Building an Artificial Intelligence Laboratory Based on Real World Data: The Experience of Gemelli Generator

The problem of transforming Real World Data into Real World Evidence is becoming increasingly important in the frameworks of Digital Health and Personalized Medicine, especially with the availability of modern algorithms of Artificial Intelligence high computing power, and large storage facilities.Even where Real World Data are well maintained in a hospital data warehouse and are made available for research purposes, many aspects need to be addressed to build an effective architecture enabling researchers to extract knowledge from data.We describe the first year of activity at Gemelli Generator RWD, the challenges we faced and the solutions we put in place to build a Real World Data laboratory at the service of patients and health researchers. Three classes of services are available today: retrospective analysis of existing patient data for descriptive and clustering purposes; automation of knowledge extraction, ranging from text mining, patient selection for trials, to generation of new research hypotheses; and finally the creation of Decision Support Systems, with the integration of data from the hospital data warehouse, apps, and Internet of Things.

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Can pragmatic research, real-world data and digital technologies aid the development of psychedelic medicine?

Journal of Psychopharmacology ◽

10.1177/02698811211008567 ◽

2021 ◽

pp. 026988112110085

Author(s):

Robin L Carhart-Harris ◽

Anne C Wagner ◽

Manish Agrawal ◽

Hannes Kettner ◽

Jerold F Rosenbaum ◽

...

Keyword(s):

Real World ◽

Best Practice ◽

Digital Health ◽

Real World Data ◽

Treatment Protocols ◽

World Data ◽

Cost Efficient ◽

Personalised Treatment ◽

New Research ◽

Confirmatory Trials

Favourable regulatory assessments, liberal policy changes, new research centres and substantial commercial investment signal that psychedelic therapy is making a major comeback. Positive findings from modern trials are catalysing developments, but it is questionable whether current confirmatory trials are sufficient for advancing our understanding of safety and best practice. Here we suggest supplementing traditional confirmatory trials with pragmatic trials, real-world data initiatives and digital health solutions to better support the discovery of optimal and personalised treatment protocols and parameters. These recommendations are intended to help support the development of safe, effective and cost-efficient psychedelic therapy, which, given its history, is vulnerable to excesses of hype and regulation.

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Leveraging Real-World Data for the Selection of Relevant Eligibility Criteria for the Implementation of Electronic Recruitment Support in Clinical Trials

Applied Clinical Informatics ◽

10.1055/s-0040-1721010 ◽

2021 ◽

Vol 12 (01) ◽

pp. 017-026

Author(s):

Georg Melzer ◽

Tim Maiwald ◽

Hans-Ulrich Prokosch ◽

Thomas Ganslandt

Keyword(s):

Data Warehouse ◽

Real World ◽

Chart Review ◽

Patient Recruitment ◽

Real World Data ◽

Eligibility Criteria ◽

Health Records ◽

World Data ◽

Paper Chart ◽

Data Elements

Abstract Background Even though clinical trials are indispensable for medical research, they are frequently impaired by delayed or incomplete patient recruitment, resulting in cost overruns or aborted studies. Study protocols based on real-world data with precisely expressed eligibility criteria and realistic cohort estimations are crucial for successful study execution. The increasing availability of routine clinical data in electronic health records (EHRs) provides the opportunity to also support patient recruitment during the prescreening phase. While solutions for electronic recruitment support have been published, to our knowledge, no method for the prioritization of eligibility criteria in this context has been explored. Methods In the context of the Electronic Health Records for Clinical Research (EHR4CR) project, we examined the eligibility criteria of the KATHERINE trial. Criteria were extracted from the study protocol, deduplicated, and decomposed. A paper chart review and data warehouse query were executed to retrieve clinical data for the resulting set of simplified criteria separately from both sources. Criteria were scored according to disease specificity, data availability, and discriminatory power based on their content and the clinical dataset. Results The study protocol contained 35 eligibility criteria, which after simplification yielded 70 atomic criteria. For a cohort of 106 patients with breast cancer and neoadjuvant treatment, 47.9% of data elements were captured through paper chart review, with the data warehouse query yielding 26.9% of data elements. Score application resulted in a prioritized subset of 17 criteria, which yielded a sensitivity of 1.00 and specificity 0.57 on EHR data (paper charts, 1.00 and 0.80) compared with actual recruitment in the trial. Conclusion It is possible to prioritize clinical trial eligibility criteria based on real-world data to optimize prescreening of patients on a selected subset of relevant and available criteria and reduce implementation efforts for recruitment support. The performance could be further improved by increasing EHR data coverage.

