Subject: NIH Strategic Plan RFI (NOT-OD-26-047), deadline May 16. 5 minutes of your time matters.

Colleagues,

NIH is developing its Strategic Plan for FY 2027-2031 and has issued an RFI (NOT-OD-26-047) requesting public comment on the framework. The submission form is short: three text boxes (500 words each), covering research areas, research capacity, and research operations. Deadline is May 16, 2026.

Submission link:

https://grants.nih.gov/grants/guide/notice-files/NOT-OD-26-047.html  (scroll down to: How to Submit a Response)

I want to be direct about why I’m writing. I spoke with an NIH program officer about whether submitting comments even matters given the current environment. Their response, paraphrased: All public comments must be collected and become part of the official record. That record provides evidence for change later, and possible legal recourse if the administration ignores public input without sound reasoning. It feels like screaming into the ether, but submitting a comment about anything is better than silence.

A second program officer put it more bluntly: The comments will be ignored by the administration. But they won’t be ignored in the historical record. It’s important to document where the scientific community is on these issues. It’s important to have documentation that this administration ignored public comments. Silence will be inferred as support.

In other words, this is not about persuading the current administration. It is about building the evidentiary record that future policymakers, oversight bodies, and courts can use. Under administrative law, agencies must demonstrate they considered public input. A robust comment record makes it harder to justify ignoring the scientific community. An empty record makes it easy.

What I’m asking: Submit something. It does not need to be comprehensive. Even 2–3 sentences on one topic you care about contributes to the record. You can submit anonymously. You do not need to fill every box.

Topics where scientist input is especially needed:

•       Payline compression is crowding out basic science in favor of low-risk, translationally proximate proposals

•       The growing backlog of meritorious but unfunded applications wastes the public investment already made in generating those programs

•       Early-career investigators are disproportionately harmed by funding uncertainty, resubmission delays, and conservative review norms

•       Interdisciplinary and cross-species translational proposals are structurally disadvantaged in single-discipline study sections

•       Peer review panels sometimes lack the expertise needed to evaluate proposals that span traditional disciplinary boundaries

•       The unidirectional translational pipeline (bench to bedside) misses the reverse direction, where clinical failures generate new basic science questions

•       Administrative burden for cross-IC proposals discourages investigators from pursuing boundary-spanning research

I’ve attached a bullet list organized by the three RFI priorities with pre-drafted points you can pick from, adapt, or use as a starting point. Feel free to use any of this language verbatim, rewrite it in your own voice, or ignore it entirely and write about whatever matters to you. The goal is volume of independent voices, not uniformity. (or visit B.I.O.N.I.C. Lab - Request for Information NIH)

If you forward this to colleagues in your own networks, even better. The PO’s message was clear: they want the record flooded with comments from working scientists.

A note to graduate students, postdocs, and early-career investigators: Your voice matters here, perhaps more than anyone’s. You are the people most affected by the decisions this strategic plan will shape, and you are the least represented in policy feedback. Do not assume your perspective is too limited or your career too early to count. The RFI accepts anonymous submissions. You do not need to be a PI or have funding to comment.

Public comment has changed NIH policy before. The BRAIN Initiative K99/R00 career transition awards exist in part because trainees and early-career scientists made the case that the pipeline was failing them. On the other side, when NIH proposed the Grant Support Index in 2017 to redistribute funding from large labs to early- and mid-career investigators, it was abandoned within a month after well-funded senior scientists mobilized against it, while the trainees and junior faculty who would have benefited largely stayed silent. The lesson is straightforward: the voices that show up in the record are the voices that shape policy. If early-career scientists do not comment, the plan will be written by and for people who already have funding.

There is also a second public webinar on April 8, 2026, 2:30-3:30 PM ET, where NIH leadership will present the framework and take questions. Registration required. Questions asked during the webinar also become part of the public record.

Thank you for considering this. Five minutes of your time now becomes part of the permanent record. Please forward to your network.

