Seven engagements, one method
Novus Proximus advises life sciences organizations across the commercialization lifecycle, from pre-launch demand modeling through in-market optimization and lifecycle transition. The seven engagements below are the practice’s client work, organized by where the product sat in its commercial life when the question was asked.
Client names, brand names, and identifying details are withheld throughout. Engagements are described by phase and capability only.
No performance figures appear anywhere on this page.
Start a conversationWhere these sit in the lifecycleNearly twenty years in-house
Follow three things, in this order
The sequence is not interchangeable. Each question is only answerable once the one before it has been answered.
Follow the patient
Where can the patient fail to reach, start, or remain on therapy?
Follow the transaction
What access, pharmacy, channel, payer, and affordability events actually occur?
Follow the financial outcome
How do those events ultimately determine Gross-to-Net, net sales, and profitability?
Market Access sees coverage. Patient Services sees support. Trade sees the channel. Sales sees prescriptions. Finance sees Gross-to-Net. The patient experiences all of them as one system. The work is to put that system back together, so the enterprise can see it the way the patient experiences it.
Four phases, four answerable questions
Advisory work is usually sold by function, which makes the organizational chart the taxonomy and asks you which box your problem belongs in. The problem rarely sits in one box. These engagements are organized by where the product sat in its commercial life, and therefore by which question was actually answerable at the time.
Pre-Launch and Launch Readiness
Launch and Early Commercialization
Lifecycle and Loss of Exclusivity
Pre-Launch and Launch Readiness
Everything is still a decision and almost nothing is measurable. The only phase where the system can be designed rather than corrected.
Ultra-Rare Pre-Launch Patient Demand Modeling and Launch Readiness
Capability Patient-based forecasting, scenario modeling, launch readiness
The situation
A therapy for an ultra-rare neurological disorder was approaching launch. The observable patient population was extremely small and claims data were thin, which made a traditional epidemiology forecast insufficient. Leadership needed to know how many patients could realistically be identified, initiated, and retained, and what commercial conditions had to be true for the forecast to hold.
What we did
- Built a patient-based commercialization forecast around the full conversion path: opportunity, diagnosis, addressable population, new starts, access, fulfillment, persistence, and total prescription volume.
- Evaluated eighteen potential outcomes using therapeutic analogs, reviewed with external clinical and analytics input before incorporation.
- Applied Monte Carlo simulation to produce a range of plausible scenarios rather than a single-point forecast.
- Modeled persistence independently, with low, base, and high cases drawn from percentiles of the simulated distribution.
What came out
- A probabilistic forecast that stated explicitly which assumptions had to hold for the central case, rather than a single number presented as certainty.
- Quality of Access treated as a core forecast variable rather than a downstream launch activity.
- A resource allocation tool that tested both directions of risk: under-investment, meaning insufficient awareness, inadequate access, poor affordability, and weak distribution, and over-investment, meaning diminishing returns beyond what access or adoption required.
Reusable insight
An ultra-rare forecast is not an epidemiology model. It is a commercialization conversion model. Written demand, approved demand, filled demand, and persistent demand are four different numbers. This engagement introduced the leaky bucket now central to the Novus Proximus framework.
505(b)(2) Pre-Launch Commercialization Strategy
Capability Commercialization strategy, scenario design, launch investment planning
The situation
A differentiated 505(b)(2) product was entering a category that was still forming. The manufacturer had to balance patient adoption, competitive positioning, payer access, channel design, investment requirements, Gross-to-Net, and long-term profitability at the same time.
What we did
- Developed an independent commercialization thesis rather than validating management’s base case, connecting clinical and regulatory assumptions to the commercial realities that decide whether prescriptions become profitable patients.
- Ran the full analytical chain: clinical and regulatory, market formation, patient demand, prescriber adoption, access, channel, pricing and Gross-to-Net, investment, net sales, and profitability.
- Reconstructed the market around the newly forming category rather than assuming it would behave like its predecessor.
