Utilize real-world data and AI to advance the research and treatment of benign prostate hyperplasia
Benign prostate hyperplasia (BPH) is one of the most common urological conditions that affect men with age, with nearly 50% of men suffering from symptoms. Despite its prevalence, treatment pathways are still complex and require a nuanced understanding of disease progression, patient responses, and realistic treatment patterns.
Traditional clinical trials provide valuable insights, but they are often limited by scope and may not fully capture the multiple experiences of patients in conventional clinical settings. This is where real-world data (RWD) and advanced artificial intelligence (AI) technologies play a transformative role.
The power of real-life data in urology research
Real-world data – derived from a variety of healthcare sources including electronic health records (EHR), medical claims and genomics – provides a comprehensive view of disease trends, treatment outcomes and patient experience outside of the controlled environment of clinical trials. For BPH, RWD can help life science companies and clinicians understand the realistic effectiveness of different treatment options, from medications to minimally invasive surgical treatments.
To be truly useful, well-planned realistic data must be of high quality, suitable, and tailor-made to its intended use. This allows researchers to gain a deeper understanding of disease progression and patient outcomes, such as tracking PSA levels and symptom scores under conditions such as BPH.
By leveraging de-identified EHR data, life science companies can identify trends in disease progression, identify subpopulations of patients most likely to benefit from specific interventions, and refine treatment guidelines to reflect real-world experiences. Additionally, RWD can be conducted longitudinal studies to track patient outcomes over time, leading to insight into treatment durability and the potential for disease recurrence.
AI-driven insights: Turning RWD into actionable knowledge
Despite the huge commitment of RWD, its massive volume and complexity require advanced analytical tools to extract meaningful insights, namely, practical evidence (RWE). AI, especially machine learning models, enhances the ability to process and analyze large-scale datasets to identify patterns from traditional analytics that may not be immediately apparent.
AI-driven models can standardize and bring structure to unstructured clinical notes, ensuring consistency in data interpretation. For example, natural language processing techniques can extract relevant clinical details from clinician notes, thereby expanding the breadth of available data for analysis. In addition, AI-driven analyses can stratify patients based on the severity of the disease, comorbidities, and treatment response, ultimately supporting personalized medical approaches in BPH management.
Enhance research and treatment decisions
The integration of RWD and AI is of great significance to clinical research and patient care. For life science companies and medical device manufacturers, access to powerful real-world datasets can enable more efficient research design, enhanced post-market surveillance efforts, and support regulatory submissions with RWE. For clinicians, AI-enhanced RWD insights can inform shared decisions to ensure treatment recommendations are consistent with real-world patient experiences and outcomes.
Furthermore, by leveraging de-identified RWDs in privacy-protected environments, researchers can perform retrospective analysis to assess the safety and effectiveness of long-term treatments without the time and expense associated with traditional prospective studies.
The future of RWD and AI-driven
The synergistic effect between RWD and AI is critical to shaping the future of urological research and patient care. The ability to leverage real-world insights at scale allows life science companies and clinicians to develop more targeted therapies that improve patient outcomes and drive evidence-based innovation in BPH treatment.
By embracing the power of security, advanced AI technology and real-world data, we can get closer to a healthcare ecosystem that is more predictive, personalized and impactful for BPH and beyond.
Photo: Nevarpp, Getty Images
Sujay Jadhav is CEO of Verana Health, who is helping accelerate company growth and sustainability by advancing clinical trial capabilities, data services, medical association partnerships and data abundance.
Sujay has over 20 years of experience as experienced executives, entrepreneurs and global business leaders along with Verana Health. Most recently, Sujay was the global vice president of Oracle’s health science business unit, operating throughout the organization’s entire product and engineering team. Prior to Oracle, Sujay was CEO of Gobalto, a cloud-based clinical research platform, who was responsible for Oracle’s acquisition of the company. Sujay is also the former executive of Life Sciences Technology Company N Model N Model, who helped oversee its transition to a public company.
Sujay holds an MBA from Harvard University and receives a bachelor’s degree in electronic engineering from the University of South Australia.
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