Tuesday, August 18, 2026

Chat GPT Reviews History of McDermott Plus Consulting - After News from Politico

We're waiting for confirmation of a news item in Politico that McDermott Plus is closing in August 2026.

While we wait, Chat GPT ran a internet search for information about the history of the firm.  This article is AI-written.  It can be used as an example of current AI ability to understand a task, do research, organize it, and write it up.  It should not be taken as ground truth.

##
##

McDermott+: A 12-Year Experiment in Health Policy, Reimbursement and Washington Advocacy

On August 18, Politico reported that McDermott+, the health policy consulting and lobbying organization affiliated with McDermott Will & Schulte, will close at the end of August, with dozens of employees entering the Washington job market. Assuming the report is correct, the closure will bring to an end a distinctive 12-year experiment in combining health policy consulting, reimbursement strategy, data analytics and conventional Washington lobbying under one roof.

For many people in health policy, McDermott+ was sufficiently familiar that its unusual corporate structure could be easy to overlook. It looked and sounded like part of the McDermott law firm, occupied the same Washington address, shared personnel and frequently worked alongside McDermott lawyers. But it was not a law practice.

A deliberate spinout — but never an independent one

McDermott Will & Emery formally launched McDermott+Consulting, or McDermottPlus, in April 2014. The announcement described it as a “separate and distinct, wholly-owned subsidiary” of the law firm. Its original menu was unusually broad: 

  • congressional and executive-branch lobbying, 
  • budget-impact and cost-effectiveness modeling, 
  • political communications, 
  • public- and private-payer coverage, coding and pricing strategy, and 
  • healthcare data analysis. 
  • The firm explicitly promoted the ability to use project fees and retainers rather than limiting engagements to traditional law-firm hourly billing to the tenth of the hour. (KSL)

Thus, McDermott+ was less a conventional corporate spinout than a closely held consulting affiliate. That distinction remained important. McDermott’s current legal notices state explicitly that McDermottPlus LLC is wholly owned by McDermott Will & Schulte and does not provide legal advice or legal services. (McDermott) Earlier McDermott+ publications similarly cautioned that communications with the consulting company did not carry attorney-client privilege.

The arrangement nevertheless allowed extremely close integration. A client could be working with McDermott+ consultants on reimbursement economics, CMS policy or lobbying and, when a question required legal analysis, bring in lawyers from the parent firm. A later McDermott case study on Medicare coverage of over-the-counter COVID-19 tests describes exactly that sequence: McDermott+ organized and advocated for a coalition, then drew on McDermott lawyers to develop the legal theory supporting a potential CMS coverage pathway. (McDermott)

The practice existed before the name

The intellectual roots of McDermott+ predated the 2014 corporate launch.

McDermott already had a prominent Washington health-policy and reimbursement practice spanning Medicare payment, coverage, coding, FDA regulation and congressional advocacy. Paul Radensky, MD, JD, and Eric Zimmerman were conspicuous participants in that world. For example, both appeared on the agenda of CMS's 2013 annual Clinical Laboratory Fee Schedule meeting, with Zimmerman representing McDermott and the Coalition for 21st Century Medicine and Radensky appearing for McDermott separately. (Centers for Medicare & Medicaid Services)

The creation of McDermott+ essentially gave that kind of work a larger nonlegal platform.

At the 2014 launch, Radensky and Zimmerman were both identified as principals. Zimmerman said the objective was a “one-stop shop” combining lobbying, analytics and policy work; Radensky emphasized the growing need for quantitative analysis and for strategies that could move new technologies through complex government regulatory and payment systems. (KSL)

Zimmerman was later explicitly described by McDermott+ as a co-founder. (McDermott+)

Paul Radensky and the reimbursement side of McDermott+

For many in the diagnostics, medical-device and biotechnology communities, however, Paul Radensky became one of the people most closely identified with McDermott+.

His background was unusual even by Washington health-policy standards: an MD from the University of Pennsylvania, internal-medicine training and a fellowship in liver disease, followed by a Harvard JD. His practice joined regulatory law to the highly specialized mechanics of obtaining Medicare coverage, coding and payment for new medical technologies. McDermott credits him with work leading to national and local Medicare coverage decisions, Coverage with Evidence Development protocols and reimbursement strategies for pharmaceuticals, biologics, devices and clinical laboratory technologies. (McDermott)

That expertise helped give McDermott+ a character different from that of a general K Street shop. A client might arrive not because a bill was moving through Congress but because a diagnostic needed a coding pathway, a medical device faced an unfavorable Medicare payment methodology, a laboratory test needed a coverage strategy, or a manufacturer needed to understand the interaction among FDA status, Medicare benefit categories, CPT or HCPCS coding and CMS payment rules.

Radensky was particularly visible in diagnostics. McDermott+ work during the period included laboratory payment policy under PAMA, advanced diagnostics, medical devices, drug reimbursement and Medicare coverage. His representative activities also included the Coalition for 21st Century Medicine and coalitions involving diabetes testing and other diagnostic technologies. (McDermott+)

Radensky subsequently stepped back from his former partner status. McDermott's current website lists him as Counsel, while still stating that he serves as a principal of McDermott+; the McDermott+ site also continued to list him among its professionals in August 2026. (McDermott) In other words, the public record suggests a gradual change in role rather than a disappearance from the organization.

From reimbursement boutique to broader health-policy operation

McDermott+ also expanded well beyond the product-reimbursement work for which Radensky was known.

By 2018, four years after its founding, the firm said it had grown to ten consultants and had deliberately recruited former executive-branch officials, congressional staff and experienced policy consultants. That year it added Mara McDermott, formerly a senior federal-affairs executive for America’s Physician Groups, and Rachel Stauffer, who had worked on Capitol Hill and in the Office of the National Coordinator for Health IT. (McDermott+)

Over time, the roster became a recognizable cross-section of Washington healthcare expertise. Debbie Curtis brought 24 years of congressional experience, including work for Rep. Pete Stark and the House Ways and Means Health Subcommittee. Rodney Whitlock had worked for Rep. Charlie Norwood, Sen. Chuck Grassley and the Senate Finance Committee. Jeffrey Davis had spent eight years at HHS before working at the American College of Emergency Physicians. (McDermott+)

Others brought expertise in Medicare Advantage, Medicaid, hospital prospective payment systems, medical devices, health economics, CMMI models and claims-data analysis. By August 2026, the public professional roster included roughly two dozen names spanning policy, lobbying, reimbursement and analytics. (McDermott+)

The resulting organization could operate at several levels of the healthcare-policy system simultaneously.

For manufacturers, McDermott+ offered product-level market-access work involving coverage, coding and payment. For hospitals and health systems, it worked on Medicare payment systems, rural-hospital policy and broader federal reimbursement issues. For plans and other organizations, it developed expertise in Medicare Advantage and Part D. For provider organizations and investors in delivery-system reform, it became active in accountable care and CMMI payment models. And for associations, coalitions and corporations, it offered traditional congressional and agency advocacy.

That breadth became the firm's defining proposition. Its website in August 2026 still described McDermott+ as combining consulting, policy and lobbying with data analytics and specialized knowledge of reimbursement, coding, coverage and quality reporting. (McDermott+)

A lobbying shop, but not only a lobbying shop

McDermott+ nevertheless became a substantial registered federal lobbying operation.

