Target Identification & Validation
At Ausovi, Target Identification & Validation is the cornerstone of our entire pipeline. Before any analog is designed or synthesized, we rigorously identify and biologically validate high-potential therapeutic targets that address serious unmet medical needs. By owning target identification and validation internally, Ausovi ensures every program starts with scientifically robust, clinically relevant, and protectable targets — dramatically increasing the probability of success through preclinical and clinical stages.
In drug discovery, the single greatest predictor of eventual clinical failure is selecting the wrong target. Historical data show that programs built on poorly validated or biologically irrelevant targets suffer attrition rates exceeding 90% by Phase II/III. Ausovi was founded to break this pattern.
We do not chase fashionable targets or rely on literature alone. Instead, we integrate human genetics, multi-omics datasets (genomics, transcriptomics, proteomics, epigenomics), disease-network modeling, and real-world patient-derived evidence to nominate targets with the highest causal linkage to disease pathology.
Validation Challenge
Ausovi solves this by treating Target Identification & Validation as the single most critical investment. Through rigorous multi-omics integration, functional genomics, disease-model validation, and early druggability filtering, we significantly reduce downstream risk and focus our analog engineering on targets with the strongest scientific and commercial rationale.
Ausovi Target Advantages
- Multi-omics integration for high-confidence target selection
- CRISPR and functional genomics for causal validation
- Disease-relevant in vitro and in vivo model confirmation
- Early assessment of druggability, selectivity, and safety liabilities
- Proprietary datasets and bioinformatics workflows
- Strategic alignment with IP strategy from target nomination
- Clear go/no-go criteria before analog investment begins
Innovative Science & Research Solutions
n drug discovery, the single greatest predictor of eventual clinical failure is selecting the wrong target. Historical data show that programs built on poorly validated or biologically irrelevant targets suffer attrition rates exceeding 90% by Phase II/III. Ausovi was founded to break this pattern.
We begin every program with a disciplined, multi-layered Target Identification & Validation process because:
- We only advance what we truly understand We do not chase fashionable targets or rely on literature alone. Instead, we integrate human genetics, multi-omics datasets (genomics, transcriptomics, proteomics, epigenomics), disease-network modeling, and real-world patient-derived evidence to nominate targets with the highest causal linkage to disease pathology.
- Biological validation is non-negotiable Nominating a target is only the hypothesis. We test it rigorously using orthogonal approaches: CRISPR knockout/knock-in, base editing, siRNA/shRNA silencing, antibody neutralization, small-molecule probes, and genetic animal models. We demand consistent, reproducible modulation of disease-relevant phenotypes across multiple systems before considering a target “validated.”
- We validate in disease-relevant context Validation occurs in human-derived cellular models (iPSC-derived cells, primary patient cells, organoids) and advanced preclinical models that recapitulate key aspects of human disease progression. This translational focus minimizes the “target-to-disease disconnect” that plagues many early programs.
- Druggability and IP are assessed from day one Parallel to biological validation, we perform structural bioinformatics, binding-site analysis, and ligandability scoring to confirm the target is chemically tractable. At the same time, our IP team conducts freedom-to-operate and patentability assessments so that validated targets enter the analog design phase already positioned for strong composition-of-matter and method-of-use protection.
- Clear go/no-go gates protect resources Every target passes through predefined, quantitative decision criteria (e.g., effect size in disease models, selectivity window, expression in target tissue, genetic human evidence LOD score ≥ 4). Targets that fail these gates are terminated early — preserving capital and team focus for only the highest-conviction opportunities.