Neoantigen × AI
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Brief · 2026-06-01

Moderna and Heterologous Platforms Show Broad Neoantigen Vaccine Efficacy

Clinical data confirms the therapeutic potential of personalized neoantigen vaccines, with Moderna showing broad efficacy and a novel heterologous adenovirus/mRNA platform demonstrating activity in metastatic solid tumors.

Simultaneously, methodological advances are addressing the translational gap: new frameworks like PimRNA integrate network biology for target prioritization, while the AOC framework quantifies the critical disconnect between in-silico AI performance and clinical outcomes.

15 items8 Clinical4 Commercial3 AI & Methods
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Clinical

Individualized, heterologous chimpanzee adenovirus and self-amplifying mRNA neoantigen vaccine for advanced metastatic solid tumors: phase 1 trial interim results - Nature

Interim results from a Phase 1 trial of an individualized, heterologous chimpanzee adenovirus and self-amplifying mRNA neoantigen vaccine show activity in advanced metastatic solid tumors. This highlights the diversification of delivery vectors beyond standard mRNA, potentially offering improved immunogenicity or manufacturing advantages.

news · 2022-08-15 · Nature
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Clinical

To Evaluate the Safety, Tolerability, and Preliminary Efficacy of XH001 Injection as Adjuvant Therapy in Patients With High-risk Recurrent Solid Tumors

Shenzhen Xinhe Biomedical has initiated a Phase 1 trial for XH001, a personalized mRNA tumor neoantigen vaccine, as adjuvant therapy for high-risk recurrent solid tumors. This entry marks the expansion of Chinese biotech players into the personalized vaccine space, focusing on post-surgical recurrence prevention.

clinicaltrials · 2026-05-19 · Shenzhen Xinhe Biomedical
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AI / Methods

A priority index-based computational medicine framework (PimRNA) for prioritising personalised mRNA cancer vaccines

Researchers present PimRNA, a computational framework that prioritizes personalized mRNA vaccines by integrating neoantigen identification with gene interaction network analysis. This addresses a key translational gap by moving beyond simple HLA binding affinity to consider biological context and mRNA design constraints like codon usage.

biorxiv · 2026-05-29 · Fang, H.; Tan, T.
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AI / Methods

Quantifying AI-to-Clinical Translation: The Algorithm-to-Outcome Concordance (AOC) Framework

The Algorithm-to-Outcome Concordance (AOC) framework quantifies the gap between AI biomarker performance and clinical results, finding that failed trials often have AOC <0.40. Validated across 6 neoantigen trials, this framework offers a quantitative tool for pre-trial risk assessment, addressing the high failure rate of AI-driven biomarkers in clinical translation.

arxiv · 2025-10-30 · Xiyao Yu, Kai Fu