One recent academic analysis using OpenSecrets data found that McDermott+ reported about $4.39 million in federal lobbying revenue from 33 clients in 2024. Of that amount, approximately $1.11 million came from seven hospital-industry clients, placing McDermott+ among the larger firms lobbying for hospitals that year. Those figures capture disclosed lobbying revenue, not the company's separate consulting, analytics or reimbursement-strategy business. (JAMA Network)

Its work also illustrates how lobbying could be combined with technical policy expertise. McDermott+ represented hospital coalitions, technology companies, diagnostics firms and other healthcare interests before Congress and executive agencies. Zimmerman, for example, has served as Washington representative for Trinity Health, rural-hospital coalitions, diabetes-testing interests and the Coalition for 21st Century Medicine. (McDermott+)

Coalitions became another recurring feature of the model. During the COVID-19 pandemic, Radensky and Zimmerman led an effort bringing together five competing suppliers of at-home testing products to seek Medicare coverage. In another case, a McDermott+ team worked with a coalition of more than 25 organizations around Medicare direct contracting and what became the ACO REACH model. (McDermott)

Those engagements captured what McDermott+ could do that a reimbursement boutique, analytics shop or lobbying firm alone might have found harder: combine the technical policy argument, its economic implications, stakeholder organization and the Washington campaign required to move it.

It also became a health-policy publisher

A quieter part of the McDermott+ story was its development into a significant public-facing source of health-policy information.

The McDermottPlus Check-Up began providing regular Washington health-policy summaries by 2019. The organization added the Health Policy Breakroom podcast, regulatory commentary, election and policy previews, Medicare data tools and interactive dashboards. By 2026, its website included dedicated products for Medicare data analytics, NTAP strategy, Medicare Advantage and Part D, physician and hospital payment dashboards and a premium information service called McDermott+ Insider. (McDermott+)

In April 2024, co-founder Eric Zimmerman appeared on the Health Policy Breakroom specifically to mark McDermott+'s tenth anniversary and discuss its first decade. (McDermott+)

The public-content operation mattered partly because it kept McDermott+ visible well beyond its paying clients. Hospital executives, laboratory-policy specialists, trade-association staff, Washington lawyers and reimbursement consultants routinely encountered its summaries of proposed and final CMS rules even if they were not currently working with the firm.

That makes the reported shutdown unusually conspicuous. As recently as August 7, 2026, the McDermott+ website was still publishing its weekly Check-Up, and in early August it had posted analyses of the FY 2027 inpatient final rule and other major Medicare regulations. (McDermott+)

A changing parent organization

The closure also occurs against a changed backdrop at the parent law firm.

McDermott Will & Emery merged with New York-based Schulte Roth & Zabel effective August 1, 2025, creating McDermott Will & Schulte, a firm of roughly 1,750 lawyers across more than 20 offices. McDermott brought particular strength in healthcare, while Schulte was especially known for private capital and investment-fund work. (Reuters)

There is not yet enough public information to attribute the reported McDermott+ closure to that merger or any other factor.  The parent firm continues to maintain a major healthcare practice, and several McDermott+ principals have simultaneously held roles at the law firm.

An unusual niche in Washington healthcare

McDermott+ lasted from the early years of Affordable Care Act implementation through MACRA and alternative payment models, PAMA laboratory reform, Medicare Advantage expansion, COVID-19 emergency policy, the Inflation Reduction Act and another major shift in federal health policy after the 2024 election.

Its enduring distinction was not any single one of those subjects. It was the attempt to place several professions that normally sit beside one another — health lawyers, former Hill staff, CMS and HHS veterans, reimbursement specialists, clinicians, lobbyists, economists and data analysts — inside one small organization.

For some clients, McDermott+ was essentially a Washington lobbying firm. For others, it was a Medicare reimbursement consultancy. For still others, it was a source of payment modeling, policy intelligence, coding strategy or coalition management.

And because the organization remained wholly owned by one of the country's best-known healthcare law firms, it occupied an unusual space between Big Law and K Street without being quite either one.

If the reported August 2026 shutdown proceeds as described, that hybrid organization will disappear. Much of its expertise almost certainly will not. In Washington health policy, where former agency officials, congressional staff, lawyers and consultants regularly reassemble in new combinations, the more consequential story may be where the McDermott+ people — and the functions they performed — turn up next.


Sunday, August 16, 2026

New Proposal Introduces Broader Authority for Political Input to NIH Grant Decisions

Back in May 2026, OMB issued a proposed rule that would lay out the authority and framework for political appointees to have a much stronger hand in grant approval decisions.  See article by AP here.  AP also linked back to a Executive Order on the topic back in August 2025 - here.  It might reduce the chance the political grant cuts would get contested in court as happened when grants were abruptly defunded around March-April 2025 (here).  

  • See 108pp OMB proposal here; comment ran to July 13.
  • The OMB policy stated in part:
  • Although Federal spending through grants and other types of Federal financial assistance has grown exponentially since the initial establishment of OMB's policies in earlier Circulars and 2 CFR, corresponding policies capable of ensuring transparency, accountability, and oversight for this increased level of spending remain deficient in the current regulatory text. As a result, Federal programs, and the activities performed under Federal awards, have not always remained properly aligned with core purposes authorized by law, nor served the needs of the American public as intended.
  • This lack of transparency, accountability, and proper oversight became increasingly clear between 2021 and 2024. Federal awards were often used during those years to promote a “woke” policy agenda that did not reflect the values of the vast majority of the American public...

Here comes what may be a related document in the set, from NIH, about presentation of data from NIH grant reviews - here.  Dated August 14, 2026. It's titled, Request for Information (RFI) on Proposed Changes to Reporting Outcomes from NIH Peer Review, Notice Number: NOT-OD-26-088.  Issued 8/14, your comments due 10/13.



##

I'll let Chat GPT discuss the details.

See also a ten-page AI generated white paper on this topic  >>>  here   <<< .

##

NIH has issued something notable. And it fits almost hand-in-glove with the OMB proposal from May 2026, although the NIH notice here is itself framed as a technical reform intended to reduce false precision in peer-review scoring.

The chronology makes the architecture clearer. In November 2025, NIH adopted its Unified Funding Strategy, effective with the January 2026 Council round, expressly moving away from rigid paylines and toward decisions that balance peer review with health priorities, scientific opportunities, workforce considerations, portfolio balance, and available funds. (Grants.gov

Then on May 29, 2026, OMB proposed its government-wide rule requiring senior appointees to independently review discretionary awards rather than routinely defer to peer-review recommendations. (Federal Register); 108pp.  Comments closed. 

Now: on August 14, NIH proposes to remove the principal quantitative output of peer review from everybody downstream of the study section. (Grants.gov)

That last point is more substantial than the headline suggests.

  • Today, an R01 might emerge from study section with, say, an impact score of 18 and 2nd percentile. The PI sees it. Program sees it. Institute leadership sees it. Council sees it. Everybody knows that this was an exceptionally highly ranked application.
  • Under the proposal, the reviewers would still score it numerically, and NIH would still calculate the final impact score behind the curtain—but the PI, institution, program staff, ICO leadership and Advisory Council would not receive either that score or the percentile. They would be told merely:

CurrentProposed
Impact score 18, 2nd percentileMost competitive
Impact score 27, 23rd percentileMost competitive
Impact score 31, 28th percentileCompetitive
Below discussion thresholdNot discussed

The first two applications therefore become formally indistinguishable in the information delivered to the people making the funding decision—even though the study section may have regarded one as markedly stronger. 

