Seal vs ValGenesis VLMS

1ValGenesis VLMS and Seal, side by side.

ValGenesis and Seal both treat validation as structured data rather than paper, and both trace a change to the requirements and tests it touches. ValGenesis sells validation as dedicated applications on its Smart GxP platform: iVal for the validation lifecycle, iClean for cleaning validation and iOps for operational logbooks.¹ Seal is the GxP operating system for biopharma. In Seal, teams configure the lab, manufacturing and quality workflows themselves, so the equipment state, clean status and test evidence a validated process depends on are checked in the work that relies on them.

2What ValGenesis VLMS is built for.

ValGenesis is made for enterprises that want a dedicated validation system covering qualification, computer system validation and cleaning validation across many sites. ValGenesis, Inc. was founded in 2005 and is headquartered in Santa Clara, California. It says it created the first fully digital validation lifecycle management system.² ValGenesis says 30 of the top 50 life sciences companies use its Smart GxP platform, and its home page still counts the GMP systems validated with ValGenesis VLMS.³

Since June 2025 ValGenesis has sold its applications as Smart GxP, in two suites. The Validation Lifecycle Suite holds iVal for end-to-end validation lifecycle management of equipment qualification, CSA, CSV and manufacturing systems; iClean for cleaning validation; and iOps for equipment, cleanroom and process logs. The Process Lifecycle Suite holds iCMC for quality-by-design CMC development and iCPV for continued process verification. ValGenesis describes Smart GxP as cloud-native and integrated with LIMS, MES, ERP and QMS.¹

iVal brings validation planning, test authoring, execution and oversight into one system, with offline execution, automated deviation handling and lifecycle traceability for CSA, CQV and CSV.⁴ Several users can author and review a document at once, and raw data and metadata from analytical instruments and manufacturing equipment can be captured over RS232, TCP/IP and PC-based connections into protocols, batch records and equipment logs.⁴ ValGenesis calls the suite CSA ready: a risk-based assessment identifies and enforces the testing type, scripted or unscripted. Customers configure templates, forms, workflows and rules themselves, and can implement the modules in phases.⁵ iOps replaces paper logbooks with digital forms for equipment use, cleaning, calibration, maintenance and quality checks, with QR codes on equipment, an offline mobile app and business rules for verification, approval and scheduling.⁶

VAL, ValGenesis’s AI, supports protocol and trace generation, gap assessment, execution review, evidence analysis and anomaly identification within governed, human-led workflows, grounded in the customer’s approved validation documents. ValGenesis launched its next generation in April 2026 with a limited pilot.⁷ Its AI responsibility statement says AI supports but does not replace human judgement, and that customers remain responsible for reviewing and validating AI-generated outputs before relying on them.⁸

3Cleaning validation and the next changeover.

Both products treat a cleaning limit as a governed calculation rather than a number copied into a protocol. They differ in where the result is used.

iClean covers cleaning validation from risk-based planning and MACO determination to execution and requalification. It calculates the maximum allowable carryover from health-based exposure limits such as ADE or PDE, taking account of shared surface areas and batch sizes, and evaluates worst-case products by potency, solubility, toxicity and difficulty to clean. Digitised 2D and 3D equipment models let users place sampling locations, which are embedded into protocols automatically, and change control and requalification workflows are included.⁹

In Seal, the same chain runs into production. In the example in Seal’s cleaning validation blueprint, residue risk matrix v07 covers four products on mixer M2, filler F4 and granulator G1. Product C on G1 scores highest and is selected as the worst case. Its MACO of 6.4 mg, calculated as PDE × next-batch size ÷ daily dose, spread over 18.6 m² of shared surface, sets a swab limit of 0.86 µg per 25 cm². Executed clean CLN-0441 then releases the train clean until 14:20. The production step checks the selected equipment’s clean state before use, and an exceeded hold blocks normal use. A change to a toxicological input, the procedure or a surface area identifies the calculations, studies and scheduled campaigns it affects. The manufacturer remains responsible for the toxicological conclusions; Seal keeps the inputs, formula version and downstream use inspectable.

4How a change reaches the validated state.

ValGenesis assesses a change from its trace matrix. Seal assesses it from the links between requirements, tests and the work that used them, and runs the selected checks before release.

