Modernizing the Data Infrastructure for Clinical Research to Meet Evolving Demands for Evidence.

Importance: The ways in which we access, acquire, and use data in clinical trials have evolved very little over time, resulting in a fragmented and inefficient system that limits the amount and quality of evidence that can be generated. Observations: Clinical trial design has advanced steadily over several decades. Yet the infrastructure for clinical trial data collection remains expensive and labor intensive and limits the amount of evidence that can be collected to inform whether and how interventions work for different patient populations. Meanwhile, there is increasing demand for evidence from randomized clinical trials to inform regulatory decisions, payment decisions, and clinical care. Although substantial public and industry investment in advancing electronic health record interoperability, data standardization, and the technology systems used for data capture have resulted in significant progress on various aspects of data generation, there is now a need to combine the results of these efforts and apply them more directly to the clinical trial data infrastructure. Conclusions and Relevance: We describe a vision for a modernized infrastructure that is centered around 2 related concepts. First, allowing the collection and rigorous evaluation of multiple data sources and types and, second, enabling the possibility to reuse health data for multiple purposes. We address the need for multidisciplinary collaboration and suggest ways to measure progress toward this goal.

Byproduct formation during the biosynthesis of spinosyn A and evidence for an enzymatic interplay to prevent its formation.

Biosynthesis of spinosyn A in Saccharopolyspora spinosa involves a 1,4-dehydration followed by an intramolecular [4 + 2]-cycloaddition catalyzed by SpnM and SpnF, respectively. The cycloaddition also takes place in the absence of SpnF leading to questions regarding its mechanism of catalysis and biosynthetic role. Substrate analogs were prepared with an unactivated dienophile or an acyclic structure and found to be unreactive consistent with the importance of these features for cyclization. The SpnM-catalyzed dehydration reaction was also found to yield a byproduct corresponding to the C11 = C12 cis isomer of the SpnF substrate. This byproduct is stable both in the presence and absence of SpnF; however, relative production of the SpnM product and byproduct could be shifted in favor of the former by including SpnF or the dehydrogenase SpnJ in the reaction. This result suggests a potential interplay between the enzymes of spinosyn A biosynthesis that may help to improve the efficiency of the pathway.

Significant shared heritability underlies suicide attempt and clinically predicted probability of attempting suicide.

Suicide accounts for nearly 800,000 deaths per year worldwide with rates of both deaths and attempts rising. Family studies have estimated substantial heritability of suicidal behavior; however, collecting the sample sizes necessary for successful genetic studies has remained a challenge. We utilized two different approaches in independent datasets to characterize the contribution of common genetic variation to suicide attempt. The first is a patient reported suicide attempt phenotype asked as part of an online mental health survey taken by a subset of participants (n = 157,366) in the UK Biobank. After quality control, we leveraged a genotyped set of unrelated, white British ancestry participants including 2433 cases and 334,766 controls that included those that did not participate in the survey or were not explicitly asked about attempting suicide. The second leveraged electronic health record (EHR) data from the Vanderbilt University Medical Center (VUMC, 2.8 million patients, 3250 cases) and machine learning to derive probabilities of attempting suicide in 24,546 genotyped patients. We identified significant and comparable heritability estimates of suicide attempt from both the patient reported phenotype in the UK Biobank (h2SNP = 0.035, p = 7.12 × 10-4) and the clinically predicted phenotype from VUMC (h2SNP = 0.046, p = 1.51 × 10-2). A significant genetic overlap was demonstrated between the two measures of suicide attempt in these independent samples through polygenic risk score analysis (t = 4.02, p = 5.75 × 10-5) and genetic correlation (rg = 1.073, SE = 0.36, p = 0.003). Finally, we show significant but incomplete genetic correlation of suicide attempt with insomnia (rg = 0.34-0.81) as well as several psychiatric disorders (rg = 0.26-0.79). This work demonstrates the contribution of common genetic variation to suicide attempt. It points to a genetic underpinning to clinically predicted risk of attempting suicide that is similar to the genetic profile from a patient reported outcome. Lastly, it presents an approach for using EHR data and clinical prediction to generate quantitative measures from binary phenotypes that can improve power for genetic studies.

Water adsorption on vanadium oxide thin films in ambient relative humidity.