NIH says this is intentional: exact scores have “imperfect discriminative ability,” and removing them will cause program officials to pay greater attention to critiques and exercise judgment about NIH priorities and portfolio considerations. (Grants.gov)

There are really two stories here

One is a perfectly respectable science-of-peer-review argument. A score of 18 versus 21 isn't a laboratory measurement. Reviewer composition, study-section dynamics and random variation matter; the literature has long questioned whether tiny score differences justify cliff-edge funding decisions. NIH's argument is basically: stop pretending a noisy ordinal judgment is a micrometer. That's defensible, and NIH specifically says that critiques, criterion scores, discussion summaries, and the actual peer-review process remain. (Grants.gov)

But the second story is governance.

NIH isn't merely saying, “Don't fetishize the score.” It proposes to withhold the score altogether from program officials, Institute directors, Advisory Councils, applicants and institutions. That substantially reduces the externally visible constraint imposed by peer review. The old system made departures from review rank conspicuous: Why was a 3rd-percentile application passed over while an 18th-percentile application was funded? Under the proposed system, both may simply read MOST COMPETITIVE.

And that intersects remarkably with the Unified Funding Strategy. NIH already says ICOs should no longer use paylines and should instead integrate scientific merit with institutional priorities, health priorities, workforce, portfolio and financial considerations. (Grants.gov) The new proposal removes much of the numerical information that could constrain—or at least make visible—how far those discretionary decisions depart from study-section ranking.

Then put the OMB May 29 proposal next to it. OMB's proposed government-wide regulation says senior appointees should exercise independent judgment rather than routinely defer to recommendations and explicitly makes peer-review recommendations advisory. (Federal Register)

So I would distinguish intent from institutional effect. The NIH RFI does not say, “We want political appointees overriding scientists,” and it would be overstating the document to describe it that way. But institutionally, the sequence is striking:

  • November 2025: abolish dependence on paylines →
  • May 2026 OMB: emphasize independent judgment of political leadership over discretionary grants →
  • August 2026 NIH: collapse peer-review results into three broad categories and conceal exact scores from downstream decision-makers.

That combination transfers information and discretion away from an easily auditable numerical peer-review ranking and toward programmatic/leadership judgment.

One additional detail caught my eye [writes Chat GPT]: NIH released NOT-OD-26-088 on Friday, August 14—the same day NIH held its previously scheduled public webinar, “Understanding NIH's Unified Funding Strategy: What the Research Community Needs to Know.” (Grants.gov) So this appears less like an isolated CSR housekeeping proposal than another deliberate step in implementing the Unified Funding Strategy.

And there's a terrific blog headline hiding in the mechanics:

NIH Peer Review: The Score Will Still Exist. You Just Won't Be Allowed to See It.

The RFI comment deadline is October 13, 2026. (Grants.gov)

This is considerably more interesting when framed as the third act of the 2025–26 story—Unified Funding Strategy → OMB grant rule → NIH score suppression—rather than as a standalone item that “NIH changes peer review details.” 

##

A negative reaction to the NIH RFI - here.

Why CMS MAC Questions for Synuclein Diagnostics Miss the Main Point

This week, on August 20, several Medicare MACs will hold a public session on the literature on alpha-synuclein tesitng for Parkinson's and related disorders (synucleinopathies).  

It's an important opportunity for the neurologic community as most physicians get very little training in neurology.  I suspect as few as ten percent take a full elective month in neurology (they only get a few electives) and once they're off in residency track (surgery, ER, pediatrics, immunology, etc) neurology is far in the rear view mirror. [*]

Questions for the advisory meeting have been posted:

 https://med.noridianmedicare.com/web/jeb/policies/lcd/cac/cac-questions-biomarkers-utilized-in-the-diagnosis-of-synucleinopathies-key-question

While there may be too many questions, and some are repetitive, they seem to question whether diagnostics matter at all in neurology.  Whether diagnosis affects management would usually be out of scope of a specific diagnostic study, and here, there is not one outcome (like "survival" in cancer) but diverse ones across the diverse presentation of disease.   The most important metric for Patient A may be a symptom patient B doesn't even have.

Parkinson's itself has protean symptoms - what other disorder causes both visual hallucinations and foot cramps?  And in between there's swallowing disorders, gastroparesis, orthostatic hypotension, constipation, bladder disorders, balance disorder with falls, restless leg syndrome, insomnia (sometimes to a toxic degree), and others.   In this sense, Parkinson's has protean entry points and outputs, like lupus.

Here's some clarification from Chat GPT:

“Protean” disease is a familiar medical concept, not an argument against the importance of diagnosis. In several classic disorders, the underlying disease is critical to figure out, precisely because a patient may enter the healthcare system through very different symptoms and may require management across multiple organ systems.

Six useful comparators:

  1. Syphilis — the archetypal “great imitator.” Depending on stage and site, it can present with dermatologic, neurologic, psychiatric, ocular, auditory, and cardiovascular disease; neurosyphilis itself ranges from meningitis and cranial neuropathies to stroke, tabes dorsalis, and general paresis. (CDC)

  2. Systemic Lupus erythematosus. One patient may present with arthritis or rash, another with nephritis, cytopenias, seizures or cognitive problems, pleuritis, pericarditis, or vasculitis. NIH explicitly notes that manifestations vary greatly among individuals and can change over time. (NIAMS)

  3. Sarcoidosis. Usually thought of as pulmonary disease, but it can involve lymph nodes, skin, eyes, heart, liver, salivary glands, and the nervous system. Thus two patients with the same underlying granulomatous disease can look almost unrelated clinically. (NHLBI, NIH)

  4. Systemic vasculitis — particularly ANCA-associated disease. Depending on which vessels are involved, presentation can be sinus disease, pulmonary hemorrhage, renal disease, rash, neuropathy/foot drop, eye disease, constitutional symptoms, or gastrointestinal involvement. The very diversity of manifestations makes establishing the unifying diagnosis especially consequential. (MedlinePlus)

  5. Systemic amyloidosis. The same protein-deposition process can manifest as cardiomyopathy, nephrotic renal disease, peripheral or autonomic neuropathy, hypotension, gastrointestinal dysfunction, hepatic disease, carpal tunnel syndrome, or combinations of these. NIDDK specifically emphasizes that different patients have different organs and tissues involved. (NIDDK)

  6. Multiple sclerosis — a particularly useful neurologic analogy. Although confined principally to the CNS rather than being truly systemic, its clinical expression is extraordinarily heterogeneous: optic/visual disease, sensory symptoms, weakness, spasticity, gait and balance problems, pain, cognitive problems, fatigue, and bowel/bladder dysfunction can appear in different combinations and at different points in the disease course. (MedlinePlus)

The analogy to Parkinson's is quite strong. The Australian “iceberg” (pic below) is not simply an advocacy graphic making Parkinson's look complicated. It reflects the fact that PD will simultaneously be a movement disorder, autonomic disorder, sleep disorder, gastrointestinal disorder, neuropsychiatric disorder, cognitive disorder, and bulbar disorder. Hallucinations and foot dystonia [cramps] may indeed belong to the same disease as gastroparesis, orthostatic hypotension, RBD, urinary dysfunction, sudden falls, dysphagia, constipation, and bradykinesia.



