When innovation becomes selection
Industries optimize around incentives. People optimize around accountability.
Canavan is one of myriad rare conditions biotechs are developing treatments for.
The most advanced Canavan clinical programs seek to correct the ASPA gene defect by delivering a wild-type version with a viral vector.
Tools to develop monogenic disease therapy have been used for decades.
DNA sequencing to identify the genetic defect
Recombinant DNA technology to deliver a gene via a vector or producing the encoded protein in a bioreactor
If successfully developed, Canavan therapy would be transformative for families affected by the disease.
For the biotechnology industry, it may increasingly feel familiar.
Milken panel highlighted opportunities and challenges in drug development
The abundance of rare diseases and paucity of therapeutics is paradoxical to us, particularly considering the theoretically attractive pTS and the willingness of payers to underwrite high costs of treatment.
The discussion by market participants on the Milken Institute Global Conference panel, “Rewriting the rules: Scaling Innovation for Rare Disease”, focused on the unmet medical need and funding challenges that frequently depend on non-profit and charitable organizations.
Approved treatments exist for only 5% of rare diseases.
One panel member commented that they “believe not only is rare disease the greatest unmet need in health care, I think we have the greatest opportunity to actually address this.”
Reconciling the two preceding observations challenges us.
After all, the prototypical rare disease therapy that launched the biotech industry icon Genzyme, Ceredase for Gaucher disease, was approved by the FDA 35 years ago.
What we found constructive were discussions on extending patent exclusivity and normalizing pricing in other major global markets, a situation not unique to rare diseases.
Why rare disease became an attractive disease target
From scientific and financial perspectives, rare disease development provides an unusually attractive template.
The path to regulatory approval has been well-charted by predecessor biotech companies.
Scarcity of subjects with rare disease can be accommodated by relatively small numbers needed to gain regulatory approval.
Correcting the genetic defect or providing the protein the gene encodes is nominally viewed as having a high pTS.
The morbidity of rare diseases and focused medical care make post-approval activities approachable by companies lacking meaningful prior experience.
Loosely based on the premise that price reflects the cost of not treating, per capita revenues can be sizable for chronic use and for one-time gene therapy.
Once a drug development template yields repeated success, the question for management teams changes
Investors reward repeatability.
Share price responds favorably to programs viewed as low risk.
The challenge is no longer about whether a disease can be treated. It is whether the next opportunity resembles one the industry has already solved.
Successful templates create tension
Repeatability vs. Innovation
Defensibility vs. Exploration
Scalability vs. Scarcity
The rare disease pricing architecture has been designed for scarcity, not scalability.
Aggregate costs to most payers to manage common chronic diseases — cardiovascular, metabolic, autoimmune — are likely substantially higher than that for rare diseases.
As diagnosis expands and development becomes more systematic, rare disease may increasingly shift from exceptional medicine toward therapeutic infrastructure.
That changes payer math.
The call to scale rare disease development appeals to humanitarian beliefs. Undoubtedly beneficial for the affected community, the unintended consequences could be significant.
And permanent.
A strange feedback loop could develop:
therapies increase diagnosis
diagnosis increases prevalence visibility
prevalence visibility changes payer math
payer math changes pricing tolerance
When broad newborn screening, exome sequencing, liquid biopsy diagnostics, federated patient databases, and AI phenotyping, et al., become standard, prevalence starts looking different.
Not because biology changes.
Because detection changes.
Historically, undiagnosed patients were economically invisible patients.
A therapy can “create” a market simply by making diagnosis worthwhile.
Today many rare disease companies are valued as:
isolated binary assets
emotionally compelling missions
protected niche economics
But if the field industrializes, investors may start evaluating them more like infrastructure or manufacturing systems.
That is a very different valuation framework.
The more successful the rare disease ecosystem becomes technologically, the more it may erode the exceptionalism supporting current economics.
Are we approaching a tipping point where the very success of the orphan model begins to challenge the assumptions supporting it?
The orphan business model may not fail because therapies stop working.
It may eventually strain because success changes scale.
Scale attracts attention.
Attention invites scrutiny.
Pricing scrutiny produces more conservative revenue assumptions.
More conservative revenue assumptions compress acquisition valuations.
Programs built around the original orphan pricing architecture may be acquired at valuations that bear little resemblance to assumptions that supported the underwriting.
One almost wants to ask how you greenlight a program if prevailing market exclusivity may not allow your hurdle rate to be cleared.
The panel didn’t answer that question directly.
Rooms assembled around shared interest in the conclusion rarely do.
The premium pays for certainty, not science
A de-risked rare disease asset is essentially a bond with a high coupon.
Phase 3 data in hand.
Defined patient population.
Established biomarker.
Clear regulatory pathway.
For a large company managing patent cliffs and revenue gaps, that’s portfolio management not drug development.
If the exit is reliably a large pharma acquisition at Phase 3, capital flows toward assets that look like acquisition targets.
Not assets that address the deepest unmet needs.
The selection bias reinforces itself at every level of the capital stack simultaneously.
The operator selects commercially viable orphan profiles over genuinely innovative biology because the exit is a large pharma acquisition.
The acquirer selects de-risked assets over early science because the acquisition is financial not strategic.
Philanthropic capital selects diseases with enough infrastructure and story to deploy against.
AI platforms select indications where the data exists to train models.
Each individual actor is being completely rational given their incentives.
That’s what makes it a structural problem rather than a moral one.
You can’t fix it by finding better actors.
Triage without a triage officer
The consequence is a kind of orphan disease triage that nobody explicitly designed but everybody implicitly enforces.
The diseases that sit at the intersection of rare enough for exclusivity, common enough for viable economics, and biologically legible enough for current tools get multiple shots at capital.
The diseases outside that intersection get essentially none regardless of unmet need.
In battlefield medicine triage implies a triage officer.
Someone with explicit authority and accountability for the allocation decision.
In the orphan ecosystem the decision is diffuse and implicit.
The diseases that fall through don’t fall through because of a decision.
They fall through because of the absence of one.
Nobody announces they’re setting aside disease #4,847.
They just never get around to it.
The selection criteria get laundered through the language of science and innovation, so the triage is never made explicit.
It is not a moral argument about forgotten patients.
It is a capital markets structure argument about how incentive misalignment produces systematic gaps that no single participant has the motivation to close.
The exception that defines the gap
David Fajgenbaum’s Every Cure is the most intellectually honest response to that gap.
It required government funding precisely because it couldn’t clear any of the normal selection filters.
No commercial exit.
No acquisition target.
No platform premium.
No narrative capital.
Just the unglamorous work of finding matches nobody else was incentivized to look for.
When the only entity systematically addressing the diseases that fall through the triage requires ARPA-H funding to exist, the structure has given you its answer.
“We don’t have business models that can really address the promise of what’s ongoing in rare genetic disease.”
— Neil Kumar, BridgeBio