In this work, ambient pressure x-ray photoelectron spectroscopy (APXPS) is used to study the initial stages of water adsorption on vanadium oxide surfaces. V 2p, O 1s, C 1s, and valence band XPS spectra were collected as a function of relative humidity in a series of isotherm and isobar experiments. Experiments were carried out on two VO2 thin films on TiO2 (100) substrates, prepared with different surface cleaning procedures. Hydroxyl and molecular water surface species were identified, with up to 0.5 ML hydroxide present at the minimum relative humidity, and a consistent molecular water adsorption onset occurring around 0.01% relative humidity. The work function was found to increase with increasing relative humidity, suggesting that surface water and hydroxyl species are oriented with the hydrogen atoms directed away from the surface. Changes in the valence band were also observed as a function of relative humidity. The results were similar to those observed in APXPS experiments on other transition metal oxide surfaces, suggesting that H2O-OH and H2O-H2O surface complex formation plays an important role in the oxide wetting process and water dissociation. Compared to polycrystalline vanadium metal, these vanadium oxide films generate less hydroxide and appear to be more favorable for molecular water adsorption.

Psychological primitives can make sense of biopsychosocial factor complexity in psychopathology.

BACKGROUND: Many agree that the biopsychosocial contributions to psychopathology are complex, yet it is unclear how we can make sense of this complexity. One approach is to reduce this complexity to a few necessary and sufficient biopsychosocial factors; although this approach is easy to understand, it has little explanatory power. Another approach is to fully embrace complexity, proposing that each instance of psychopathology is caused by a partially unique set of biopsychosocial factors; this approach has high explanatory power, but is impossible to comprehend. Due to deficits in either explanatory power or comprehensibility, both approaches limit our ability to make substantial advances in understanding, predicting, and preventing psychopathology. Thus, how can we make sense of biopsychosocial factor complexity? MAIN TEXT: There is a third possible approach that can resolve this dilemma, with high explanatory power and high comprehensibility. This approach involves understanding, predicting, and preventing psychopathology in terms of a small set of psychological primitives rather than biopsychosocial factors. Psychological primitives are the fundamental and irreducible elements of the mind, mediating all biopsychosocial factor influences on psychopathology. All psychological phenomena emerge from these primitives. Over the past decade, this approach has been successfully applied within basic psychological science, most notably affective science. It explains the sum of the evidence in affective science and has generated several novel research directions. This approach is equally applicable to psychopathology. The primitive-based approach does not eliminate the role of biopsychosocial factors, but rather recasts them as indeterminate causal influences on psychological primitives. In doing so, it reframes research away from factor-based questions (e.g., which situations cause suicide?) and toward primitive-based questions (e.g., how are suicidality concepts formed, altered, activated, and implemented?). This is a valuable shift because factor-based questions have indeterminate answers (e.g., infinite situations could cause suicide) whereas primitive-based questions have determinate answers (e.g., there are specific processes that undergird all concepts). CONCLUSION: The primitive-based approach accounts for biopsychosocial complexity, ties clinical science more directly to basic psychological science, and could facilitate progress in understanding, predicting, and preventing psychopathology.

Depression and hopelessness as risk factors for suicide ideation, attempts and death: meta-analysis of longitudinal studies.

BACKGROUND: Many studies have documented robust relationships between depression and hopelessness and subsequent suicidal thoughts and behaviours; however, much weaker and non-significant effects have also been reported. These inconsistencies raise questions about whether and to what degree these factors confer risk for suicidal thoughts and behaviours.AimsThis study aimed to evaluate the magnitude and clinical utility of depression and hopelessness as risk factors for suicide ideation, attempts and death. METHOD: We conducted a meta-analysis of published studies from 1971 to 31 December 2014 that included at least one longitudinal analysis predicting suicide ideation, attempt or death using any depression or hopelessness variable. RESULTS: Overall prediction was weaker than anticipated, with weighted mean odds ratios of 1.96 (1.81-2.13) for ideation, 1.63 (1.55-1.72) for attempt and 1.33 (1.18-1.49) for death. Adjusting for publication bias further reduced estimates. Effects generally persisted regardless of sample severity, sample age or follow-up length. CONCLUSIONS: Several methodological constraints were prominent across studies; addressing these issues would likely be fruitful moving forward.Declaration of interestNone.

Predicting suicide attempts in adolescents with longitudinal clinical data and machine learning.

