What the OSTP’s New Policy Blueprint Means for Pharma Manufacturing and Development

In late July 2026, the White House Office of Science and Technology Policy (OSTP) released Science: A New Golden Age, a 123-page report to the President authored by OSTP Director Michael Kratsios.¹ Framed explicitly as a modern sequel to Vannevar Bush's 1945 report Science: The Endless Frontier²—the document that created the postwar federal science funding system and led to the founding of the National Science Foundation (NSF)—the new report diagnoses what it calls a slowdown in American scientific productivity and lays out a reform agenda covering federal research funding, regulatory policy, domestic manufacturing, and the role of AI in science.¹

Much of the report is broad science policy: restructuring NSF grant mechanisms, opening national laboratories to industry, reforming graduate education. But several sections speak directly to the CMC, manufacturing, regulatory, and supply-chain concerns that matter those working in pharmaceutical manufacturing and development. Here's what's in it, and what to watch for.

The Productivity Problem: Eroom's Law Goes Official

The report leads its diagnosis of American science with a well-recognized statistic: the steady decline in drug-development efficiency often called "Eroom's Law" (Moore's Law spelled backward). According to the report, pharmaceutical R&D efficiency, measured as new drugs approved per billion dollars spent, has fallen roughly eightyfold in inflation-adjusted terms since 1950, with efficiency roughly halving every nine years.¹ That figure traces directly to the 2012 paper that coined the term, by Jack Scannell and colleagues in Nature Reviews Drug Discovery, which reported the identical eightyfold decline and nine-year halving period.³ The report also notes that despite the NIH budget more than doubling since the 1990s, breakthrough treatments, citation impact per dollar, and overall scientific productivity have not scaled proportionally.¹

This isn't a new observation to industry insiders, but its inclusion in a formal White House policy document elevates it from an industry talking point to an official justification for reform of grant structures, regulatory review, and how the government funds biomedical research generally.

Reproducibility and the Alzheimer's Cautionary Tale

One of the more pointed case studies in the report involves a 2009 Alzheimer's research paper published in a top journal that proposed a promising treatment target.⁴ The report recounts that other researchers demonstrated the finding was not reproducible by 2012, and that a pharmaceutical company's internal review had already ended a drug development program based on the work. Even so, the report notes, the paper continued to accumulate more than 800 citations and helped misdirect research priorities and federal funding for roughly another decade before being formally retracted 15 years after its original publication, and only after its lead author resigned amid a separate investigation into data manipulation.¹

While the report doesn't name names, the details identify the case precisely: it's the 2009 Nature paper "APP binds DR6 to trigger axon pruning and neuron death via distinct caspases," co-authored by Marc Tessier-Lavigne while he was a scientist at Genentech. Genentech's own internal review had flagged reliability problems with the paper's central finding as early as 2008, before publication.⁴ The paper drew more than 800 citations by the time Tessier-Lavigne, president of Stanford University by then, resigned that post in July 2023 following a Stanford investigation into data manipulation across several of his papers; the Alzheimer's paper itself was formally retracted in December 2023, about 15 years after it appeared.⁵

The report uses this episode to argue for what it calls "Gold Standard Science," a push, tied to an existing "Restoring Gold Standard Science" executive order,⁶ to mandate reproducibility, transparency, data sharing, and falsifiability across federally funded research.¹ For those involved in sponsored biomedical research or NIH-funded programs, this points toward tighter expectations around data transparency and replication going forward, and toward AI-assisted "verification infrastructure" intended to catch irreproducible results before they propagate.¹

Deregulation: Pharma as the Test Case

Chapter III of the report calls for "restoring permissionless innovation," reweighting regulatory review to account for the cost of inaction, not just the risk of action, and expanding regulatory sandboxes that let companies test new technologies under controlled conditions. Notably, the report cites the administration's existing reforms in "nuclear, pharmaceuticals, and drones" as the model it wants to extend into other sectors.¹

That's a signal worth flagging: pharma is being held up in this document as a precedent-setting example of the administration's deregulatory approach, meaning further changes to FDA review processes, expanded use of real-world evidence, or new regulatory sandbox frameworks could follow, framed as extensions of work already underway rather than new policy territory.

New Funding Models that Could Reach Bio/pharma

A large portion of the report is devoted to reforming how federal science funding actually works, and several of the proposed mechanisms are directly relevant to bio/pharma researchers used to navigating NIH's standard R01 grant structure.

