NIH's flat budget for 2024 will force 'very difficult decisions'.

Belated Senate and House compromise eliminates policy riders restricting certain studies.

Once reluctant, new NIH chief Monica Bertagnolli embraces role.

Improving patient care is top priority for head of world's largest biomedical research funder.

Rates of National Institutes of Health Funding for Surgeon-Scientists, 1995-2020.

Importance: Surgeon-scientists are uniquely positioned to facilitate translation between the laboratory and clinical settings to drive innovation in patient care. However, surgeon-scientists face many challenges in pursuing research, such as increasing clinical demands that affect their competitiveness to apply for National Institutes of Health (NIH) funding compared with other scientists. Objective: To examine how NIH funding has been awarded to surgeon-scientists over time. Design, Setting, and Participants: This cross-sectional study used publicly available data from the NIH RePORTER (Research Portfolio Online Reporting Tools Expenditures and Results) database for research project grants awarded to departments of surgery between 1995 and 2020. Surgeon-scientists were defined as NIH-funded faculty holding an MD or MD-PhD degree with board certification in surgery; PhD scientists were NIH-funded faculty holding a PhD degree. Statistical analysis was performed from April 1 to August 31, 2022. Main Outcome: National Institutes of Health funding to surgeon-scientists compared with PhD scientists, as well as NIH funding to surgeon-scientists across surgical subspecialties. Results: Between 1995 and 2020, the number of NIH-funded investigators in surgical departments increased 1.9-fold from 968 to 1874 investigators, corresponding to a 4.0-fold increase in total funding (1995, $214 million; 2020, $861 million). Although the total amount of NIH funding to both surgeon-scientists and PhD scientists increased, the funding gap between surgeon-scientists and PhD scientists increased 2.8-fold from a $73 million difference in 1995 to a $208 million difference in 2020, favoring PhD scientists. National Institutes of Health funding to female surgeon-scientists increased significantly at a rate of 0.53% (95% CI, 0.48%-0.57%) per year from 4.8% of grants awarded to female surgeon-scientists in 1995 to 18.8% in 2020 (P < .001). However, substantial disparity remained, with female surgeon-scientists receiving less than 20% of NIH grants and funding dollars in 2020. In addition, although there was increased NIH funding to neurosurgeons and otolaryngologists, funding to urologists decreased significantly from 14.9% of all grants in 1995 to 7.5% in 2020 (annual percent change, -0.39% [95% CI, -0.47% to -0.30%]; P < .001). Despite surgical diseases making up 30% of the global disease burden, representation of surgeon-scientists among NIH investigators remains less than 2%. Conclusion and Relevance: This study suggests that research performed by surgeon-scientists continues to be underrepresented in the NIH funding portfolio, highlighting a fundamental need to support and fund more surgeon-scientists.

Dissemination of the Results of Pediatric Clinical Trials Funded by the US National Institutes of Health.

This study examines practices related to trial registration and results submission in ClinicalTrials.gov and publication of pediatric clinical trials funded by the National Institutes of Health.

Current Status of National Institutes of Health Research Funding for Women Surgeon-Scientists.

Importance: Women have made substantial advancements in academic surgery, but research funding disparities continue to hamper their progress, and current literature on the status of National Institutes of Health (NIH) funding awarded to women surgeon-scientists appears to be conflicting. Objective: To examine gender-based differences in NIH funding awarded to surgeon-scientists by comparing total grant amounts awarded and the distribution of grants by gender and research type. Design, Setting, and Participants: This cross-sectional study was performed using a previously created database of NIH-funded surgeons from 2010 to 2020. Active physician data from the Association of American Medical Colleges were used to calculate total surgeon populations. This study was performed at the NIH using the NIH internal data platform, iSearch Grants. A total of 715 men and women surgeon-scientists funded by the NIH in 2010 and 1031 funded in 2020 were included in the analysis. Main Outcomes and Measures: The main outcome was the number of women among the total number of surgeons who received NIH grants and the total grant amounts awarded to them. Bivariate χ2 analyses were performed using population totals and substantiated by z tests of population proportions. Results: This study included 715 physicians (n = 579 men [81.0%]) in 2010 and 1031 physicians (n = 769 men [74.6%]) in 2020. In 2020, women comprised 27.4% of the surgical workforce and 25.4% of surgeons with research funding in the US, but they received only 21.7% of total NIH research funding awarded to all surgeons. The number of funded women surgeon-scientists, however, significantly increased from 2010 to 2020 (262 [25.4%] in 2020 vs 136 [19.0%] in 2010; P < .001) as did their funding ($189.7 million [21.7%] in 2020 vs $75.9 million [12.3%] in 2010; P < .001). Furthermore, the proportion of US women surgeons overall with NIH funding significantly increased in 2020 vs 2010 (0.7% vs 0.5%; P < .001). Basic science, clinical outcomes, and clinical trial R01 grants also increased among women surgeon-scientists. Women and men K grant holders had a similar mean (SD) number of R01 application attempts before success (2.7 [3.01] vs 2.3 [3.15]; P = .60) and similar K-to-R award conversion rates (23.5% vs 26.7%; P = .55). Conclusions and Relevance: This cross-sectional study found an increasing number of women surgeon-scientists receiving NIH funding in 2020 vs 2010 as well as increases in the median grant amounts awarded. Although these results are promising, a discrepancy remains in the proportion of women in the surgical workforce compared with those funded by the NIH and the total grant amounts awarded to them.