BACKGROUND: Adolescents have high rates of nonfatal suicide attempts, but clinically practical risk prediction remains a challenge. Screening can be time consuming to implement at scale, if it is done at all. Computational algorithms may predict suicide risk using only routinely collected clinical data. We used a machine learning approach validated on longitudinal clinical data in adults to address this challenge in adolescents. METHODS: This is a retrospective, longitudinal cohort study. Data were collected from the Vanderbilt Synthetic Derivative from January 1998 to December 2015 and included 974 adolescents with nonfatal suicide attempts and multiple control comparisons: 496 adolescents with other self-injury (OSI), 7,059 adolescents with depressive symptoms, and 25,081 adolescent general hospital controls. Candidate predictors included diagnostic, demographic, medication, and socioeconomic factors. Outcome was determined by multiexpert review of electronic health records. Random forests were validated with optimism adjustment at multiple time points (from 1 week to 2 years). Recalibration was done via isotonic regression. Evaluation metrics included discrimination (AUC, sensitivity/specificity, precision/recall) and calibration (calibration plots, slope/intercept, Brier score). RESULTS: Computational models performed well and did not require face-to-face screening. Performance improved as suicide attempts became more imminent. Discrimination was good in comparison with OSI controls (AUC = 0.83 [0.82-0.84] at 720 days; AUC = 0.85 [0.84-0.87] at 7 days) and depressed controls (AUC = 0.87 [95% CI 0.85-0.90] at 720 days; 0.90 [0.85-0.94] at 7 days) and best in comparison with general hospital controls (AUC 0.94 [0.92-0.96] at 720 days; 0.97 [0.95-0.98] at 7 days). Random forests significantly outperformed logistic regression in every comparison. Recalibration improved performance as much as ninefold - clinical recommendations with poorly calibrated predictions can lead to decision errors. CONCLUSIONS: Machine learning on longitudinal clinical data may provide a scalable approach to broaden screening for risk of nonfatal suicide attempts in adolescents.

Understanding suicide risk within the Research Domain Criteria (RDoC) framework: A meta-analytic review.

BACKGROUND: The field is in need of novel and transdiagnostic risk factors for suicide. The National Institute of Mental Health's Research Domain Criteria (RDoC) provides a framework that may help advance research on suicidal behavior. METHOD: We conducted a meta-analytic review of existing prospective risk and protective factors for suicidal thoughts and behaviors (ideation, attempts, and deaths) that fall within one of the five RDoC domains or relate to a prominent suicide theory. Predictors were selected from a database of 4,082 prospective risk and protective factors for suicide outcomes. RESULTS: A total of 460 predictors met inclusion criteria for this meta-analytic review and most examined risk (vs. protective) factors for suicidal thoughts and behaviors. The overall effect of risk factors was statistically significant, but relatively small, in predicting suicide ideation (weighted mean odds ratio: wOR = 1.72; 95% CI: 1.59-1.87), suicide attempt (wOR = 1.66 [1.57-1.76), and suicide death (wOR = 1.41 [1.24-1.60]). Across all suicide outcomes, most risk factors related to the Negative Valence Systems domain, although effect sizes were of similar magnitude across RDoC domains. CONCLUSIONS: This study demonstrated that the RDoC framework provides a novel and promising approach to suicide research; however, relatively few studies of suicidal behavior fit within this framework. Future studies must go beyond the "usual suspects" of suicide risk factors (e.g., mental disorders, sociodemographics) to understand the processes that combine to lead to this deadly outcome.

Implicit attitudes toward eating stimuli differentiate eating disorder and non-eating disorder groups and predict eating disorder behaviors.

OBJECTIVE: The current study tested whether people with and without eating disorders (EDs) varied in their implicit attitudes toward ED-relevant stimuli. Additionally, the study tested whether implicit evaluations of ED-relevant stimuli predicted ED symptoms and behaviors over a 4-week interval. METHOD: Participants were people without EDs (N = 85) and people seeking treatment for EDs (N = 92). All participants completed self-report questionnaires and a version of the affect misattribution procedure (AMP) at baseline. The AMP indexed implicit evaluations of average body stimuli, eating stimuli, and ED-symptom stimuli. Participants with EDs completed weekly follow-up measures of ED symptoms and behaviors for 4 weeks. RESULTS: Contrary to predictions, the anorexia nervosa (AN) group did not differ from the no ED group on implicit attitudes toward ED-symptom stimuli, and the bulimia nervosa (BN) group had less positive implicit attitudes toward ED-symptom stimuli relative to the no ED group. In line with predictions, people with AN and BN had more negative implicit attitudes toward average body and eating stimuli relative to the no ED group. In addition, among the ED group more negative implicit attitudes toward eating stimuli predicted ED symptoms and behaviors 4 weeks later, over and above baseline ED symptoms and behaviors. DISCUSSION: Taken together, implicit evaluations of eating stimuli differentiated people with AN and BN from people without EDs and longitudinally predicted ED symptoms and behaviors. Interventions that increase implicit liking of eating-related stimuli may reduce ED behaviors.