That matters directly the somewhat odd premise running through the MAC  questions. MACs acknowledge that synucleinopathies encompass “multiple diseases and a broad array of signs and symptoms,” yet repeatedly asks what useful outcome, if any, could follow diagnosis in the absence of curative (disease-modifying0 therapy.  (And a trial could only pick one or two definitive endpoints; for synuclein diagnostics in early patients, surely that can't be 20-year survival).

In a protean progressive disease, heterogeneity is a powerful reason why diagnosis matters: identifying the unifying disease organizes otherwise disconnected symptoms, directs surveillance, anticipates complications, informs medication and referral choices, and gives meaning to new manifestations as they emerge.

Syphilis, lupus, sarcoidosis, vasculitis, amyloidosis—and PD—would all be vastly harder to manage if medicine insisted that "diagnosis had little value" until there was a curative treatment.

##

[*] I have some content knowledge here.  I did a two year postdoc in basal ganglia research before residency, and I spent a month at the PD iinstitute affiliated with the royal neurologic hospital - Queen's Square - in London, before getting board-certified in Neuropathology.

You Can Still Register for "CAC" Meeting on Synuclein Testing (Neurodegeneration)

On Thursday, August 20, 2026, Noridian and some other MACs will hold a listen-only conference on neurodegeneration, specifically, use of alpha-synuclein testing.  This is typically for Parkinson's and related conditions.  The webinar is 2-4 central, 12-2 pacific, 3-5 eastern.

Find the home page here, and see the bar at upper right for "Register."

https://events.teams.microsoft.com/event/8e7d3e2c-b57f-4625-bc2e-32df0234c0d1@d949fb00-e2f5-40e9-a077-ad0421619953

You can also reach that page by going to this webpage and scrolling for Upcoming Meetings and clicking "Registration."  This webpage also has questions-to-be-asked.

https://med.noridianmedicare.com/web/jeb/policies/lcd/cac#upcomingmeetings


##


##
I registered Sunday and got an email with a "join event" link in a minute.  It says Reg is open to 8/20, but I'd suggest not waiting til the last minute.

Noridian made me a calendar invite, but it doesn't seem to hold the link (at least not in my system) so you may need to track the link from the email itself.

##
Palmetto GBA, Wellpoint Administrators, and Noridian Healthcare Solutions will host a Multi-Jurisdictional Contractor Advisory Committee (CAC) Meeting via Microsoft Teams Webinar on August 20, 2026, from 2-4pm CT. Discussions will focus on Biomarkers Utilized in the Diagnosis of Synucleinopathies.

The Centers for Medicare & Medicaid Services (CMS) assigned Medicare Administrative Contractors (MACs) the task of developing Local Coverage Determinations (LCDs). The purpose of the CAC meeting is to provide a formal mechanism for healthcare professionals to be informed of the evidence used in developing an LCD and promote communications between the MACs and the healthcare community. The CAC panel will discuss the clinical literature related to Biomarkers Utilized in the Diagnosis of Synucleinopathies. Discussions will occur between CAC panelists and Contractor Medical Directors. 

The public may attend; however, questions from the public will not be entertained.

 

Interested stakeholders are invited to attend via Microsoft Teams; however, advanced registration is required.




Saturday, August 15, 2026

Patient Rights Group Sues AMA Over the "CPT Monopoly"

 AMA CPT was in the spotlight in mid-July, when CMS released a "request for information" that was highly concerned about both the AMA CPT (coding) and AMA RUC (valuation).  Entry point from my blog at the time, here.

Now, headlines that the "Patient Rights Advocate" organization has sued AMA over the CPT "monopoly" (so called).   Find PRA here, find the legal case here, find news at Fierce Healthcare here.


Here's a summary:

  • PatientRightsAdvocate.org has sued the AMA in federal court, seeking authority to publish CPT freely online. The 25-page complaint argues that CPT cannot remain privately controlled because federal and state governments have incorporated it into law and require its use across Medicare, Medicaid, HIPAA transactions, and much of healthcare billing. Alternatively, PRA argues that free nonprofit publication is fair use and that AMA’s copyright remains unenforceable because of earlier copyright misuse. 
  • The case arrives only a month after CMS, in its July 2026 Physician Fee Schedule RFI, explicitly questioned AMA’s CPT licensing monopoly and the related CPT/RUC payment processes. 
  • Sen. Bill Cassidy has separately attacked the “government-backed monopoly” and licensing fees. 
    • Both developments were reported unusually quickly and prominently by Dan Diamond at the Washington Post
  • A sweeping invalidation of CPT copyright is uncertain, but narrower victories—especially fair use, mandated free access, or revised federal licensing—appear considerably more plausible.
  • .
  • Chat GPT did an online search and summary about the moving party, the P.R.A.  Its results are here.    See the online 20-page PDF version of this story >> here << .

Friday, August 14, 2026

AI Guest Author: How Far Away Are AI-Generated Path Reports? Closer Than You Knew! (Ver2)

 Only seven days ago, we published a white paper asking, “How Far Away Are AI-Generated Pathology Reports?” Since then, we encountered several important papers, commercial programs, and industry reports that we had not incorporated in the original review—and they materially change the answer. In particular, current prostate-biopsy AI is considerably closer to assembling and prepopulating a pathology report than we had appreciated. We therefore went back to the evidence and substantially revised the white paper. The original August 7 version is available here; the new August 14 edition reflects this much more advanced pathology landscape.

Find the new paper: >>   here   <<



Summary

Medical imaging AI is moving beyond detection and measurement toward systems that assemble the diagnostic work product. The clearest regulatory example is DeepHealth SMART-B, an FDA-cleared breast ultrasound system that analyzes lesions and generates report findings and impressions for radiologist review. Pathology is approaching the same boundary faster than expected, particularly in prostate biopsy. Current commercial systems can identify cancer, assign Gleason patterns and Grade Groups, measure tumor length and percentage involvement, and transfer structured results directly into reporting interfaces. European products from Aiforia and Ibex already describe first-read and automated-reporting workflows, while U.S. FDA authorizations remain more conservative and largely adjunctive or second-read.

Research systems push further. HistoGPT generates dermatopathology reports from whole-slide images; TITAN and PRISM2 demonstrate report generation or completion of structured pathology fields. Importantly, the first useful pathology reports may not require an unconstrained language model. A validated image-analysis stack can produce structured diagnostic facts, and a deterministic template can convert those facts into an editable draft linked to supporting image evidence. The remaining barriers are less about fluent writing than reliable case assembly, uncommon findings, laboratory variability, workflow integration, safety, provenance, and FDA authorization. Prostate needle biopsy may be the first major U.S. test case.

##

See a Linked In essay by Jonathan Govette about the importance of AI actually drafting diagnostic reports - here.

Also at Linked In, Branko Perunovic discusses how the powerful digital platforms will in turn transform the nature of the departments that use them - here.

Also from Agatha Krason here.


AI Guest Author: A New White Paper, The Ten-Year Outlook of Pathology and AI

This week, I ran across an interesting article in Modern Healthcare on radiology, AI, and rural hospitals.  And that led to a new 22-page report from BAAI on the ten-year outlook of AI in radiology and how it could affect the field as a profession.

I put those together with about ten other sources and asked Chat GPT to write about the ten-year outlook for AI in Pathology.   Find it here:

https://drive.google.com/file/d/1zH3ALNo3PaeEw9QAOUxP429Rk0cR3GUm/view?usp=sharing



CMS NTAP: CMS Didn't Kill Breathrough Status, But Gave It a Leave-By Date

 For several years, CMS granted a special easier review path for new devices that had breakthrough status, and who wanted NTAP (hospital extra payment) or the equivalent in OPPS.

