Global seroprevalence of neutralizing antibodies against adeno-associated virus serotypes used for human gene therapies.

Adeno-associated virus (AAV) vectors are promising gene therapy candidates, but pre-existing anti-AAV neutralizing antibodies (NAbs) pose a significant challenge to successful gene delivery. Knowledge of NAb seroprevalence remains limited and inconsistent. We measured activity of NAbs against six clinically relevant AAV serotypes across 10 countries in adults (n = 502) and children (n = 50) using a highly sensitive transduction inhibition assay. NAb prevalence was generally highest for AAV1 and lowest for AAV5. There was considerable variability across countries and geographical regions. NAb prevalence increased with age and was higher in females, participants of Asian ethnicity, and participants in cancer trials. Co-prevalence was most frequently observed between AAV1 and AAV6 and less frequently between AAV5 and other AAVs. Machine learning analyses revealed a unique clustering of AAVs that differed from previous phylogenetic classifications. These results offer insights into the biological relationships between the immunogenicity of AAVs in humans beyond that observed previously using standard clades, which are based on linear capsid sequences. Our findings may inform improved vector design and facilitate the development of AAV vector-mediated clinical gene therapies.

Using large language models for safety-related table summarization in clinical study reports.

Objectives: The generation of structured documents for clinical trials is a promising application of large language models (LLMs). We share opportunities, insights, and challenges from a competitive challenge that used LLMs for automating clinical trial documentation. Materials and Methods: As part of a challenge initiated by Pfizer (organizer), several teams (participant) created a pilot for generating summaries of safety tables for clinical study reports (CSRs). Our evaluation framework used automated metrics and expert reviews to assess the quality of AI-generated documents. Results: The comparative analysis revealed differences in performance across solutions, particularly in factual accuracy and lean writing. Most participants employed prompt engineering with generative pre-trained transformer (GPT) models. Discussion: We discuss areas for improvement, including better ingestion of tables, addition of context and fine-tuning. Conclusion: The challenge results demonstrate the potential of LLMs in automating table summarization in CSRs while also revealing the importance of human involvement and continued research to optimize this technology.

Artificial Intelligence for Pharma: Time for Internal Investment.

Artificial intelligence (AI) has achieved human-level capabilities and continues to rapidly improve. For the pharmaceutical industry, AI can improve decision-making and transform the quest for better medicines. The keys are investing in data management and in internal AI talent who can create value by leveraging corporate data to tackle crucial business problems.

CATO: The Clone Alignment Tool.

High-throughput cloning efforts produce large numbers of sequences that need to be aligned, edited, compared with reference sequences, and organized as files and selected clones. Different pieces of software are typically required to perform each of these tasks. We have designed a single piece of software, CATO, the Clone Alignment Tool, that allows a user to align, evaluate, edit, and select clone sequences based on comparisons to reference sequences. The input and output are designed to be compatible with standard data formats, and thus suitable for integration into a clone processing pipeline. CATO provides both sequence alignment and visualizations to facilitate the analysis of cloning experiments. The alignment algorithm matches each of the relevant candidate sequences against each reference sequence. The visualization portion displays three levels of matching: 1) a top-level summary of the top candidate sequences aligned to each reference sequence, 2) a focused alignment view with the nucleotides of matched sequences displayed against one reference sequence, and 3) a pair-wise alignment of a single reference and candidate sequence pair. Users can select the minimum matching criteria for valid clones, edit or swap reference sequences, and export the results to a summary file as part of the high-throughput cloning workflow.

miRNA Alterations Modify Kinase Activation In The IGF-1 Pathway And Correlate With Colorectal Cancer Stage And Progression In Patients.

Investigation of therapy naïve human tumor and adjacent normal tissue biopsies demonstrated that expression levels of miRNAs are altered at and between stages of CRC. Targets of these altered miRNAs are members of the Insulin signaling pathways. Phosphorylation states of several molecules in the Insulin signaling pathways were altered between stages of CRC, and significantly the change in molecular phosphorylation state correlated with decreases in specific miRNAs that target them. This data establishes a direct relationship between decreased expression of specific miRNAs and increased phosphorylation events in the IGF-1 pathway and identifies the IGF-1 pathway as a critical driver of colorectal cancer.The expression levels of 319 miRNAs and phosphorylation levels of major signaling proteins were determined. Interestingly, we observed that miRNAs were altered in expression and several signaling molecules were altered in phosphorylation levels at and between each stage of CRC. Furthermore, many of the miRNAs that are differentially expressed at each CRC stage were targeting these same signaling proteins identified to be altered in phosphorylation level. Thus, our studies define a subset of important miRNAs to classify CRC stage and a relationship between miRNA depression and elevated phosphorylation of IGF-1R pathway signaling molecules.

ERK activation by GM-CSF reduces effectiveness of p38 inhibitor on inhibiting TNFalpha release.

Tumor necrosis factor alpha (TNFalpha), a pro-inflammatory factor, plays an important role in many inflammatory diseases. Inhibition of p38 is being pursued as a pharmaceutical treatment to reduce TNFalpha release. Since a variety of cytokines and factors may exist at different amounts in patients, we explored how differences in the cytokine environment impact p38 inhibitor potency. Cytokine co-stimulation with LPS was compared against LPS stimulation alone. In both differentiated U937 cells and peripheral monocytes, GM-CSF co-stimulation with LPS increased TNFalpha release and led to an increased residual TNFalpha levels with p38 inhibitor. Adding MEK inhibitor in the presence of p38 inhibitor further reduced TNFalpha release suggesting that the ERK pathway plays a role in GM-CSF induced reduction of the p38 inhibitor potency. When cells were stimulated with different concentrations of LPS and GM-CSF, the minimal TNFalpha level obtained by MEK inhibitor was not dependent on the stimulation condition; while it was dependent on GM-CSF level for p38 inhibitor. TNFalpha release in the presence of combinations of p38 and MEK inhibitors under different stimulation conditions was measured. A linear model was created using the initial relative ERK and p38 phosphorylation levels and p38 and MEK inhibitor concentrations to accurately predict released TNFalpha level, suggesting these four parameters are sufficient to predict TNFalpha levels. We then used the model to show that with same TNFalpha levels, higher ERK pathway activity reduces p38 inhibitor potency. These results suggest that p38 inhibitor will be a more potent anti-TNFalpha therapy for patients with low ERK pathway activity.

Cellular imaging predictions of clinical drug-induced liver injury.

Drug-induced liver injury (DILI) is the most common adverse event causing drug nonapprovals and drug withdrawals. Using drugs as test agents and measuring a panel of cellular phenotypes that are directly linked to key mechanisms of hepatotoxicity, we have developed an in vitro testing strategy that is predictive of many clinical outcomes of DILI. Mitochondrial damage, oxidative stress, and intracellular glutathione, all measured by high content cellular imaging in primary human hepatocyte cultures, are the three most important features contributing to the hepatotoxicity prediction. When applied to over 300 drugs and chemicals including many that caused rare and idiosyncratic liver toxicity in humans, our testing strategy has a true-positive rate of 50-60% and an exceptionally low false-positive rate of 0-5%. These in vitro predictions can augment the performance of the combined traditional preclinical animal tests by identifying idiosyncratic human hepatotoxicants such as nimesulide, telithromycin, nefazodone, troglitazone, tetracycline, sulindac, zileuton, labetalol, diclofenac, chlorzoxazone, dantrolene, and many others. Our findings provide insight to key DILI mechanisms, and suggest a new approach in hepatotoxicity testing of pharmaceuticals.