Target Validation with Perturbation
Test if your target disrupts normal B-cell differentiation before clinical investment
The Challenge
On-Target Toxicity Unknown
Your target (e.g., TARGET_A, TARGET_B) is essential for myeloma cells, but is it also required for normal plasma cell formation? Finding out in Phase I = patient safety issues and trial halts.
Tumor vs. Normal Selectivity Unclear
Tumor cell lines show your target is essential, but normal cells may have compensatory pathways. Without testing normal differentiation, therapeutic window is unknown.
Phase I Failures Due to Immunodeficiency
Many myeloma drug trials fail or require dose reduction due to hypogammaglobulinemia (loss of normal antibody production). This could be identified pre-clinically.
Expensive CRISPR Screens Miss Context
Standard CRISPR screens use tumor cell lines. They don't capture normal differentiation context—whether knocking out your target prevents healthy B-cell→plasma cell transition.
"Our TARGET_B inhibitor looked perfect in myeloma cells, but completely blocked normal plasma cell differentiation in patients. If we had tested normal B-cell differentiation in vitro first, we would have pivoted the program."
The Helomnix Solution
Helomnix performs CRISPR knockout or drug perturbation experiments on our in-vitro normal B-cell→plasma cell differentiation model. We knock down your target gene using CRISPR/Cas9 or treat with your drug candidate, then monitor differentiation progression with flow cytometry and scRNA-seq.
This reveals: (1) Does knocking out/inhibiting your target block normal differentiation? (2) At which stage (MBC→Pre-PB→PB→PC)? (3) What is the therapeutic window—dose where tumor cells die but normal differentiation proceeds? (4) Are there compensatory pathways in normal cells?
De-risk your Phase I investment by identifying on-target safety issues before clinical trials. If toxicity is discovered, the mechanistic data supports informed program decisions: modified dosing strategies, combination approaches, or alternative target prioritization.
Unique Differentiator
We test perturbations in the FUNCTIONAL context of differentiation, not static cell lines. ScRNA-seq reveals whether cells attempt to differentiate and fail vs. remain viable but arrested—critical mechanistic insight.
How It Works
CRISPR/Drug Perturbation Setup
Deliver CRISPR/Cas9 targeting your gene OR treat with your drug candidate. Culture primary human memory B-cells through 10-day differentiation protocol with perturbation.
Differentiation Monitoring
Flow cytometry at days 0, 3, 7, 10 measures viability and differentiation markers (CD19, CD27, CD38, CD138). Compare perturbed vs. control cells.
ScRNA-Seq Profiling
Single-cell RNA-seq at days 3, 7, 10 reveals transcriptional changes. Do cells die, arrest, or activate compensatory pathways? Which differentiation genes are affected?
Safety Assessment Report
Receive dose-response curves, differentiation stage impact analysis, scRNA-seq mechanistic insights, and therapeutic window characterization.
Real-World Application
A pharma partner was developing a TARGET_C inhibitor for myeloma. TARGET_C is essential for tumor proliferation, but its role in normal plasma cell differentiation was unclear.
Before
Proceed to Phase I based on tumor cell line data showing TARGET_C essentiality. Risk: Unknown whether TARGET_C inhibition blocks normal antibody production, potentially causing severe immunodeficiency.
After
Helomnix CRISPR knockout of TARGET_C in normal B→PC differentiation model. Found TARGET_C is required for plasmablast expansion but NOT plasma cell maturation. Dose-response showed therapeutic window exists.
Outcome
The perturbation data informed dosing strategy considerations. The therapeutic window characterization supported program advancement with de-risked safety concerns.
Value to Your Organization
Phase I De-Risking
Identify on-target safety issues before Phase I. De-risk program investment by detecting potential differentiation toxicity early.
Therapeutic Window Discovery
Quantify therapeutic window: dose where tumor cells die but normal differentiation proceeds. Informs preclinical dose characterization.
Early Safety Signal
Receive safety assessment in weeks vs. discovering toxicity in Phase I after extended timelines and substantial investment.
Our Methodology
Data Inputs
- Target gene information
- CRISPR sgRNA sequences (we can design if not provided)
- Drug compound (if testing drug vs. CRISPR)
- Desired dose range for testing
- Known tumor essentiality data
AI/ML Techniques
- CRISPR/Cas9 knockout (RNP delivery or lentiviral)
- Primary human memory B-cell isolation from healthy donors
- 10-day in-vitro B→PC differentiation protocol
- Flow cytometry for viability and differentiation markers
- Single-cell RNA-seq (10X Genomics) at days 3, 7, 10
- Dose-response curve analysis
- Pathway enrichment analysis to identify compensatory mechanisms
Deliverables
- Viability and differentiation curves (CRISPR/drug vs. control)
- Flow cytometry analysis of differentiation markers
- ScRNA-seq dataset with differential expression analysis
- Mechanistic report: Which differentiation stage is affected and how
- Therapeutic window assessment: Safe dose range vs. tumor activity
- Compensatory pathway analysis: Can normal cells escape toxicity?
- Structured evidence summary to support program decisions
Discuss a Translational Application
We welcome discussions about how this approach can support your translational research.