01
Most companies start with a disease. We start with the entire rare disease landscape.
Traditional rare disease companies often focus on a single disease or technology platform and build everything around that starting point. Proxy systematically evaluates thousands of rare diseases, genetic drivers, therapeutic targets, and approved medicines to identify opportunities where biology, clinical feasibility, and development strategy align. Instead of asking, "How do we develop a treatment for this disease?" we ask, "Which diseases have the highest probability of successful development?"
02
We optimize for approval, not just discovery.
Finding a promising drug-disease relationship is only the beginning. Many programs fail because of trial design, patient recruitment challenges, safety limitations, regulatory barriers, or commercial realities. Proxy evaluates potential programs through the lens of development success, incorporating clinical, regulatory, and operational factors early in the process to prioritize opportunities that can realistically reach patients.
03
We use New Approach Methodologies.
Animal studies can't fully anticipate human responses. Differences in target biology, pharmacokinetics, metabolism and off-target effects between species mean many risks only surface in human trials. Proxy uses New Approach Methodologies (NAMs): real tissue, grown from real patients, tested before anyone is exposed to risk. Using patient-derived organoids, we test candidate therapies directly in human tissue, before a compound ever reaches an animal model or a patient.
04
We focus on mechanisms, not symptoms.
Rare diseases that look similar on the surface may have completely different biological causes. Conversely, diseases that appear unrelated may share common molecular drivers. Proxy integrates genetic, biological, clinical, and pharmacological evidence to identify mechanistic relationships rather than relying on symptom matching alone. The goal is to uncover therapies that address the underlying biology of disease.
05
Our platform is designed for rare disease reality.
Rare disease development faces unique challenges: small patient populations, fragmented evidence, limited clinical data, and highly heterogeneous disease presentations. Proxy was built specifically to operate in this environment. Our infrastructure, data models, and workflows are designed around rare disease evidence gaps rather than adapted from large-market therapeutic areas.
06
Every recommendation is traceable.
Scientific and regulatory decisions require transparency. Proxy emphasizes evidence provenance, source tracking, uncertainty identification, and auditability. Rather than treating AI as a black box, we focus on creating evidence-backed outputs that investigators, partners, and regulators can independently review and verify.
07
We consider the entire development pathway from day one.
Drug repurposing is often approached as a discovery problem. Proxy views it as a development problem. Our process integrates disease biology, target selection, regulatory strategy, natural history evidence, intellectual property considerations, and clinical development planning into a unified framework. This helps ensure that promising candidates are evaluated in the context of the pathway required to bring them to patients.
08
We are built to enable modern rare disease trial designs.
Conventional randomized controlled trials are often difficult or impossible in very small patient populations. Proxy incorporates natural-history-based approaches, patient-as-own-control strategies, and other rare disease development paradigms to help identify development pathways that can reduce cost, accelerate timelines, and improve feasibility while maintaining scientific rigor.
09
We search for the right disease, the right target, the right drug, and the right patient.
Many platforms focus on a single dimension of the problem. Proxy evaluates diseases, targets, drugs, modalities, and patient populations together. This multidimensional approach allows us to identify opportunities where multiple factors align, increasing confidence that a therapeutic hypothesis can ultimately translate into clinical success.
10
We combine AI with regulatory-grade evidence generation.
AI can generate thousands of hypotheses. The challenge is determining which ones matter. Proxy combines computational discovery with structured evidence generation, disease characterization, regulatory planning, and scientific validation to transform hypotheses into development-ready opportunities. Our goal is not simply to discover new ideas, but to create programs capable of advancing toward patients.