In Inpatient rulemaking released around August 1, CMS didn't kill the BT pathway, but gaved it a timed closure date.  You still get the easy road if you get BT from FDA by 9/30/2026, and if you get FDA approval by 5/1/2028.

9/30/2026 isn't coincidental, it gives you 60 days notice from August 1, and it is the day before the new Fiscal Year for FY policymaking.

Steve Farmer, a physician who held a senior role at CMs, discusses in detail at Linked In. And, they link to an even longer article.

https://www.linkedin.com/posts/activity-7493659447328927744-fBZl


For even more detail:

https://www.linkedin.com/pulse/breakthrough-reimbursement-shortcut-didnt-disappear-brown-md-mba-zldwe/


And a separate group discussing BT and NTAP, see David Davis here.


Thursday, August 13, 2026

Chat GPT Asks Why MEDPAC is Different

 With the current administratioin, some federal activities like PAC CARB (experts for antibiotic resistance) and USPSTF (for prevention) seemed to come to a halt.  But others, like MEDPAC (advisory body on Medicare) percolate right along.

Why is this?

###

Could We Have Predicted Which Federal Health Agencies Would Keep Running Under Trump?

Could an expert, looking ahead from December 2024, have predicted what would happen under the second Trump administration to three rather different federal health-policy institutions—MedPAC, PACCARB, and the U.S. Preventive Services Task Force (USPSTF)?

The answer is: to a surprising extent, yes—but not perfectly. The important clue was not necessarily the subject matter each organization dealt with. It was the way each institution was built and, especially, how dependent it was on the executive branch.

First, the three organizations are quite different.

MedPAC, the Medicare Payment Advisory Commission, advises Congress on Medicare payment and policy. Although its work concerns CMS and HHS constantly, MedPAC itself is an independent legislative-branch agency. Its commissioners are appointed by the Comptroller General, and it has statutory responsibilities to report regularly to Congress.

PACCARB, the Presidential Advisory Council on Combating Antibiotic-Resistant Bacteria, advises the federal government on antimicrobial resistance. It is much more conventionally an executive-branch advisory body: a presidential advisory council operating within the HHS structure and dependent on the department for meetings, staff support, appointments, and continuation of its work.

The USPSTF, meanwhile, occupies a fascinating middle position. It is an expert panel that evaluates evidence and recommends preventive services such as cancer screening. By statute, its scientific judgments are supposed to be independent. But its administrative home is AHRQ within HHS. HHS provides its support and appoints its members. Moreover, litigation over the Affordable Care Act had already raised the question of just how independent the Task Force was from the HHS Secretary.

What could one have predicted in December 2024?

MedPAC was the easy case.

CMS Releases List of CPT Lab Codes with No 1H2025 PAMA Pricing Data


HEADER: CMS RELEASES PAMA CODES WITH "NO DATA"

CMS’s PAMA “no data” list included roughly 90 conventional CPT codes, seven M-codes, and about 300 PLA codes—fully 60% of all active PLA codes.

The PLA pattern is not simply “new codes lack data”: code age was a weak predictor. Instead, commercial traction differed sharply by test type. Infectious-disease and transplant assays were far more likely to have data, while whole-genome, red-cell genetics, and therapeutic-drug tests were less likely. Oncology was surprisingly average overall. 

Read about CMS plans for a "no data" meeting Sept 15-16, 2026: Plans from Fed Reg May1, here.

If you actually want to come in person, or present, register here.  Seek the header for MEETINGS and find the link for REGISTRATION.   Reg closes August 21.  If you want to just watch the meeting(s), there will be an easy open access web link.

###

This summer, CMS called for labs nationwide to submit pricing data for claims in 1H2025, which CMS can use to reset a new fee schedule  for labs for CY 2027, '28, '29.

CMS has released a spreadsheet of over 400 codes for which NO pricing data was submitted.

Find it here:

https://www.cms.gov/files/document/pama-test-codes-no-pp-data.pdf

CMS will seek public comment and hold a public meeting about how the 400-odd codes should be priced for 2027.

CMS posted the data as a PDF File.   I exported that into an XLS and stored it open access in the cloud.  note that the Google Sheets has 2 tabs, one with all codes with no data, the second just PLA codes with no data.   Google Sheets is easily downloaded back into XLS.

https://docs.google.com/spreadsheets/d/1fNE0-rQent-VgJGnQQ_RMNJa9O2Pp9Dw/edit?usp=sharing&ouid=110053226805181888143&rtpof=true&sd=true

###

AI ASSESSES the PAMA Data

I asked Chat GPT to compare the full list of Spring 2025 PLA codes, with the new list of Spring 2025 PLA codes with no commercial pricing data.   Result;  Chat GPT is a nerd!   Seriously, Chat GPT provides a number of observational and exploratory analyses, you'll have to decide which ones might matter to you.

###

CMS’s newly released PAMA files allow an unusually simple experiment: compare proprietary laboratory analysis (PLA) codes for which CMS received no applicable private-payer information for 1H2025 against the remaining PLA codes active on the Clinical Laboratory Fee Schedule in 2Q2025.

The result is more interesting than a simple story of “new codes have no data.”

First, the headline number is surprisingly large

After cleaning the two CMS spreadsheets, there were 495 unique active PLA U-codes in the 2Q2025 CLFS file. Of these:

  • 304 codes — 61.4% — were on CMS’s “no data” list.

  • 191 codes — 38.6% — were not on the list and therefore are treated here as having PAMA data.

The cleaning matters. The CMS no-data file contained eight non-PLA G, P, and Q codes, which were excluded. The CLFS file contained duplicate identical entries for 0240U and 0241U, which were counted only once. All 304 PLA codes on the no-data list successfully matched to their longer CLFS descriptors.

Thus, nearly two-thirds of active PLA codes apparently generated no reportable PAMA private-payer data for the period.

That fact alone is striking.

Code age helps — but much less than expected

PLA numbers are issued roughly sequentially, so the numeric code provides a useful, although imperfect, proxy for age.

One might expect a straightforward pattern: older PLA codes have had years to obtain payer coverage, establish billing pathways, and generate private-payer claims, while newly issued codes have not.

The data do not show such a clean progression.

PLA code-number cohortActive codesNo-data codesPercent no data
0001–01501145750.0%
0151–030014511478.6%
0301–04501367353.7%
0451–05511006060.0%

The very oldest cohort does perform better: only half of codes 0001U–0150U lacked data. But the relationship is emphatically not monotonic. The 0151U–0300U generation performed dramatically worse than both older and newer cohorts.

At finer resolution, an extraordinary 43 of 47 codes from 0151U through 0200U — 91.5% — had no data. Some of this reflects a large block of highly specialized red-cell and blood-group genotyping codes, but those codes do not explain the entire effect.

The median code number was actually 270.5 among no-data codes versus 320 among codes with data. In other words, simple code age is a surprisingly poor predictor.

Test type tells a much more interesting story

Using the informative CLFS long descriptors, several recognizable test families can be compared. These classifications are descriptive and sometimes overlap, but the contrasts are large.