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Real-World Data and Real-World Evidence

Innovative Methods for Rare Disease Drug Development ◽

10.1201/9781003049364-8 ◽

2020 ◽

pp. 141-166

Author(s):

Shein-Chung Chow

Keyword(s):

Real World ◽

Real World Data ◽

World Data ◽

Real World Evidence

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Development of an Innovative Real-World Evidence Registry for the Herpes Simplex Virus: Case Study

JMIR Dermatology ◽

10.2196/16933 ◽

2020 ◽

Vol 3 (1) ◽

pp. e16933 ◽

Cited By ~ 2

Author(s):

Michelle Helena van Velthoven ◽

Ching Lam ◽

Caroline de Cock ◽

Terese Stenfors ◽

Hassan Chaudhury ◽

...

Keyword(s):

Herpes Simplex Virus ◽

Herpes Simplex ◽

Real World ◽

Physical Symptoms ◽

Use Cases ◽

Real World Data ◽

World Data ◽

Real World Evidence ◽

Simplex Virus

Background Infection with the herpes simplex virus (HSV) is common but not well understood. Furthermore, there remains a social stigma surrounding HSV that can have psychosocial implications for those infected. Despite many patients infected with HSV experiencing mild-to-severe physical symptoms, only one subeffective treatment is available. A registry collecting real-world data reported by individuals potentially infected with HSV could help patients to better understand and manage their condition. Objective This study aimed to report on the development of a registry to collect real-world data reported by people who might be infected with HSV. Methods A case study design was selected as it provides a systematic and in-depth approach to investigating the planning phase of the registry. The case study followed seven stages: plan, design, prepare, collect, analyze, create, and share. We carried out semistructured interviews with experts, which were thematically analyzed and used to build use cases for the proposed registry. These use cases will be used to generate detailed models of how a real-world evidence registry might be perceived and used by different users. Results The following key themes were identified in the interviews: (1) stigma and anonymity, (2) selection bias, (3) understanding treatment and outcome gaps, (4) lifestyle factors, (5) individualized versus population-level data, and (6) severe complications of HSV. We developed use cases for different types of users of the registry, including individuals with HSV, members of the public, researchers, and clinicians. Conclusions This case study revealed key considerations and insights for the development of an appropriate registry to collect real-world data reported by people who might be infected with HSV. Further development and testing of the registry with different users is required. The registry must also be evaluated for the feasibility and effectiveness of collecting data to support symptom management. This registry has the potential to contribute to the development of vaccines and treatments and provide insights into the impact of HSV on other conditions.

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Ondansetron use is associated with lower COVID-19 mortality in a Real-World Data network-based analysis

10.1101/2021.10.05.21264578 ◽

2021 ◽

Author(s):

Gregory M Miller ◽

Austin J Ellis ◽

Rangaprasad Sarangarajan ◽

Amay Parikh ◽

Leonardo O Rodrigues ◽

...

Keyword(s):

Artificial Intelligence ◽

Real World ◽

Clinical Decision Making ◽

Clinical Decision ◽

Long Term Effects ◽

Real World Data ◽

World Data ◽

Antiemetic Agent ◽

Future Loss ◽

Selection Operator

Objective: The COVID-19 pandemic generated a massive amount of clinical data, which potentially holds yet undiscovered answers related to COVID-19 morbidity, mortality, long term effects, and therapeutic solutions. The objective of this study was to generate insights on COVID-19 mortality-associated factors and identify potential new therapeutic options for COVID-19 patients by employing artificial intelligence analytics on real-world data. Materials and Methods: A Bayesian statistics-based artificial intelligence data analytics tool (bAIcis®) within Interrogative Biology® platform was used for network learning, inference causality and hypothesis generation to analyze 16,277 PCR positive patients from a database of 279,281 inpatients and outpatients tested for SARS-CoV-2 infection by antigen, antibody, or PCR methods during the first pandemic year in Central Florida. This approach generated causal networks that enabled unbiased identification of significant predictors of mortality for specific COVID-19 patient populations. These findings were validated by logistic regression, regression by least absolute shrinkage and selection operator, and bootstrapping. Results: We found that in the SARS-CoV-2 PCR positive patient cohort, early use of the antiemetic agent ondansetron was associated with increased survival in mechanically ventilated patients. Conclusions: The results demonstrate how real world COVID-19 focused data analysis using artificial intelligence can generate valid insights that could possibly support clinical decision-making and minimize the future loss of lives and resources.

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