- Evaluated first-mover dynamics and multiple entrants, pediatric opportunity, prescriber and key opinion leader adoption, formulary access and prior authorization exposure, copay positioning, retail, specialty, cash and alternative distribution, institutional opportunity, internal versus outsourced field models, direct-to-consumer investment, list price and rebate trade-offs, and contracting strategy.
What came out
- A scenario framework spanning base, conservative, higher-investment, and alternative go-to-market constructs, including a high-list with rebate model and a lower-list, consumer-oriented direct distribution model.
- An answer to a strategic rather than arithmetic question: what combination of access, channel, price, commercial investment, and patient adoption creates the most defensible path to sustainable profitability.
- One decision framework holding Finance, Market Access, Commercial, Patient Services, Trade and Distribution, and Forecasting in a single view.
Reusable insight
Individually reasonable functional assumptions can assemble into materially different enterprise outcomes. A launch forecast is only as credible as the commercialization system built to deliver it.
Launch and Early Commercialization
The architecture is running and there is data for the first time. It is thin, noisy, and easy to over-read.
Prior Authorization Intelligence and Hub Workflow Assessment
Capability Access technology validation, workflow assessment, executive measurement narrative
The situation
A prior authorization intelligence capability was in pilot inside an existing hub workflow. Leadership needed a defensible view of what the capability actually did, how it performed, and how to sequence expansion across prescriber technology environments without overstating its value.
What we did
- Traced the prescription from creation through coverage determination and fulfillment, mapping where the capability intervened and what decision it actually informed.
- Held the capability claim to what was true: the tool evaluates whether a prescription aligns with payer policy requirements. It does not predict whether a payer will approve.
- Corrected assumptions carried in earlier materials about which pharmacy pathways were operationally live, so the baseline reflected reality rather than planned architecture.
What came out
- An executive workflow assessment, delivered across several iterations, with a measurement narrative that would survive scrutiny.
- A corrected operational baseline.
- A sequenced expansion path separating connected-practice environments from broader extension, protecting continued investment in a capability whose value was real but had been difficult to articulate.
Reusable insight
Access technology fails on credibility before it fails on capability. A tool that checks policy alignment is genuinely valuable, but only when it is described as what it is. Precision about what a capability does is a prerequisite to sustaining executive investment in it.
In-Market Optimization
The most data and the least clarity about what it means. Three engagements sit here, and two of them approach the same problem from opposite ends.
Patient Access, Channel and Affordability Redesign
Capability Channel architecture, affordability governance, patient journey orchestration
The situation
A high-demand brand was generating strong prescriber demand and losing opportunity between prescription creation and therapy initiation. The manufacturer needed more appropriate patients converting to therapy, better visibility, controlled affordability spend, and protected brand economics.
What we did
- Followed the prescription through the entire access ecosystem: coverage, prior authorization, affordability, pharmacy, fulfillment, patient, data, and economics.
- Reframed the governing question from vendor optimization to where a prescription can disappear, and whether the manufacturer has enough visibility and control to know why.
- Declined to assume that a hub, a specialty pharmacy, a copay program, or a field intervention was the answer before the diagnosis was complete.
What we found
- A fragmented channel architecture spanning broad retail, an enhanced specialty network, and out-of-network pharmacies, so the same prescription could meet materially different journeys depending on which pharmacy received it.
- A non-mandatory hub, which made consistent intervention across the patient population difficult.
- The overwhelming majority of prior authorization activity handled manually, creating delay, administrative burden, and abandonment risk.
- A complex affordability architecture spanning multiple assistance pathways, raising the central financial question: is every copay dollar removing an access barrier, or is some of it being spent where assistance is not incremental?
- An accumulator, maximizer, alternative funding, and waste, fraud and abuse environment that required visibility before intervention.
What came out
- A future-state architecture in which the patient journey is orchestrated across technologies and partners rather than delegated to a single vendor, spanning patient engagement and consent, independent copay adjudication, maximizer identification, waste and abuse analytics, and performance-based pharmacy management.