Bill would bar NIH and CDC from funding lab research in China.

House of Representatives measure catalyzed in part by suspicions that Wuhan lab leak led to pandemic.

Funds dwindle for NIH program for puzzling cases.

Patient groups, hospitals urge continued support for the Undiagnosed Diseases Network.

Will ARPA-H work?

A new federal agency-approved last month by the United States Congress-is already off to a rocky start. The Advanced Research Projects Agency for Health (ARPA-H), proposed by President Biden in 2021, aims to tackle the most intractable biomedical problems by funding innovative, high-risk, high-reward research and swiftly turning discoveries into treatments and cures. But Congress gave the agency a much smaller budget than sought by the administration-$ 1 billion over 3 years, a fraction of the $6.5 billion requested. And as happens whenever there is new money and a new federal agency, a political scrum has erupted over who should control ARPA-H. It is now expected to answer to both the National Institutes of Health (NIH) and the Department of Health and Human Services (HHS). If it is to deliver on its mission, ARPA-H needs to be an autonomous entity that approaches biomedical research in a way never done before by the federal government. The stakes are high: If ARPA-H fails to produce new clinical advances relatively quickly, it will erode trust in US science. It's time for clear thinking and action about what it will take to make ARPA-H successful.

Translatability Analysis of National Institutes of Health-Funded Biomedical Research That Applies Artificial Intelligence.

Importance: Despite the rapid growth of interest and diversity in applications of artificial intelligence (AI) to biomedical research, there are limited objective ways to characterize the potential for use of AI in clinical practice. Objective: To examine what types of medical AI have the greatest estimated translational impact (ie, ability to lead to development that has measurable value for human health) potential. Design, Setting, and Participants: In this cohort study, research grants related to AI awarded between January 1, 1985, and December 31, 2020, were identified from a National Institutes of Health (NIH) award database. The text content for each award was entered into a Natural Language Processing (NLP) clustering algorithm. An NIH database was also used to extract citation data, including the number of citations and approximate potential to translate (APT) score for published articles associated with the granted awards to create proxies for translatability. Exposures: Unsupervised assignment of AI-related research awards to application topics using NLP. Main Outcomes and Measures: Annualized citations per $1 million funding (ACOF) and average APT score for award-associated articles, grouped by application topic. The APT score is a machine-learning based metric created by the NIH Office of Portfolio Analysis that quantifies the likelihood of future citation by a clinical article. Results: A total of 16 629 NIH awards related to AI were included in the analysis, and 75 applications of AI were identified. Total annual funding for AI grew from $17.4 million in 1985 to $1.43 billion in 2020. By average APT, interpersonal communication technologies (0.488; 95% CI, 0.472-0.504) and population genetics (0.463; 95% CI, 0.453-0.472) had the highest translatability; environmental health (ACOF, 1038) and applications focused on the electronic health record (ACOF, 489) also had high translatability. The category of applications related to biochemical analysis was found to have low translatability by both metrics (average APT, 0.393; 95% CI, 0.388-0.398; ACOF, 246). Conclusions and Relevance: Based on this study's findings, data on grants from the NIH can apparently be used to identify and characterize medical applications of AI to understand changes in academic productivity, funding support, and potential for translational impact. This method may be extended to characterize other research domains.