Best,
TK

NIH Strategic Plan RFI (NOT-OD-26-047)

Pick-and-Choose Bullet Points for Each Priority

How to use this document:

Each priority below has standalone bullet points you can copy, combine, or adapt. Pick 1-3 points that resonate with your experience, paste them into the submission form, and add a sentence or two from your own perspective. You do not need to address all three priorities. Even a single point in one box counts. The form is at: NOT-OD-26-047. Deadline: May 16, 2026.

This document has two sections. Section A contains structural and scientific arguments that apply regardless of administration. Section B addresses the current NIH climate directly, including recent policy actions, grant terminations, and political interference in funding decisions. Choose your comfort level. Both sections contribute to the public record.

SECTION A: STRUCTURAL AND SCIENTIFIC ARGUMENTS

Priority 1: Research Areas

Protecting Basic Science Under Budget Pressure

•       When paylines compress, basic science proposals are the first to be crowded out because the uncertainty inherent in foundational research becomes disqualifying in a zero-sum scoring environment. The strategic plan should include structural protections ensuring that foundational research is not sacrificed to translational pressure under constrained budgets.

•       NIH’s mission foregrounds “fundamental knowledge about the nature and behavior of living systems,” yet portfolio drift toward applied, incremental work is a predictable consequence of tightening funding. Goal 1 needs operational safeguards, not just aspirational language. Portfolio-level metrics tracking the balance between foundational and translational awards would provide transparency and enable course correction.

•       Many of the most important biomedical advances of the past 50 years originated from basic research programs with no foreseeable clinical application at the time of funding. Compressing paylines selects against precisely this kind of work by rewarding proposals with the most immediate translational justification.

•       The current funding environment incentivizes investigators to frame basic science questions in translational terms, often artificially. This distorts both the science and the review process. NIH should create space for proposals that are evaluated on the quality of the biological question rather than proximity to a clinical endpoint.

Bidirectional Translation

•       The framework’s three goals (foundational knowledge, prevention, interventions) recapitulate the conventional unidirectional pipeline from bench to bedside. In practice, the most productive research programs operate bidirectionally: clinical failures reveal fundamental biological questions that cannot be anticipated from first principles, and mechanistic insight reshapes what interventions are feasible.

•       Reverse translation, where clinical observations generate new basic science questions, should be recognized as a distinct and valued research mode, not an afterthought. Current study sections often penalize proposals that move in this direction, categorizing them as “too basic” for clinical panels or “too applied” for basic panels.

•       Examples of reverse translation span domains: implantable neural interfaces degrade due to biological responses discovered only after clinical performance decline; gene therapies encounter immune reactions revealing uncharacterized cell biology; regenerative medicine approaches fail when host tissue responses override engineered microenvironments. In each case, the critical science emerged from tracing failure back to mechanism.

•       NIH should establish funding mechanisms that explicitly support bidirectional translation, where clinical or engineering observations motivate new basic science questions, with review criteria that value this approach rather than penalize it.

Cross-Species and Cross-Scale Research

•       Translation fails when findings from one model system are assumed to generalize without systematic cross-species validation. Funding mechanisms that span rodent, large animal, and human studies within a single award would reduce fragmentation and improve translational success rates.

•       Research on biological barriers to therapeutic durability should be a cross-cutting theme linking Goals 1 and 3. The host biological response to any intervention (device, molecule, cell, gene) is a fundamental determinant of long-term efficacy, and this problem is shared across biomedical research.

•       Understanding biological responses to chronic therapeutic interventions (implants, sustained drug delivery, gene expression modification) is essential to long-term safety. Proactive investment in the biology of therapeutic durability will prevent costly post-market failures.

Priority 2: Research Capacity

Early-Career Investigator Vulnerability

•       Early-career investigators are disproportionately harmed by funding uncertainty. Tenure clocks run regardless of NIH funding timelines, and a 2–3 year resubmission cycle can end a career before it begins. The strategic plan should recognize this asymmetry and develop protective mechanisms.

•       Under compressed paylines, the proposals most likely to survive are disciplinarily legible, backed by established reputations, and low-risk. Early-career investigators pursuing novel, interdisciplinary, or high-risk research absorb the cost of this conservatism disproportionately because they lack the funding buffer and track record to survive a single poor review cycle.