- A governance principle that changed the client’s sequencing: rather than immediately altering the existing voucher architecture, get visibility into leakage and patient behavior first, then let those insights determine the future-state adjudication model.
- A controlled current-state to future-state migration covering pharmacy participation, affordability programs, patient communication, consent, data continuity, and vendor responsibilities, rather than a disruptive replacement.
Reusable insight
Do not change the affordability mechanism before you can see what is actually happening. Demand is not access, and access is not fulfillment. The patient who never receives the drug rarely appears in prescription reporting and always appears in lost enterprise value.
Specialty Channel, Patient Orchestration and Affordability Governance
Capability Channel optionality, patient orchestration, copay adjudication governance
The situation
A rare disease product where every patient carries outsized clinical and economic weight. The manufacturer needed better conversion from prescription to therapy, less dependence on a highly concentrated channel, stronger affordability controls, and visibility into patient and financial outcomes.
What we did
- Followed the patient across the entire access pathway rather than evaluating the hub, the specialty pharmacy, the copay program, and the payer environment independently.
- Centered the assessment on one question: does the manufacturer have enough control and visibility to know where a patient is, what is preventing therapy initiation, and who is accountable for resolving it?
What we found
- Heavy concentration inside a single specialty pharmacy organization connected to a broader vertically integrated payer and pharmacy benefit ecosystem, so payer economics, pharmacy economics, benefits investigation, patient fulfillment, and manufacturer data all intersected within one entity.
- Significant benefits investigation and verification functionality sitting with the same dispensing organization, placing it upstream in how coverage and access pathways were understood.
- A non-mandatory hub, strong for the patients who entered it and incomplete across the total prescribed population.
- Prior authorization overwhelmingly manual, with repeated handoffs where delay and abandonment could occur.
- Material affordability exposure in an environment of accumulators, maximizers, and vertically integrated benefit structures.
What came out
- Hub orchestration established as a manufacturer-controlled layer that sees the patient before the prescription enters downstream channel complexity.
- An independent specialty pharmacy evaluated for optionality, benchmarking, data transparency, patient experience, and economic balance, rather than simply as another dispensing location.
- Independent primary copay adjudication, to set consistent program rules, understand individual transactions, identify inappropriate utilization, respond to accumulator and maximizer behavior, and separate affordability strategy from dispensing economics.
- Electronic prior authorization and workflow improvement, and a uniform data architecture producing a consistent patient-level view regardless of which partner dispensed.
Reusable insight
The organization that dispenses the medicine does not need to control the patient journey. Dispensing, orchestration, affordability adjudication, benefits investigation, and data aggregation are distinct capabilities. When they concentrate inside one vertically integrated organization, the manufacturer should know what visibility, control, and optionality it is surrendering. Copay is not a patient-service expense. It is a commercialization transaction that requires financial governance.
In-Market Revenue Leakage Diagnostic
Capability Revenue leakage diagnostics, Gross-to-Net analysis, channel economics
The situation
A commercialized brand was generating prescription volume that was not translating into expected financial return. Leadership could see the variance on the income statement and could not identify where, between prescription generation and recognized net revenue, the value was being lost.
What we did
- Worked backward through the patient-to-profitability continuum rather than treating Gross-to-Net as the problem itself: prescription, access, pharmacy, affordability, fulfillment, utilization, Gross-to-Net, net revenue, profitability.
- Started from the recognition that a finance-only analysis identifies the variance without identifying the commercial behaviors producing it.
- Examined payer and rebate economics, distribution economics, copay leakage, pharmacy performance, patient fulfillment, utilization behavior, and field deployment.
What we found
- Substantial rebate exposure alongside additional sources of margin compression.
- Prescription volume alone did not explain brand economics. Two territories generating similar prescription activity produced materially different economics depending on payer mix, pharmacy behavior, copay utilization, and net price.
- Limited visibility into where prescriptions were being lost, which obscured the connection between commercial activity and financial outcome.
