Life Sciences
Life sciences teams work in environments where rigour, traceability, and careful review matter. Corentis helps organisations introduce AI into selected operational workflows with testing, oversight, and evidence around the process.
Where The Value Lies
Life sciences organisations are under pressure to use AI in practical operational work, but the value only lands when the surrounding process remains bounded, reviewable, and suitable for regulated environments.
$60bn-$110bn
McKinsey estimates generative AI could create significant annual value across pharma and medical products, with R&D and clinical development among the areas of interest.
The adoption pressure is real, but life sciences teams need controlled workflows rather than broad automation promises.
Source: McKinsey, generative AI in pharma57%
Tufts CSDD research found substantial protocol amendments were common, and nearly half were deemed avoidable by sponsors.
Better structure around review, escalation, and evidence can reduce friction when operational changes need to be understood later.
Source: Tufts CSDD protocol amendment analysis$141k-$535k
The same Tufts CSDD analysis reported median direct costs of $141k for Phase II and $535k for Phase III substantial amendments.
Corentis does not prevent protocol change, but it can help teams keep operational review, sign-off, and evidence clearer around bounded workflows.
Source: Tufts CSDD protocol amendment analysisAudit trails
ICH E6(R3) data-governance guidance emphasises traceability, metadata, review of audit trails, and documented processes across the data lifecycle.
That is the environment Corentis is designed for: AI-supported work with visible controls, human review, and evidence that can be inspected.
Source: ICH E6(R3) Step 4 final guidelineWho It Is For
Corentis is aimed at teams working around regulated operational workflows, including document-heavy review processes, governance functions, QA-linked activities, and other bounded areas where oversight matters.
Support document-heavy operational review with clearer visibility, stronger controls, and audit-friendly outputs.
Help teams organise and assess deviation-related information while preserving human review and sign-off.
Support bounded summarisation workflows with oversight, review steps, and evidence around the process.
What Corentis Is For
Corentis is designed for operational and governance support around regulated workflows. It is not presented as a diagnostic or treatment tool.
Its purpose is to help organisations introduce AI into selected processes in a way that is easier to monitor, review, and evidence over time.
Why This Matters
In life sciences operations, the question is not simply whether AI can save time. The deeper question is whether the surrounding process remains transparent, reviewable, and appropriate for a regulated environment.
Corentis helps teams build that surrounding structure so operational gains do not come at the cost of confidence.
What Corentis Is
What Corentis Is Not
Bounded Workflow View
This prototype-style module is intended to show bounded workflow support rather than broad automation claims.
Intake
Documents, deviations, or summarisation inputs are gathered in a workflow that still expects oversight.
Controls
Completeness checks, sign-off requirements, and escalation rules are attached before outputs are relied on.
Review
Named reviewers remain central wherever the workflow crosses a threshold or requires judgement.
Evidence
Approval history, exceptions, and supporting materials are preserved to support later review.
Prototype event trail
Intended to show the kind of reviewable workflow state Corentis is being built to expose.
01
Deviation material structured for review rather than auto-actioned
02
Named reviewer sign-off recorded before workflow progresses
03
Evidence retained for QA and governance inspection
Detailed Example
A practical starting point is protocol-deviation triage: a bounded operational workflow where AI may help organise information, but human judgement and review remain central.
Step 1
Deviation-related information is gathered and an AI-supported process helps structure, summarise, or classify the material for review.
Step 2
Corentis applies workflow rules around required checks, completeness, escalation conditions, and who must review outputs before they are relied on.
Step 3
Named reviewers assess the output, approve it, request changes, or escalate it when the workflow crosses defined thresholds.
Step 4
The workflow retains approval history, exceptions, and supporting materials so teams have a clearer record of what happened around the process.
What Corentis Adds
Review snapshot
01
Policy checks attached
02
Named review gate visible
03
Evidence ready for export
Bounded Adoption
Practical FAQ
These questions matter because careful adoption in life sciences depends on scope, review discipline, and clarity about what the system is and is not intended to do.
Corentis is designed for operational, quality, governance, and document-heavy review teams working around regulated life sciences processes where oversight and evidence matter.
No. Corentis is positioned as a governance and oversight layer for bounded operational AI workflows. It is not presented as a diagnostic, treatment, or clinical decision system.
The focus is on bounded operational workflows such as document review, protocol-deviation triage, or summarisation support where human sign-off and process visibility remain essential.
The platform is designed to add testing, control mapping, review gates, runtime visibility, and evidence generation around a workflow rather than replace the underlying tools already in use.
In regulated environments, confidence depends on more than output quality. Teams need to know what was checked, who reviewed it, what exceptions arose, and what record remains afterwards.
