A Framework for Inclusive and Accessible Clinical Research in Rare Diseases

A Framework for Inclusive and Accessible Clinical Research in Rare Diseases | medRxiv /* */ /* */ <!-- <!-- /*! * yepnope1.5.4 * (c) WTFPL, GPLv2 */ (function(a,b,c){function d(a){return"[object Function]"==o.call(a)}function e(a){return"string"==typeof a}function f(){}function g(a){return!a||"loaded"==a||"complete"==a||"uninitialized"==a}function h(){var a=p.shift();q=1,a?a.t?m(function(){("c"==a.t?B.injectCss:B.injectJs)(a.s,0,a.a,a.x,a.e,1)},0):(a(),h()):q=0}function i(a,c,d,e,f,i,j){function k(b){if(!o&&g(l.readyState)&&(u.r=o=1,!q&&h(),l.onload=l.onreadystatechange=null,b)){"img"!=a&&m(function(){t.removeChild(l)},50);for(var d in y[c])y[c].hasOwnProperty(d)&&y[c][d].onload()}}var j=j||B.errorTimeout,l=b.createElement(a),o=0,r=0,u={t:d,s:c,e:f,a:i,x:j};1===y[c]&&(r=1,y[c]=[]),"object"==a?l.data=c:(l.src=c,l.type=a),l.width=l.height="0",l.onerror=l.onload=l.onreadystatechange=function(){k.call(this,r)},p.splice(e,0,u),"img"!=a&&(r||2===y[c]?(t.insertBefore(l,s?null:n),m(k,j)):y[c].push(l))}function j(a,b,c,d,f){return q=0,b=b||"j",e(a)?i("c"==b?v:u,a,b,this.i++,c,d,f):(p.splice(this.i++,0,a),1==p.length&&h()),this}function k(){var a=B;return a.loader={load:j,i:0},a}var l=b.documentElement,m=a.setTimeout,n=b.getElementsByTagName("script")[0],o={}.toString,p=[],q=0,r="MozAppearance"in l.style,s=r&&!!b.createRange().compareNode,t=s?l:n.parentNode,l=a.opera&&"[object Opera]"==o.call(a.opera),l=!!b.attachEvent&&!l,u=r?"object":l?"script":"img",v=l?"script":u,w=Array.isArray||function(a){return"[object Array]"==o.call(a)},x=[],y={},z={timeout:function(a,b){return b.length&&(a.timeout=b[0]),a}},A,B;B=function(a){function b(a){var a=a.split("!"),b=x.length,c=a.pop(),d=a.length,c={url:c,origUrl:c,prefixes:a},e,f,g;for(f=0;f<d;f++)g=a[f].split("="),(e=z[g.shift()])&&(c=e(c,g));for(f=0;f<b;f++)c=x[f](c);return c}function g(a,e,f,g,h){var i=b(a),j=i.autoCallback;i.url.split(".").pop().split("?").shift(),i.bypass||(e&&(e=d(e)?e:e[a]||e[g]||e[a.split("/").pop().split("?")[0]]),i.instead?i.instead(a,e,f,g,h):(y[i.url]?i.noexec=!0:y[i.url]=1,f.load(i.url,i.forceCSS||!i.forceJS&&"css"==i.url.split(".").pop().split("?").shift()?"c":c,i.noexec,i.attrs,i.timeout),(d(e)||d(j))&&f.load(function(){k(),e&&e(i.origUrl,h,g),j&&j(i.origUrl,h,g),y[i.url]=2})))}function h(a,b){function c(a,c){if(a){if(e(a))c||(j=function(){var a=[].slice.call(arguments);k.apply(this,a),l()}),g(a,j,b,0,h);else if(Object(a)===a)for(n in m=function(){var b=0,c;for(c in a)a.hasOwnProperty(c)&&b++;return b}(),a)a.hasOwnProperty(n)&&(!c&&!--m&&(d(j)?j=function(){var a=[].slice.call(arguments);k.apply(this,a),l()}:j[n]=function(a){return function(){var b=[].slice.call(arguments);a&&a.apply(this,b),l()}}(k[n])),g(a[n],j,b,n,h))}else!c&&l()}var h=!!a.test,i=a.load||a.both,j=a.callback||f,k=j,l=a.complete||f,m,n;c(h?a.yep:a.nope,!!i),i&&c(i)}var i,j,l=this.yepnope.loader;if(e(a))g(a,0,l,0);else if(w(a))for(i=0;i (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0];var j=d.createElement(s);var dl=l!='dataLayer'?'&l='+l:'';j.src='//www.googletagmanager.com/gtm.js?id='+i+dl;j.type='text/javascript';j.async=true;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-P4HH5NV'); Skip to main content Home About Submit ALERTS / RSS Search for this keyword Advanced Search A Framework for Inclusive and Accessible Clinical Research in Rare Diseases View ORCID Profile Lavanyaa Manjunatha , View ORCID Profile MS Saundarya , View ORCID Profile Nisha Venugopal , View ORCID Profile Jenifer Ngo Waldrop , View ORCID Profile Linda Goler Blount , View ORCID Profile Reena V Kartha , View ORCID Profile Harsha K Rajasimha doi: https://doi.org/10.1101/2025.05.07.25326565 Lavanyaa Manjunatha 1 Indo US Organization for Rare Diseases (IndoUSrare) , Herndon, VA, USA PhD Find this author on Google Scholar Find this author on PubMed Search for this author on this site ORCID record for Lavanyaa Manjunatha MS Saundarya 1 Indo US Organization for Rare Diseases (IndoUSrare) , Herndon, VA, USA MSc Find this author on Google Scholar Find this author on PubMed Search for this author on this site ORCID record for MS Saundarya Nisha Venugopal 1 Indo US Organization for Rare Diseases (IndoUSrare) , Herndon, VA, USA PhD Find this author on Google Scholar Find this author on PubMed Search for this author on this site ORCID record for Nisha Venugopal Jenifer Ngo Waldrop 5 Rare Disease Diversity Coalition, Black Women’s Health Imperative , Atlanta, GA, USA MS Find this author on Google Scholar Find this author on PubMed Search for this author on this site ORCID record for Jenifer Ngo Waldrop Linda Goler Blount 5 Rare Disease Diversity Coalition, Black Women’s Health Imperative , Atlanta, GA, USA MPH Find this author on Google Scholar Find this author on PubMed Search for this author on this site ORCID record for Linda Goler Blount Reena V Kartha 1 Indo US Organization for Rare Diseases (IndoUSrare) , Herndon, VA, USA 4 Center for Orphan Drug Research, Department of Experimental and Clinical Pharmacology, University of Minnesota Twin Cities , Minneapolis, MN, USA PhD Find this author on Google Scholar Find this author on PubMed Search for this author on this site ORCID record for Reena V Kartha Harsha K Rajasimha 1 Indo US Organization for Rare Diseases (IndoUSrare) , Herndon, VA, USA 2 Jeeva Clinical Trials, Inc. , Manassas, VA, USA 3 School of Systems Biology, George Mason University , Fairfax, VA, USA MS, PhD Find this author on Google Scholar Find this author on PubMed Search for this author on this site ORCID record for Harsha K Rajasimha For correspondence: harshakarur{at}gmail.com Abstract Full Text Info/History Metrics Supplementary material Data/Code Preview PDF Abstract Background Equitable representation of all populations is crucial for generalizing rare disease (RD) clinical research outcomes, especially given the low prevalence and geographically sparse distribution of patients with RDs. In our companion manuscript ( Current State and Demographic Trends of Medically Underserved Populations in Rare Disease Research , Manjunatha et al. ) we quantified reporting of demographics, socioeconomic factors (SF), and participation trends of medically underserved populations (MUPs) in RD research and clinical trials. Methods The study builds on the findings of Manjunatha et al ., where we analyzed the reporting of demographics and SF in RD clinical research, here we perform a representation and policy gap analysis of this extracted data. The representation analysis evaluated 13 variables, including age, sex or gender, race, ethnicity, and SF, using four key analyses: reporting statistics, representation, participant distribution, and benchmarking against the US census data. The qualitative policy analysis included existing national and international policies and guidelines. Results Only age, sex or gender, race, and ethnicity had sufficient data for the representation analysis. While diversity was moderate for these variables, equity, inclusion, and accessibility were low, particularly