What came out
- Copay audit and recovery, to find unnecessary or inappropriate affordability spend and see where copay dollars were producing incremental access.
- Pharmacy segmentation that moved past volume to evaluate the ability to convert prescriptions into filled, persistent patients.
- Contracting optimization, testing whether payer access purchased through rebates was producing sufficient incremental utilization and economic value.
- Field-force optimization that put institutional and patient economics into targeting rather than relying predominantly on prescription opportunity.
Reusable insight
Revenue leakage does not begin on the income statement. It begins somewhere in the patient journey. The financial outcome is simply where the leakage finally becomes visible.
Lifecycle and Loss of Exclusivity
The system has to be repositioned before the event, not after it.
Lifecycle Profitability, Channel Redesign and Loss-of-Exclusivity Strategy
Capability Lifecycle strategy, authorized generic economics, channel redesign
The situation
An established pediatric brand needed better profitability and patient-access performance while preparing for increasing generic pressure and eventual loss of exclusivity.
What we did
- Assessed payer behavior, access restrictions, patient economics, reimbursement, channel performance, profitability, current Gross-to-Net, and authorized-generic economics, including the implications of doing nothing versus intervening before exclusivity loss.
- Established that aggregate Gross-to-Net was insufficient and payer-specific net price was required, because the economics of retaining, converting, or losing a patient varied materially across payers, with downstream government pricing implications including Medicaid CPI penalties and AMP effects.
- Held to the operational reality that a prescription written is not a patient started, making prescription-to-fill confidence the central objective.
What we found
- Payer-specific economics, not blended averages, determined the value of each retained or converted patient.
- Prescription abandonment and time to fill represented recoverable value that aggregate reporting concealed.
- The sequence and timing of an authorized generic relative to exclusivity loss would shape patient, pharmacy, and payer behavior well beyond the pricing decision itself.
What came out
- An alternative channel architecture combining specialty pharmacy, an electronic hub, and patient support, designed to reduce abandonment, shorten time to fill, improve prior authorization and appeals management, give visibility into failed prescriptions, establish consistent business rules, and improve pharmacy network consistency.
- A lifecycle plan spanning the authorized generic and loss-of-exclusivity timeline through the transition to a multi-source generic environment.
- A reframing of the central question, from what price to set on an authorized generic to whether the manufacturer could deliberately transition the market before exclusivity loss, so that patient behavior, pharmacy behavior, payer economics, and channel architecture were better positioned when generic competition arrived.
Reusable insight
Loss of exclusivity is not a pricing event. It is a commercialization transition. Patient behavior, pharmacy behavior, payer economics, and channel architecture should be positioned before generic competition arrives, not after.
Seven answers to one question
These engagements are stronger together than as independent case studies. Each answers a different enterprise question at a different point in the commercialization lifecycle, and each applies the same underlying discipline.
Two of the Phase 3 engagements illustrate the same problem from opposite directions. One begins with the economic signal and works backward, asking why commercial activity is not producing expected profitability. The other begins with the patient journey and works forward, asking where patients are getting lost and what that costs. Both arrive at the same place: pharmaceutical financial performance cannot be fully understood without understanding what happens to the patient between prescription and therapy.
Follow the patient. Follow the transaction. Follow the financial outcome. Patient friction creates revenue leakage, and the enterprise that can see the journey the way the patient experiences it is the enterprise that can protect both.
Which of these is your situation?
Each of these is a different engagement, because each is answerable with different evidence. Pick the one that sounds like the room you are sitting in.
We are building the commercialization system
The forecast exists. Whether the system that delivers it exists is a separate question.
The architecture is live and we cannot describe how it is performing
There is data for the first time, and it is thin enough to be read three different ways.
Volume is not becoming profit
The variance is visible on the income statement and invisible everywhere it was created.
The lifecycle event is coming
The decision looks like pricing and is actually about where the patients, pharmacies, and payers stand when it arrives.
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