EMA/EU
- Guideline on computerized systems and electronic data in clinical trials
- EU AI Act
- Reflection paper on the use of Artificial Intelligence (AI) in the medicinal product lifecycle
- Ethics Guidelines for Trustworthy AI
Artificial intelligence solutions
Artificial intelligence is the “next big thing” and is on a par with the invention of the steam engine, the automobile, the internet and the iPhone. The use of artificial intelligence will also fundamentally change the pharmaceutical industry in all areas, from research and development to the manufacture and distribution of medical products. AI systems are therefore also relevant to GxP and are subject to the same regulations.
For example, AI can be used in the research and development of new drugs to identify patterns in large amounts of data and thus accelerate the discovery of new therapies. In production, AI enables the optimization of manufacturing processes through precise control and monitoring, leading to higher quality and lower costs. In the field of clinical trials, AI can be used to improve patient selection and evaluate study data more efficiently, which increases the safety and speed of development of new therapies.
When validating AI systems, however, special aspects and particularities in planning and implementation must be taken into account. These include definitions of acceptance criteria, adequate selection of training, test and validation data. Furthermore, additional controls are also necessary during operation in order to ensure that the acceptance criteria are permanently met and data quality is assured.
Our aim is not only to support customers in complying with regulatory requirements, but also to fully exploit the potential of AI to increase process efficiency, drive innovation and ultimately deliver better outcomes for patients.
QFINITY∞ SUPPORTS THE VALIDATION OF KI SOLUTIONS WITH THE FOLLOWING SERVICES:
- Integration of AI solutions into the system landscape
- Planning validation activities for AI systems
- Ensuring transparency and traceability in AI decision-making
- Definition of acceptance criteria
- Implementation of robust documentation processes
- Definition of data requirements for training, test and validation data
- Design of monitoring systems for operations
- Change management for AI-specific requirements
AI software validation by QFINITY fulfills the relevant regulatory requirements set out in various regulations and guidelines, depending on the customer’s specific task:
QUESTIONS?
What is artificial intelligence?
Artificial intelligence (AI) refers to the ability of computer systems to perform tasks that normally require human intelligence. There are different types and manifestations of artificial intelligence, e.g. machine learning, deep learning, generative AI, natural language processing.
These types of artificial intelligence can be used in different combinations and applications to solve problems in different areas.
What is training, test and validation data?
The training data is the basis for all predictions that the model makes later, as it is used to train the system and optimize the weights in the AI algorithm.
The validation data is used to automatically verify the model with known data to check/evaluate the success of the training.
The test data consists of unknown data that is processed by the system and then manually checked for correctness and accuracy.
