From Spatial Biomarkers to Development Decisions
Spatial biology maps cells and their molecules in situ within intact tissue linking identity and function to precise location and nearby neighbors. The value of a spatial biomarker is not the image, it is the decision it enables.
From preclinical to clinical phases, as the biological question evolves, the mechanistic thread should remain continuous.
Download the presentation to learn how to answer key development questions including:
- Did the drug reach the tissue?
- Did it reach the right cells?
- Did the expected biology change?
- Do we progress, adapt or stratify?
From Spatial Biomarkers to Development Decisions
Spatial biology maps cells and their molecules in situ within intact tissue linking identity and function to precise location and nearby neighbors. The value of a spatial biomarker is not the image, it is the decision it enables.
From preclinical to clinical phases, as the biological question evolves, the mechanistic thread should remain continuous.
Download the presentation to learn how to answer key development questions including:
- Did the drug reach the tissue?
- Did it reach the right cells?
- Did the expected biology change?
- Do we progress, adapt or stratify?
Biodistribution Design Strategies for CNS-Targeted Oligonucleotides
Antisense oligonucleotides (ASOs) and newer conjugate modalities, antibody-oligonucleotide conjugates (AOCs) and antibody-siRNA conjugates (ARCs), are expanding treatment options for neurological disease. But route of administration changes everything about the LC-MS/MS strategy needed to support them: intrathecal (IT) dosing produces high, fast-decaying local CSF concentrations, while intravenous (IV) dosing yields much lower CNS exposure after blood-brain-barrier transcytosis, pushing sensitivity requirements to their limits.
This webinar covers how to build LC-MS/MS methods, ion-pairing reversed-phase and hybridization LC-MS/MS, for primary PK quantification across CSF, plasma, and tissue, including how to independently track intact conjugate, free oligonucleotide payload, and antibody component as distinct PK analytes.
What you’ll learn:
- How IT vs. IV dosing shifts expected Cmax, dynamic range, and LLOQ requirements
- Ion-pairing reversed-phase LC-MS/MS method development for oligonucleotides
- When to use hybridization LC-MS/MS for low-abundance targets
- Quantifying intact AOC/ARC conjugate, free payload, and antibody as distinct PK analytes
- Matrix considerations for CSF, plasma, and tissue with limited sample volume
Rethinking Biomarker Strategies for Antibody–Drug Conjugates
Antibody–drug conjugates (ADCs) have transformed oncology and represent one of the fastest-growing therapeutic modalities in cancer drug development. Advances in antibody engineering, linker chemistry and payload design have expanded the clinical success of ADCs, leading to numerous approvals and a rapidly growing development pipeline. Yet despite these advances, predicting which patients will respond remains a major challenge.
Historically, biomarker strategies have focused on target expression. While antigen expression is essential for ADC binding, recent studies consistently show that it does not fully explain therapeutic outcome. Tumors with similar antigen expressions frequently exhibit markedly different responses, suggesting that additional biological mechanisms determine productive ADC activity.
This white paper explores how biomarker strategies for ADCs are evolving from isolated measurements toward integrated biological evidence. Rather than presenting individual technologies, it illustrates how spatially connecting drug distribution, target engagement, pharmacodynamic response, and tumor microenvironment can identify the biological bottlenecks driving sensitivity or resistance and ultimately support development decisions across preclinical and clinical programs.
Download the white paper to learn more.
From Manual Analysis to Scalable Biomarker Workflows
As biomarker studies increase in size and analytical complexity, high-performing analytical methods must also be executed
consistently, reproducibly and efficiently across increasing numbers of samples and studies.
Traditional workflows based on manually coordinated Bash, R or Python scripts can be effective for small or isolated projects.
At production scale, however, operators must coordinate software dependencies, parallel execution, intermediate files, failures
and computational resources. This increases hands-on effort and the risk of inconsistent processing, limited traceability and
unnecessary recalculation
Aliri optimizes workflow scalability using Nextflow to automate and standardize key steps of analytical pipelines. The results?