•       The growing backlog of meritorious but unfunded applications is not merely a budget problem. It is a workforce problem. When scientifically excellent programs wait years for support, trainees graduate without seeing the work funded, preliminary data ages out, and institutional commitments expire. The human capital invested in generating these programs depreciates with every resubmission cycle.

•       NGRI-style payline relaxation for early-stage investigators was an important precedent. Analogous protections should be developed specifically for early-career investigators pursuing interdisciplinary or category-spanning proposals, where review penalties are compounded by disciplinary boundary dynamics.

•       The current environment is driving early-career scientists toward conservative, single-discipline research programs at precisely the career stage when intellectual risk-taking has the highest long-term return for the scientific enterprise.

Interdisciplinary Training and Workforce Development

•       True interdisciplinary research requires investigators with deep expertise in one discipline and functional literacy in adjacent fields. This is distinct from multidisciplinary collaboration, where specialists contribute in parallel. Training programs that produce genuinely interdisciplinary investigators are rare and lack stable funding.

•       T32 and institutional training grant structures should be adapted to support cross-disciplinary cohorts that span departments and schools, rather than department-anchored programs that reproduce existing silos.

•       Reverse-translational competency, the ability to trace clinical outcomes back to biological mechanism and reformulate basic science questions, is a trainable skill. Training programs should teach this framework explicitly alongside conventional translational methodology.

•       NIH can influence institutional culture around interdisciplinary work through funding mechanisms that require and reward sustained cross-disciplinary integration, not merely letters of collaboration on grant applications. Current promotion and tenure structures at most institutions reward depth within a single field, and NIH funding signals are one of the few levers that can shift this.

•       Small, problem-focused workshops and conferences that convene investigators across the basic-to-clinical spectrum generate more productive interactions than large society meetings. Dedicated funding mechanisms (R13, U13) should be maintained and expanded, with review criteria that weight cross-disciplinary integration alongside scientific merit.

Research Infrastructure

•       Shared-use facilities designed for cross-species, cross-modality research would accelerate translational integration. Many bottlenecks arise because laboratories studying different model systems operate in physical and administrative isolation.

•       Data infrastructure for sharing negative results and translational failures across institutions would reduce redundant investment and accelerate learning. Currently, the knowledge of why interventions fail is fragmented across individual laboratories and rarely disseminated systematically.

Priority 3: Research Operations

Peer Review Structure and Bias

•       Peer review panels for interdisciplinary and cross-species proposals must include reviewers with expertise spanning the relevant disciplines and model systems. When panels lack this expertise, proposals are evaluated on the components reviewers understand and penalized on those they do not.

•       Research in organizational science has shown that in evaluation settings where reviewers serve as disciplinary gatekeepers, the penalty for category-spanning candidates is driven by boundary maintenance, not by confusion about the candidate’s abilities. Evaluators penalize high-performing interdisciplinary candidates because they threaten the distinctiveness of the evaluator’s own field. This effect is strongest when evaluators are highly typical members of their discipline.

•       Review criteria should explicitly value bidirectional translation. Proposals that move from clinical observation back to mechanistic investigation currently score poorly because reviewers perceive them as lacking a clear clinical endpoint. Recognizing reverse translation as a valued approach within scoring criteria would correct this bias without requiring new funding mechanisms.

•       The consensus-averaging process in study sections mechanically suppresses high-variance proposals. A single skeptical reviewer can effectively veto an innovative proposal. NIH should consider structural reforms, such as modified scoring algorithms or separate innovation tracks, that prevent the systematic elimination of high-risk, high-reward science.

•       Transparency in how panel expertise is matched to proposal content would improve public trust. Summary-level information about panel disciplinary composition relative to the scope of reviewed proposals (without identifying individuals) would strengthen confidence in fairness.

