Medicinal Products (IDMP)
Get ready for IDMP
Embrace the digital transformation!
Qdossier supports companies to drive digital transformation within the enterprise by aliging people, processes and tools. Not only to achieve IDMP compliance, but to turn knowledge into an asset with considerable strategic and operational value. Benefit from increased transparency and informed decision making.
We can help you in various ways to prepare for IDMP compliance and beyond. This includes:
- Gap analyses and readiness assessment
- Definition of a strategy and roadmap
- Proof of Concepts for software solutions
- Definition and implementation of business processes and workflows tuned towards IDMP
- Data definition and specification of standards and terminologies
- Data collection, transformation and consolidation
Master data on products, organisations and substances to drive (regulatory) processes
IDMP is a set of ISO standards which enables marketing authorization holders (MAH) to take immediate action to reduce the occurrence of adverse events attributed to substandard batches of substances, package materials, finished products or inferior manufacturers. It also allows determination of adverse events that could be prevented with improvements in the prescribing information. The standards support various other use cases including regulatory processes, inspections, provision of product information from regulator to other stakeholders like e-prescription, traceability in supply chain to detect falsified medicines. The data model is also used as a reference and driver for master data management at both agency and industry side.
Improved signal detection and safeguarding of patients
Health Authorities (HA) currently collect information across multiple marketing authorization holders who market generic and similar products. Unfortunately, this is hampered since not the same taxonomy is used across products. Furthermore, product’s key characteristics are insufficiently captured in databases and scattered over paper or electronic documents. Objective is to improve the ability to perform analyses by using databases and to increase specificity and selectivity of the analyses by using the same taxonomy within- and across MAHs and HAs. Both changes improve signal detection and allow taking corrective actions to safeguard patients.