Descriptor featureCodesNo dataPercent no data
All PLA codes49530461%
Infectious disease511835%
Transplant-related13215%
AI/image-analysis related16744%
Cell-free DNA/ctDNA261350%
NGS-related502754%
Pharmacogenomics/drug metabolism291759%
Oncology overall1479263%
Whole-genome/exome related201785%
Red-cell/blood-group genetics343191%
Drug testing/therapeutic monitoring161594%

Several findings stand out.

Infectious-disease PLA codes were much more likely to produce PAMA data. Only 35% lacked data, compared with 61% of PLA codes overall. This is consistent with infectious-disease tests entering relatively conventional laboratory workflows with large numbers of commercial patients.

Transplant testing was even more striking. Only 2 of 13 transplant-related PLA codes lacked data. Although the sample is small, this is almost the mirror image of the overall PLA universe.

At the opposite extreme, 31 of 34 red-cell/blood-group genetic codes had no data, as did 15 of 16 codes related to prescription-drug testing or therapeutic drug monitoring.

Whole-genome/exome testing also stood out: 17 of 20 codes had no PAMA data.

PGx itself was not unusually disadvantaged

Pharmacogenomics provides an instructive counterexample.

A broad group of 29 drug-metabolism/PGx codes produced a 59% no-data rate — essentially the same as the 61% baseline for PLA codes overall.

Thus, a simple conclusion that “commercial payers do not pay PGx” is not supported by this comparison.

There were important differences inside PGx. Several highly specific older CYP2D6 component codes lacked data, while a number of later multigene pharmacogenomic panels did generate PAMA data.

The apparent market behavior seems to depend more on the particular test and billing model than on the label “pharmacogenomics.”

Oncology was remarkably average — until individual cancers were examined

Oncology is the largest identifiable group, with 147 codes. Overall, 63% lacked PAMA data, almost identical to the 61% rate for the complete PLA population.

But oncology was anything but homogeneous.

Among the larger recognizable subgroups:

  • Prostate: 9 of 18 no data — 50%

  • Breast: 7 of 12 — 58%

  • Lung: 5 of 9 — 56%

  • Colorectal: 13 of 14 — 93%

  • Hematolymphoid: 4 of 5 — 80%

  • Bladder: 5 of 5 — 100%

The smaller groups need cautious interpretation, but colorectal is especially notable. The no-data colorectal codes include assays spanning urine metabolites, microRNA, protein algorithms, tissue AI, methylation, cfDNA, NGS, and conventional KRAS/NRAS testing.

This suggests that even a very mainstream cancer indication does not guarantee meaningful private-payer reporting for a particular proprietary test.

Nor did “cutting-edge technology” automatically predict no data

Another surprising finding is that several technologies commonly thought of as newer or more exotic were not especially enriched among the no-data codes.

Only 50% of the 26 codes whose descriptors referenced cell-free DNA or ctDNA lacked data. NGS-related codes were at 54%. A small group involving AI or image analysis was at 44%.

By contrast, whole-genome/exome codes were at 85%.

This distinction is important. The sequencing technology itself does not appear to determine whether a PLA code generates PAMA data. The clinical application and commercial pathway appear to matter much more.

Price was also a weak discriminator

The CLFS payment amount did not divide the two populations particularly well.

The median CLFS rate was about $451 for no-data codes versus $598 for codes with data. But the distributions overlapped enormously.

Even among PLA tests priced at $2,000 or more, 45 of 84 — 54% — still had no PAMA data.

Higher-priced tests were somewhat more likely to have data, but there was no obvious price threshold at which private-payer reporting suddenly appeared.

What does “no data” really measure?

The analysis suggests that PAMA no-data status should not be interpreted simply as “private payers do not cover this test.”

At the code level, CMS is observing whether applicable laboratories reported applicable private-payer information for that HCPCS code during the collection period. Absence of data can therefore reflect several different commercial circumstances: extremely low test volume, Medicare-heavy utilization, limited private-payer coverage, use by laboratories outside the applicable-laboratory reporting universe, or a test that has simply failed to gain routine billing traction.

Conversely, the appearance of PAMA data establishes that some applicable private-payer transactions occurred; it does not establish broad national coverage or strong utilization.

Still, the binary signal is remarkably informative.

The strongest pattern in these CMS files is not that new PLA codes fail while old PLA codes succeed. Nor is it that oncology succeeds while PGx fails, or that expensive sequencing tests succeed while inexpensive tests fail.

Instead, the PAMA data seem to reveal something closer to commercial embedding: whether a proprietary assay has found its way into ordinary private-payer laboratory transactions at applicable laboratories.

Some relatively mundane infectious-disease and transplant tests clearly have. Many rare-disease, blood-group, therapeutic-drug, and whole-genome tests clearly have not.

And in 1H2025, that latter category still represented more than 60% of the active PLA code universe.



COMPARE TO CMS 2024 UTILIZATION

We compared the "zero" utilization codes in PAMA data to actual CMS  utilization of each code in 2024.

About 30 codes had CMS utilization (between 11 and 2700) in 2024.  Most were regular Cat I, not PLA.

Another 80 codes had CMS utilization, but suppressed because 10 units or less.

The remaining about 300 codes had no CMS utilization, either.

click to enlarge



Wednesday, August 12, 2026

Medicare Neurodegeneration Tests - Public Meeting - Question List Posted.

 On August 20, 2026, Medicare MACs will hold a public workshop (Contractor Advisory Committee) about neurodegeneration tests, with a focus on synuclein tests used in Parkinson's and other movement disorders.

See our original blog about it, here.

See the MAC home page, here.

Question List Now Released

A very detailed question list to guide discussion, has been released.  Find it here;

https://www.ngsmedicare.com/documents/d/ngs/2651_072826_cac_topic_biomarkers_utilized_in_the_diagnosis_of_synucleinopathies_508.pdf

The bibliography for the meeting has not been released, as of August 12.


Role of Pathologists in Molecular Ordering: in Breast Cancer, Kohle et al.

 Just a few days ago we covered Pineault et al, clinical behavior around ordering molecular testing in NSCLC.  Find the blog here: https://www.discoveriesinhealthpolicy.com/2026/08/clinical-behavior-in-genomics-new-paper.html

Don't miss a similar article, but in breast cancer, by Kohle et al., August 2026 in J Molec Dx.   Find it here:  https://www.jmdjournal.org/article/S1525-1578(26)00086-3/fulltext

See also:
An interview with Gina Murdoch, CEO of the Personalized Medicine Coalition, on "making precision medicine automatic," similar to the themes of Pineault and of Kohle.  Here.
##

AI Corner: Summary of Kohle

##

This 2026 Journal of Molecular Diagnostics consensus statement argues that pathologists should play a substantially larger role in molecular biomarker testing for metastatic breast cancer (mBC). Although NGS can identify actionable alterations, resistance mechanisms, and molecular subtypes relevant to therapy, comprehensive genomic profiling remains underused: the authors cite an estimate that only about 7% of patients with mBC receive it.

The paper is based on semistructured interviews with 19 U.S. pathologists from academic, community, and central-laboratory settings. Current practice generally leaves treatment-related biomarker ordering to oncologists, while pathologists focus on tissue adequacy, interpretation, quality assurance, and conventional markers such as ER, PR, HER2, and Ki-67. 

  • The authors argue that pathologists’ expertise in tissue selection, assay choice, histopathologic context, NGS interpretation, and laboratory quality makes them well suited to participate earlier and more proactively.