Stewardship and Efficiency

•       The backlog of meritorious but unfunded proposals represents a stewardship failure. When scientifically excellent programs wait years for funding, the public investment already made in those programs (trained personnel, institutional infrastructure, preliminary data) depreciates. The strategic plan should commit to transparency about the gap between meritorious and funded applications.

•       NIH should invest in systematic analysis of translational failure. Many therapeutic programs fail at predictable stages for identifiable biological reasons. Cataloging why interventions fail would reduce redundant investment and generate new basic science questions. This is analogous to the aviation industry’s systematic accident investigation, where understanding failure prevents recurrence.

•       Administrative burden for cross-IC proposals (spanning NINDS, NIBIB, NEI, NIA, etc.) discourages investigators from pursuing boundary-spanning research. Streamlining application preparation, reporting, and compliance for genuinely interdisciplinary programs would improve both efficiency and the willingness of investigators to take on this work.

•       Good stewardship of public research investment requires that funding decisions, peer review, and program management reflect how productive science actually works, not how it is traditionally organized within NIH’s institutional structure.

Public Trust and Accountability

•       Public trust in science is strengthened when operational structures visibly match the stated mission. If NIH’s mission prioritizes fundamental knowledge but its funding structures systematically favor translational and applied work, the gap between rhetoric and practice erodes credibility.

•       Transparency about how funding decisions are made, including the role of paylines, program officer discretion, and IC-level priorities, would help investigators and the public understand the system and trust its fairness.

•       The strategic plan should commit to regular, public reporting on portfolio balance across foundational, translational, and applied research, enabling external assessment of whether NIH’s funding patterns match its stated priorities.

SECTION B: CURRENT NIH CLIMATE

The bullets below address recent policy actions and their impact on the research enterprise. These are more politically direct than Section A. Use them if they reflect your experience and concerns. All public comments become part of the permanent record and provide evidence for future oversight, litigation, and policy correction. You can submit anonymously.

Priority 1: Research Areas

Content-Based Grant Terminations and Self-Censorship

•       NIH terminated nearly 1,000 grants representing approximately $1.7 billion in 2025, many based on keyword screening rather than scientific review. Internal IC guidelines included trigger words such as “gender,” “justice,” “marginalized,” and “climate.” The strategic plan should affirm that research topics are determined by scientific merit and public health need, not by political alignment.

•       The chilling effect of content-based terminations extends far beyond the terminated grants themselves. Investigators are now avoiding entire research areas, including health disparities, environmental health, and behavioral determinants of disease, not because the science lacks merit but because they fear keyword-triggered review. This self-censorship narrows the scope of American biomedical research in ways that will not be visible in any official count of terminated grants.

•       From 2012 through January 2025, NIH terminated fewer than 6 grants midstream in 13 years. The scale of recent terminations is unprecedented and represents a fundamental departure from established norms of scientific funding stability. The strategic plan should commit to procedural protections ensuring that funded grants can only be terminated for cause, with transparent scientific justification and an appeals process.

•       A federal judge stated he had “never seen racial discrimination by the government like this” during four decades on the bench, referring to the pattern of grant terminations. Regardless of one’s position on specific research topics, the absence of consistent, transparent criteria for termination decisions undermines confidence in the entire funding system.

Health Disparities Research as Foundational Science

•       Population-level differences in disease incidence, treatment response, and health outcomes are empirical observations, not ideological positions. Understanding why certain populations experience higher rates of cardiovascular disease, diabetes, or cancer is mechanistic biology. Reframing health disparities research as foundational science rather than as a political category would protect it from ideological interference while strengthening Goal 1.

•       NIH leadership has stated that research “based on ideologies that promote differential treatment of people based on race or ethnicity” does not meet agency priorities. However, studying biological, environmental, and social determinants of health across populations is not “differential treatment.” It is the scientific method applied to observable variation. Conflating empirical investigation of health differences with ideological advocacy undermines Goal 1’s commitment to foundational knowledge.

•       Research on health disparities has direct relevance to the health of rural, low-income, and geographically underserved populations, including many communities that the current administration has identified as priorities. Defunding this research does not serve those communities. It abandons them.

