Learn more about PV Intelligent Automation and AI
PV Intelligent Automation and AI
- Evaluation of the client’s existing PV environment with respect to intelligent automation, knowledge processes, data management practices and technical capacities.
- Tailored strategy and roadmap for more automated and AI-driven/-assisted PV processes including data acquisition (monitoring, intake), case processing or signal detection.
- Transition by initializing and driving relevant Proofs of Concepts, implementation projects and corporate change initiatives
- Covered intelligent automation improvements might include:
- Monitoring of relevant data sources - literature, social media, mail inboxes etc.
- Exploratory Data Analysis, data/text preparation and pre-processing
- Entity recognition and pre-coding (MedDRA PTs, products), AERs and duplicate detection/classification, seriousness suggestion, case summarization, results evaluation
- Simulations, visualizations, modeling temporal relations and causality assessment
- Augmented AI patterns (AI vs. human-assisted) and related explainability and validation compliance
- Tuning models (hyper-parameters) and architectures for regression, classification, deep learning (NLP) and others
- Productionalizing PV IT operations towards scalable architectures, faster turnaround (CI/CD), continuous improvements and Machine Learning PV IT operations (MLOps covering train/test/validation/production pipelines, etc.)
- Active awareness of relevant community activities - open-source models and libraries, no-code SaaS tools, regulatory AI PV guidelines and actions, ethical and green AI, and more.
