Where drug teams run their entire program, from discovery to FDA approval.
Enjamb's agents run the entire drug program: clinical evidence, trial design, statistical programming, and regulatory submissions, all on top of the systems you already use, with no migration.
Trusted by users at top pharma
ENJAMB PLATFORM
One auditable workspace from discovery to FDA approval
Enjamb unifies the evidence, analysis, document editing, compute, and review trail behind a drug program. Agents do the work where scientists, biostats, clinical, and regulatory teams already need to make decisions.
Agentic orchestration
Agents that execute the drug program, not just summarize it.
Describe the outcome you need and Enjamb coordinates specialized agents across evidence, trial design, statistical programming, and regulatory writing inside one auditable workspace.
Connection layer
Agents on top of the systems pharma already runs.
Enjamb runs the entire drug program for biopharma teams, from discovery to FDA approval, without forcing a migration. It connects agents to existing systems and data so they can execute across the whole program in one auditable layer.
Existing stack
Enjamb agent layer
AI and MCP-style connections for the work legacy tools were not built to run.
No rip-and-replace. No disconnected copilots. Agents work on the source systems, files, analyses, and documents teams already use.
The problem
Making drugs is hard. The handoffs make it slower.
It can take more than $2.6B and 10+ years to ship a single drug. The bottleneck is not one isolated task. It is the chain of handoffs where evidence, data, analysis, and documents drift apart.
Evidence lives in one system.
Protocols move through another.
Analysis waits on a separate team.
Regulatory drafts lose the source trail.
Enjamb
One context from question to approval.
Agents work across the whole program, and every output keeps its sources, files, code, and decisions attached.
View use cases →Synthesize the evidence
Search literature, trial precedent, real-world signals, and internal files to identify targets, biomarkers, populations, and rationale.
Design the trial
Turn evidence into protocol concepts, endpoint strategy, inclusion criteria, comparator rationale, and SAP scaffolds.
Run the statistics
Use Python and R agents for data cleaning, statistical programming, SDTM, ADaM, TFLs, figures, QC, and analysis narratives.
Draft and audit
Generate and review INDs, protocols, SAPs, NDAs, briefing books, and response materials with source-backed traceability.
Use cases
Put agents across the program, not beside it.
Enjamb moves from clinical evidence to trial design, analysis, statistical programming, and regulatory output while preserving the context behind every claim.
Discovery and preclinical
Preclinical to IND
Move from hypothesis to clinic with evidence and rationale intact
Clinical development
Trial Design
Endpoints, populations, protocols, and SAPs from evidence
Biostatistics and programming
Statistical Programming
Analysis, SDTM, ADaM, TFLs, QC, and narratives
Regulatory
Regulatory Submissions
Draft, audit, and align INDs, protocols, SAPs, and NDAs
What makes Enjamb different
AI for regulated science.
Not generic chat.
Drug programs need traceable evidence, reproducible analysis, document control, and human review.
Enjamb was built so agents can execute real scientific work while keeping the context visible from the first question to the final submission artifact.
Auditable by default
Every source, file, tool call, code run, and document change can remain attached to the output it produced, giving teams a clearer review trail across high-stakes program work.
Evidence-grounded execution
Agents search, read, extract, and compare clinical evidence before drafting or analyzing, so important claims can be traced back to the papers, data, and artifacts behind them.
Human review stays central
Enjamb is built for scientists, clinical teams, statisticians, and regulatory reviewers to inspect, redirect, and approve agent work instead of accepting a black-box answer.
Built for the full program stack
Full document, spreadsheet, and slide editors sit beside Python and R compute, source PDFs, datasets, integrations, and agent workflows in a single browser-based workspace.
“We spent months on this one screening dataset just trying to find a pattern. We didn't get much at first, but when I uploaded the raw data into Enjamb, it autonomously plotted the stats and pulled the matching papers. I just kept looking at the screen saying, ‘how did we miss this?’”
Researcher
Top 10 University
The browser workspace for real program work
Full Word, Excel, and PowerPoint editors. Python and R compute. Full-text papers, data files, source-backed drafting, scientific integrations, and agent review in one place.
Bring agents into your drug program
See how Enjamb carries work from clinical evidence to trial design, statistical programming, regulatory drafting, and audit in one browser workspace.
Request a demo