for racial and ethnic minorities, nonbinary genders, and older adults. Data were insufficient for MUPs such as lesbian, gay, bisexual, transgender, queer or questioning individuals, rural residents, veterans, military spouses, people affected by poverty, and religious minorities. Based on the representation analysis and building upon existing foundational policies and guidelines, we propose three recommendations and a six-pillar framework to mandate and standardize data reporting practices and improve the representation of MUPs in RD clinical research with broader relevance to all clinical research in general. The six pillars are patient advocacy, policy legislation, governmental oversight, standardized data collection and reporting, technological enablement, and global epidemiological research. Conclusions Addressing the historical underrepresentation of MUPs requires upgrading the foundation of clinical research instead of a piecemeal, siloed approach. This study underscores the systemic gaps in the representation of MUPs in RD research and proposes a six-pillar actionable framework to address these disparities. The systematic implementation of these six pillars can enhance the integrity and outcomes of future RD clinical research. Introduction Equitable representation of all populations, including medically underserved populations (MUPs) in clinical research is crucial to ensure the generalizability of the evidence, maintain public trust in the healthcare industry, and unlock medical innovation and the full potential of precision medicine to improve health outcomes for all ( 1 ). Diversity, equity, inclusion, and accessibility (DEIA) is critical in rare diseases (RDs), given their low prevalence and sparse geographical distribution of affected individuals. Except for a few studies, little is known about the comprehensive MUPs in RD clinical trials ( 2 – 5 ). Our companion manuscript ( 6 ) addressed this issue by analyzing the reporting of and participant distribution in 13 demographic and socioeconomic factors (SFs) in RD clinical research in the United States (US) over 40 years. Manjunatha et al. assessed MUPs, including children, older adults, women, lesbian, gay, bisexual, transgender, queer or questioning (LGBTQ+) individuals, historically underserved racial and ethnic groups, multiracial groups, rural residents, veterans, religious minorities, immigrants, people living with disabilities, and those disadvantaged by poverty. The key findings were the underreporting of race, ethnicity, and SF; the lack of standardized reporting in publications; and the underrepresentation of MUPs. Historically underserved racial and ethnic groups were underrepresented in RD trials compared with the US census. There was little or no data on LGBTQ+ individuals, members of religious groups, rural residents, veterans, people living with disabilities, and those disadvantaged by poverty. Recent recommendations or frameworks to improve clinical trial diversity include the American Society of Hematology (ASH) DEI toolkit, Diversity Convergence Project (DCP), the Multi-Regional Clinical Trials (MRCT) Center’s Achieving Diversity, Inclusion, and Equity in Clinical Research guidance and toolkit, and recommendations from the National Academy of Science, Engineering, and Medicine (NASEM) ( 7 – 10 ). RD patient advocacy groups and researchers have underscored the need to enhance DEIA to achieve health equity ( 11 , 12 ). The proposed solutions range from innovative trial designs, increasing patient participation in guiding trial design, including logistical considerations, standardized reporting of population data in electronic health records (EHRs), enhancing cultural competency, engaging with diverse communities, and routine monitoring and evaluation of DEIA initiatives ( 11 – 13 ). These frameworks and solutions provide recommendations in a silo without duly considering how they may overlap with existing foundational national and international policies and guidelines for clinical research, particularly for RDs. Our study aimed to develop an actionable framework to improve the representation of MUPs in RD research. Specifically, we 1) evaluated the gaps in MUP representation and 2) analyzed relevant national and international policies or legislative documents governing clinical research. Accordingly, we developed three recommendations and a six-pillar framework. Methods Representation analysis We performed a representation analysis of the results reported in our companion manuscript ( 6 ). Data for 13 demographics and SF variables and their subcategories were extracted and evaluated based on 1) reporting statistics, 2) representation, 3) participant distribution statistics, and 4) comparing participant distribution with US census data as a benchmark (Additional File 1: Table S1). See Additional File 2: Supplementary methods for details. Diversity was evaluated based on the reporting statistics and representation. Equity and inclusion were evaluated based on distribution statistics and comparisons with the US census as an external benchmark. Accessibility was inferred from assessments of diversity, equity, and inclusion, as reporting and distribution statistics cannot serve as direct markers for how trials were made accessible. Policy analysis The Food and Drug Administration (FDA), National Institutes of Health (NIH), ClinicalTrials.gov, Congress.gov, and the US Department of Health and Human Services websites were searched for policies, guidance documents, laws, bills, and guidelines related to clinical research published up to 2024. Google searches were performed using specific keywords (Additional File 2: Supplementary methods). The documents (hereafter referred to as policy) were evaluated to identify if they reported 1) measures of diversity, 2) provisions for increasing diversity, and 3) recommendations or frameworks for improving inclusion and accessibility in clinical trials. Results Representation and policy gaps analysis The representation analysis ( Table 1 ) revealed several gaps in RD clinical research, which we illustrate using age as an example. The age variable was scored “high” along the diversity axis as it was reported in >75% of publications and clinical trials and had data for subcategories (child; adult; older adult; child and adult; child, adult, and older adult; adult and older adult). However, diversity for age subcategories “child” and “older adults” was scored “low” because of the lower reporting levels. Children and older adults were scored “low” for inclusion based on the low participant proportions in trials. Similarly, equity was scored “low” based on participant distribution alone rather than a direct comparison with the US census, as three of the six age subcategories included mixed age groups, making it difficult to make meaningful comparisons. Accessibility was also inferred to be “low” for older adults and children based on diversity, equity, and inclusion assessments. The overall assessments of the 13 variables are detailed in Additional File 1: Table 1 . View this table: View inline View popup Download powerpoint Table 1: Evidence-based categorical assessment of Diversity, Equity, Inclusion, and Accessibility in US-based RD clinical research Of the different variables, only age, sex or gender, race, and ethnicity could be evaluated for DEIA due to reporting levels and the availability of granular data ( Table 1 , eTable1). Diversity was assessed as “high” for age and moderate for sex or gender, race, and ethnicity based on the reporting statistics and categorical diversity or representation. However, equity, inclusion, and accessibility were assessed as “low” for these characteristics. For male, female, and White participants, equity, inclusion, and accessibility were assessed to be “high.” In contrast, they were “low” for older adults, nonbinary gender, American Indian or Alaska Native, Asian, Black or African American, and Native Hawaiian or Other Pacific Islander participants. Representation analysis was possible for only 4 of the 13 variables because of the significant lack of information reporting on several variables, including SF. Table 2 provides an overview of the national and international policies, laws, and guidelines included in the policy analysis and their current scope. Age, sex, race, and ethnicity were the most common measures of diversity mentioned in most of these documents, which aligned with our analysis ( Table 1 ). Only the 21 st Century Cures Act focuses on improving the inclusion of sexual minorities. The Food and Drug Omnibus Reform Act of 2022 (FDORA) and the resulting FDA draft guidance (2024) acknowledged SF as variables affecting trial diversity ( 14 – 16 ). Table 2 also presents the proposed potential policy enhancements to improve the scope of the existing provisions to improve MUP participation. View this table: View inline View popup Table 2: Foundational and recent policies a governing clinical research b Recommendations and Framework for improving MUP representation in RD clinical research Our companion manuscript ( 6 ) and analysis revealed a lack of standardized data reporting, inclusion, and accessibility of MUPs in RD research. To address these gaps, we recommend the following: 1) complete, clear, accurate, and standardized collection and reporting of demographics, including sexual orientation, gender identity (SOGI), SF, and special status, such as veteran, caregiver, disability, immigrant, and religion in publications and clinical trials; 2) remove barriers to including MUPs in clinical trials; and 3) enhance the accessibility of trials for increased MUP participation. Table 3 elaborates on these recommendations and provides a rationale. We propose an actionable six-pillar framework ( Figure 1 ) to apply these three recommendations for enhancing DEIA in RD clinical research by drawing on our evidence-based assessment ( Table 1 , Additional File 1: Table S1) and analyzing gaps in existing policies, laws, and guidelines ( Table 2 ). Download figure Open in new tab Figure 1: Framework for improving the representation of medically underserved populations in US-based RD clinical research View this table: View inline View popup Table 3: Recommendations a for improving DEIA in publications and clinical trials Pillar 1: Patient advocacy Patient advocacy is the hallmark of progress in RD clinical research. Patient advocacy groups (PAGs) support research, create patient registries, conduct natural history studies, contribute to clinical trials, and educate healthcare providers and patients. PAGs can play a crucial role in enhancing MUP participation in RD clinical research by 1) understanding and advocating the needs of the affected populations; 2) incorporating patient feedback to remove barriers to inclusivity, such as native languages; 3) facilitating trust and engagement by providing culturally competent educational materials to stakeholders; 4) advocating for comprehensive DEIA reporting and moral policing in RD research; and 5) forming PAG coalitions to advocate for policy amendments to the bilateral and bicameral RD caucus. Pillar 2: Policy legislation Legislative advocacy is required to adopt and mandate the implementation of new guidelines for improving MUPs’ representation in RD clinical research. We recommend1) revising existing bills or laws such as the Orphan Drug Act of 1983, 21 st Century Cures Act, DEPICT Act of 2002, and NIH Clinical Trial Diversity Act of 2023, to include SOGI and SF data as measures of diversity; 2) adapting the social determinants of health-related International Classification of Diseases (ICD)-10 Z codes from Centres for Medicare & Medicaid Services ( 17 ) data to enhance collection and reporting SF data in clinical research; 3) mandating expedited implementation of ICD-11 ( 18 , 19 ) to better track RDs; 4) modernizing newborn screening (NBS) to incorporate new methods for aggregating clinical and genomic data so that newer disease conditions can be added to the Recommended Uniform Screening Panel (RUSP) ( 20 ); 5) incentivizing compliance through financial and regulatory benefits that allow using real-world evidence (RWE) or pragmatic studies for RD clinical research; and 6) incentivizing research that includes MUPs by offering tax incentives to institutions that focus on recruiting these participants. Pillar 3: Enforcement and governmental oversight The US federal, state, and local government executive branches play a key role in enforcing and implementing DEIA mandates defined in relevant legislation, irrespective of the funding sources of RD research. We recommend that these governmental agencies 1) implement the mandated SOGI and SF data elements across clinical trial registries, patient registries, and any research programs managed by those agencies; 2) require demographics, including SOGI and SF results in research reporting stages; 3) establish a task force to oversee the implementation of complete, clear, accurate, and standardized collection and reporting of demographics and SF data to enhance interoperability, efficient decision-making, and to improve health equity for all; 4) support workforce development by encouraging existing federally funded programs to prioritize training and development opportunities in healthcare for those from MUPs backgrounds; 5) such as the FDA can consider updating the DAP 2024 guidance to include SOGI and SF as measures of diversity; and 6) such as the NIH and FDA could create guidelines for reporting demographics and SF data in publications. Pillar 4: Implementation of standardized data collection, reporting, and publication We recommend that stakeholders involved in conducting or reporting clinical trials 1) update or develop standard operating procedures for the complete, clear, accurate, and standardized collecting and reporting of demographics, including SOGI and SF by collaborating with international consortia such as the Clinical Data Interchange Standards Consortium (CDISC) and the International Council for Harmonisation (ICH) of Technical Requirements for Pharmaceuticals for Human Use; 