SIBIUS: Battling cognitive disorders Custom Case Solution & Analysis

Evidence Brief: SIBIUS Case Data

1. Financial Metrics

Seed Funding: The company raised 1.5 million Euros in initial seed capital to develop the Eye-Tracking Cognitive Assessment (ETCA) prototype.
Market Opportunity: The global market for cognitive assessment and training was valued at approximately 3.5 billion dollars, with a projected compound annual growth rate exceeding 25 percent.
Development Costs: Research and development expenses accounted for 70 percent of the total capital expenditure during the first 24 months of operation.
Target Pricing: Preliminary models suggested a per-test fee of 50 to 100 dollars for clinical use, or a subscription model for pharmaceutical partners ranging from 10,000 to 50,000 dollars per trial site.

2. Operational Facts

Technology Core: The ETCA utilizes a 10-minute non-invasive eye-tracking protocol paired with proprietary machine learning algorithms to identify biomarkers of cognitive impairment.
Patent Status: Two primary patents held for the specific oculomotor tracking sequences and the diagnostic AI model.
Clinical Validation: Initial pilot studies involved 150 subjects, showing a 92 percent sensitivity rate in distinguishing healthy controls from early-stage Alzheimer patients.
Hardware Dependency: The software currently requires high-specification infrared eye-tracking cameras, limiting deployment to specialized clinical settings.

3. Stakeholder Positions

Angus, CEO: Prioritizes clinical credibility and FDA approval as the primary moat against competitors.
Venture Capital Investors: Focused on rapid scaling and recurring revenue; pushing for a software-as-a-service model targeting general practitioners.
Pharmaceutical Partners: Express interest in using the tool for patient stratification in Phase 2 and Phase 3 clinical trials for neurodegenerative drugs.
Regulators (FDA): Classify the tool as a Class II medical device, requiring a De Novo pathway or 510(k) clearance depending on the intended use claim.

4. Information Gaps

Unit Economics: The case lacks specific data on the manufacturing cost of the proprietary hardware versus licensing third-party eye trackers.
Competitor Performance: Limited comparative data on the accuracy of traditional Pen-and-Paper tests (like MoCA) versus the ETCA in real-world primary care settings.
Customer Acquisition Cost: No historical data on the cost to convert a neurology clinic or a pharmaceutical research unit.

Strategic Analysis

1. Core Strategic Question

Should Sibius pursue the high-barrier clinical diagnostic market requiring FDA approval, or the lower-barrier pharmaceutical research and wellness markets to secure immediate cash flow?

2. Structural Analysis

Value Chain Analysis: The current bottleneck lies in the diagnostic phase of the patient journey. Traditional methods are slow and subjective. Sibius shifts the value from subjective observation to objective data. However, the hardware dependency creates a physical constraint in the digital health value chain that competitors using standard smartphone cameras might bypass.

Jobs-to-be-Done: For neurologists, the job is to increase diagnostic throughput. For pharmaceutical companies, the job is to reduce trial failure rates by ensuring participants actually have the early-stage symptoms the drug targets. The latter offers a more immediate and high-value economic return.

3. Strategic Options

Option 1: The Clinical Gold Standard. Focus exclusively on FDA Class II clearance for primary care physicians.
- Rationale: Establishes a permanent medical moat and enables insurance reimbursement.
- Trade-offs: High burn rate during the multi-year regulatory wait; risk of total failure if FDA clearance is denied.
Option 2: The Pharma Research Partner. Pivot to a B2B model providing data services to drug developers.
- Rationale: Immediate revenue; lower regulatory hurdles for research use only (RUO) tools.
- Trade-offs: Smaller total addressable market compared to primary care; high dependency on the R&D budgets of a few large firms.
Option 3: The Hardware-Agnostic Licensor. Abandon proprietary hardware and optimize the algorithm for standard mobile device cameras.
- Rationale: Rapid scalability and low distribution costs.
- Trade-offs: Significant drop in data precision and diagnostic sensitivity; loss of control over the user experience.

4. Preliminary Recommendation

Sibius should adopt Option 2 (Pharma Research Partner) as the immediate priority to fund the long-term pursuit of Option 1 (Clinical Gold Standard). The pharmaceutical market provides the necessary capital and clinical data to strengthen the eventual FDA application without requiring dilutive bridge financing.

Implementation Roadmap

1. Critical Path

Month 1-3: Secure three pilot contracts with mid-sized biotech firms for Phase 2 trial integration.
Month 4-6: Refine the AI model using the high-fidelity data gathered from pharma pilots to meet FDA sensitivity requirements.
Month 7-12: Submit De Novo classification request to the FDA while launching a specialized sales team for the top 20 global pharmaceutical companies.

2. Key Constraints

Data Privacy Compliance: Managing patient data across multiple jurisdictions (GDPR and HIPAA) requires a centralized, encrypted infrastructure that the current team lacks.
Capital Allocation: The company must survive the 18-month regulatory cycle. If pharma revenue does not materialize within 6 months, the clinical path must be paused.

3. Risk-Adjusted Implementation Strategy

The plan assumes a staggered rollout. By focusing on Research Use Only (RUO) status for the first 12 months, the company avoids the operational paralysis of waiting for government approval. A contingency plan involves licensing the oculomotor sequences to existing diagnostic imaging companies if direct sales targets are missed by 30 percent in the first year.

Executive Review and BLUF

1. BLUF

Sibius must prioritize the pharmaceutical research market to secure non-dilutive capital and validate its algorithm. Pursuing the clinical diagnostic market as a first step is a capital-intensive error that ignores the 18-month regulatory lag. The company should position the ETCA as a patient-stratification tool for drug trials. This generates immediate revenue and builds the clinical evidence required for eventual FDA clearance. Success depends on transitioning from a hardware-centric mindset to a data-as-a-service model. Delaying the clinical market entry in favor of pharma partnerships is the only path that ensures solvency.

2. Dangerous Assumption

The analysis assumes that pharmaceutical companies will accept eye-tracking data as a valid surrogate endpoint for cognitive decline. If drug developers remain committed to traditional cognitive scores, the B2B pivot will fail, leaving the company without a viable revenue stream or a regulatory path.

3. Unaddressed Risks

Big Tech Entry: Companies like Apple and Google are integrating advanced eye-tracking into consumer hardware. Their entry would commoditize the Sibius hardware moat instantly. (Probability: High; Consequence: Severe).
Algorithmic Bias: The current pilot data (150 subjects) is too small to ensure the algorithm performs across diverse demographic and age groups. (Probability: Medium; Consequence: Moderate).

4. Unconsidered Alternative

The team failed to consider a joint venture with a major medical imaging or diagnostic hardware provider. Instead of building a sales force, Sibius could integrate its software into existing diagnostic suites, trading margin for immediate global distribution and credibility.