BY HANNAH SHEEHAN, PH.D. CEO SAUVEBIO
In the world of preclinical development of advanced modalities such as gene therapies, cell therapies, and complex biologics, the in vivo phase is often the most resource-intensive part of the journey.
Working with a premier partner like Biomere ensures that your in vivo studies are executed with precision to generate meaningful go/no-go data. Whether it is a rodent PK study or a complex AAV biodistribution program, in vivo studies provide critical input to making decisions. As consultants and scientific partners, we at SauveBio often see a critical gap in the Discovery studies to understand mechanism of action, efficacy and early toxicology. Too often, researchers take precious, high-value tissue samples that have been exposed to a novel therapy and subject them to “bulk” analysis. They grind up a lymph node or a tumor and look at the average gene expression but there is a problem. Biology doesn’t happen in averages; it happens in specific cells.
This is where the partnership between Biomere’s in vivo excellence and SauveBio’s advanced cell sorting capabilities becomes a force multiplier for your data package. By physically isolating specific cell populations from treated animal model samples before downstream analysis, we turn a standard safety study into a goldmine of mechanistic insight. Here are three scenarios where integrating SauveBio’s sorting expertise into your in vivo PK study design is not a nice to have, but is a necessity.
1. The “Needle in the Haystack”: Isolating Rare Immune Subsets
The Problem:
In many immunology and oncology studies, the cells that actually mat- ter (the tumor-infiltrating lymphocytes (TILs) or specific memory B-cells) comprise less than 1% of the total tissue. If you perform bulk RNA sequencing on a whole tumor biopsy, the signal from these rare cells is drowned out by the noise of millions of structural cells and necrotic debris. You might miss a subtle but critical immune response simply because the signal was diluted
The Solution:
SauveBio works with Biomere to receive fresh tissue suspensions imme- diately following necropsy. Using multi-parametric Fluorescence-Activat- ed Cell Sorting (FACS), we can physically sort out that 0.1% popula- tion of specific T-cells into a tube. When you sequence that tube, you aren’t looking at an average; you are looking at a pure, concentrated signal that provides detailed data on the cell type that matters.
2. Protecting Your Genomics Investment: “Garbage In, Garbage Out”
The Problem:
Single-cell RNA sequencing (scRNA-seq) has revolutionized how we understand drug toxicity and efficacy. However, it is also incredibly expensive. The quickest way to burn through a budget is to feed a commercially available chip with dead cells or debris. When tissues are dissociated (especially tough tissues like lung or NHP brain), cell viability often drops. If you load this raw mixture into a sequencer, a good amount of the data may not be usable.
The Solution:
SauveBio acts as the quality control gatekeeper. We employ “Live/ Dead” sorting strategies to remove dead cells and debris, delivering a suspension of high-viability, single cells to the genomics facility. This ensures that every dollar you spend on sequencing yields high-quality data, maximizing the ROI of the in vivo study.
3. Validating the Vector: GFP+ vs. The Bystanders
The Problem:
In AAV gene therapy or CRISPR editing studies, “transduction efficiency” is a key endpoint and it is important to know which cells actually received the therapy. Established PCR methods tells you how many vector copies are in the tissue on average, but it doesn’t tell you if the therapy changed the phenotype of the cells receiving the gene modification therapy.
The Solution:
If your vector includes a reporter (like GFP), SauveBio can sort the sample into two distinct populations: the “GFP-Positive” cells (those that got the drug) and the “GFP-Negative” cells (the bystanders). By analyzing these two groups separately, you can definitively prove that phenotypic changes, like the downregulation of a disease marker, are directly linked to your therapy, rather than just general environmental changes.
In summary, the partnership between Biomere and Sauve combines physiological context and cellular resolution. Your preclinical samples are too valuable to waste on low-resolution data so by integrating high-end cell sorting into your workflow, you ensure that you are seeing every single tree in the forest.