2) such as publishers, journals, and editors should require authors to report demographics, including SOGI and SF data in published works or provide justifications if specific data were not reported; and 3) provide training, resources, and support for researchers to implement these reporting practices. Pillar 5: Technological enablement Inclusion and accessibility remain key challenges for RD patients. Technological advances in digital health, remote patient monitoring, virtual trials, and decentralized trials are transforming RD research and trials. We recommend 1) implementing decentralized and hybrid trial designs that leverage both randomized controlled trials and pragmatic, real-world data (RWD) that integrate remote monitoring and tele-visits where in-person visits are not justifiable; 2) using wearable technology to facilitate automated and continuous data collection from participants to minimize burden, especially for women, children, and older adults; 3) using artificial intelligence/ machine learning and natural language processing approaches to identify potential trial participants by mining RWD, such as EHRs, insurance claims, prescription drugs data, and registries, thereby minimizing bias in participant selection; 4) providing access to stable internet or digital devices for participants lacking these resources; and 5) implementing multichannel communication (audio, video, text, and multimedia) to accommodate those with special needs. Pillar 6: Global epidemiology-based research Historically, 90% of the clinical trials are conducted in 5% of the countries (Global North), excluding most low-and-middle-income countries. Each RD is a global public health issue with varying prevalence in different geographies, races, genetic haplogroups, and ethnicities. We recommend 1) supporting the understanding of epidemiological data such as prevalence and incidence of RDs in different geographic locations; 2) requiring trial designs that reflect the diversity of the populations affected by RDs globally; 3) expanding FDA’s involvement in global clinical trial networks to enable US sponsors access to the relevant global, diverse populations; and 4) agencies such as the NIH and FDA should require sponsors and clinical researchers to include epidemiological data as part of patient recruitment plans. Discussion The findings of our study underscore the urgent need to improve MUP representation in RD clinical research. Therefore, we have proposed three specific recommendations and a six-pillar actionable framework ( Tables 2 and 3 , Figure 1 ). They broadly align with those of NASEM, the MRCT Center’s Diversity Guidance, the DCP, and the ASH DEI Toolkit ( 7 – 10 ). The key areas of overlap are standardized data collection and reporting, patient advocacy and engagement, improving access through technology, and governmental oversight. Our recommendation of including SOGI and SF as measures of diversity is aligned with the 21 st Century Cures Act, and FDORA ( 14 , 16 ). Building on these, we also recommend collecting and reporting special status, such as veteran, migrant, caregiver, and disability status, as these can influence individuals’ socioeconomic status and ability to access clinical trials. Our framework proposes policy legislation as an essential pillar to achieving equitable representation of MUPs in RD clinical research. Our analysis demonstrated a clear association between the demographic variables reported in RD clinical research and the existing policy requirements ( Table 2 ). While both the DCP and MRCT’s guidance acknowledge existing regulatory guidelines concerning clinical trial diversity, our framework considers legislative changes crucial for standardized data collection and reporting changes and improving inclusion and access to clinical trials. The Orphan Drug Act of 1983, a patient-led legislative initiative that spurred a revolution in developing treatments for RDs, exemplifies the impact of policy legislation ( 21 ). Modernizing NBS and expediting the implementation of the ICD-11 are crucial to enable patient participation in RD clinical research. Currently, the RUSP covers 35 core and 26 secondary conditions, most of which are RDs ( 20 ). Modernizing NBS can help reduce the time needed to diagnose RDs. The US healthcare system is yet to implement the ICD-11 codes, which covers about 5,500 unique RDs and synonyms ( 19 ). The ICD-10 system has specific codes for only 500 RDs. Adopting the ICD-11 can aid in data-driven monitoring of prevalence and incidences in MUP for at least half the known RDs. The global epidemiology pillar recognizes that each RD is a global public health challenge and acknowledges the geographic dispersion of affected individuals. US legislators have already recognized the need to modernize clinical trials through decentralized trials and are augmenting clinical trials with RWE ( 22 , 23 ). Given the challenges of RDs, our framework acknowledges the need to balance the urgency of making RD treatments available with the imperative of ensuring that research is diverse and inclusive. Hybrid trials and RWE can alleviate these difficulties. Therefore, we propose advocating for regulatory relaxation to allow the use of real-world evidence in regulatory decision-making. Additionally, we want to note that a strong synergy between PAGs and legislators is required to bring sustainable changes to clinical research legislation. About 30% of the RD patient advocacy groups advocate for research funding, resources, and policies ( 24 ). PAGs and multi-stakeholder clinical research communities should educate lawmakers about the need for representative clinical research, including its economic benefits. Several existing RD research, advocacy, and data-sharing initiatives ( 25 – 30 ) overlap with key components of our framework (Additional File 2: Table S1), highlighting its practical application. CDISC data standards for clinical trials have been successfully applied or recommended across regulatory agencies worldwide. Although the framework is aimed at RD clinical research, most of the recommendations can also be applied to other areas of clinical research where the underrepresentation of MUPs is prevalent ( 31 – 34 ). While our framework and recommendations broadly align with existing frameworks and initiatives, there could be potential implementation barriers. Participants may have privacy and confidentiality concerns about collecting and reporting SOGI and intersectional identity data. Data security and confidentiality were reported as the main concerns about sharing health information in the database in the Rare-X DEI scoping review ( 35 ). These concerns should be addressed at the outset of participant engagement through linguistically diverse and culturally sensitive informed consent forms and materials that provide adequate information about the importance of these data and measures taken to safeguard them. Although DEIA metrics can be standardized for the US, harmonized global minimum metrics are essential given the dispersed nature of