SCIENCEBRING   /   HAMBURG, GERMANY
Login Register
International Journal of Advance Scientific Research SCIENTIFIC IDEAS. INTERNATIONAL PERSPECTIVES.
ISSN 2750-1396 12 issues per year · Monthly
Crossref DOI: 10.37547/ijasr
Submit Manuscript ↗

Search the Journal
Articles Published:

Navigating the Digital Transformation of Clinical Research: A Unified Framework for Patient-Focused Outcomes, Data Lake Governance, And AI-Driven Therapeutic Interventions

Vol. 5 No. 11 (2025): Volume 05 Issue 11 Pages 241-248
Authors
  • Ellara Dekoit
    Department of Biomedical Informatics and Clinical Research, Stanford University School of Medicine, United States of America
RESEARCH OVERVIEW

Abstract

The intersection of digital medicine and clinical research has catalyzed a shift toward highly personalized, data-driven healthcare paradigms. This research article examines the evolution of Clinical Outcome Assessments (COAs) and the integration of digital health technologies into patient-focused drug development. By analyzing the transition from traditional paper-based diaries to electronic and wearable-based monitoring, the study highlights the transformative potential of continuous, real-world data collection in chronic conditions such as epilepsy, overactive bladder, and oncology. Central to this digital migration is the architectural necessity of robust data management; thus, this paper explores the metadata modeling and governance principles required to maintain "data lakes" as functional, high-quality repositories rather than disorganized "data swamps." Furthermore, the article investigates the role of Artificial Intelligence (AI) and Machine Learning (ML) in critical care and pharmacovigilance, proposing a framework for moving from "bit to bedside" via AWS Lake House architectures and real-time monitoring. The findings suggest that while digital tools increase patient engagement and data granularity, significant challenges remain regarding data disambiguation, privacy, and the ethical deployment of large language models like ChatGPT in clinical settings. This study provides an exhaustive theoretical elaboration on these themes, offering a roadmap for the next generation of clinical trial design and post-marketing surveillance.

Keywords

  • Patient-Focused Drug Development
  • Clinical Outcome Assessments
  • Data Lake Management
  • Digital Medicine
SOURCES & CITATIONS

