Partnering challenge
Stop navigating the clinical landscape in the dark
Engine
The Engine
ClinForecast™ unifies massive clinical trial repositories into a structured unified data protocol using temporal deep learning and fine-tuned RAG/LLM models. By integrating entity-level caching and homogenization of medical language ambiguity, we move past static trial summaries to predict optimal design criteria and overall success metrics.
Workflow
Value Pipeline
01. Trial Aggregation & Cleansing
The TechSemantic search engines and a unified global data protocol layer.
Value addedIntegrates worldwide clinical trial repositories seamlessly. Harmonizes ambiguous medical language at ingestion to isolate high-fidelity historical signals.
02. Trial Landscape Mapping
The TechMulti-factor competitor pipeline trackers and site intelligence analytics.
Value addedMaps optimal trial sites, dynamic enrollment patterns, and real-time entrant landscapes. Uncovers the systemic reasons behind previous trial failures.
03. Protocol Optimization
The TechPathophysiology bottleneck predictors and inclusion/exclusion scoring models.
Value addedEvaluates average patient counts and duration parameters per phase. Identifies unmet patient population needs by refining inclusion and exclusion boundaries.
04. Outcome Engineering
The TechPhase-gated progression and drug modality probability graphs.
Value addedPredicts the exact probability of an asset advancing to subsequent clinical phases. Maximizes commercial opportunity and safeguards patent life by preventing costly amendments.
Evidence
Proof
Peer-reviewed & published
Vetted and approved by independent peer review across the rare disease space, Prader-Willi Syndrome (PWS), and anorexia nervosa, replacing unverified "trial and error" guesswork with rigorous science.
Time & cost compression
slashes evaluation workflows from a traditional 30-40 day timeframe down to a highly efficient 5-8 day process.
CDP financial optimization
Drops total pharma Clinical Development Plan (CDP) activity costs from an estimated $2.5M baseline to under $1M.
Institutional adoption
Formally trusted, deployed, and validated in trial intelligence by prominent institutions including Ipsen Pharma, CHU Saint Etienne and Karolinska University Hospital.
For partners
Buyer details
What we organize
Eliminate guesswork by using deep learning to optimize inclusion criteria, map endpoints, and engineer protocols around failure bottlenecks.
Partner-ready outputs
Temporal trial design recommendations, site-mapping briefs, and phase-gated success metrics.
Compliance
100% EU-designed and hosted; built by machine learning engineers and researchers to be verifiable, traceable, explainable, and auditable.
Access model
Flexible Annual Platform Subscription (following fee-for-build) or project-specific Contract Research Agreement (CRA).
Resources
Publications and case studies
Publication · 2024
Clinical Efficacy Landscaping in Genetic Obesity: A Meta-analysis in Prader–Willi Syndrome (PWS)
Sarkar M, von Horsten HH, Milunov D, Lefebvre NB, Saha S. Drug Repurposing. 2024;1(2).
View publisher recordPublication · 2025
Quantifying hope: an EU perspective of rare disease therapeutic space and market dynamics
Cacoub E, Lefebvre NB, Milunov D, Sarkar M, Saha S. Frontiers in Public Health. 2025;13:1520467.
View publisher recordPublication · 2026
Mapping the Clinical Trial Landscape in Anorexia Nervosa: A Registry-Based Analysis of Research Activity and Translational Gaps
Galusca B, Germain N, Sarkar M, Gandit B, Milunov D, Urakpo K, Khaddour M, Saha S. medRxiv. 2026.03.19.26348323.
View DOI
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