people affected by RDs. For instance, while race and ethnicity are standard variables in clinical research in the US, countries like France and Germany do not collect ethnicity data ( 36 ). Therefore, these metrics must be adaptable to regional and sociocultural differences. Greater collaboration is required between international organizations like the CDISC, ICH, and regional regulatory bodies to align core DEIA metrics with add-on adaptable metrics for flexibility. Technological advancements in streamlining clinical research with AI agents such as Jeeva Clinical Trials, to simplify, standardize, and automate the human workflows ( 37 ), can help reduce trial accessibility barriers for all stakeholders. This is especially true given the cost and time required to find patients meeting inclusion/exclusion criteria, especially for ultra-rare conditions. However, sponsors and trial sites should address the varying levels of comfort with technology among participants, the issue of 21% of the US population lacking home broadband connections ( 38 ), and issues of data and algorithmic biases in AI/ML ( 39 , 40 ) to further minimize the digital divide in clinical research participation. Representative RD research is critical for scientific validity, especially given its low prevalence. Beyond the ethical and moral responsibility of making clinical research representative, stakeholders have a substantial economic incentive to embrace DEIA initiatives. The economic burden of RDs in the US alone is $997 billion ( 41 ). A recent NASEM report using the Future Elderly Model simulation projected potential gains of $33 trillion when racial and ethnic disparities were eliminated in chronic diseases through increased life-expectancy, disability-free years, and workforce participation ( 42 ). The study highlights the consequences of removing disparities for MUPs, suggesting that similar economic and public health benefits can be achieved if RD trials are made equitable and inclusive. Our evaluation of policies, laws, and guidelines governing clinical research and suggested enhancements aim for holistic changes to the clinical research landscape. To illustrate, revising the Declaration of Helsinki ( 43 ) to ensure that informed consent forms are accessible to people from diverse backgrounds and needs, including various linguistic backgrounds and individuals with disabilities, will significantly advance clinical research to be truly inclusive and diverse. Embedding DEIA principles in all documents governing clinical research can change the fabric of clinical research, bringing about a paradigm shift in clinical trial conduct and leading to equitable health outcomes for all. Limitations Although our study could draw key inferences, it has certain limitations. First, the use of arbitrary cut-offs (low, moderate, high) for evaluating reporting statistics may limit the representation analysis. These cut-offs were based on the ideal of 100% reporting of variables to reveal broad trends in MUP representation. Second, considering participant distribution alone can limit our understanding of inclusion. Other factors such as eligibility criteria, accessibility barriers, and disease prevalence should also be considered for the complete picture. Third, since all RD trials were analyzed, comparing participant distribution with the US census was a practical choice to assess equity. Because RDs may disproportionately affect different populations, prevalence should be used as a benchmark for each RD. Fourth, our analysis was not stratified by the age-based prevalence of RDs, therefore insights regarding equity and inclusion can be distorted. Fifth, accessibility was inferred and could not be measured based on the reporting or distribution statistics, thus limiting the ability to quantify access challenges for MUPs with RD. Lastly, evaluating genetic ancestry as a diversity variable fell outside the scope of this work; however, it is worth noting that 80% of RDs are genetic in origin. Conclusions This study is the first to evaluate the DEIA landscape in RD clinical research and policy and propose a framework to improve the participation of MUPs. Each pillar of our framework strengthens the foundation of RD clinical research through patient advocacy, policies, guidelines, implementation, enablement, and global impact, improving the representation of MUPs. We call upon patient advocacy groups, lawmakers, federal agencies, regulatory agencies, trial sites, trial coordinators, sponsors, industry, and researchers to adopt this framework for enhancing MUP participation in RD clinical research. Now is the time to take action for diverse, inclusive, equitable, accessible, and globally impactful RD research. Data Availability The data used in this manuscript are derived from our companion manuscript, Manjunatha et al., Current State and Demographic Trends of Medically Underserved Populations in Rare Disease Research in the United States. Additional data may be available upon reasonable request. Declarations Ethics approval and consent to participate Not applicable Consent for publication Not applicable Availability of data and material The data used in this manuscript are derived from our companion manuscript, Manjunatha et al., Current State and Demographic Trends of Medically Underserved Populations in Rare Disease Research in the United States, submitted to BMC Health Services Research (Submission ID 86faf02b-24c8-40c7-bdb4-1d1e06ba2e58). Additional data may be available upon reasonable request. Competing interests The Rare Disease Diversity Coalition (RDDC) funded the study. RDDC facilitated access to members of the Diversity in Clinical Trials Working Group, some of whom participated as non-author collaborators in this study. Additionally, RDDC contributed to and supported data analysis, interpretation, journal selection, and manuscript review and approval. IndoUSrare independently designed, executed, and reported the study, retaining full autonomy over all aspects of the research process. The authors declare that they have no other competing interests to declare. Funding Indo US Organization for Rare Diseases (IndoUSrare) received funding from the RDDC for this work. Author contributions HKR, LM, and SMS contributed to the conceptualization of the study. LM and SMS acquired data, developed methods, conducted investigation, validated the data, drafted the manuscript, and prepared figures; LM and SMS analyzed the data. LM, SMS, NV, RVK, HKR, JNW, and LGB interpreted the data, reviewed it for important intellectual content, and revised and edited the manuscript. HKR, NV, and RVK obtained funding for the study. LM managed the project administration with JNW and LGB, providing administrative, technical, or material support. HKR supervised the study. All authors read and approved the manuscript. Authors’ information Indo US Organization for Rare Diseases, Herndon, VA 20171, USA Lavanyaa Manjunatha, PhD; Saundarya MS, MSc; Deepika Dokuru, PhD; Nisha Venugopal, PhD; Reena V Kartha, PhD; Harsha K Rajasimha MS, PhD