Is externalizing psychopathology a robust risk factor for suicidal thoughts and behaviors? A meta-analysis of longitudinal studies.

OBJECTIVE: Our primary objective was to determine the potency of externalizing psychopathology as a risk factor for suicidal thoughts and behaviors (STBs). METHOD: We conducted a random effects meta-analysis of 174 prospective studies (839 unique statistical tests) examining externalizing psychopathology and suicidal thoughts and behaviors (STBs) published prior to December 8, 2017. The weighted mean odds ratios for the overall relationship between externalizing psychopathology and STBs were below 2.00 in magnitude, and all risk factor subcategories were also fairly modest predictors of STBs. Taking publication bias into account reduced the magnitude of these associations, particularly for death. Although externalizing psychopathology modestly predicts STBs, this may be due to design limitations of existing studies. Future research should employ shorter follow-up periods, consider risk factors in combination, and focus on forms of externalizing psychopathology that have not been studied extensively. RESULTS: The weighted mean odds ratios for the overall relationship between externalizing psychopathology and STBs were below 2.00 in magnitude, and all risk factor subcategories were also fairly modest predictors of STBs. Taking publication bias into account reduced the magnitude of these associations, particularly for death. Additionally, our results were mostly consistent regardless of sample age, sample severity, follow-up length, and predictor scale. CONCLUSIONS: Although externalizing psychopathology modestly predicts STBs, this may be due to design limitations of existing studies. Future research should employ shorter follow-up periods, consider risk factors in combination, and focus on forms of externalizing psychopathology that have not been studied extensively.

How to Implement Therapeutic Evaluative Conditioning in a Clinical Setting.

Self-injurious behaviors (SIBs), including both suicidal and nonsuicidal self-injury, are major public health problems that have been on the rise in recent decades. There are few effective SIB interventions, and those that are effective cannot reach most people who are in need of help-that is, these interventions are not scalable. To address this need, we recently developed a scalable, app-based treatment called Therapeutic Evaluative Conditioning (TEC) that preliminary studies have shown causes reductions in SIBs (Franklin et al., 2016). Although TEC was developed and evaluated as a standalone, self-administered intervention, it may also be a valuable therapeutic tool within traditional clinical settings. Here we provide a case illustration of a young adult female who presented at an outpatient clinic with a long history of self-injurious behaviors and multiple failed treatment attempts. In discussing this case, we describe how to implement TEC within such a setting and what might be expected as a result.

Evidence-based psychosocial treatments for self-injurious thoughts and behaviors in youth.

The purpose of this study was to review the current evidence base of psychosocial treatments for suicidal and nonsuicidal self-injurious thoughts and behaviors (SITBs) in youth. We reviewed major scientific databases (HealthSTAR, MEDLine, PsycINFO, PubMed) for relevant studies published prior to June 2013. The search identified 29 studies examining interventions for suicidal or nonsuicidal SITBs in children or adolescents. No interventions currently meet the Journal of Clinical Child and Adolescent Psychology standards for Level 1: well-established treatments. Six treatment categories were classified as Level 2: probably efficacious or Level 3: possibly efficacious for reducing SITBs in youth. These treatments came from a variety of theoretical orientations, including cognitive-behavioral, family, interpersonal, and psychodynamic theories. Common elements across efficacious treatments included family skills training (e.g., family communication and problem solving), parent education and training (e.g., monitoring and contingency management), and individual skills training (e.g., emotion regulation and problem solving). Several treatments have shown potential promise for reducing SITBs in children and adolescents. However, the probably/possibly efficacious treatments identified each have evidence from only a single randomized controlled trial. Future research should focus on replicating studies of promising treatments, identifying active treatment ingredients, examining mediators and moderators of treatment effects, and developing brief interventions for high-risk periods (e.g., following hospital discharge).