In ValGenesis, a user starts an impact assessment by selecting the updates needed, and the system identifies the directly and indirectly affected specifications and tests from the dynamic requirements trace matrix. Only the affected requirements, specifications and tests are modified, without revising each document, and the system can generate a consolidated document from the affected components.⁵ Deliverables related to the same change can be bundled together.⁴

In Seal, coverage is computed from the records. In the example in Seal’s commissioning and qualification blueprint, water-for-injection system WFI-02 shows 42 requirements, 41 passed and one conditional, with no orphan tests, and a requirement made not applicable keeps its rationale instead of leaving the denominator. The qualified state becomes the baseline for change control and periodic review. Because instrument and person eligibility is recorded against each execution, a later calibration failure identifies the tests recorded as using that instrument and opens an impact assessment. For a change to a Seal workflow, selected user acceptance tests run in a background simulation when the change is prepared for review, publication requires current passing results, and earlier runs keep the version they used.

5Where ValGenesis VLMS is the better fit.

ValGenesis is the better fit when you want a dedicated, enterprise validation system run by a validation function across many sites.

• You validate many kinds of system and equipment, including third-party computer systems, and want CSA, CSV and CQV in one application, with offline execution in the field.⁴
• You run a cleaning validation programme across many products and shared equipment, and want MACO calculation, worst-case selection and 3D sampling maps in a dedicated application.⁹
• You want validation connected to CMC process development and continued process verification from one vendor, through iCMC and iCPV.¹
• You want raw instrument data captured directly into protocols and equipment logs.⁴
• You prefer a modular rollout, one application at a time.⁵

6Where Seal is the better fit.

Seal is the better fit when the processes you validate run in Seal and the validated state has to hold at the moment of use.

• You want the clean, calibrated and qualified state checked by the step that uses the equipment, so a lapsed hold or a missing prerequisite stops that path and shows why.
• You want laboratory, manufacturing and quality on one set of records. A swab result is a laboratory result linked to its sample, the clean, the equipment and the next batch, through a shared ontology rather than an interface.
• You expect to keep changing the process. Each improvement becomes a new process version with its specifications, test evidence and approvals, and earlier runs keep the version they used.
• You want an AI agent whose output is configuration your team can test. Neil compares a change with the tested baseline, traces the affected records and prepares the verification cases; your team checks coverage and decides release. In line with the EU’s draft GMP Annex 22 on AI, Neil is not used in GMP execution. It helps set up configuration, which your team verifies and releases under change control.

7Running Seal alongside ValGenesis.

You can keep ValGenesis for qualification packages and the CSV of other systems while one process runs in Seal. Seal has no dedicated ValGenesis connector. Where a system is not on Seal’s integrations list, Seal’s REST API and Scripts can connect it: the API reads and writes records from another system, and Scripts are versioned Python that can call an external service after an event or on a schedule, edited in a changeset, tested and published like other Seal records. ValGenesis describes Smart GxP as integrating with LIMS, MES, ERP and QMS on its side.¹

Agree the records, the direction of transfer, the credentials and the failure handling before implementation. Start with read access, and treat any write to ValGenesis as a separate decision with its own review gates and audit evidence. Qualify the connection by defining identifiers and mappings, testing missing and duplicate records, and reconciling against the source, as the regulatory guide describes.

8Moving from ValGenesis VLMS to Seal.

Start with one process where the validated state has to hold at the moment of use.

1. Choose one shared equipment train across a changeover, with at least three products, a justified worst case and a failed result, or one release-test limit you need to change.
2. Bring the matrix and limit inputs, the procedure and recent results. Start with sample records, or arrange an NDA before sharing confidential ones.
3. Neil proposes the configuration and prepares the verification cases, and your team checks them against how the work runs. In the 48-hour evaluation, Seal turns one process into a working workflow with a validation pack to inspect. Production timing then depends on scope, interfaces, migration and your release requirements.
4. Exercise the difficult cases before relying on it: a failed swab result, an exceeded hold, a changed PDE and the release decision that follows.
5. Use existing ValGenesis protocols as source material. Imported evidence keeps its original version and context, and the packages that stay in ValGenesis remain retrievable for their retention period.

The validation blueprint sets out the approach in detail.