Major barriers include fragmented education, lack of standardized institutional workflows, limited access to send-out molecular results, insufficient molecular-pathology training, administrative resistance, reimbursement and prior-authorization burdens, and institutional emphasis on surgical volume rather than molecular programs. 

Community practices face particular disadvantages because they more often depend on send-out testing, increasing turnaround time and reducing integration with tumor boards.

The authors recommend greater pathologist participation in molecular tumor boards, standardized reflex-testing protocols, stronger molecular education, more in-house testing where feasible, clearer reimbursement pathways, and closer pathology-oncology collaboration. The page 3 diagram organizes these proposals into four areas: education/resources, institutional leadership, multidisciplinary collaboration, and insurance/health policy. Ultimately, the paper frames pathologists not merely as test interpreters but as potential leaders of institution-wide biomarker strategies that can reduce redundant testing, conserve tissue, shorten turnaround time, improve testing equity, and better connect genomic findings to treatment decisions.

##

##

COMPARE KOHLE, PINEAULT

## 

Kohle and Pineault reach essentially the same destination—greater pathologist ownership of molecular testing—but Pineault supplies much stronger evidence that this model is already functioning in practice.

Kohle et al. addresses metastatic breast cancer and is primarily a consensus/advocacy statement. Based on interviews with 19 pathologists, it argues that oncologists still usually initiate treatment-related biomarker testing, leaving pathologists in stand-by consultative roles despite their expertise in tissue selection, test choice, interpretation, quality assurance, and tumor-board integration. The authors call for standardized protocols, more molecular training, stronger institutional leadership, and reimbursement policies that permit greater pathologist involvement.

Pineault et al., studying NSCLC, is more concrete and quantitative. In a national survey, 77.5% of respondents reported standardized comprehensive biomarker-testing protocols, and 88.4% of those protocols included reflex multigene testing. Importantly, where reflex protocols existed, pathologists were the predominant ordering providers: 68.3% reported pathologist ordering, versus 12.2% using an oncologist standing order.

Thus Pineault effectively demonstrates the operational model that Kohle advocates: diagnosis can trigger guideline-driven molecular testing without waiting for a subsequent oncology order. Both identify reimbursement, institutional workflows, education, and multidisciplinary coordination as barriers. But Pineault goes further into CMS policy, explicitly supporting recognition of pathologists as valid ordering physicians and highlighting insurance authorization and the Medicare 14-day rule.

In shorthand: Kohle says “pathologists should own more of the process”; Pineault shows that in lung cancer they often already do—and argues CMS policy should catch up.

Monday, August 10, 2026

Example of AI at Work: AI Runs a Very Specific Information Request for Me, Every Monday

Last week, I was struck by FDA approval of software that generates a ready-to-edit report for the radiologist from ultrasounds.  (Here).

I asked Chat GPT to do a recurrent comples search every Monday.

1) Track FDA K260303 webpage for any updates like release of safety & effectiveness review.

2) Track trade journals for articles on auto-generation of reports, in radiology & pathology

3) Track PUBMED for peer review articles on auto-generation of reports, in radiology & pathology

Here's the first week's output.  The original output showed links which don't cut-paste here.
##
##

Weekly AI-generated-report watch

FDA K260303 — important baseline update. The FDA record for See-Mode Augmented Reporting Tool, Breast (SMART-B) now contains a live 510(k) Summary and says the database page was last updated August 10, 2026. However, I do not find a separately posted FDA Decision Summary or Safety and Effectiveness review/SSED. The available document is the sponsor’s 24-page 510(k) Summary, not an FDA-authored review memorandum. 

The document is nevertheless unusually relevant to our question. It states explicitly that SMART-B analyzes breast-ultrasound images, generates BI-RADS categories and descriptors, and then “generates a report based on the image analysis results” for physician review, modification, and approval.  So the regulatory record now gives us quite clear documentary evidence of FDA clearance of an image-analysis → machine-generated draft report → physician QC/finalization workflow.

Trade literature, August 3–10. One item is worth noting, although it concerns AI-generated summaries rather than autonomous diagnostic reports: Radiology Business/Health Imaging, August 5, 2026, reported on a new ACR resource for patients using AI-generated summaries of radiology reports. It is evidence that generated radiology text is moving into practical workflow and patient communication, but I would classify it as adjacent rather than another SMART-B-type image-to-report system. 

A second useful signal appeared in The Pathologist on August 6, 2026. In an interview on AI in biomarker assessment, Roche’s Audrey Bennett said the near-term computational-pathology trajectory remains collaborative rather than autonomous, with pathologist judgment retained and regulatory attention focused on the end-to-end diagnostic system. That is pertinent to our pathology-report thesis, but it does not describe a newly deployed machine-generated pathology-report product. 

PubMed. I found no PubMed-indexed paper newly published during August 3–10 that meets the strict criterion of substantive progress toward machine generation of diagnostic radiology or pathology reports. Searches did identify recent 2026 work on radiology-report generation and pathology vision-language models, but the directly relevant papers were published or placed online earlier than this seven-day window. For example, the recent American Journal of Pathology review explicitly identifies  report generation as an emerging pathology VLM capability, but it was accepted July 1 and published online in July, so I am not counting it as this week’s development.  PMID 42508637 Xia et al.

Bottom line: no new FDA Decision Summary/Safety-and-Effectiveness document yet. The most important development is that the current K260303 FDA record now exposes the detailed 510(k) Summary, which very plainly documents the machine-generated-draft-report architecture we have been tracking. I’ll continue watching specifically for the separate FDA review documents and for genuinely new image-to-report systems rather than merely generic generative-AI or report-simplification articles.

Sunday, August 9, 2026

White House, Office of Science & Technology Policy: New 123-page Guide to Administration's Thinking

It's not every day you get a 100-page-plus document that summarizes the Administration's thinking on an area like science and technology policy.   But this month, we've got one.

The government document is called, "Science: A New Golden Age."  With that somewhat gassy title, it could be anything.  But what it is, is a highly detailed and forceful plan to reboot the whole approach to  US science funding.  And the last third - pages 85-112 - are a memo from OMB/OSTP to the rest of the administration on how to fund science from FY2028 forward.

See the source government document PDF here.   It's from the OSTP - Office of Science and Technology Policy.  Which is headed by Michael Kratsios (formerly with investor Peter Thiel).

See also a news article at WSJ by Palantir's Mike Gallagher - here.

###

Now: Get a new white paper by Chat GPT 5.6 that assesses the OSTP report.  

  • Find the 11-page AI white paper >> here.<<

This is an AI-generated white paper, so it can be a benchmark for current AI abilities to read, assess, and write-up.  It should not be taken as a truth standard.

Some AI Highlights

SUMMARY

The White House Office of Science and Technology Policy’s Science: A New Golden Age is an unusually ambitious attempt to redesign the American scientific enterprise. Written by OSTP Director Michael Kratsios, whose background spans Peter Thiel, technology policy, defense R&D, and Scale AI, the report reflects a distinctly Silicon Valley and national-security view of science.

Its central argument is that the postwar research system has become too bureaucratic, institutionally entrenched, slow, and dependent on consensus-driven peer review. Kratsios proposes funding individual scientists more directly, experimenting with long-term grants, fast grants, prizes, “golden tickets,” ARPA-like organizations, and new mission-driven research institutions. NIH and biomedical research are particular targets for reform, while foundational biology, genomics, synthetic biology, neuroscience, and biomanufacturing remain strategic priorities.

