An investment to redefine predictivity in drug discovery
Revenue today. Strategic asset for tomorrow. We address a fundamental inefficiency in pharmaceutical R&D in the highest-growth, highest-need niche: rare diseases.
Request the deckDrug discovery is a high-risk, low-efficiency process
The traditional development model is a funnel with an extremely low success rate — and historical data confirm the low predictivity of the preclinical phase.
In rare diseases, these structural barriers intensify
More than 50% of new drugs approved by CDER in 2023–2024 received orphan drug designation — yet the tools have not kept up.
Few patients and samples
Makes building robust cohorts difficult.
Fragmented clinical data
Information is dispersed across multiple institutions.
Low model predictivity
Current preclinical models fail to replicate disease complexity.
These limitations dramatically increase the risk of the “preclinical-to-clinical” leap, creating a critical need for better tools.
At the intersection of two market macrotrends
Increasing rare disease focus, plus accelerated outsourcing of specialized R&D, creates a structural need for highly predictive preclinical platforms.
Increasing focus on rare diseases
The pharmaceutical industry is pivoting toward rare diseases, with orphan designation now the majority of new approvals.
Accelerated R&D outsourcing
Pharma outsources complex capabilities and data it cannot build in-house — see Roche–Recursion and Sanofi–Exscientia.
From preclinical services to translational twin intelligence
Advanced experimental models
Cell lines, organoids and PDX sold in premium-priced packs.
Preclinical evaluation services
In vitro testing projects such as drug efficacy, on a project-based fee.
Collaborative research agreements
Technology transfer to academia and consortium collaborations.
Predictive intelligence licensing
Drug-response prediction models, tiered dataset access, subscription or milestone-based agreements.
Data-driven co-development
Joint target validation programs, risk-sharing agreements, milestones and downstream royalties.
Translational asset licensing
Validated target portfolios, option-to-license structures, high-value translational packages.
A patient-anchored biological–digital twin engine: TheraSigna evolves from a revenue-generating preclinical platform into a predictive translational intelligence engine anchored in real patient biology.
Five reasons the timing matters
Critical problem
A fundamental inefficiency in pharmaceutical R&D, in the highest-growth, highest-need niche.
Unique & defensible
A platform integrating biological models with deep patient data — difficult to replicate.
Early traction
A first commercial agreement already demonstrates market demand.
Top-tier team & alliances
Clinical, scientific and business excellence with access to key infrastructure.
Scalable vision
A clear plan toward short-term profitability and a high-value drug discovery model.