PubMed · 12018063
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R Nelson. Trials & errors.. https://pubmed.ncbi.nlm.nih.gov/12018063/
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Personalized neoantigen cancer vaccine is a promising strategy for precision immunotherapy by targeting patient-specific and mutation-derived tumor antigens. Early clinical studies have demonstrated the feasibility, safety, and immunogenicity of these vaccines across multiple solid tumors, with encouraging outcomes particularly when combined with immune checkpoint blockade. However, broader clinical translation remains limited by sequential bottlenecks across the vaccine development pipeline, including false-positive neoantigen selection,  imperfect modeling of antigen processing and HLA presentation, limited prediction of T-cell receptor recognition, and challenges in formulation, delivery, and manufacturing. Artificial intelligence and advanced computational workflows are increasingly integrated into this pipeline to improve candidate prioritization and support more reproducible decision-making. In this review, we summarize clinical progress and key translational barriers in personalized neoantigen vaccination, and discuss how AI-enabled approaches may contribute across four major stages: multi-omics integration for neoantigen discovery, processing-aware HLA presentation prediction, structure-aware and TCR-informed immunogenicity modeling, and data-driven formulation optimization, particularly for lipid nanoparticle-based delivery systems. These approaches are able to help narrow biological and chemical search spaces, improve prioritization, and provide mechanistic insights into antigen presentation and immune recognition rather than replacing experimental validation. This articlefurther addresses future implementation challenges, including dataset diversity, model interpretability, prospective benchmarking, manufacturing traceability, and evolving regulatory frameworks for individualized mRNA cancer immunotherapies. Integrating computational innovation with rigorous immunological validation, scalable manufacturing, and regulatory oversight will be essential for advancing personalized neoantigen vaccines toward broader clinical implementation.
Nanovaccines co-assemble antigens and adjuvants to elicit robust immune responses but often require complex synthesis and post-modification procedures. Here, a programmable nanovaccine platform based on the M13 bacteriophage is developed for the scalable production of vaccines and single-step modular engineering of adjuvanticity, length, and antigen density. By reprogramming the sequence and size of the noncoding phage genome, the Toll-like receptor 9 activation and the length of the phage are precisely controlled. With a novel molecular engineering approach, the antigen density is tuned from 13.6% to 70.3%. A systematic modulation reveals an optimal adjuvanticity at a constant antigen density for maximum anti-tumor CD8+ T cell response, and vice versa, using the model antigen SIINFEKL. The M13 phage-based nanovaccine induces durable memory immunity lasting over a year. In addition, a 24-fold increase in neoantigen-specific CD8+ T cell frequency is achieved when increasing both the adjuvanticity and antigen density. Furthermore, when combined with anti-PD-1 therapy, the M13 phage-based personalized vaccine eradicates established MC-38 tumors in 75% of treated animals and they develop 100% resistance against tumor invasion when challenged 5 months after treatment. These findings establish M13 phage as a powerful and versatile nanovaccine platform with transformative potential for personalized cancer immunotherapy.
Analyses of crude samples from biotechnology processes are often required in order to demonstrate that residual host cell impurities are reduced or eliminated during purification. In later stages of development, as the processes are further developed and finalized, there is a tremendous volume of testing required to confirm the absence of residual host cell proteins (HCP) and DNA. Analytical tests for these components are very challenging since (1). they may be present at levels that span a million-fold range, requiring substantial dilutions; (2). are not a single component, often existing as fragments and a variety of structures; (3). require high sensitivity for final steps in process; and (4). are present in very complex matrices including other impurities, the product, buffers, salts and solvents. Due to the complex matrices and the variety of potential analytes, the methods of analysis are not truly quantitative for all species. Although these limitations are well known, the assays are still very much in demand since they are required for approval of new products. Methods for final products, described elsewhere, focus on approaches to achieve regulatory requirements. The study described herein will describe the technical rationale for measuring the clearance of HCP and DNA in the entire bioprocessing to purification from an Escherichia coli-derived expression system. Three analytical assays, namely, reversed-phase high-performance liquid chromatography (RP-HPLC), enzyme-linked immunosorbent assay (ELISA), and Threshold Total DNA Assay, were utilized to quantify the protein product, HCP and DNA, respectively. Product quantification is often required for yield estimation and is useful since DNA and HCP results are best expressed as a ratio to product for calculation of relative purification factors. The recombinant E. coli were grown to express the protein of interest as insoluble inclusion bodies (IB) within the cells. The IB were isolated by repeated homogenization and centrifugation and the inclusion body slurry (IBS) was solubilized with urea. After refolding the product, the solution was loaded on several commonly used ion exchangers (CM, SP, DEAE, and Q). Product was eluted in a salt gradient mode and fractions were collected and analyzed for product, HCP and DNA. The IBS used for this study contained about 15 mg/ml product, 38 mg/ml HCP and 1.1 mg/ml DNA. Thus, the relative amounts of HCP and DNA in the IBS was excessive, and about 10(3) times greater than typical (because the cells and IB were not processed with the normal number of washing steps during isolation). This was of interest since similar samples may be encountered when working with non-inclusion body systems, such as periplasmic expressions, or in cases where the upstream unit operations under-perform in IB cleaning. The study described herein describes the development of three robust methods that provide the essential process data needed. These findings are of general interest to other projects since applications of similar analytical technology may be used as a tool to develop processes, evaluate clearance of impurities, and produce a suitable product.