International Collaboration Under Threat

•       The new PF5 mechanism for international research collaborations adds substantial administrative complexity at precisely the moment when global scientific competition demands faster cross-border partnerships. While oversight of foreign subawards is legitimate, the structural change risks deterring international collaboration rather than improving it. The strategic plan should explicitly value international partnerships as essential research infrastructure.

•       The combination of funding uncertainty, political scrutiny of foreign-born researchers, and restructured international funding mechanisms is driving talent out of the U.S. research system. Chinese and Chinese-American researchers, who represent a disproportionate fraction of NIH-funded investigators, are reassessing their futures here. Every researcher who leaves takes training, expertise, and networks that took years to build.

Priority 2: Research Capacity

Forward Funding and Award Compression

•       Forward funding (paying multi-year grants as lump sums) mechanically reduces new awards even when the total budget is stable. Estimates suggest a roughly 38% reduction in new award slots. Congress blocked further expansion of forward funding in the FY2026 appropriations bill, but damage to the 2025 pipeline is already done. The strategic plan should commit to multi-year incremental funding as the default, preserving the maximum number of new awards per dollar appropriated.

•       Forward funding is presented as modernization but functions as a bottleneck. The same total dollars distributed as lump sums fund fewer investigators than the same dollars distributed annually. This is arithmetic, not a policy disagreement. The strategic plan should be explicit about which funding distribution model maximizes the number of supported investigators.

•       New competitive NIH awards dropped 74% year-over-year in 2025. R01 success rates fell to approximately 17%, the lowest in nearly three decades. These numbers reflect not a budget cut (Congress increased NIH funding) but administrative decisions about how appropriated funds are distributed. The strategic plan should commit to transparency about the relationship between appropriated budgets and actual award numbers.

Training Pipeline Collapse

•       Universities are already reducing graduate cohort sizes and withdrawing financial support from admitted students in direct response to grant uncertainty. UMass Amherst cut its doctoral cohort from 997 to 712 in a single year. These are not temporary adjustments. Every student not admitted represents a 5–7 year gap in the training pipeline that cannot be recovered by restoring funding later.

•       A recent national survey found that 58% of NIH-funded researchers are slower to hire new lab members and 62% of junior tenure-track faculty are very concerned recent changes could derail their tenure. This is not anxiety. It is rational risk assessment in an environment where funding timelines are unpredictable and grant terminations can occur without scientific cause.

•       The strategic plan’s workforce goals are meaningless if the training pipeline is collapsing in real time. Workforce development requires funding predictability across at least a 5-year horizon, the minimum time to train a doctoral student. Episodic disruptions compound into generational losses that no future budget increase can fully repair.

Indirect Cost Infrastructure

•       The proposed 15% indirect cost cap (currently blocked by courts and the FY2026 appropriations bill) targeted the physical infrastructure that makes research possible: vivaria, biosafety facilities, IACUC coordination, equipment maintenance, institutional review boards. The strategic plan should explicitly identify institutional infrastructure funded through indirect costs as essential research capacity, not administrative overhead.

•       Unlike a budget cut that Congress can reverse in the next cycle, infrastructure degradation compounds. Shutting down a vivarium, scattering a trained research team, or letting specialized equipment lapse from service contracts creates damage that takes years and more money to repair than the original investment. The strategic plan should recognize infrastructure continuity as a core stewardship principle.

•       Indirect cost rates are negotiated based on audited institutional expenditures. They are not arbitrary markups. They reflect the actual cost of maintaining the research environment that makes grant-funded science possible. The strategic plan should defend negotiated rates as an evidence-based mechanism, not a target for across-the-board reduction.

International Talent Retention

•       The U.S. research enterprise depends on international talent at every career stage. Foreign-born scientists represent a substantial fraction of NIH-funded investigators, postdoctoral fellows, and graduate students. Policies that create uncertainty about visa status, foreign collaboration, or the political acceptability of research topics drive the most mobile talent to competing nations first.

•       China, the EU, and other competitors are actively recruiting researchers leaving the U.S. system. The strategic plan’s workforce goals should acknowledge that talent retention requires not only training programs but a stable, welcoming, and scientifically free research environment.

