Taking biotech Start-ups to
the Next Level
CelCyr provides a clinical trial optimisation platform that uses AI-driven tools to improve patient selection and streamline enrolment.
We are particularly effective in clinical trials management and startup support in rare-disease patient populations and hard-to-recruit in Oncology, Immunology, Haematology and Neurology & Rehabilitation
We also empower startups growth by bringing together visionary leaders and astute angel investors to accelerate breakthroughs—achieving the extraordinary, ahead of expectations.
Empowering Growth
1. Cutting-Edge Technology
Leverage advanced biomarker discovery, real-time monitoring tools, and AI-powered analytics to accelerate timelines and improve trial outcomes.
2. Expertise in strategic management
Specialised knowledge and skills to navigate the unique challenges of building and scaling early-stage companies, including strategic planning, agile decision-making, resource optimisation, and leadership in fast-paced, uncertain environments. .
3. Comprehensive Clinical Trial Support
From preclinical studies to Phase III trials, you will have a dedicated experienced senior medical VP to provide end-to-end solutions and support encompass protocol design, patient recruitment, data management, and regulatory compliance, tailored to meet the unique needs of any study.
4. Startup-Centric Approach
Our commitment to innovation and discovery and our startup-centric approach is focused on delivering agile, innovation-driven, and scalable solutions tailored to the unique needs of early-stage and growth-stage companies. Our methodology prioritises speed, lean operations, iterative development, and rapid validation, mirroring the mindset and pace of startups themselves.
DR Stephane ShekarSarai
Co-founder and co-CEO
Chief Medical Officer
Stefano Juno
Co-founder and co-CEO
Chief Financial Officer
DR Eduardo Benso di Cavour
SVP and Chief Scientific Officer
Marcus Jacob Nielsen
SVP and Chief Operating Officer
Services
Clinical Trial Optimisation
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Protocol simulation & optimisation: Use historical and real-world data to model different trial designs (e.g., adaptive designs).
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Endpoint selection: AI can recommend optimal primary/secondary endpoints based on biomarker data and prior studies.
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Patient stratification strategy: Identify high-responder subgroups using machine learning on preclinical or early clinical data
Analytics & Insights
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Predictive site performance: AI analyses site histories to predict enrollment rates, protocol adherence, and data quality.
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Investigator matching: Matches trials with investigators with relevant experience, patient access, and performance metrics.
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Retention prediction: Identify patients at risk of dropout using engagement and behavioral data
Product Development / go/no-go Strategic Decision
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Futility analysis: AI models can simulate future trial outcomes to guide early termination or continuation decisions.
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Portfolio optimisation: Evaluate how a candidate fits within the broader pipeline and competitor landscape.
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Anomaly detection: Flag potential data entry errors, protocol deviations, or fraudulent data in real time.
Documentation
Support
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Scientific insight generation: Link compounds, targets, diseases, and outcomes using AI-curated knowledge graphs
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Automated report generation: Draft clinical study reports (CSRs), investigator brochures, or regulatory summaries using NLP.
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Protocol compliance checks: Validate trial protocols against evolving regulatory guidance and best practices
Why Does A-I Matter?
1. Accelerated Patient Recruitment and Stratification
Why it matters: Recruiting the right patients quickly is one of the biggest bottlenecks in early trials.
AI advantage: AI can analyse health records, NLP algorithms, genomic data, and registry databases to identify eligible and high-responder patients more efficiently than traditional methods.
Impact: Speeds up trial initiation, reduces costs, and increases the likelihood of detecting drug efficacy early
2. Data-Driven Trial Design and Decision-Making
Why it matters: Startups often have limited resources and cannot afford trial failures due to poor design or wrong endpoints.
AI advantage: Platforms simulate various protocol designs, optimize endpoint selection, and predict success probabilities based on preclinical and historical data.
Impact: Increases the likelihood of regulatory success and investor confidence by enabling smarter go/no-go decisions early.
3. Real-Time Monitoring and Risk Management
Why it matters: Early-phase trials are prone to deviations, safety concerns, and data integrity risks.
AI advantage: AI can monitor trial data in real time to detect anomalies, predict dropout risks, and flag emerging safety signals.
Impact: Improves trial quality, patient safety, and ensures compliance with regulatory standards without heavy manual oversight.
Career
Join the Future of Biotechnology
At CelCyr, we work at the intersection of biotech innovation and AI-driven research, advancing transformative solutions from discovery to early-phase clinical development.
While we can’t reveal all the details just yet, we're actively hiring for multiple confidential roles across the following areas:
- Clinical Research & Trial Operations
- Computational Biology & Bioinformatics
- AI/ML in Drug Discovery
- Data Science & Biostatistics
- Platform Engineering & DevOps
Please email your CV along with a brief but enthusiastic cover letter highlighting your experience, passion, and how you see yourself contributing to our team. We’re excited to learn more about you and where you believe you can make the biggest impact within our organisation.
