Built for pharma.
We learn how your scientists, quality and regulatory teams really work, and put AI to work in the systems they already use.
Request a briefingTarget assessment, compound design and assay analysis, learned from how your scientists work.
Target assessment
Compound design
Assay plates
Protein structures
Dose-response curves
Lab protocolsProtocols, site selection and study reports, learned from the teams who run your trials.
Study protocols
Site selection
Patient cohorts
Survival analysis
Safety review
Study reportsDossiers, labels and authority questions, learned from the people who prepare your submissions.
Submission dossiers
Label comparison
Authority questions
Change control
Country requirements
Submission planningPrior art, claim charts and portfolio decisions, learned from the daily work of your IP team.
Prior art search
Patent families
Claim charts
Freedom to operate
Portfolio landscape
Renewal decisionsBatch records, deviations and process data, learned from your manufacturing and quality teams.
Batch record review
Bioreactor runs
Chromatography
Fill and finish
Deviation investigations
Stability studiesWho it is for
- Big Pharma
- Research, development and regulatory teams spread across sites, systems and time zones.
- Biotech
- Small teams taking one programme from the bench to its first trial.
- CDMOs
- Process development, tech transfer and batch release, for many clients at once.
- CROs
- Study teams running trials and lab work to a sponsor's protocol and timeline.
Where the work happens
- Research
- Experiments planned, run and written up in Benchling and the lab systems around it.
- Quality and manufacturing
- Deviations, batch records and investigations, where one open question can hold a release.
- Regulatory
- Filing sections and replies to an agency's questions, drafted and reviewed in Veeva Vault.
- Clinical
- Trial documents and data, from the protocol to the site files, in Veeva Vault and Medidata Rave.
What good work means
A pharma team is judged on a record that survives an audit.
Speed alone is not rewarded. One finding can stop a trial or a plant, and every day runs against a patent clock. So the measure of success is agreed with the people who sign the work off, before anything runs.
Your data stays yours
Trial data and lab records stay inside your company.
Each person owns the record of their own work and decides what the team sees. We never measure individual productivity. Security, privacy, legal and the works council are at the table from the first week.
How we start
One team, one workflow, one baseline.
A sponsor picks a team of five to ten people and one workflow. We sit with them for four weeks, then review the result together against the measure agreed at the start.