Nelson Dusetti: The applicability of our signatures in predicting treatment sensitivity and resistance in PDAC patients
Nelson Dusetti, Scientific Director of the company Predicting Med(CSO) and Chair of TRANSLATE-IT CRCM, shared an article by N. Fraunhoffer on LinkedIn:
“Our Reply to the Letter to the Editor has been published in Annals of Oncology!
We are thrilled that the main article, “Development and validation of artificial intelligence-assisted transcriptomic signatures to personalize adjuvant chemotherapy in patients with pancreatic ductal adenocarcinoma,” has garnered such significant attention and feedback within the scientific community. This is the second letter to the editor we have responded to, underscoring the impact of our work in tailoring treatments for pancreatic cancer.
In this response, we highlight the substantial advantages that our AI algorithms, including LASSO and Random Forest, bring to the robustness and accuracy of our transcriptomic signatures. These algorithms enable penalized feature selection with double cross-validation, enhancing the model’s predictability while avoiding issues like overfitting and multicollinearity common in high-dimensional data. Additionally, the model gains greater interpretability, which is essential for clinical application, and has demonstrated significant transferability across independent cohorts.
This work reinforces the applicability of our signatures in predicting treatment sensitivity and resistance in PDAC patients, and we are grateful for the community’s engagement. We are committed to advancing this critical area of clinical research.”
Author: N. Fraunhoffer, et al.
Nelson Dusetti is a Scientific Director of the company Predicting Med (CSO) and Chair of TRANSLATE-IT CRCM. He is also research director at INSERM. He is the Head of the Department of Translational Research and Innovative Therapies at CRCM.
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