Revolutionizing Bioanalysis: Harnessing AI for Enhanced Precision, Insights, and Efficiency
Does AI have a place in bioanalysis? We say YES!
In this session, tenured biomarker expert, Corinne Ramos, Phd, R&D Director at Aliri Bioanalysis, and Stephanie Papas-Farmer, PhD, President and Founder of BioData Solutions, share an overview of the state of AI in the drug development landscape, and real, data-backed bioanalytical applications for this powerful tool. Join us to explore how the power of AI in conjunction with genomic, proteomic, and metabolomic analyses can help predict the effectiveness of immunotherapies at an early stage in the drug development process, well before traditional methods would allow.
Watch the full-length recording below and reach out to learn how Aliri can enhance your drug development program and help you predict the effectiveness of immunotherapies earlier.
Validation of an LCMS Hybrid Assay with EVOSEP Cleanup for the Quantitation of Islet Amyloid Polypeptide in Human Plasma
Islet Amyloid Polypeptide (IAPP) is a peptide hormone produced by the pancreas’ beta cells that regulates blood glucose. Research on IAPP and its role in diabetes is ongoing, and there is a need for a reliable method to accurately detect this hormone at clinically relevant levels and possibly the different forms of the peptide. We set out to validate a hybrid LCMS assay for this biomarker that could be validated to an appropriate level to support clinical studies.
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Validated Biomarker Assay for the Analysis of Coproporphyrin I and Coproporphyrin III in Human Plasma
Coproporphyrin I (CP‐I) and Coproporphyrin III (CP‐III) are potential endogenous biomarkers for hepatic organic anion transporting polypeptide (OATP)1B1/1B3 function. We developed and validated a bioanalytical assay for monitoring these biomarkers to assess OATP1B1/1B3 inhibition in place of a standalone prospective clinical drug-drug interaction (DDI) study. Currently, investigational drugs that alter the pharmacokinetics of other medications are subject to additional testing to understand how to manage a DDI risk safely. By monitoring the effect of an investigation drug on the levels of these endogenous substrates of OATP1B1/1B3 in early clinical development, the potential need for a dedicated clinical DDI study could be avoided.
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Quantifying and Mapping ATP Distribution Within Tissues to Inform Targeted Therapeutic Strategies in Drug Development
ATP levels, as indicators of cellular metabolic activity, offer critical insights into the viability and growth dynamics of tumor cells, presenting potential targets for therapeutic strategies. The aim of this study is to explore how ATP distribution and quantification across various mouse tumor models can optimize drug development approaches. For this purpose, we utilized Quantitative Mass Spectrometry Imaging (QMSI) to measure ATP levels in different mouse models, determining the most suitable model for targeted drug development.
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Integrating Omics Data Through AI Predicting Novel Therapeutic Targets for Therapy-Resistant Cancer Patients
Artificial intelligence (AI) is transforming biomedicine by facilitating the thorough analysis of multi-omics data, thereby deepening our grasp of intricate biological systems and the underlying mechanisms of diseases. Our study leverages AI to synthesize diverse omics datasets— including genomics, proteomics, and metabolomics—with the goal of identifying novel therapeutic targets for cancer patients resistant to current treatments. This strategy is designed to enhance the development of personalized medicine and refine treatment approaches, offering new avenues for addressing complex medical challenges.
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Exploring the Spatial Distribution of mRNA-Lipid Nanoparticles in Mouse Whole-Body and Isolated Organs Using MALDI MSI
To investigate the biodistribution and potential toxicity of lipid nanoparticles (LNP1 and LPN2), which are crucial carriers for mRNA-based treatments after administration to male and female mice, by analyzing their distribution in whole-body carcasses and specific organs using MALDI-MSI.
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Elucidating the Role of IL-18 in NSCLC Integrated Analysis through Imaging Mass Cytometry, Mass Cytometry, and Single-Cell Sequencing
Interleukin-18 (IL-18) plays a pivotal role in nonsmall cell lung cancer (NSCLC) progression, influencing both tumor growth and immune response dynamics. Recent insights into the heterogeneity and functional status of tumorinfiltrating T cells have underscored their critical impact on antitumor immunity and responses to immunotherapy, paralleling the observed complexity in IL-8 interactions within the tumor microenvironment. This study employs Imaging Mass Cytometry (IMC), Mass Cytometry (CyTOF), and Single-Cell RNA Sequencing (scRNA-seq) to map IL-18 expression, explore its impact on immune cell subsets, and identify its role in the tumor microenvironment
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Distribution of Standard-of-Care Antituberculosis Drugs in Cynomolgus Macaque Lungs
The non-human primate (NHP) provides the most clinically relevant model of human tuberculosis. The aim of this study was to determine the tissue pharmacokinetics of orally delivered isoniazid (H), rifampicin (R), pyrazinamide (Z) and ethambutol (E) combination therapy (HRZE) in the lung of cynomolgus macaques to prepare following studies in Mycobacterium tuberculosis-infected animals usinq QMSI.
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Development of Quantitative MALDI Mass Spectrometry Imaging Methods for Studying Distribution of Antituberculosis Drugs at their Site of Action
Tuberculosis (TB), caused by Mycobacterium tuberculosis (MTb), remains a global health challenge, with treatment involving a year-long regimen of four drugs: Isoniazid, Rifampicin, Pyrazinamide, and Ethambutol. However, the emergence of drug resistance calls for the development of new therapeutic molecules. Due to the complex granulomatous lesions formed by MTb, plasma drug concentrations often do not reflect tissue drug levels, making it crucial to assess drug exposure at the site of action. To address this, we have developed Mass Spectrometry Imaging (MSI) methods to study the distribution of anti-TB drugs and their metabolites, including pyrazinoic acid, across both healthy and diseased tissues.
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Development of a Mitra Tip Extraction Assay Coupled with LC-MSMS
Biomarkers such as L-Citrulline, L-Arginine, and L-Argininosuccinic Acid play crucial roles in various physiological processes and pathological conditions. However, their accurate quantitation presents challenges due to sample complexity and low concentrations. Here, we present a novel approach utilizing Mitra tip extraction coupled with liquid chromatography-tandem mass spectrometry (LC-MS/MS) for the simultaneous quantitation of these biomarkers. Mouse models are known to produce small blood volumes while Mitra tips offer advantages in sample collection, allowing for convenient and reproducible extraction from biological matrices.
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