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Spatial biology is revolutionizing the way in which we extract biological insights from precious clinical samples, allowing profiling of thousands of RNA species and ever higher numbers of antibodies to be analyzed from a single tissue slide. But with new 'omics capabilities scaling the analytical and infrastructure requirements for these high-content datasets is more critical than ever, as these datasets contain billions of data points and hundreds of images that require more extensive storage and analysis capabilities. To enable scientists to leverage spatial 'omics instruments, we have launched the AtoMx™ Spatial Informatics Platform, which will enable analytics across NanoString's spatial profiling and imaging solutions.The AtoMx platform was designed to specifically host, ingest, and manage data generated from both the GeoMx® Digital Spatial Profiler and the CosMx™ Spatial Molecular Imager. Data generated by either of these platforms is analyzed, stored, and managed in cloud or private HPC environments. Within the AtoMx platform, we provide native, comprehensive analysis suites specifically designed to integrate the high content, multiplexed imaging from either platform with the molecular readouts. Machine learning methods in key analysis modules allow AtoMx to scale to the billions of data points collected while still maintaining lower compute times. The AtoMx platform is built to conform to open data standards and will support customization through custom analysis scripts, APIs for integration to external software, and a community standard data model that facilitates the integration of tools in open source repositories.With the CosMx platform we have been able to demonstrate a 75x decrease in data processing times compared to locally resourced servers for equivalent data analysis requests by utilizing the scaling tools a cloud service provides such as scaling by compute type for greater RAM access or multiple, parallel compute instances. The platform is designed to facilitate data sharing and collaborative in silico analysis of spatial data, with direct permissions management and compliance with regional privacy requirements. The AtoMx Spatial Informatics Platform provides an extensible, secure management and analysis solution, capable of processing transcriptome-wide expression or high plex protein profiling from the GeoMx Digital Spatial Profiler as well as subcellular spatial 'omics data Citation Format: Jason W. Reeves, David Henderson, Matt Crow, April Munn, Kenlyn Terai, Joachim Schmid. Solving the problem of spatial informatics: Harnessing the power of the cloud and enabling the integration of open source tools for spatial ‘omics analytics [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2023; Part 1 (Regular and Invited Abstracts); 2023 Apr 14-19; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2023;83(7_Suppl):Abstract nr 2083.

Aims Perhaps the most important step when designing and conducting randomized controlled trials (RCTs) in addiction is to put methodological safeguards in place to minimize the likelihood for bias to affect trial outcomes. In this study, we applied the revised Cochrane risk of bias tool (ROB 2) to RCTs of drug, alcohol or tobacco interventions. Methods We searched for trials published in 15 addiction medicine journals over a 7-year period. Our primary endpoint is the risk of bias of included studies. We conducted a sensitivity analysis of publicly funded trials. Results Overall, included RCTs were most often at high risk of bias per our judgments (244/487, 50.1%). However, significant proportions of included RCTs were at low risk of bias (123/487, 25.3%) or some concerns for bias (120/497, 24.6%). RCTs with behavioral modification interventions (19/44, 43.2%) and alcohol interventions (80/150, 53.3%) had the highest proportion of high-risk judgments. In a sensitivity analysis of publicly funded RCTs), 195/386 (50.5%) were at high risk of bias. Conclusions Approximately half of included drug, alcohol or tobacco RCTs in our sample were judged to be at high risk of bias with the most common reason being a lack of proper blinding or proper description of blinding. Key action items to reduce bias in future addiction RCTs include adequate randomization, blinding and inclusion of a trial registry number and protocol.

Introduction and aims: The high prevalence and economic burden of alcohol use disorder (AUD) requires methodologically sound research to guide treatment decisions. Systematic reviews (SR) are fundamental to clinical decision making as they collate results of all studies for a given topic and provide summaries of the clinical evidence. Bias resulting from industry relationships can compromise the validity of SRs. Thus, we investigated financial conflicts of interests (FCOI) within SRs involving the pharmacologic treatment of AUD. Design and Methods: We conducted a systematic search of PubMed, Embase, and the Cochrane Database to retrieve SRs published between September 2016 and December 2019. Screening and data extraction were performed in duplicate, blinded fashion-collecting characteristics of the reviews including the authors' FCOI statements. The results and discussion sections were rated as favorable or unfavorable toward the treatment drug. A stepwise method was used to identify undisclosed FCOIs for all SR authors. Results: Nineteen (of 51) authors representing 7 (of 12) SRs were found to have FCOI. Among reviews with conflicted authors, 3 of 7 (42.9%) results sections were favorable toward the treatment drug, whereas 6 of 7 (85.7%) conclusions were rated as favorable. Discussion and Conclusions: More than one-third of SR authors and nearly two-thirds of studies were found to have FCOIs. Our investigation shows that financial ties are frequent among SR authors on AUD pharmacotherapies and that discussion sections often favored the drug for which the sponsor provided payments.

Introduction: Children and adolescents/young adults (AYAs) with cancer are a vulnerable population susceptible to numerous late effects, such as fatigue and depression, which may diminish their long-term psychological, physical, spiritual, and emotional health. A well-rounded understanding of how positive psychological constructs affect the quality of care and treatment outcomes is therefore warranted. Methods: We conducted a scoping review of 15 positive psychological constructs in children and AYAs with cancer. The primary research questions were (1) what is known about positive psychological constructs in children and AYAs with cancer; (2) what value is ascribed to these constructs by patients? Results: Two hundred seventy-six articles were included after database search and screening. These studies were mostly observational or qualitative and conducted in North America. Constructs were often poorly defined, and measurement tools used to gather data were wide ranging. Numerous factors were correlated with increased or decreased expression of certain constructs, but overall themes were difficult to identify. Similarly, patients often spoke of what increased or decreased expression of a construct, with less emphasis on what they implicitly value. Discussion: This scoping review found ample evidence for what increases or decreases expression of positive psychological constructs, but this evidence was observational and often conflicting. In the future, we recommend the development of a core set of psychological outcomes, with definitions and corresponding measurement tools. We further recommend an emphasis on randomized trials to more rigorously study how expression of constructs can be improved and what effect this has on the quality of life.