How developmental psychopathology theory and research can inform the research domain criteria (RDoC) project.

The recently proposed Research Domain Criteria (RDoC) project has the potential to stimulate new research and overcome many of the limitations of the Diagnostic and Statistical Manual of Mental Disorders taxonomy. In the present article we focus, in three main sections, on how theory and research from developmental psychopathology can inform RDoC. First, we discuss the ontology of mental illness and the potential advantages of the RDoC approach to understanding the nature of mental illness. Second, we note potential issues to consider when implementing the RDoC framework, including (a) integrating developmental processes, (b) classifying mental illness within a dimensional approach, and (c) avoiding problems associated with biological reductionism. Third, we describe how a developmental psychopathology perspective may inform each of these potential issues within RDoC. Finally, we highlight the study of emotion and the centrality of affective processes within the RDoC framework. Specifically, we describe how constructionist models of emotion are consistent with developmental psychopathology and how this perspective on emotion can help to guide RDoC research.

The structure and repertoire of small interfering RNAs in Leishmania (Viannia) braziliensis reveal diversification in the trypanosomatid RNAi pathway.

Among trypanosomatid protozoa the mechanism of RNA interference (RNAi) has been investigated in Trypanosoma brucei and to a lesser extent in Leishmania braziliensis. Although these two parasitic organisms belong to the same family, they are evolutionarily distantly related raising questions about the conservation of the RNAi pathway. Here we carried out an in-depth analysis of small interfering RNAs (siRNAs) associated with L. braziliensis Argonaute1 (LbrAGO1). In contrast to T. brucei, Leishmania siRNAs are sensitive to 3' end oxidation, indicating the absence of blocking groups, and the Leishmania genome does not code for a HEN1 RNA 2'-O-methyltransferase, which modifies small RNA 3' ends. Consistent with this observation, ~20% of siRNA 3' ends carry non-templated uridines. Thus siRNA biogenesis, and most likely their metabolism, is different in these organisms. Similarly to T. brucei, putative mobile elements and repeats constitute the major Leishmania siRNA-producing loci and AGO1 ablation leads to accumulation of long transcripts derived from putative mobile elements. However, contrary to T. brucei, no siRNAs were detected from other genomic regions with the potential to form double-stranded RNA, namely sites of convergent transcription and inverted repeats. Thus, our results indicate that organism-specific diversification has occurred in the RNAi pathway during evolution of the trypanosomatid lineage.

Chronic pain and suicide: understanding the association.

Chronic pain conditions are associated with an elevated risk for suicide. Of particular importance is the question of why pain conditions might be linked to increased suicide risk. We discuss the association between chronic pain and psychological pain, particularly in the context of depression, and the use of suicide as an attempt to escape from what is perceived as unbearable suffering. We also consider the role that chronic pain may play in increasing the capacity for suicide. Bridging across research areas and drawing on the interpersonal-psychological theory of suicide, we suggest that chronic pain may facilitate the development of a key risk factor for suicide: fearlessness about death. Given that chronic pain can lead to (and be exacerbated by) depression, engender hopelessness, facilitate a desire for escape through death, and erode the natural fear of dying, clinicians must be aware of psychological processes that can combine to create elevated suicide risk in patients with chronic pain, and they should also assess and treat suicide risk factors in these patients.

Mechanistic Insights from the Crystal Structure and Computational Analysis of the Radical SAM Deaminase DesII.

Radical S-adenosyl-L-methionine (SAM) enzymes couple the reductive cleavage of SAM to radical-mediated transformations that have proven to be quite broad in scope. DesII is one such enzyme from the biosynthetic pathway of TDP-desosamine where it catalyzes a radical-mediated deamination. Previous studies have suggested that this reaction proceeds via direct elimination of ammonia from an α-hydroxyalkyl radical or its conjugate base (i.e., a ketyl radical) rather than 1,2-migration of the amino group to form a carbinolamine radical intermediate. However, without a crystal structure, the active site features responsible for this chemistry have remained largely unknown. The crystallographic studies described herein help to fill this gap by providing a structural description of the DesII active site. Computational analyses based on the solved crystal structure are consistent with direct elimination and indicate that an active site glutamate residue likely serves as a general base to promote deprotonation of the α-hydroxyalkyl radical intermediate and elimination of the ammonia group.

Mobilizing data during a crisis: Building rapid evidence pipelines using multi-institutional real world data.