Priority 3: Research Operations

Political Interference in Funding Decisions

•       NIH eliminated published paylines and replaced them with discretionary factors including “geographic balance of funding” and alignment with administration priorities. While some flexibility in funding decisions is reasonable, the absence of transparent, pre-announced criteria creates uncertainty and opens the door to political influence over which science gets funded.

•       Internal NIH emails have shown DOGE flagging specific grants for IC review, suggesting that entities outside the scientific peer review process are influencing which grants survive. The strategic plan should commit to structural insulation of peer review from political direction, with clear boundaries between scientific evaluation and programmatic decision-making.

•       The strategic plan should affirm that scientific priorities are determined by scientific merit and public health need, reviewed by domain experts through peer review, and insulated from executive override. This is not a partisan position. It is the foundation of the system that has made American biomedical research the global standard for 75 years.

•       Funding decisions made behind closed doors, without transparent criteria, and subject to political screening cannot sustain public trust regardless of which party holds power. Goal 2 (transparency and accountability) requires that the process for making funding decisions be as rigorous and transparent as the science those decisions are meant to support.

Procedural Protections for Funded Research

•       The strategic plan should commit to procedural due process for grant terminations. Funded grants represent contractual commitments supported by peer review. Terminating them without scientific cause, transparent justification, and an appeals process violates the trust that the entire system depends on.

•       Researchers who have had grants terminated or frozen report lasting damage to their programs, trainees, and collaborations, even when funding is eventually restored. The process itself is the punishment. Delayed reviews, frozen applications, and retroactive changes to funding criteria inflict harm regardless of eventual outcomes. The strategic plan should recognize that funding predictability is itself a form of stewardship.

•       When investigators cannot trust that a funded grant will remain funded for its awarded duration, they cannot responsibly hire trainees, commit to longitudinal studies, or invest in infrastructure. The strategic plan should treat grant stability as a core operational principle, not a discretionary benefit.

Timely Obligation of Appropriated Funds

•       OMB released NIH’s FY2026 funds on March 16, nearly six months into the fiscal year. Congress appropriated the money. NIH’s job is to spend it on the best science. Delays in obligating appropriated funds cascade through every institution dependent on federal research support. The strategic plan should commit to timely obligation as a non-negotiable operational standard.

•       Late obligation of funds does not save money. It destroys value. Research teams that cannot plan beyond a quarterly horizon cannot execute multi-year science. The strategic plan should recognize that the timing of fund distribution is as important to research productivity as the amount distributed.

Independence of Scientific Priority-Setting

•       The pattern of keyword-based screening, content-based terminations, DOGE-flagged reviews, and elimination of transparent paylines represents a structural shift from peer-review-driven to executive-driven science funding. The strategic plan should name this risk explicitly and commit to preserving the independence of scientific priority-setting from political direction.

•       American biomedical research leadership was built on a system where the government funds science but does not direct it. The peer review process, for all its imperfections, ensures that funding decisions are made by people who understand the science. Replacing that system with political screening, whether overt or through administrative mechanisms like keyword triggers and discretionary paylines, will produce a research portfolio optimized for political palatability rather than scientific impact.

•       The strategic plan is a public document that will outlast any single administration. It should articulate principles of scientific independence, procedural fairness, and evidence-based priority-setting that future leaders can be held to, regardless of political affiliation. This is precisely why the public comment record matters.

TK Draft
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Priority 1: Research Areas 

The framework identifies foundational knowledge (Goal 1) and interventions/cures (Goal 3) as distinct priorities, but the sequential implication, that basic discovery feeds forward into translation, underrepresents how biomedical research actually advances. The most productive programs operate bidirectionally. Clinical and engineering failures routinely expose fundamental biological questions that cannot be anticipated from first principles, and mechanistic discoveries reshape what interventions are feasible.