Center for Orphan Drug Research, Department of Experimental and Clinical Pharmacology, University of Minnesota Twin Cities, Minneapolis, MN, USA Reena V Kartha, PhD Jeeva Clinical Trials Inc., Manassas, VA 20109, USA; School of Systems Biology, George Mason University, Fairfax, VA 22030, USA Harsha K Rajasimha MS, PhD Rare Disease Diversity Coalition, Black Women’s Health Imperative, Atlanta, GA 3013, USA Jenifer Ngo Waldrop, MS; Linda Goler Blount, MPH Additional information Additional File 1_Manjunatha et al_Framework Inclusive and Accessible_RD Clinical Research_20032025.xlsx Additional File 1: Table S1. Additional File 2_Manjunatha et al_Framework Inclusive and Accessible_RD Clinical Research_06052025.docx Additional File 2: Supplementary methods, Table S1: Existing programs or initiatives that overlap with our framework Acknowledgments IndoUSrare acknowledges the RDDC for providing funding. The authors thank the RDDC Clinical Trials Working Group members for their invaluable contributions during manuscript development. We acknowledge Dr Dora Akinyi Mugambi, Ms Leanne Marie Woehlke, Ms Kathleen Machuzak, Ms Veronica Mullins, and Dr Paul I Howard for analysis, interpretation, and content review and Ms Jocelyn Cooper and Ms Lolita Smith-Moore for administrative support. We also acknowledge support from the Children’s National Hospital. Abbreviations MUPs Medically underserved populations DEIA Diversity, Equity, Inclusion, Accessibility RD Rare disease SF Socioeconomic factors US United States LGBTQ+ lesbian, gay, bisexual, transgender, queer or questioning ASH American Society of Hematology DCP Diversity Convergence Project MRCT Multi-Regional Clinical Trials NASEM National Academy of Science, Engineering, and Medicine EHR electronic health records DAP Diversity Action Plan RD Rare Disease FDA Food and Drug Administration NIH National Institute of Health FDORA Food and Drug Omnibus Reform Act SOGI Sexual Orientation and Gender Identity PAG Patient advocacy group ICD International Classification of Diseases NBS Newborn Screening RUSP Recommended Uniform Screening RWE Real-world evidence CDISC Clinical Data Interchange Standards Consortium ICH International Council for Harmonisation RWD Real-world data ML Machine learning DEI Diversity, Equity, Inclusion References 1. ↵ Carter-Edwards L , Hidalgo B , Lewis-Hall F , Nguyen T , Rutter J . Diversity, equity, inclusion, and access are necessary for clinical trial site readiness . J Clin Transl Sci . 2023 Nov 30; 7 ( 1 ): 268 – 9 . doi: 10.1017/cts.2023.660 OpenUrl CrossRef 2. ↵ U.S. Food and Drug Administration . Drug Trials Snapshots Summary Report: Five-Year Summary and Analysis of Clinical Trial Participation and Demographics Contents . 2015 [cited 2024 Apr 27]; Available from: https://www.fda.gov/media/143592/download?attachment 3. Roberts AL , Johnson NJ , Chen JT , Cudkowicz ME , Weisskopf MG. Race/ethnicity, socioeconomic status, and ALS mortality in the United States . Neurology [Internet] . 2016 Nov 11; 87 ( 22 ): 2300 – 2308 . doi: 10.1212/WNL.0000000000003298 OpenUrl Abstract / FREE Full Text 4. McGarry ME , McColley SA . Minorities are underrepresented in clinical trials of pharmaceutical agents for cystic fibrosis . Ann Am Thorac Soc . 2016 Oct 1; 13 ( 10 ): 1721 – 1725 . doi: 10.1513/AnnalsATS.201603-192BC OpenUrl CrossRef PubMed 5. ↵ Hantel A , Luskin MR , Garcia JS , Stock W , DeAngelo DJ , Abel GA . Racial and ethnic enrollment disparities and demographic reporting requirements in acute leukemia clinical trials . Blood Adv . 2021 Nov 11; 5 ( 21 ): 4352 – 4360 . doi: 10.1182/bloodadvances.2021005148 OpenUrl CrossRef PubMed 6. ↵ Current state and demographic trends of medically underserved populations in rare disease research in the United States . medRxiv . 2025 Apr 30. doi: 10.1101/2025.04.30.25326209 . OpenUrl Abstract / FREE Full Text 7. ↵ American Society of Hematology . ASH DEI Toolkit for Clinical Trial Sponsors Incorporating DEI Principles Throughout the Clinical Trial Life Cycle [Internet] . [cited 2025 Feb 8]. Available from: https://www.hematology.org/diversity-equity-and-inclusion/toolkits 8. Bierer BE , DeCormier Plosky W , Hanger M , Krofah E , Long Y , Mervin-Blake S , Okun S. Toward a national action plan for achieving diversity in clinical trials [Internet] . 2023 May [cited 2025 Feb 7]. Available from https://ctti-clinicaltrials.org/wp-content/uploads/2024/05/Toward-a-National-Action-Plan-for-Achieving-Diversity-Clinical-Trials-240502_FINAL.pdf 9. Bierer BE , White SA , Meloney LG , Ahmed HR , Strauss DH , Clark LT. . Achieving diversity, inclusion, and equity in clinical research: Guidance Document [Internet] . Vol. 1.2 . Multi-Regional Clinical Trials Center of Brigham and Women’s Hospital and Harvard (MRCT Center) ; 2021 [cited 2025 Feb 8]. 143 p. Available from: https://mrctcenter.org/diversity-in-clinical-research/guidance/guidance-document/ OpenUrl 10. ↵ National Academies of Sciences, Engineering, and Medicine. Recommendations for improving representation in clinical trials and clinical research . Improving representation in clinical trials and research: Building research equity for women and underrepresented groups [Internet] . Washington (DC) : National Academies Press ; 2022 May 17 [cited 2023 Dec 13]. p. 1 – 260 . Available from: https://www.ncbi.nlm.nih.gov/books/NBK584405/ 11. ↵ Frazier ZJ , Brown E , Rockowitz S , Lee T , Zhang B , Sveden A , et al. Toward representative genomic research: the children’s rare disease cohorts experience . Therapeutic Advances in Rare Disease [Internet] . 2023 Jan 1 [cited 2024 Aug 18]; 4 . Available from: https://pmc/articles/PMC10445838/ 12. ↵ Baynam G , Baker S , Steward C , Summar M , Halley M , Pariser A. Increasing Diversity, Equity, Inclusion, and Accessibility in Rare Disease Clinical Trials . Pharmaceut Med . 2024 Jul; 38 ( 4 ): 261 – 276 . doi: 10.1007/s40290-024-00529-8 . Epub 2024 Jul 9 OpenUrl CrossRef 13. ↵ Adachi T , El-Hattab AW , Jain R , Nogales Crespo KA , Quirland Lazo CI , Scarpa M , et al. Enhancing Equitable Access to Rare Disease Diagnosis and Treatment around the World: A Review of Evidence, Policies, and Challenges . Int J Environ Res Public Health [Internet] . 2023 Mar 1 [cited 2024 Aug 26]; 20 ( 6 ): 4732 . Available from: https://pmc.ncbi.nlm.nih.gov/articles/PMC10049067/ OpenUrl 14. ↵ Public Law 114-255, 21st Century Cures Act [Internet] . Washington (DC) : U.S. Congress ; 2016 [cited 2025 Feb 7]. Available from: https://www.congress.gov/114/plaws/publ255/PLAW-114publ255.pdf 15. U. S Food and Drug Administration . Diversity Action Plans to Improve Enrollment of Participants from Underrepresented Populations in Clinical Studies Guidance for Industry . [cited 2024 Aug 19]; Available from: https://www.fda.gov/media/179593/download 16. ↵ U.S. Congress . H.R.7667 - Food and Drug Amendments of 2022 [Internet]. 117th Congress (2021-2022) . 