The COVID-19 pandemic generated tremendous interest in using real world data (RWD). Many consortia across the public and private sectors formed in 2020 with the goal of rapidly producing high-quality evidence from RWD to guide medical decision-making, public health priorities, and more. Experiences were gathered from five large consortia on rapid multi-institutional evidence generation during the COVID-19 pandemic. Insights have been compiled across five dimensions: consortium composition, governance structure and alignment of priorities, data sharing, data analysis, and evidence dissemination. The purpose of this piece is to offer guidance on building large-scale multi-institutional RWD analysis pipelines for future public health issues. The composition of each consortium was largely influenced by existing collaborations. A central set of priorities for evidence generation guided each consortium, however different approaches to governance emerged. Challenges surrounding limited access to clinical data due to various contributors were overcome in unique ways. While all consortia used different methods to construct and analyze patient cohorts ranging from centralized to federated approaches, all proved effective for generating meaningful real-world evidence. Actionable recommendations for clinical practice and public health agencies were made from translating insights from consortium analyses. Each consortium was successful in rapidly answering questions about COVID-19 diagnosis and treatment despite all taking slightly different approaches to data sharing and analysis. Leveraging RWD, leveraged in a manner that applies scientific rigor and transparency, can complement higher-level evidence and serve as an important adjunct to clinical trials to quickly guide policy and critical care, especially for a pandemic response.

Solvent-mediated oxide hydrogenation in layered cathodes.

Self-discharge and chemically induced mechanical effects degrade calendar and cycle life in intercalation-based electrochromic and electrochemical energy storage devices. In rechargeable lithium-ion batteries, self-discharge in cathodes causes voltage and capacity loss over time. The prevailing self-discharge model centers on the diffusion of lithium ions from the electrolyte into the cathode. We demonstrate an alternative pathway, where hydrogenation of layered transition metal oxide cathodes induces self-discharge through hydrogen transfer from carbonate solvents to delithiated oxides. In self-discharged cathodes, we further observe opposing proton and lithium ion concentration gradients, which contribute to chemical and structural heterogeneities within delithiated cathodes, accelerating degradation. Hydrogenation occurring in delithiated cathodes may affect the chemo-mechanical coupling of layered cathodes as well as the calendar life of lithium-ion batteries.

Feeling worse to feel better: pain-offset relief simultaneously stimulates positive affect and reduces negative affect.

Although pain itself induces negative affect, the removal (or offset) of pain induces a powerful state of relief. Despite being implicated in a wide range of psychological and behavioral phenomena, relief remains a poorly understood emotion. In particular, some theorists associate relief with increased positive affect, whereas others associate relief with diminished negative affect. In the present study, we examined the affective nature of relief in a pain-offset paradigm with psychophysiological measures that were specific to negative valence (startle eyeblink reactivity) and positive valence (startle postauricular reactivity). Results revealed that pain offset simultaneously stimulates positive affect and diminishes negative affect for at least several seconds. Results also indicated that pain intensity differentially affects the positive and negative valence aspects of relief. These findings clarify the affective nature of relief and provide insight into why people engage in both normal and abnormal behaviors associated with relief.

Diversity, Equity, and Inclusion in Clinical Research: A Path Toward Precision Health for Everyone.

Healthcare disparities are a persistent societal problem. One of the contributing factors to this status quo is the lack of diversity and representativeness of research efforts, which result in nongeneralizable evidence that, in turn, provides suboptimal means to enable the best possible outcomes at the individual level. There are several strategies that research teams can adopt to improve the diversity, equity, and inclusion (DEI) of their efforts; these strategies span the totality of the research path, from initial design to the shepherding of clinical data through a potential regulatory process. These strategies include more intentionality and DEI-based goal-setting, more diverse research and leadership teams, better community engagement to set study goals and approaches, better tailored outreach interventions, decentralization of study procedures and incorporation of innovative technology for more flexible data collection, and self-surveillance to identify and prevent biases. Within their remit of overlooking research efforts, regulatory authorities, as stakeholders, also have the potential for a positive effect on the DEI of emerging clinical evidence. All these are implementable tools and mechanisms that can make study participation more approachable to diverse communities, and ultimately generate evidence that is more generalizable and a conduit for better outcomes. The research community has an imperative to make DEI principles key foundational aspects in study conduct in order to pursue better personalized medicine for diverse patient populations.