From:  Dissecting the link between PD-1/PD-L1-based immunotherapy and cancer pain: mechanisms, research implications, and artificial intelligence perspectives

Research challenges and perspectives

TargetNeedFuture directions
Clinical implications and challengesPD-1/PD-L1-based immunotherapy presents challenges in managing cancer-related pain and requires attention from healthcare providers.Developing targeted pain management strategies to improve patient care
Patient monitoring and feedback are crucial for adjusting pain management strategies in real-time.PROMs, PROs, and PREMs to gather data on patient experiences and outcomes
Ameliorate diagnosis of pain phenomena (e.g., neuropathic pain)Fostering collaboration across multidisciplinary teams to address pain management challenges
Preclinical researchMechanisms through which PD-L1/PD-1 immunotherapy modulates painDeveloping ad hoc pain models
Exploring the intersection of analgesic pathways and chronic pain processes
Identifying specific mechanisms and biomarkers to guide targeted pain management
Clinical researchThe link between immunotherapy and pain conditionsComprehensive data collection, longitudinal studies EBM analyses
Artificial intelligence

Artificial intelligence can be used to:

  • analyze large datasets, such as patient records and genomic data, to identify patterns and correlations between immunotherapy and pain;

  • identify potential biomarkers and risk factors for pain-related complications;

  • molecular docking;

  • assess risk and aid in tailoring treatments;

  • assist in making informed decisions (clinical decision support systems);

  • simulate treatment scenarios and predict potential outcomes for improved pain management.

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Addressing ethical issues and risk of bias. PD-1/PD-L1: programmed cell death-1/programmed cell death ligand-1; PROMs: patient-reported outcome measures; PROs: patient-reported outcomes; PREMs: patient-reported experiences measures; EBM: evidence-based medicine