The last two years have been unusually busy in terms of chemical and laboratory legislation. The 11th revised edition of the GHS was published on September 12, 2025 , and introduced changes regarding aerosols, methods that do not use animal testing for skin sensitization, and simplification of hazard and precautionary statements regarding contribution to global warming. On the European Union side , the application of new hazard classes to mixtures began on May 1, 2026. On the pharmaceutical side, the comprehensive revision of the regulation on computerized systems is ongoing after fourteen years, and the final text is expected to be published in mid-2026.
The practical consequence of this intensity for businesses is that compliance is no longer a one-off project, but a continuous process. The difference between systems where the rule set is versionable and affected products can be found with a single query when a rule change occurs, and manually managed structures, grows with each regulatory change.
2. The entry of artificial intelligence into the laboratory.
Artificial intelligence in laboratory software is progressing at two different levels. The first is the operational level : predicting equipment failures, detecting anomalous results, prioritizing workflows, querying data in natural language, and generating document drafts. The second is the scientific level : proposing formulations, optimizing experimental design, and extracting patterns from past experimental data.
In regulated environments, this development raises a new question: how can an AI-powered decision be verified and monitored? The fact that the European Union's pharmaceutical legislation includes a separate annex on AI-based systems shows that this question is also being considered by regulators. The approach adopted in practice is that AI generates recommendations, the decision is made by an authorized person, and this decision is recorded .
3. System integration
Sample management, electronic lab ledger, execution system, and device data management components, which have been sold as separate products for many years, are now combined into a single platform. Why is it practical? Keeping the same data across four systems creates both interface costs and data integrity risks. The weakest link in a lab is often the data transfer between two systems.
A more advanced layer of this trend is the integration of the laboratory system with enterprise resource planning and product lifecycle management . This integration is necessary so that the sample can be linked to the production batch, the result to the batch release, the recipe to the product record, and the classification to the label. In separate systems, these links are established through integration projects; in a single system, they exist naturally.
4. The changing approach to cloud computing and verification.
Migrating lab systems to the cloud is not just an infrastructure choice; it also means a change in the validation approach. Current regulatory expectations are that validation should encompass the application, infrastructure, and service provider. In return, the provider's readily available validation documentation, change management, and backup proofs significantly reduce the burden on the customer.
5. Bringing sustainability data back to the lab.
Digital product passports and ecodesign regulations are leading to the requirement of machine-readable information on a product's material composition, restricted substances, repairability, and end-of-life data. The source of this information is largely laboratory and product safety data. Thus, laboratory data is now becoming the basis not only for quality decisions but also for market access rights .
6. Laboratory and product safety on leading corporate platforms.
The two major market providers address laboratory and chemical compatibility functions with different components. The table below compares their approaches.
Function
Approach 1
Approach 2
Quality control laboratory
Inspection batch, inspection plan and results record through the quality management component.
Inspection plan, nonconformity and corrective action flow through the quality management solution.
Prescription and formulation
A prescription development component built on a specification database; centralized management of prescriptions, formulations, labels, and process steps.
Product registration and formula and composition management via the product master data center.
Pest classification
Product safety component includes control of prohibited and restricted substances via prescription or product tree, hazard assessment and hazardous substance labeling.
Product compatibility and material declaration capabilities for restricted substance tracking.
Safety data sheet
Generating documents through compliance templates; producing updated and real-time reports for different languages and countries.
Deriving compliance documentation from product data and distributing it to channels.
Product development link
Integration of recipe development with product lifecycle and product fit components.
Innovation management involves linking requirements and concept objects to the product registry.
Architectural note
The transition from classic product safety solutions to next-generation product compliance solutions is ongoing.
The transition process from a classic product lifecycle solution to a cloud solution is ongoing.