Early Patient Identification
Early Patient Identification Programs at subrosa OmicsAI
Prospective programs that find genetically confirmed patients years earlier than today’s standards.
From Database to Validated Cohort
A transparent, data-to-clinic pipeline — illustrated with Danon disease. The subrosa workflow.
Over 600,000 patients (Europe, USA, Asia) with full HPO-based clinical characterization and WES / WGS genetic data.
From the genetically verified sub-cohort of a given diagnosis (e.g. Danon disease) we analyze the detailed clinical phenotype, earliest symptoms and disease progression.
Using clinical data from many patients with overlapping phenotypes but other diagnoses (e.g. cardiomyopathy), we retrospectively compute the positive and negative predictive value of the symptom constellation most indicative of the specific disease.
We prospectively recruit patients who present exactly this clinical signature into a clinical study, and then confirm them genetically.
Such prospective studies are typically balanced to a positive diagnostic rate of ~4–10% — an enrichment factor of ~200–1,000× vs. the general population.
Clinical Study Protocol for Early Patient Identification
Study Elements and Descriptions
Develop a comprehensive framework for the study, outlining objectives, methodologies, and expected outcomes to align stakeholders.
Ensure all clinical and operational details are clearly defined in a robust protocol, adhering to regulatory and ethical standards.
Manage submissions and approvals with Ethics Committees to secure compliance and obtain necessary permissions for study execution.
Conduct regular meetings with Principal Investigators to ensure alignment, training, and efficient communication throughout the study.
Identify and engage study sites through questionnaires and site selection processes, ensuring readiness for smooth trial operations.
Why Early Patient Identification Programs are a Competitive Imperative
XCLR8ED — Patient Enrollment That Delivers
Timely patient enrollment is one of the biggest bottlenecks in clinical development — especially in rare and ultra-rare disease. Roughly 3 out of 4 clinical trials experience delays, causing major cost overruns and endangering maximal financial returns from the patent-window period. Recruitment shortfall is the dominant delay driver — the operational domain largely handled by CROs and sites. But CROs only optimize execution; our models address the root cause, de-risking enrollment BEFORE CRO execution starts, increasing the number of enrolled patients and reducing dropouts. The result: faster, predictable recruitment and more reliable study execution.
What subrosa OmicsAI combines
- Partially unique knowledge of clinical insights from our proprietary rare disease patient genome database.
- Experience from 40+ successfully executed global identification studies (proven and published) over the past two decades.
- Deep access to more stakeholders than CROs in a global, trusted ecosystem — rare disease KOLs and sites, patients directly (counseling, funds-pooling, PSPs, home treatment), patient organizations, and data-driven targeted HCPs outside the excellence centers (awareness education).
…to improve the main KPIs of patient enrollment
- Optimize protocol design — including optimal inclusion criteria and primary endpoints — BEFORE the CRO starts, so no more patients than necessary are excluded from screening and milestones stay achievable for investor milestone payments.
- Recruit additional, also younger patients through subrosa OmicsAI’s clinical programs and register them to accelerate speed and quality of enrollment.
- Increase site productivity and reduce the number of sites, especially zero-enrollment sites.
- Improve the screen-to-enroll ratio through better pre-screening and targeting (patient conversion funnel).
- Decrease time-to-first-patient / time-to-first-site for an earlier enrollment curve.
subrosa de-risks enrollment BEFORE CRO execution starts
Protocol Design & Patient Enrollment Optimization
Reasons for rare disease trial-enrollment shortfalls — and what we can do.
| Area | Primary Owner | Where subrosa Group can have impact on enrollment |
|---|---|---|
| Protocol design (eligibility, endpoints) | Sponsor | With unique real-world evidence from our proprietary rare disease patient database, subrosa OmicsAI provides essential insights to optimize protocol design and trial strategy before selecting a CRO — ensuring you don’t exclude a significant share of the accessible patient population from screening. |
| Feasibility & site selection | Shared (Sponsor + CRO) | Through our unmatched global rare disease KOL & site network we typically gain additional insights into optimal site selection and geographical match. |
| Site activation & operations | CRO | …and into site activation, especially in unmet-need indications. |
| Patient recruitment execution | CRO + sites | Our clinical programs identify patients that CROs typically never reach — far beyond the major excellence centers and often at a very early age. Proven. Published (PubMed). This broader patient range and higher proportion of young patients can have a massive positive impact on trial outcomes. |
| Patient awareness / referral ecosystem | Sponsor + external networks | With 40+ global identification studies completed (proven and published) over two decades, subrosa teams have deep access to rare-disease KOLs, sites and PAOs, allowing us to influence more referred patients to join a trial. We also find patients through omnichannel awareness education (42health) of targeted HCPs outside the excellence centers. |
| Retention / dropout | CRO + sites | 42health’s rare disease patient adherence and support programs — with site personnel (global) or at the patient’s home (Europe only) — remarkably reduce drop-out rates. |
Include us in time, and you may not have to complain about CRO performance — in case of genetic-based rare disease indications.
The Hidden Patient Problem That Costs Pharma Billions
A patient with a rare genetic disease waits an average of 7 to 12 years for a correct diagnosis. During that time the disease progresses — often irreversibly. Every year of delay is a year without therapy.
Historical prevalence estimates are based on incomplete registry data. Our prospective studies consistently show the real patient pool is up to 5× larger — with direct impact on pharma valuations and market access strategies.
Over 85% of rare diseases have a genetic cause — yet most patients are never genetically tested. They remain invisible to pharma, to clinicians, and to the healthcare system. That is the gap subrosa OmicsAI closes.
Real Data Real Patients Up to 5x Higher Market Value
Validated real-world patient numbers — not modeled estimates — directly translate into higher market confidence and stronger pharma valuations.
Delta: ~4-5x — Represents incremental implied value for Rare Disease1 vs. Market cap.
1) Outside-in assumption.
The subrosa OmicsAI Advantage
The only partner that turns genetically confirmed real-world patient data into your competitive advantage — across trials, market access and valuation.
Identifying Rare Patients. Precisely. Earlier. Globally.
What sets us apart — Three layers of differentiation no CRO or data provider can replicate
Over 58,000 rare disease patients recruited across 48+ countries — genetically confirmed, clinically deep-characterized, longitudinally followed. Not modeled. Not estimated. Real.
▸ Proof: ROPAD study — 12,580 PD patients from 122 sites in 9 months
We go beyond diagnosis: genomics, transcriptomics, proteomics and metabolomics combined with AI models sub-stratify patients into clinically actionable groups — de-risking your trial design from day one.
▸ Proof: HAE study — 150× higher prevalence in targeted screening vs. general population
Our epidemiological programs have consistently shown patient pools 4–5× larger than pharma estimated — translating directly into higher market confidence and stronger regulatory submissions.
▸ Proof: Validated programs showed 4–5× implied value uplift for rare disease assets
subrosa OmicsAI Services
Identifying Rare. Precisely. Early. Globally.
* OENI – Observational Epidemiological Non-Interventional Study
The Rare Disease Patient Intelligence Partner
Identifying Rare Patients. Precisely. Earlier. Globally.
Proven at scale: We identify patients for gene-based rare diseases data-driven, not estimated — accelerating your development timeline from day one.
De-risk your enrollment before the CRO starts
Talk to us about an early patient identification program for your indication.