This pattern recurs across therapeutic domains. Implantable neural interfaces degrade over months to years not from engineering limitations but from biological responses (reactive gliosis, neurovascular disruption, blood-brain barrier compromise) characterized only after clinical performance decline prompted re-examination of basic neurobiology. Gene therapies encounter immune responses revealing previously uncharacterized cell biology. Regenerative medicine approaches fail when host tissue responses override engineered microenvironments. In each case, the critical scientific questions emerged from reverse translation, from clinical observation back to mechanism.

A structural threat to Goal 1 deserves explicit attention. When paylines compress, the proposals most likely to survive are those with immediate translational justification, extensive preliminary data, and low perceived risk. Basic science proposals, which by definition explore less predictable territory, are systematically disadvantaged not because reviewers score them poorly but because the funding margin is so thin that any perceived uncertainty becomes disqualifying. The result is portfolio drift toward applied, incremental work, even as NIH's mission foregrounds "fundamental knowledge about the nature and behavior of living systems." Goal 1 requires not only aspirational language but structural protections ensuring that foundational research is not crowded out by translational pressure under constrained budgets.

Recommendations:

(1) Establish funding mechanisms that explicitly support bidirectional translation, where clinical or engineering observations generate new basic science questions. Current study section structures often penalize proposals spanning this boundary, categorizing them as "too applied" for basic panels or "too basic" for clinical panels. This structural mismatch suppresses precisely the research most likely to solve translational bottlenecks.

(2) Prioritize research on biological barriers to therapeutic durability as a cross-cutting theme linking Goals 1 and 3. The host biological response to any intervention (device, molecule, cell, gene) is a fundamental determinant of long-term efficacy. This is not disease-specific or technology-specific but a shared challenge warranting coordinated investment.

(3) Support cross-species research pipelines integrating rodent, large animal, and human studies within coordinated programs. Translation fails when findings from one model system are assumed to generalize without systematic cross-species validation. Funding mechanisms spanning model systems within a single award would reduce fragmentation.

(4) Commit to protecting basic science funding proportions even during periods of payline compression. Portfolio-level metrics tracking the balance between foundational and translational awards would provide transparency and enable course correction when drift occurs. Without such safeguards, Goal 1 risks becoming aspirational rather than operational.

(5) Under Goal 2, recognize that understanding biological responses to chronic therapeutic interventions is essential to long-term safety. Proactive investment in the biology of therapeutic durability will prevent costly post-market failures and protect patients.

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Priority 2: Research Capacity 

Goal 1 (interdisciplinary workforce) addresses a genuine structural deficit, but "interdisciplinary" requires specification. True interdisciplinary research demands investigators holding deep expertise in one discipline while possessing functional literacy in adjacent fields sufficient to identify shared problems, co-design experiments, and speak across technical vocabularies. This is distinct from multidisciplinary collaboration, where specialists contribute in parallel without intellectual integration.

Training programs producing this kind of investigator are rare. Most graduate and postdoctoral training remains organized by department and discipline. Students in neuroscience rarely receive engineering training. Bioengineering students rarely engage with fundamental neurobiology at the level needed to identify which biological problems constrain device performance. The result is a workforce that reproduces disciplinary silos rather than bridging them.

Early-career investigators face compounding disadvantages when pursuing interdisciplinary or reverse-translational research. Under compressed paylines, a growing backlog of meritorious but unfunded proposals means that scientifically excellent programs can wait years for support. Each resubmission cycle costs 6-12 months. For early-career investigators, this delay is existential, as trainees graduate, preliminary data ages out, and tenure clocks run regardless. The proposals most likely to survive this bottleneck are disciplinarily legible, low-risk, and backed by established reputations. Investigators who span categories are further penalized by a boundary-maintenance dynamic in which disciplinary gatekeepers on review panels are most resistant to high-performing candidates whose profiles threaten the distinctiveness of the evaluators' own field. Early-career investigators absorb this penalty disproportionately because they lack the funding buffer and reputation to survive a single poor review cycle. The strategic plan should recognize this structural selection pressure against precisely the investigators NIH most needs.

Recommendations:

(1) Fund cross-school training structures that embed trainees in laboratories spanning different disciplines within a single research program. T32 and institutional training grant structures should support genuinely cross-disciplinary cohorts rather than department-anchored programs.