The report also advocates “permissionless innovation,” faster translation of discoveries into products, increased use of real-world evidence, tighter integration of academia with industry, and stronger domestic manufacturing.

Its most futuristic section concerns AI. The proposed Genesis Mission would combine national datasets, supercomputing, AI models, scientific instruments, and autonomous laboratories. At the same time, Kratsios warns that AI could industrialize bad science, making reproducibility, machine-verifiable research, and automated scientific validation increasingly essential.

##

What are six surprises in the report?

##

  • It is much more radical than the title suggests. Rather than a celebratory science-policy essay, it argues that the postwar U.S. research system itself is outdated and needs redesign—from grantmaking and peer review to institutional structure, regulation, publication, and scientific verification.

  • It treats NIH-style peer review as a structural problem, not just a process problem. The report explicitly favors alternatives such as long-duration grants, fast grants, prizes, ARPA-like models, and even “golden tickets” that let one reviewer rescue a bold proposal rejected by consensus.

  • It is pro-science but skeptical of the biomedical research establishment. The report argues that large increases in biomedical funding have not produced commensurate gains in breakthroughs, and it implicitly challenges the assumption that “more NIH” is automatically the right answer.

  • It elevates foundational biology while downgrading the broader category of “life sciences.” Genomics, synthetic biology, neuroscience, molecular biology, and biomanufacturing remain strategic priorities, but the FY2028 guidance explicitly pushes agencies toward foundational biological science rather than simply expanding downstream life-science spending.

  • Its most futuristic proposal is not AI-assisted science, but AI-native science. The Genesis Mission envisions scientific foundation models, shared national datasets, autonomous laboratories, instrument interoperability, and closed-loop systems in which AI generates hypotheses, runs experiments, interprets results, and iterates.

  • It worries that AI could make science worse even while making every scientist more productive. One of the report’s sharpest insights is that AI may flood the system with papers, grants, and plausible findings faster than humans can verify them, so it calls for machine-auditable replication, automated verification, and continuous reproducibility infrastructure.

###
If you were one of the biggest genomics companies - think Tempus or Natera - what's the message for CEO and Board?   If you're an earlier-stage company - think Freenome - what's the message?
How would your messaging be different for the C-level team as a whole?
###

For a Natera, Tempus, or Freenome, my message would be: this OSTP report is not merely “science policy.” It is an early map of where federal research, regulatory, data, AI, and industrial-policy preferences may move over the next several years—and genomics sits unusually close to the center of that map.

To the CEO and Board

  • This is potentially favorable policy terrain for genomics—but not automatically favorable to every genomics business model. The report explicitly treats genetics, genomics, synthetic biology, quantitative biology, biotechnology, and biomanufacturing as strategically important foundational capabilities. The board-level question is therefore not “Will Washington still care about genomics?” but which parts of genomics will be treated as national infrastructure, which as commercial products, and which as legacy biomedical spending.

  • The administration appears to value platforms more than isolated tests. Shared datasets, scientific foundation models, automated laboratories, interoperable instruments, large-scale data generation, and precompetitive infrastructure are repeatedly favored. A genomics company should ask whether it can credibly present itself not merely as a seller of assays, but as an AI/data/biology platform capable of contributing to national-scale scientific infrastructure.

  • The traditional NIH-to-publication-to-commercialization pathway is being challenged. OSTP wants faster grants, long-duration awards, prizes, ARPA-like mechanisms, public-private consortia, and stronger industry participation. For a company, that potentially creates new ways to obtain federal partnership or validation that do not look like a conventional academic grant.

  • Regulatory strategy may become a competitive weapon. The report strongly endorses “permissionless innovation,” real-world evidence, reduced administrative burden, faster translation, and regulatory experimentation. A board should assume that companies capable of generating high-quality evidence rapidly—and of engaging FDA early around new evidentiary models—could gain a meaningful advantage.

  • Data assets may become more strategically important than the individual assay. OSTP treats curated scientific data as infrastructure for AI and specifically favors capturing negative results, operational laboratory data, and other material that is normally discarded. For Tempus especially, but also Natera or Freenome, the board should be asking: what proprietary dataset do we possess that becomes dramatically more valuable in an AI-for-science world?

  • Do not underestimate the China and domestic-capacity dimension. The report repeatedly links biotechnology to domestic manufacturing, resilient supply chains, strategic technology leadership, and national security. A company with U.S.-based laboratories, sequencing infrastructure, biobanks, reagents, compute, or manufacturing should think about how to make that part of its policy narrative.

  • The biggest risk is assuming that “biomedical innovation” itself guarantees favored status. OSTP explicitly argues that life sciences have absorbed a disproportionate share of non-defense R&D while productivity has disappointed. The winning argument will therefore be not “we are health care, please fund us,” but “we are foundational technology that increases scientific productivity, creates strategic capability, and produces measurable downstream value.”

I would phrase it differently to the C-level team as a whole

Yes. With the CEO and Board, I would emphasize strategic positioning, capital allocation, federal-policy risk, and potential competitive advantage.

With the broader C-suite, I would make it operational:

“Assume that Washington may increasingly reward genomics companies that can demonstrate five things: unique data, AI-enabled scientific productivity, rapid real-world validation, domestic strategic capability, and willingness to participate in precompetitive federal infrastructure.”

Then I would assign concrete workstreams.

The Chief Scientific Officer should identify which company assets could fit Genesis Mission-style science: multimodal datasets, longitudinal genomic records, foundation models, autonomous analytics, assay-development automation, or large-scale validation.

The regulatory leader should examine where FDA's evolving use of RWE, one-pivotal-trial concepts, adaptive evidence generation, and other streamlined approaches could change development plans. The report clearly endorses these directions, although it does not specify a new genomics-specific FDA pathway.

The government-affairs team should stop treating OSTP as peripheral. NIH, FDA, HHS, NSF, DOE, OMB, and White House technology policy are becoming more interconnected under this framework. The FY2028 annex is particularly important because OSTP and OMB explicitly tell agencies to use these priorities in budget formation.

The CTO/data team should ask what would be required to make company data AI-ready, interoperable, auditable, and scientifically reusable—because those characteristics are repeatedly privileged in the report.

The business-development team should look for federal consortia, challenge prizes, shared infrastructure, national missions, and cost-shared partnerships, not merely grants. OSTP explicitly encourages those mechanisms.

And the CFO should recognize one important nuance: this philosophy is simultaneously pro-innovation and skeptical of routine federal subsidy. Later-stage projects may increasingly be expected to attract private cost share, while government concentrates on foundational or precompetitive work.

If I had to reduce the CEO/Board message to one slide, I would probably title it:

OSTP Is Redefining What Counts as a Strategically Valuable Genomics Company

And underneath:

The favored company of this policy framework is not simply one with a good molecular test. It owns differentiated biological data, uses AI to accelerate discovery, validates rapidly in the real world, contributes to national scientific infrastructure, and can translate innovation into scalable U.S. capability.

For Natera, that points toward its enormous longitudinal clinical-genomic evidence base and scale of real-world testing. For Tempus, the fit with multimodal data, AI, clinical data infrastructure, and foundation-model thinking is almost explicit. For Freenome, the opportunity is somewhat different: position MCED not simply as another diagnostic product, but as a large-scale biology-and-data platform whose validation could itself become national scientific infrastructure.

That last distinction is where I would spend a surprising amount of CEO time.

#

#

#