Services
Senior scientific advisory across strategic biological decision making, experiments and data integration, at the interface of immunology and AI.
ImmSilico provides expert guidance for complex immunology-driven research programmes, where experimental design, data complexity, and biological uncertainty matter.
Our advisory work draws on the scientific framework outlined on the Home page, and is delivered through flexible modes of engagement tailored to the needs of each project.
Areas of Advisory Involvement
Sceintific Decision Making
Decide with clarity under uncertainty
We help startups, biotech founders, and academic teams make high-stakes biological and translational decisions before irreversible resources, data generation, or program commitments are made.
Platform viability and readiness assessment for specific biological questions
Independent evaluation of emerging technologies and their suitability for a defined experimental objective
Selection of appropriate gene panels, measurement modalities, and spatial transcriptomics strategies
Comparative analysis of technological strengths, limitations, and trade-offs for a given research task
Assessment of data sufficiency, required sample sizes, and evidentiary thresholds for robust conclusions
Evaluation of platform adaptability when research questions evolve or expand
Identification of technical and analytical risks before large-scale experimental investment
Typical output: structured decision memo with risk mapping and recommendation pathway.
Experimental Design & Strategy
Experimental design grounded in biological and statistical rigor
Rapidly evolving technologies are transforming how biological science. We help teams to adopt accordingly to efficiently translate biological questions into experimental strategies that are technically feasible, statistically robust, and aligned with the capabilities and limitations of modern experimental and analytical technologies.
Our advisory support focuses on designing technologically intensive experiments to ensure high quality data.
Fit-for-purpose selection of experimental technologies and measurement modalities
Study design architecture, including sample size evaluation and statistical power strategy
Pre-execution feasibility assessment and identification of technical or analytical risks
Design of cost-effective pilot experiments to validate experimental assumptions
Evaluation of protocols for robustness, reproducibility, and adaptability
Clarification of hypotheses and mapping of biological and experimental uncertainty
Planning experimental scalability while controlling cost and operational complexity
Typical output: Technology-aware scalable experimental design for complex immunlogical questions
AI-Tailored Data Integration
Integrate complexity without losing mechanism
Modern biological programmes generate increasingly complex, multi-modal datasets. We help teams design analytical and AI frameworks that extract meaningful biological insight while remaining interpretable, scalable, and mechanistically grounded.
Our advisory support focuses on aligning data architecture, computational methods, and biological interpretation from the outset.
Alignment and integration strategies across heterogeneous biological data modalities
Evaluation of analytical frameworks and computational tools for specific biological questions
Design of data architectures that enable scalable cross-modality analysis
Pre-analysis planning prior to data acquisition to ensure analytical tractability
Selection and validation of appropriate AI and machine learning methodologies
Safeguards for interpretability, robustness, and generalisability of computational models
Linking computational outputs back to mechanistic biological hypotheses
Typical output: robust data integration and interpretability framework.
How Engagements Typically Work
We work with clients in flexible ways, depending on the nature, scale, and complexity of the scientific challenge.
Our involvement may range from focused advisory input on a specific experimental or analytical question, through ongoing strategic support across a research programme, to deeper collaboration around complex, immunology-driven decisions at critical stages of discovery or translation.
Each engagement is shaped by the scientific context and requirements of the project, rather than a fixed service model. If you are facing a complex immunology-driven decision across research, translation, or strategy, we invite an initial discussion.
Initiate a Discussion
If you are facing complex immunology-driven decisions across research, translation, or strategy, we would be happy to explore how our advisory input could help.