SERVICING THE PRECLINICAL LIFECYCLE
SERVICES
Our services are designed from working inside real preclinical programmes and seeing the same issues repeat themselves. Every programme was built from scratch, key assumptions were not explicit and risks surfaced late – often after capital was committed.
WHAT THE INDUSTRY SAYS
QUANTIFYING the problem
Timeline Delays
Investor Confidence Loss
Vendor Fragmentation
Compliance Lapses
OUR APPROACH
building our services
We build compliant, transparent and secure preclinical services across the full development lifecycle – from early planning through execution, regulatory documentation, quality assurance and multi-jurisdictional pathways.
Our approach reflects emerging regulatory expectations for the responsible use of AI in drug development, including principles articulated by the U.S. Food and Drug Administration and the European Medicines Agency: AI is used to support decision-making, not replace judgement; risks are made explicit; and outputs are transparent, auditable and fit for regulatory scrutiny.
WHAT WE DO
OUR Services
PLANNING & SET-UP
Early-stage biotechs need more than activity lists – they need a defensible development pathway.
Our AI-enabled, rules-based platform generates a structured preclinical blueprint that:
- aligns programmes to regulatory expectations, defines activity sequencing and dependencies
- estimates indicative timelines and costs
- surfaces scientific, regulatory, and execution risk early
Crucially, every output is produced with a clear context of use and is reviewed by experienced scientific and regulatory experts. This ensures assumptions are challenged, limitations are understood and decisions remain accountable – consistent with good practice for AI-supported evidence generation.
The result is not automation for its own sake, but disciplined planning before capital is committed.
EXECUTION
Preclinical execution demands coordination across safety, toxicology and CMC – areas where fragmentation most often introduces delay and risk.
We support execution by:
- coordinating vendor selection and oversight,
- standardising study design and protocol expectations,
- providing ongoing QA and GLP-aligned review.
AI supports oversight and consistency, but control, accountability and risk management remain human-led.
dOCUMENTATION & QUALITY ASSURANCE
Regulatory documentation is only as strong as the decisions behind it.
We combine AI-assisted drafting with standardised, regulator-aligned QA frameworks to produce documentation that is:
- coherent across modules,
- transparent in rationale,
- traceable to underlying decisions and data.
This approach reduces rework, supports audit readiness and ensures submissions reflect not just what was done, but why key decisions were taken – a core expectation of regulators evaluating AI-informed evidence.