References

1. Abirami MS. AI Clinical Decision Support System (AI-CDSS) for Cardiovascular Diseases. In 2023 International Conference on Computer Science and Emerging Technologies (CSET). 2023;1-7.
2. Abrams P. et al. Electronic bladder diaries of differing duration versus a paper diary for data collection in overactive bladder. Neurourol. Urodyn. 35, 743–749 (2016).
3. Beheshti A., Benatallah B., Nouri R., Tabebordbar A. CoreKG: a knowledge lake service. Proc. VLDB Endow., 11 (12) (2018), pp. 1942-1945.
4. Brinkmann B. H. et al. Seizure diaries and forecasting with wearables: epilepsy monitoring outside the clinic. Front. Neurol. 12, 690404 (2021).
5. Chakraborty A, Venkatraman JV. Pharmacovigilance Through Phased Clinical Trials, Post-Marketing Surveillance and Ongoing Life Cycle Safety. In The Quintessence of Basic and Clinical Research and Scientific Publishing. Singapore: Springer Nature Singapore. 2023;427-42.
6. Cherradi M., El Haddadi A., Routaib H. Data lake management based on dlds approach. Networking, Intelligent Systems and Security: Proceedings of NISS 2021, Springer Singapore (2022), pp. 679-690.
7. Cherradi M., Haddadi A.El. EMEMODL: Extensible metadata model for big data lakes. Int. J. Intell. Eng. Syst., 16 (2023).
8. Egeria Metadata Management Tool. Egeria, egeria-project.org (2018).
9. Eichler R., Giebler C., Gröger C., Schwarz H., Mitschang B. Handle-a generic metadata model for data lakes. Big Data Analytics and Knowledge Discovery: 22nd International Conference, DaWaK 2020, Bratislava, Slovakia, September 14–17, 2020, Proceedings 22, Springer International Publishing (2020), pp. 73-88.
10. M. Farid, A. Roatis, I.F. Ilyas, H.F. Hoffmann, X. Chu, CLAMS: bringing quality to data lakes, in: Proceedings of the 2016 International Conference on Management of Data, 2016, pp. 2089–2092.
11. Fisher R. S. et al. Seizure diaries for clinical research and practice: limitations and future prospects. Epilepsy Behav. 24, 304–310 (2012).
12. Ghavami P. Big Data Management: Data Governance Principles for Big Data Analytics. Walter de Gruyter GmbH & Co KG (2020).
13. Hellerstein J.M., Sreekanti V., Gonzalez J.E., Dalton J., Dey A., Nag S., . . . A.M., Sun E. Ground: A data context service. CIDR (2017).
14. Higgins D, Madai VI. From bit to bedside: a practical framework for artificial intelligence product development in healthcare. Advanced Intelligent Systems. 2020;2(10):2000052.
15. Izmailova E. S. & Ellis, R. D. When work hits home: the cancer-treatment journey of a clinical scientist driving digital medicine. JCO Clin. Cancer Inform. (2022).
16. Leventidis A., Di Rocco L., Gatterbauer W., Miller R.J., Riedewald M. DomainNet: Homograph detection for data lake disambiguation (2021) arXiv preprint arXiv:2103.09940.
17. Li R, Curtis K, Zaidi ST, Van C, Castelino R. A new paradigm in adverse drug reaction reporting: consolidating the evidence for an intervention to improve reporting. Expert Opinion on Drug Safety. 2022;21(9):1193-204.
18. Miller K. R., Barnard, S., Juarez-Colunga, E., French, J. A. & Pellinen, J. Long-term seizure diary tracking habits in clinical studies: evidence from the Human Epilepsy Project. Epilepsy Res 203, 107379 (2024).
19. Oreščanin D., Hlupić T., Vrdoljak B. Managing personal identifiable information in data lakes. IEEE Access (2024).
20. Patel J. et al. Use of an electronic seizure diary in a randomized, controlled trial of natalizumab in adult participants with drug-resistant focal epilepsy. Epilepsy Behav. 118, 107925 (2021).
21. Pramanik S, Khang A. Cardiovascular Diseases: Artificial Intelligence Clinical Decision Support System. In AI-Driven Innovations in Digital Healthcare: Emerging Trends, Challenges, and Applications. IGI Global. 2024;274-87.
22. Quinn P., Goka, J. & Richardson, H. Assessment of an electronic daily diary in patients with overactive bladder. BJU Int 91, 647–652 (2003).
23. Ray P.P. ChatGPT: A comprehensive review on background, applications, key challenges, bias, ethics, limitations and future scope. Internet Things Cyber-Phys. Syst. (2023).
24. Regalia G., Onorati, F., Lai, M., Caborni, C. & Picard, R. W. Multimodal wrist-worn devices for seizure detection and advancing research: focus on the Empatica wristbands. Epilepsy Res. 153, 79–82 (2019).
25. Sarramia D., Claude A., Ogereau F., Mezhoud J., Mailhot G. CEBA: A data lake for data sharing and environmental monitoring. Sensors, 22 (7) (2022), p. 2733.
26. Sawadogo P.N., Scholly E., Favre C., Ferey E., Loudcher S., Darmont J. Metadata systems for data lakes: models and features. New Trends in Databases and Information Systems: ADBIS 2019 Short Papers, Bled, Slovenia, 2019, pp. 440-451.
27. Sawadogo P., Darmont J. On data lake architectures and metadata management. J. Intell. Inf. Syst., 56 (1) (2021), pp. 97-120.
28. Scholly E., Sawadogo P., Liu P., Espinosa-Oviedo J.A., Favre C., Loudcher S., . . . S.E., Noûs C. Coining goldmedal: A new contribution to data lake generic metadata modeling (2021) arXiv preprint arXiv:2103.13155.
29. Tiwari PC, Pal R, Chaudhary MJ, Nath R. Artificial intelligence revolutionizing drug development: Exploring opportunities and challenges. Drug Development Res. 2023;84(8):1652-63.
30. U.S. Department of Health and Human Services Food and Drug Administration. Patient-Focused Drug Development: Selecting, Developing, or Modifying Fit-for-Purpose Clinical Outcome Assessments. (FDA, 2025).
31. Weatherall J, Khan FM, Patel M, Dearden R, Shameer K, Dennis G, et al. Clinical trials, real-world evidence, and digital medicine. In The Era of Artificial Intelligence, Machine Learning, and Data Science in the Pharmaceutical Industry. Academic Press. 2021;191-215.
32. Worlikar, S. Real-Time Patient Monitoring and Alerting in Hospitals Using AWS Lake House Architecture. Frontiers in Emerging Computer Science and Information Technology. 2, 08 (Aug. 2025), 07–14. https://doi.org/10.37547/fecsit/Volume02Issue08-02.
33. Yoon JH, Pinsky MR, Clermont G. Artificial intelligence in critical care medicine. Annual Update in Intensive Care and Emergency Medicine. 2022;353-67.
DISCOVER RELATED RESEARCH

Similar Articles

Continue exploring the collection ↗
1-10 of 598