- Less Manual Intervention
- Consistent Execution
- Faster Cohort Processing
- Improved Traceability
- Scalable Biomarker Analysis
Download the case study to learn how to spend less time coordinating execution and troubleshooting individual runs and more time on data quality, biological interpretation and scientific decision-making.
Case Study: From Divergent Calibration Curves to 100% Sample Acceptance - ASO Quantitation
A sponsor developing a 17-mer 2’-MOE antisense oligonucleotide (ASO) needed a qualified bioanalytical method to quantify drug levels not only in cerebrospinal fluid, but in brain and spinal cord tissue homogenate matrices that are notoriously difficult for oligonucleotide LCMS work.
Rather than treating the divergence as an instrument or suppression problem by default, Aliri scientists systematically ruled out the
more common explanations and evaluated two extraction chemistries in parallel:
- Liquid-liquid extraction (LLE)
- Phenyl SPE with TEAA/DIPEA chemistry
Download the case study to view the results.
High-Throughput LC-HRMS Method for the Quantitation of 20 Bile Acids in Human Serum and Urine
Bile acids are commonly extracted from complex biological samples with methanol -based extraction procedures. However, with these simple extraction procedures, numerous reports have found that accumulating lipids on the analytical column interferes with LC/MS analyses of bile acids. In our experience, these adverse effects included increasing column backpressure, retention time drift and peak shape broadening over multiple injections. In lieu of employing an alternative offline solid -phase extraction (SPE) cleanup, we investigated several column chemistries and mobile phase combinations in conjunction with the simple protein precipitation extraction.
Download the poster to learn how Aliri approached the quantitation of 20 bile acids in human serum and urine.
Single Clinical Trial Strategy to Accelerate your Drug’s Path to Market
Recent FDA discussions surrounding plausible mechanism and confirmatory evidence frameworks reflect this broader shift. Increasingly, translational success may depend not only on demonstrating that a therapy produced a measurable effect, but also on confirming how that effect emerged within intact biological systems. FDA guidance and recent regulatory discussions increasingly reference mechanistic, pharmacodynamic, and target engagement evidence as important components of confirmatory evidence frameworks.
As spatial biology moves closer to regulated translational and clinical development environments, the challenge is no longer simply generating more molecular data. The next phase of the field will depend on the ability to generate biologically coherent, reproducible, scalable, and clinically actionable mechanistic evidence.
Download the white paper to learn how spatial biology can support the FDA’s Evolving Confirmatory Evidence Framework.
A Spatial PK/PD Framework to Predict ADC Response in Solid Tumors
Antibody-drug conjugates achieve therapeutic activity only when payload delivery, target accessibility, and microenvironmental readiness align within tumor tissue. Conventional biomarkers capture isolated components of this biology but fail to resolve the spatial coordination that ultimately governs pharmacodynamic activity.
To address this gap, we developed a translational spatial PK/PD framework integrating MSI, spatial proteomics/transcriptomics, and multiplex tissue imaging to spatially interpret coordinated ADC activity within solid tumors
Download the poster, recently presented at EACR 2026 in Budapest, Hungary to learn more.
Qualification of Translational Spatial Biomarker Panel to Enable Predictive Tissue Profiling in Oncology Drug Development
Spatial biology technologies are transforming translational oncology by enabling high-resolution characterization of tumor–immune ecosystems. However, the clinical utility of spatial biomarkers remains limited by a lack of standardized, qualified panels capable of generating reproducible and decision-enabling data across studies. To address this gap, we developed a framework for the qualification of translational spatial biomarker panels designed to support drug development and clinical trial biomarker strategies. By integrating multiplex immunofluorescence, digital pathology, and AI-assisted image analysis, our objective was to establish reproducible workflows capable of generating biologically relevant and analytically robust spatial biomarkers suitable for translational oncology applications.
Download the poster, recently presented at EACR 2026 in Budapest, Hungary to learn more.