(2) Create protective mechanisms for early-career investigators pursuing interdisciplinary or reverse-translational research, analogous to the NGRI payline relaxation for early-stage investigators but specifically targeting category-spanning proposals. Without such protection, the system selects for disciplinary conformity at the career stage when intellectual risk-taking has the highest long-term return.

(3) Develop career incentives for faculty maintaining active collaborations across disciplinary boundaries. NIH can influence promotion and tenure culture through funding mechanisms that require and reward sustained cross-disciplinary integration, not merely letters of collaboration.

(4) Recognize that reverse-translational competency, the ability to trace clinical outcomes back to biological mechanism and reformulate basic science questions, is a trainable skill. Training programs should explicitly teach this framework alongside conventional translational methodology.

(5) Expand support for workshops and conferences convening investigators across the basic-to-clinical spectrum within focused problem domains. Small, problem-focused meetings generate more productive cross-disciplinary interactions than large society conferences. Dedicated funding mechanisms (R13, U13) for such meetings should be maintained and expanded, with review criteria weighting cross-disciplinary integration alongside scientific merit.

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Priority 3: Research Operations

Scientific stewardship (Goal 1) and public trust (Goal 2) are strengthened when operational structures match how productive science actually works.

First, peer review panel composition must reflect the interdisciplinary nature of proposals being reviewed. Cross-species translational proposals integrating rodent, large animal, and human studies are frequently reviewed by panels lacking expertise in one or more component disciplines. Research in organizational science has demonstrated that in evaluation settings where reviewers serve as disciplinary gatekeepers, the valuation penalty for category-spanning candidates is driven not by confusion about the candidate's abilities but by boundary maintenance, the evaluators' motivation to protect the distinctiveness of their own field. This penalty falls hardest on the highest-performing interdisciplinary candidates and is most pronounced when evaluators are highly typical members of their discipline. NIH should ensure that review panels for translational and cross-species proposals include reviewers with demonstrated expertise across the relevant model systems and clinical contexts, and should actively recruit evaluators who themselves work across disciplinary boundaries.

Second, review criteria should explicitly value bidirectional translation. Current scoring norms treat the basic-to-clinical pipeline as the default. Proposals moving in the reverse direction, from clinical observation to mechanism, score poorly when reviewers perceive them as lacking a clear clinical endpoint. Incorporating reverse-translational logic as a recognized approach within review criteria would remove this structural bias.

Third, the growing backlog of meritorious but unfunded proposals represents a stewardship failure, not merely a budget constraint. When scientifically excellent programs wait years for funding, the human capital invested in those programs (trained personnel, institutional infrastructure, preliminary data) depreciates. A system that consistently funds only the top 10-12% of applications, when a much larger fraction is judged scientifically meritorious, wastes the public investment already made in generating those programs. The strategic plan should commit to transparency about the gap between meritorious and funded applications and develop mechanisms to reduce the cost of this backlog, whether through bridge funding, streamlined resubmission, or portfolio-level rebalancing.

Fourth, NIH should invest in systematic analysis of translational failure. Many therapeutic programs fail at predictable stages for identifiable biological reasons. Cataloging and disseminating why interventions fail, not only why they succeed, would reduce redundant investment and simultaneously generate new basic science questions. The failure database is not merely an audit tool but a research-generating infrastructure that connects Priority 3 back to Priority 1.

Fifth, the strategic plan should reduce administrative burden on investigators engaged in cross-IC research. Programs spanning multiple Institutes face disproportionate overhead in application preparation, reporting, and compliance. Streamlining cross-IC coordination for genuinely interdisciplinary programs would improve both efficiency and investigators' willingness to pursue boundary-spanning work.

Good stewardship requires that funding decisions, peer review, and program management reflect how productive science actually works. When structural incentives select for disciplinary conformity, translational proximity, and investigator seniority, the system underinvests in precisely the foundational, interdisciplinary, and reverse-translational research that NIH's own mission demands.