AI-Powered Prognostic Tool for Lung Cancer: A New Era in Personalized Oncology Care
The FDA has granted breakthrough device designation to serial CTRS, an AI-powered prognostic tool developed by onc.AI. This innovative technology aims to revolutionize the way non-small cell lung cancer (NSCLC) is treated by stratifying patients into high- or low-risk mortality categories based on thier individual characteristics and medical history.
“We are honored to be awarded breakthrough device designation for our Serial CTRS AI model,” said Akshay Nanduri, CEO of Onc.AI,in a press release. “Onc.AI aims to equip oncologists with vital, automated prognostic insights using routinely collected diagnostic imaging scans and ultimately improve treatment strategy and provide risk stratification throughout [the] journey [for a patient with cancer].” 1
How Serial CTRS Works:
Serial CTRS utilizes a deep-learning model trained on real-world datasets from patients with advanced NSCLC who received immune checkpoint inhibitor therapy. The model analyzes serial CT scans, identifying patterns and features that correlate with patient outcomes. this analysis goes beyond customary methods like manual tumor volume segmentation and RECIST 1.1 response categories, providing a more comprehensive and accurate prediction of survival.The model’s performance has been validated using additional real-world data, demonstrating superior predictive accuracy. The C-index for predicting overall survival (OS) was significantly higher with Serial CTRS (0.734) compared to RECIST (0.631) and tumor volume measurement changes (0.679). Furthermore, in patients with stable disease, Serial CTRS showed a 12-month area under the receiver operating characteristic (AUROC) curve of 0.74,outperforming tumor volume change (AUROC 0.62). 2
Benefits for Patients and Oncologists:
The potential benefits of Serial CTRS are significant for both patients and oncologists:
Personalized Treatment: By accurately predicting individual patient outcomes, Serial CTRS allows oncologists to tailor treatment plans to each patient’s unique needs and risk profile. This personalized approach can lead to more effective treatment strategies and improved patient outcomes.
Early Intervention: Serial CTRS can identify patients at high risk of poor outcomes early on, allowing for timely interventions and potentially improving survival rates.
Reduced Healthcare Costs: By optimizing treatment strategies and avoiding unneeded interventions for low-risk patients, Serial CTRS can potentially reduce healthcare costs associated with unnecessary treatments.
The Future of AI in Oncology:
Serial CTRS represents a significant step forward in the application of AI in oncology. As AI technology continues to advance, we can expect to see even more refined tools that will further personalize cancer care and improve patient outcomes.
Jacqueline law, Vice President of Corporate Strategy at Flatiron Health, highlighted the importance of real-world data in AI progress, stating, “We are thrilled to see the application of Flatiron’s high-quality, curated real-world data in the development and validation of regulatory-grade AI models for clinical use.” 1
Dwight Owen, MD, MS, Associate Professor of Medicine and Head of Thoracic Oncology at the James Cancer Center at Ohio State University, expressed his excitement for the potential of Serial CTRS, stating, “Having been involved in product definition and evaluating results throughout the evolution of this product, I look forward to seeing this breakthrough technology enter the clinic and impact early phase trials and clinical development.” 3
Conclusion:
serial CTRS is a groundbreaking development in the field of oncology, offering a powerful tool for personalized cancer care. as AI technology continues to evolve, we can expect to see even more innovative applications that will transform the way cancer is diagnosed, treated, and managed.
References:
- Onc.AI awarded FDA breakthrough device designation for Serial CT Response Score deep learning model. News release. Onc.AI. February 6, 2025. Accessed February 10, 2025. https://tinyurl.com/3a2m2hrd
- Sako C, Schmidt TG, Patel AA, et al. Deep learning serial CT response score predicts overall survival in advanced NSCLC treated with PD-(L)1 immune checkpoint inhibitors.
J Immunother Cancer*. 2024;12(suppl 2):1237. doi:10.1136/jitc-2024-SITC2024.1237
- Onc.AI Serial Imaging Response Score outperforms traditional methods for early assessment of NSCLC immunotherapy outcomes. News release. Onc.AI.november 6, 2024. Accessed February 10, 2025. https://tinyurl.com/3rmsfnr8
AI Predicts Lung Cancer Outcomes: A Conversation with Time.news
Time.news Editor: We’re excited to talk today about the groundbreaking AI tool, Serial CTRS, which has just received breakthrough device designation from the FDA for its potential in personalized lung cancer treatment.
Future Oncology expert: It’s a very exciting time in oncology! This AI-powered prognostic tool has the potential to revolutionize how we approach non-small cell lung cancer (NSCLC) treatment.
time.news Editor: Can you explain how Serial CTRS works and what makes it so different from existing methods?
Future Oncology Expert: Absolutely. Serial CTRS uses a deep-learning model trained on real-world patient data, specifically focusing on advanced NSCLC patients treated with immune checkpoint inhibitor therapy. It analyzes serial CT scans, looking for patterns and features that correlate with patient outcomes.
unlike customary methods that rely solely on tumor volume measurements or RECIST 1.1 response categories,Serial CTRS offers a more comprehensive analysis. It’s shown to significantly outperform these methods in predicting overall survival, even in patients with stable disease.
Time.news Editor: This sounds incredibly promising. What specific benefits does this bring to patients and oncologists?
Future Oncology Expert: Well, imagine knowing exactly how a patient’s cancer is likely to progress. Serial CTRS provides that personalized insight. Oncologists can use this information to tailor treatment plans, choosing the most effective approach for each individual patient. This personalized approach has the potential to improve treatment outcomes and perhaps extend survival rates.
Moreover, Serial CTRS can help identify patients at high risk early on, allowing for timely interventions.
Time.news Editor: Are there any potential implications for healthcare costs?
Future Oncology Expert: Absolutely. By optimizing treatment strategies and avoiding unnecessary interventions for low-risk patients, Serial CTRS has the potential to reduce healthcare costs associated with overly aggressive treatments.
Time.news Editor: The article mentions Real-World Data (RWD) playing a crucial role. Why is that so crucial for AI development in oncology?
Future Oncology Expert: Real-world data is absolutely essential. AI models learn from the vast amounts of patient information contained in RWD. this real-world context helps ensure the AI tool accurately reflects the complexities of cancer and individual patient characteristics.
Time.news Editor: Looking ahead, what’s the future for AI in oncology?
Future Oncology Expert: We’re at the cusp of a revolution! AI has the potential to transform every aspect of cancer care, from diagnosis to treatment and personalized monitoring. Tools like Serial CTRS are just the beginning.
I believe we’ll see even more complex AI-powered solutions emerge,ultimately leading to more precise,personalized,and ultimately,more successful cancer treatments.
Keywords: AI, Oncology, Lung Cancer, Serial CTRS, FDA Breakthrough Device, Personalized Medicine, Treatment, predictive Analytics, Deep Learning, Real-World Data, RECIST, Immune Checkpoint Inhibitors, NSCLC, Healthcare Costs.