Overview of comments received on 'ICH reflection paper on proposed ICH guideline work to advance patient focused drug development’
Stakeholder no.
Section No.
Comment and rationale
Proposed change / recommendation
Pharma companies have found ePROs as useful tools to have in their drug development. Collecting patient reported symptoms in cancer care there is possibility to create models for predictive symptom management by using machine learning and artificial intelligence. With predictive capabilities in the DHI applications patient safety, treatment tolerance and co-operation will be much improved and getting more realistic end points in trials, and also more comprehensive data about drugs under development, becomes feasible. We have published several abstracts of Kaiku´s feasibility in general use as an ePRO and also in symptom prediction with our collaborators in cancer care, ie. Patients, hospitals and pharma industry. References: 1. Basch E et al. Overall Survival Results of a Trial Assessing Patient-Reported Outcomes for Symptom Monitoring During Routine Cancer Treatment. JAMA. 2017;318(2):197. 2. Denis F et al. Two-Year Survival Comparing Web- Based Symptom Monitoring vs Routine Surveillance Following Treatment for Lung Cancer. JAMA. 2019;321(3):306–307. 3. Basch E, Deal A, Kris M, Scher H, Hudis C, Sabbatini P et al. Symptom Monitoring With Patient-Reported Outcomes During Routine Cancer Treatment: A
Overview of comments received on 'ICH reflection paper on proposed ICH guideline work to advance patient focused drug development’ (EMA/CHMP/ICH/415588/2020) EMA/194133/2021
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