2022 [cited 2024 Dec 18]; Available from: https://www.congress.gov/bill/117th-congress/house-bill/7667 17. ↵ Centers for Medicare & Medicaid Services (CMS) . Using Z codes: The social determinants of health (SDOH) data journey to better outcomes: Step 5 report: SDOH Z code data findings [Internet] . [cited 2024 Dec 24]. Available from: https://www.cms.gov/files/document/zcodes-infographic.pdf 18. ↵ World Health Organization . International Classification of Diseases (ICD) [Internet] . [cited 2025 Jan 20]. Available from: https://www.who.int/standards/classifications/classification-of-diseases 19. ↵ World Health Organization . Rare diseases [Internet] . [cited 2025 Jan 20]. Available from: https://www.who.int/standards/classifications/frequently-asked-questions/rare-diseases 20. ↵ Health Resources and Services Administration . Recommended Uniform Screening Panel [Internet] . [cited 2025 Jan 20]. Available from: https://www.hrsa.gov/advisory-committees/heritable-disorders/rusp 21. ↵ Orphan Drug Act, Public Law 97-414, 96 Stat 2049. [Internet] . 1983 [cited 2025 Jan 7]; Available from: https://www.congress.gov/bill/97th-congress/house-bill/5238/text 22. ↵ U.S. Congress . H.R.6584 - DEPICT Act [Internet]. 117th Congress (2021-2022) . 2022 [cited 2024 Dec 16]. Available from: https://www.congress.gov/bill/117th-congress/house-bill/6584/text 23. ↵ Public Law 112-144, Food and Drug Administration Safety and Innovation Act [Internet] . Washington (DC) : U.S. Congress ; 2012 [cited 2025 Feb 7]. Available from: https://www.congress.gov/112/plaws/publ144/PLAW-112publ144.pdf 24. ↵ Patterson AM , O’Boyle M , VanNoy GE , Dies KA . Emerging roles and opportunities for rare disease patient advocacy groups . Therapeutic Advances in Rare Disease [Internet] . 2023 Jan 1 [cited 2025 Feb 8]; 4 : 26330040231164424 . Available from: https://pmc.ncbi.nlm.nih.gov/articles/PMC10184204/ OpenUrl 25. ↵ IAMRARE® Program - National Organization for Rare Disorders [Internet] . [cited 2025 Jan 20]. Available from: https://rarediseases.org/advancing-research/patient-registry-program/ 26. Rare Disease Cures Accelerator-Data and Analytics Platform [Internet] . [cited 2025 Jan 20]. Available from: https://c-path.org/program/rare-disease-cures-accelerators-data-and-analytics-platform/ 27. EveryLife Foundation for Rare Diseases . Rare Disease Legislative Advocates. [Internet] . [cited 2025 Jan 20]. Available from: https://everylifefoundation.org/rare-advocates/ 28. Rare-X. Patient’s Data Powering Progress [Internet] . [cited 2025 Jan 20]. Available from: https://rare-x.org/ 29. Rare-X. Diversity, Equity, and Inclusion for Rare Disease [Internet] . [cited 2025 Jan 20]. Available from: https://rare-x.org/dei/ 30. ↵ Rare Diseases International Rare Diseases International [Internet] . [cited 2025 Jan 20]. Available from: https://www.rarediseasesinternational.org/ 31. ↵ Soomro QH , McCarthy A , Varela D , Keane C , Ways J , Charytan AM , et al. Representation of Racial and Ethnic Minorities in Nephrology Clinical Trials: A Systematic Review and Meta-Analysis . J Am Soc Nephrol . 2023 Apr; 34 ( 7 ): 1167 – 1177 . doi: 10.1681/ASN.0000000000000134 OpenUrl CrossRef PubMed 32. Pittell H , Calip GS , Pierre A , Ryals CA , Altomare I , Royce TJ , et al. Racial and Ethnic Inequities in US Oncology Clinical Trial Participation From 2017 to 2022 . JAMA Netw Open [Internet] . 2023 Jul 3 [cited 2024 May 16]; 6 ( 7 ): e2322515 – e2322515 . Available from: https://jamanetwork.com/journals/jamanetworkopen/fullarticle/2807488 OpenUrl 33. Donzo MW , Nguyen G , Nemeth JK , Owoc MS , Mady LJ , Chen AY , et al. Effects of socioeconomic status on enrollment in clinical trials for cancer: A systematic review . Cancer Med [Internet] . 2024 Jan 1 [cited 2024 Aug 12]; 13 ( 1 ): e6905 . Available from: https://onlinelibrary.wiley.com/doi/full/10.1002/cam4.6905 OpenUrl 34. ↵ Lau SWJ , Huang Y , Hsieh J , Wang S , Liu Q , Slattum PW , et al. Participation of Older Adults in Clinical Trials for New Drug Applications and Biologics License Applications From 2010 Through 2019 . JAMA Netw Open [Internet] . 2022 Oct 3 [cited 2025 Jan 21]; 5 ( 10 ): e2236149 – e2236149 . Available from: https://jamanetwork.com/journals/jamanetworkopen/fullarticle/2797323 OpenUrl 35. ↵ Rare-X . Strategic Directions and Recommendations: Diversity, Equity, and Inclusion Scoping Review . 2021 [cited 2025 Jan 20]; Available from: https://rare-x.org/wp-content/uploads/2022/02/dei-020722.pdf 36. ↵ Farkas Lilla . Analysis and comparative review of equality data collection practices in the European Union: data collection in the field of ethnicity . Publications Office of the European Union ; 2017 . 37. ↵ Jeeva Clinical Trials Inc . Unify and accelerate clinical trials with user-friendly software [Internet] . [cited 2025 Feb 7]. Available from: https://jeevatrials.com/ 38. ↵ Pew Research Center . Demographics of Internet and Home Broadband Usage in the United States [Internet] . [cited 2025 Jan 20]. Available from: https://www.pewresearch.org/internet/fact-sheet/internet-broadband/?tabItem=e60540d5-6342-47eb-835d-21b1c0a5e37b 39. ↵ Gichoya JW , Thomas K , Celi LA , Safdar N , Banerjee I , Banja JD , et al. AI pitfalls and what not to do: mitigating bias in AI . Br J Radiol [Internet] . 2023 Oct 1 [cited 2025 Jan 21]; 96 ( 1150 ): 20230023 . Available from: https://pmc.ncbi.nlm.nih.gov/articles/PMC10546443/ OpenUrl 40. ↵ Hutson M . How AI is being used to accelerate clinical trials . Nature . 2024 Mar 14; 627 ( 8003 ): S2 – S5 . doi: 10.1038/d41586-024-00753-x OpenUrl CrossRef PubMed 41. ↵ Yang G , Cintina I , Pariser A , Oehrlein E , Sullivan J , Kennedy A . The national economic burden of rare disease in the United States in 2019 . Orphanet J Rare Dis [Internet] . 2022 Dec 1 [cited 2024 Apr 27]; 17 ( 1 ): 163 . Available from: https://pmc/articles/PMC9004040/ OpenUrl 42. ↵ National Academies of Sciences, Engineering, and Medicine . Improving representation in clinical trials and research: Building research equity for women and underrepresented groups . Washington (DC) : National Academies Press ; 2022 . 1 – 260 p. 43. ↵ World Medical Association . Declaration of Helsinki: Ethical Principles for Medical Research Involving Human Participants [Internet] . [cited 2024 Dec 24]. Available from: https://www.wma.net/policies-post/wma-declaration-of-helsinki/ 44. U.S Health and Human Services . Read the Belmont Report [Internet] . [cited 2024 Dec 26]. Available from: https://www.hhs.gov/ohrp/regulations-and-policy/belmont-report/read-the-belmont-report/index.html#xselect 45. International Council for Harmonisation of Technical Requirements for Pharmaceuticals for Human Use . ICH harmonised guideline: Good clinical practice (GCP) E6(R3) [Internet] . 2023 May [cited 2025 Feb 7]. Available from: https://database.ich.org/sites/default/files/ICH_E6%28R3%29_DraftGuideline_2023_0519.pdf 46. Code of Federal Regulations . eCFRL: 45 CFR Part 46 (July 19, 2018) -- Protection of Human Subjects [Internet] . [cited 2024 Dec 26]. Available from: https://www.ecfr.gov/on/2018-07-19/title-45/subtitle-A/subchapter-A/part-46 47. U.S. Congress . S.1 - National Institutes of Health Revitalization Act of 1993 [Internet]. 