Prediction of lymphoma response to CAR T cells by deep learning-based image analysis

New regulatory thinking is needed for AI-based personalised drug and cell therapies in precision oncology

Until recently the application of artificial intelligence (AI) in precision oncology was confined to activities in drug development and had limited impact on the personalisation of therapy. Now, a number of approaches have been proposed for the personalisation of drug and cell therapies with AI applied to therapy design, planning and delivery at the patient's bedside. Some drug and cell-based therapies are already tuneable to the individual to optimise efficacy, to reduce toxicity, to adapt the dosing regime, to design combination therapy approaches and, preclinically, even to personalise the receptor design of cell therapies. Developments in AI-based healthcare are accelerating through the adoption of foundation models, and generalist medical AI models have been proposed. The application of these approaches in therapy design is already being explored and realistic short-term advances include the application to the personalised design and delivery of drugs and cell therapies. With this pace of development, the limiting step to adoption will likely be the capacity and appropriateness of regulatory frameworks. This article explores emerging concepts and new ideas for the regulation of AI-enabled personalised cancer therapies in the context of existing and in development governance frameworks.

PET/CT in the Evaluation of CAR-T Cell Immunotherapy in Hematological Malignancies

Chimeric antigen receptor (CAR)-T cell-based immunotherapy has emerged as a path-breaking strategy for certain hematological malignancies. Assessment of the response to CAR-T therapy using quantitative imaging techniques such as positron emission tomography/computed tomography (PET/CT) has been broadly investigated. However, the definitive role of PET/CT in CAR-T therapy remains to be established. [18F]FDG PET/CT has demonstrated high sensitivity and specificity for differentiating patients with a partial and complete response after CAR-T therapy in lymphoma. The early therapeutic response and immune-related adverse effects such as cytokine release syndrome and immune effector cell-associated neurotoxicity syndrome can also be detected on [18F]FDG PET images. In otherwise asymptomatic lymphoma patients with partial response following CAR-T therapy, the only positive findings could be abnormal PET/CT results. In multiple myeloma, a negative [18F]FDG PET/CT after receiving B-cell maturation antigen-directed CAR-T therapy has been associated with a favorable prognosis. In leukemia, [18F]FDG PET/CT can detect extramedullary metastases and treatment responses after therapy. Hence, PET/CT is a valuable imaging tool for patients undergoing CAR-T therapy for pretreatment evaluation, monitoring treatment response, assessing safety, and guiding therapeutic strategies. Developing guidelines with standardized cutoff values for various PET parameters and tumor cell-specific tracers may improve the efficacy and safety of CAR-T therapy.