. The physician making the initial diagnosis may not prescribe your therapy — but they determine where the patient ends up.

Ignoring this dynamic leads to misaligned targeting.

Tools that map referral patterns allow teams to identify:

• which physicians act as entry points

• which providers act as treatment hubs

• where decision-making is concentrated

This network view is increasingly emphasized in real-world data strategies discussed by institutions like the National Institutes of Health (https://www.nih.gov/).

5. Where Does Care Actually Take Place?

The shift toward site-of-care complexity is one of the most important changes in healthcare.

According to data from the American Medical Association (https://www.ama-assn.org/), fewer physicians operate in independent practices than a decade ago. Care is increasingly delivered through systems, outpatient centers, and specialized facilities.

This has direct implications for pharma.

A therapy may be:

• prescribed in one setting

• approved in another

• administered in a third

For example, infusion therapies are often administered in hospital outpatient departments or specialty clinics, even if prescribed elsewhere.

Without mapping site-of-care dynamics, teams risk targeting the wrong accounts entirely.

Alpha Sophia connects providers to organizations and facilities, allowing teams to see where treatment actually occurs — not just where physicians are listed.

6. Which Accounts Actually Drive Opportunity?

Not all accounts are equally valuable, but many commercial strategies treat them as if they are.

A high-value account is not defined by size alone. It is defined by:

• concentration of relevant patients

• influence within referral networks

• alignment with treatment pathways

For example, a mid-sized oncology group with strong referral inflow may represent a greater opportunity than a larger but less specialized institution.

This shift toward account-based strategy mirrors broader trends in pharma commercialization and is discussed in industry analyses by firms like IQVIA (Insights | IQVIA).

Alpha Sophia enables teams to prioritize accounts based on real activity rather than assumptions.

7. Is Our Speaker Program Built on the Right Criteria?

Speaker programs remain one of the most effective tools in pharma — but only when executed correctly.

Too often, speakers are selected based on reputation rather than relevance.

A more effective approach considers:

• whether the physician actively treats the condition

• their credibility within local networks

• their ability to influence peers

For example, a physician who regularly treats patients aligned to your therapy and participates in regional case discussions may be far more effective than a distant academic expert.

This aligns with best practices in medical education and peer-to-peer engagement, widely discussed across platforms like Medscape (Medscape).

8. Are We Inviting the Right Physicians to Events?

Event targeting is one of the clearest opportunities for improvement in pharma.

Many events include a broad mix of attendees, reducing their effectiveness.

A more precise approach involves:

• identifying physicians treating the specific condition

• focusing on referral clusters

• targeting geographies with high patient density

For example, instead of hosting a general oncology event, a team might focus on physicians treating a specific subtype within a defined network.

This approach increases both engagement and conversion.

9. Do We Understand the Systems Behind Prescribing Behavior?

Physicians operate within structures that influence their decisions.

These include:

• formularies

• clinical pathways

• procurement processes

Understanding these layers is critical, particularly in hospital and IDN settings.

For example, even if a physician is interested in your therapy, adoption may depend on system-level approval.

This is why mapping organizational structures is just as important as identifying individual physicians.

10. Can We Execute With Confidence — or Are We Guessing?

Ultimately, all of these questions lead to one central issue: confidence.

Most teams are working with fragmented datasets, leading to:

• internal disagreements

• delayed decisions

• inconsistent targeting

As Alpha Sophia explains in its discussion on moving beyond spreadsheets (Why Healthcare Growth Teams Are Moving Beyond Spreadsheet-Based Targeting | Alpha Sophia), the real challenge is not data availability — it is data alignment.

By integrating diagnosis, procedure, provider, and organizational data, teams can operate from a single, consistent view of the market.

Final Thought

Six months before launch is not a buffer.

It is the moment when your strategy either becomes grounded in reality — or drifts further away from it.

The teams that succeed are not the ones who execute more activity.

They are the ones who:

identify the right physicians, understand the real market, and engage early enough to matter.