103rd Congress (1993-1994) . Washington (DC) : Library of Congress ; 1993 [cited 2024 Dec 20]. Available from: https://www.congress.gov/bill/103rd-congress/senate-bill/1/text 48. U.S Department of Health and Human Services . Summary of the HIPAA Privacy Rule [Internet] . [cited 2025 Jan 20]. Available from: https://www.hhs.gov/hipaa/for-professionals/privacy/laws-regulations/index.html 49. ClinicalTrials.gov . FDAAA 801 and the Final Rule [Internet] . Bethesda (MD) : National Library of Medicine (US) ; [cited 2024 Dec 24]. Available from: https://clinicaltrials.gov/policy/fdaaa-801-final-rule 50. National Institute of Health . NOT-OD-18-116: Revision: NIH Policy and Guidelines on the Inclusion of Individuals Across the Lifespan as Participants in Research Involving Human Subjects [Internet] . [cited 2024 Dec 29]. Available from: https://grants.nih.gov/grants/guide/notice-files/NOT-OD-18-116.html 51. Public Law 115-52, FDA Reauthorization Act of 2017 (FDARA) [Internet] . Washington (DC) : U.S. Congress ; 2017 Aug 18 [cited 2025 Feb 7]. Available from: https://www.congress.gov/115/plaws/publ52/PLAW-115publ52.pdf 52. U.S. Food and Drug Administration . Enhancing the Diversity of Clinical Trial Populations-Eligibility Criteria, Enrollment Practices, and Trial Designs Guidance for Industry . 2020 [cited 2025 Jan 4]; Available from: https://www.fda.gov/drugs/guidance-compliance-regulatory-information/guidances-drugsand/or 53. U.S. Congress . H.R.3503 - NIH Clinical Trial Diversity Act of 2023 [Internet]. 118th Congress (2023-2024) . Washington (DC) : U.S. Congress ; 2023 [cited 2024 Dec 18]; Available from: https://www.congress.gov/bill/118th-congress/house-bill/3503/text 54. U.S. Food and Drug Administration . Postmarketing Approaches to Obtain Data on Populations Underrepresented in Clinical Trials for Drugs and Biological Products Guidance for Industry [cited 2025 Jan 20]; Available from: https://www.fda.gov/media/170899/download 55. U.S Food and Drug Administration . Diversity Action Plans to Improve Enrollment of Participants from Underrepresented Populations in Clinical Studies Guidance for Industry [Internet] . 2024 [cited 2024 Dec 27]; Available from: https://www.fda.gov/vaccines-blood-biologics/guidance - 56. U.S. Food and Drug Administration . Collection of Race and Ethnicity Data in Clinical Trials and Clinical Studies for FDA-Regulated Medical Products Guidance for Industry . [cited 2025 Jan 20]; Available from: https://www.fda.gov/media/170899/download 57. Bierer BE. Achieving diversity, inclusion, and equity in clinical research: Toolkit . Multi-Regional Clinical Trials Center of Brigham and Women’s Hospital and Harvard (MRCT Center) ; 2021 . 143 p. 58. U.S. Congress . H.R.8412 - Clinical Trial Modernization Act [Internet]. 118th Congress (2023-2024) . Washington (DC) : U.S. Congress ; 2024 [cited 2025 Jan 5]; Available from: https://www.congress.gov/bill/118th-congress/house-bill/8412/text 59. U.S. Food and Drug Administration . Conducting clinical trials with decentralized elements: guidance for industry, investigators, and other interested parties . 2024 Sep [cited 2025 Jan 20]; Available from: https://www.fda.gov/media/167696/download View the discussion thread. Back to top Previous Next Posted May 08, 2025. Download PDF Supplementary Material Data/Code Email Thank you for your interest in spreading the word about medRxiv. NOTE: Your email address is requested solely to identify you as the sender of this article. Your Email * Your Name * Send To * Enter multiple addresses on separate lines or separate them with commas. You are going to email the following A Framework for Inclusive and Accessible Clinical Research in Rare Diseases Message Subject (Your Name) has forwarded a page to you from medRxiv Message Body (Your Name) thought you would like to see this page from the medRxiv website. Your Personal Message CAPTCHA This question is for testing whether or not you are a human visitor and to prevent automated spam submissions. Share A Framework for Inclusive and Accessible Clinical Research in Rare Diseases Lavanyaa Manjunatha , MS Saundarya , Nisha Venugopal , Jenifer Ngo Waldrop , Linda Goler Blount , Reena V Kartha , Harsha K Rajasimha medRxiv 2025.05.07.25326565; doi: https://doi.org/10.1101/2025.05.07.25326565 Share This Article: Copy Citation Tools A Framework for Inclusive and Accessible Clinical Research in Rare Diseases Lavanyaa Manjunatha , MS Saundarya , Nisha Venugopal , Jenifer Ngo Waldrop , Linda Goler Blount , Reena V Kartha , Harsha K Rajasimha medRxiv 2025.05.07.25326565; doi: https://doi.org/10.1101/2025.05.07.25326565 Citation Manager Formats BibTeX Bookends EasyBib EndNote (tagged) EndNote 8 (xml) Medlars Mendeley Papers RefWorks Tagged Ref Manager RIS Zotero Tweet Widget Facebook Like Google Plus One Subject Area Health Systems and Quality Improvement Subject Areas All Articles Addiction Medicine (568) Allergy and Immunology (863) Anesthesia (300) Cardiovascular Medicine (4435) Dentistry and Oral Medicine (444) Dermatology (382) Emergency Medicine (608) Endocrinology (including Diabetes Mellitus and Metabolic Disease) (1509) Epidemiology (15228) Forensic Medicine (30) Gastroenterology (1124) Genetic and Genomic Medicine (6599) Geriatric Medicine (668) Health Economics (997) Health Informatics (4536) Health Policy (1368) Health Systems and Quality Improvement (1613) Hematology (540) HIV/AIDS (1264) Infectious Diseases (except HIV/AIDS) (15916) Intensive Care and Critical Care Medicine (1103) Medical Education (623) Medical Ethics (146) Nephrology (667) Neurology (6599) Nursing (346) Nutrition (998) Obstetrics and Gynecology (1144) Occupational and Environmental Health (957) Oncology (3332) Ophthalmology (974) Orthopedics (369) Otolaryngology (420) Pain Medicine (436) Palliative Medicine (130) Pathology (663) Pediatrics (1693) Pharmacology and Therapeutics (691) Primary Care Research (711) Psychiatry and Clinical Psychology (5447) Public and Global Health (9231) Radiology and Imaging (2198) Rehabilitation Medicine and Physical Therapy (1370) Respiratory Medicine (1196) Rheumatology (593) Sexual and Reproductive Health (712) Sports Medicine (530) Surgery (712) Toxicology (99) Transplantation (289) Urology (265) (function(){function c(){var b=a.contentDocument||a.contentWindow.document;if(b){var d=b.createElement('script');d.innerHTML="window.__CF$cv$params={r:'a005c4b00e5d8650',t:'MTc3OTU1NzIxNA=='};var a=document.createElement('script');a.src='/cdn-cgi/challenge-platform/scripts/jsd/main.js';document.getElementsByTagName('head')[0].appendChild(a);";b.getElementsByTagName('head')[0].appendChild(d)}}if(document.body){var a=document.createElement('iframe');a.height=1;a.width=1;a.style.position='absolute';a.style.top=0;a.style.left=0;a.style.border='none';a.style.visibility='hidden';document.body.appendChild(a);if('loading'!==document.readyState)c();else if(window.addEventListener)document.addEventListener('DOMContentLoaded',c);else{var e=document.onreadystatechange||function(){};document.onreadystatechange=function(b){e(b);'loading'!==document.readyState&&(document.onreadystatechange=e,c())}}}})();