Far-to-FairIs the PAP materially improving access?
Enter a manufacturer. The view returns the impact verdict, where it comes from, and what market pressure does to the case.
Where impact is coming from
Market pressure
Regional access signal
Directional footprint for the sample scenario; replace with geography-level reporting when available.
Program mix
Impact breakdown
Best next moves
Each move estimates the extra access benefit created per additional rupee of support.
*Impact means the difference between supported patients and the no-support baseline. Replace sample assumptions before using the figures in review.
Market Reality
Only credible, current, relevant market evidence changes the impact read. Weak claims stay out.
Evidence standard
Every market adjustment carries an evidence grade and a visible source trail.
Signals in view
Cancer burden is still climbing
14.6 lakh new cancer cases (2022) → 15.7 lakh projected (2025); breast leads at ~2.33 lakh. A growing eligible pool means PSP reach gaps translate into more unreached patients each year, not fewer.
Biosimilars are collapsing the subsidy case
Trastuzumab fell from ₹1.2 lakh → ~₹19,500 (150mg) across ~7 brands; imatinib is commoditized (~₹1,220/strip). For eroding molecules, a PSP's value shifts from price subsidy to adherence, diagnostics & navigation.
The generic disruption shock
Natco's generic risdiplam at ₹15,900 vs Roche's ₹6.2 lakh/bottle (−97%), after a Delhi HC injunction denial (Mar 2025). A donation/bottle-exchange PSP's economics can vanish overnight when a generic lands.
Public cover widens, but the drug gap persists
OOP fell 64.2% → 39.4%; PM-JAY now covers 70+ (Vay Vandana) and 4.14 cr oncology cases. But the ₹5 lakh cap excludes most high-cost outpatient targeted drugs — the exact gap PSPs fill. More public cover raises the counterfactual and lowers attribution.
How market reality changes the impact case
| Force (2024-26) | Signal | Effect on PSP impact |
|---|
Strategic read
Data & Inputs
Edit the assumptions directly or upload a CSV to make the readout reflect your program.
Program inputs (click any number to edit)
| Program | Enrolled | ₹/mo | Cost/pt/yr | Persist w/ | Persist w/o | Free mo | OOP red % | Abandon % | Attrib α | Margin % | LY factor |
|---|
LY factor = life-years credited per patient-year on effective therapy (curative-intent high, palliative low). Attribution α (0–1) = share of the outcome genuinely caused by the program. Enrolment defaults use public program reach where companies publish it; otherwise they are deliberately conservative scenario placeholders.
Methodology & Sources
Definitions, assumptions, and source trails behind the readout.
Impact logic
For each program, impact = outcome with the program − the counterfactual without it, × attribution (α). Patients retained = enrolled × would-abandon rate × α. OOP relieved = enrolled × annual cost × OOP-reduction × on-therapy months. Incremental patient-months = enrolled × (persistence-with − persistence-without) × α; life-years = patient-months × LY factor ÷ 12. Manufacturer revenue defended = enrolled × monthly price × incremental months × margin × paid-fraction. ROI = revenue defended ÷ program cost. Portfolio view sums every program under the same assumptions.
Program view vs market view
Program view: impact from the assumptions currently loaded. Market view: the same program read after molecule maturity, policy cover, biosimilars, and price erosion are considered. The gap shows how much of the access and business case holds up in the real market.
Evidence grades
| Grade | Evidence | Treatment |
|---|---|---|
| High | Regulators, government releases, company filings, peer-reviewed papers, official hospital or payer documents | Can move the readout when dated and specific. |
| Medium | Reputable business or healthcare press, named analyst reports, established databases, pharmacy price listings | Supports directional adjustment; stronger claims need corroboration. |
| Low | SEO blogs, reposted snippets, anonymous social posts, unsourced PDFs, aggregator pages with no provenance | Watch item only. |
| Rejected | Contradictory, stale, unverifiable, or hallucination-like claims | Excluded or labelled unverified. |
Current intelligence anchors (2024–2026)
Sources
Sample assumptions are drawn from public reporting and real-world ranges, but they are not audited program data. Treat the figures as scenario estimates until internal data is loaded. Market evidence current as of 22 Jul 2026; some figures are analyst estimates or global proxies where India-specific PSP outcomes are sparse. Not investment, legal, medical, or pricing advice.
FAR → FAIR
Turning the promise of patient support into proven patient impact.
For millions of Indians, a life-changing therapy sits just out of reach: not far in distance, but far in affordability, awareness, and access. Patient Assistance Programs and Patient Support Programs exist to close that distance. Far to Fair measures whether they truly do, and where value quietly leaks away before it reaches a patient.
The Promise
They lower the wall.
Free-drug donation, buy-and-benefit dosing, income-tiered pricing, and financing can cut out-of-pocket burden by 40–100%, turning an impossible bill into a payable one.
They keep patients on therapy.
Nurse navigation, reminders, diagnostics, and home delivery can lift adherence by up to 40% and extend persistence, which is the difference between a course completed and a course abandoned.
They open the door earlier.
Free biomarker and rare-disease testing gets the right patient to the right therapy sooner, often the cheapest and highest-leverage act in the journey.
The Leak
A program brochure describes intended value. A patient receives realized value. Between the two sits value leakage: the loss created by awareness gaps, onboarding friction, eligibility rules, affordability cliffs, geography, and attribution to routes that would have helped anyway.
Illustrative value-leakage waterfall: share of intended, sustained, attributable patient value.
Largest leak: patients never enrolled because of awareness, referral, and onboarding friction.
Recoverable value: leakage is design and friction, not destiny. The cockpit should size which leak to close first.
These waterfall percentages are an illustrative composite of documented PAP and PSP failure modes. They are directional prompts for diagnosis, not a measured figure for any single program. Use the Impact Cockpit with your own data to quantify real leakage.
The Far to Fair Principle
Measure honestly.
Count impact against the counterfactual: what would have happened anyway. Fair value is what the program added, net of attribution.
Find every leak.
Trace the drop from intended to realized value across enrollment, eligibility, donation cliffs, abandonment, geography, and attribution.
Recover the value.
Rank fixes by impact per rupee and close the biggest leaks first. Fair is not what you fund. Fair is what reaches the patient and stays.
Far to Fair is that discipline made operational: an honest impact engine, a market-intelligence brain, and a leakage lens. A program's value is judged not by its intent, but by the distance it actually closes for a patient. Every recovered percentage point of leakage is a patient who has a better shot at staying on therapy.