The report highlights "Focused Research Organizations" (FROs), time-bound, non-profit research entities designed to break specific scientific bottlenecks that are too large for an academic lab but not commercially attractive enough for a pharmaceutical company to pursue on its own. It gives the example of platform technologies for decoding basic biology, noting that pharmaceutical companies "face much stronger incentives to chase the next drug breakthrough than to build platform technologies for decoding basic biology," precisely the kind of infrastructure work FROs are meant to fill.¹

The report also points to NSF's newly launched "X-Labs" program, the agency's first initiative explicitly designed to fund independent research organizations outside traditional academic institutions, offering full-time research teams operational autonomy and milestone-based funding.¹ Other funding mechanisms discussed include "golden ticket" systems (piloted in Denmark and now being tested by NSF) that let individual reviewers champion high-risk proposals outside of consensus review, prize challenges and advanced market commitments that pay for outcomes rather than effort, and "fast grant" models capable of turning around funding decisions in 48 hours rather than 6-9 months.¹

For those involved in academic-industry partnerships or grant-funded biomedical research, these mechanisms represent a widening menu of funding pathways beyond the traditional NIH grant cycle, worth tracking as they scale.

Manufacturing Reshoring Gets Elevated to a "National Character" Issue

Chapter IV argues that scientific discovery alone doesn't guarantee that the resulting manufacturing jobs, supply chains, and process knowledge stay in the United States. The report points to lithium-ion batteries and EUV lithography as cautionary examples, technologies the U.S. helped invent but where manufacturing capacity and supply chains are now dominated by companies headquartered in Asia and Europe.¹ It argues explicitly that "discovery without domestic manufacturing leaves America paying the research bill while rivals develop the process improvements and capture the economic, strategic, and knowledge returns."¹

The report frames reshoring not simply as an economic policy goal but as a national security and "national character" issue, which suggests continued (and possibly expanded) federal attention to incentives for domestic pharmaceutical manufacturing, alongside workforce development proposals, including new apprenticeship pathways, practitioner-in-residence programs pairing skilled technicians with PhD researchers, and expanded community college partnerships aimed at rebuilding the "hands-on" manufacturing workforce alongside the research workforce.¹

AI for Science: The "Genesis Mission"

The report's final chapter calls for launching and scaling what it calls the "Genesis Mission," a flagship national AI-for-science initiative intended to integrate supercomputers, AI models, scientific instruments, and datasets across national laboratories, with a stated goal of doubling the productivity of U.S. science within a decade.¹ It also calls for accelerating investment in autonomous, closed-loop laboratories and robotics-driven experimentation, arguing these could compress discovery timelines "by orders of magnitude."¹

Expect new federal funding vehicles and infrastructure investments aimed at AI-driven discovery and automated experimentation, which biologics developers, CDMOs, and drug discovery teams may be able to access through partnerships with national laboratories as these programs scale.

What to Watch for

Taken together, a few practical threads stand out:

Regulatory policy: Watch for FDA guidance or executive actions that build on the report's framing of pharmaceutical deregulation as an already-successful model to extend elsewhere.

Funding access: New mechanisms like FROs, X-Labs, golden-ticket review, and fast grants could open funding pathways for platform technology development that don't fit neatly into a standard NIH grant.

Research integrity: Expect increased emphasis on reproducibility and data-sharing requirements in federally funded biomedical research, tied to the "Gold Standard Science" executive order.

Manufacturing and workforce policy: Reshoring incentives and new workforce training models are likely to remain a policy priority, reinforcing trends already underway in API and biologics manufacturing.

AI infrastructure: The Genesis Mission and related AI-for-science investments may create new collaboration opportunities between national labs and industry for AI-driven drug discovery and automated experimentation.

One important caveat: this is a policy vision document from the OSTP director, not enacted legislation. Many of its central proposals—the Genesis Mission, new institutional funding models, expanded regulatory sandboxes—are recommendations rather than current law. How much of this translates into actual FDA guidance, NIH funding structures, or budget appropriations remains to be seen and will depend on subsequent executive and legislative action.

References

1. Kratsios, M. Science: A New Golden Age. Office of Science and Technology Policy, A Report to the President, July 2026, https://www.whitehouse.gov/wp-content/uploads/2026/07/Science-A-New-Golden-Age.pdf.
2. Bush, V. Science, the Endless Frontier, 75^th Anniversary Edition. National Science Founcation. https://nsf-gov-resources.nsf.gov/2023-04/EndlessFrontier75th_w.pdf
3. Scannell J, Blanckley A, Boldon H, Warrington B. Diagnosing the Decline in Pharmaceutical R&D Efficiency. Nature Reviews Drug Discovery. 2012;11(3):191-200. https://doi.org/10.1038/nrd3681.
4. Wosen J. Stanford President to Resign After Investigation of Research. STAT. July 19, 2023. https://www.statnews.com/2023/07/19/marc-tessier-lavigne-stanford-president-resignation
5. Retraction Watch. Former Stanford president retracts Nature paper as another gets expression of concern. December 2023, https://retractionwatch.com/2023/12/18/former-stanford-president-retracts-nature-paper-as-another-gets-expression-of-concern
6. The White House. Restoring Gold Standard Science – Executive Order 14303. Available at https://www.whitehouse.gov/presidential-actions/2025/05/restoring-gold-standard-science/.