Some important constraints of anesthesia must be taken into consideration when the pharmacological properties of modern anesthetics are discussed. The most imp- tant of these could be that the target effect be achieved preferably within seconds, at most within a few minutes. Similarly, offset of drug action should be achieved within minutes rather hours. The target effects, such as unconsciousness, are pot- tially life-threatening, as are the side effects of modern anesthetics, such as respi- tory and cardiovascular depression. Finally, the patient’s purposeful responses are not available to guide drug dosage, because, either the patient is unconscious, or more problematically, the patient is aware but unable to communicate pain because of neuromuscular blockade. These constraints were already recognised 35 years ago, when in 1972 Volume XXX entitled “Modern Inhalation Anesthetics” appeared in this Handbook Series. The present volume is meant as a follow up and extension of that volume. At the beginning of the 1970’s anesthesia was commonly delivered by inhalation, with only very few exceptions. The clinical understanding of that time considered anesthesia as a unique state achieved by any of the inhalation anesthetics, in- pendent of their specific molecular structure. “The very mechanism of anesthetic action at the biophase” was discussed within the theoretical framework of the “u- tary theory of narcosis”.

Der Autor untersucht in dieser Studie die spezifischen Wirkungen des neuen Pharmakons Propofol auf das zentrale Nervensystem durch pharmakokinetisch/-dynamische Modellbildung. Die Modellbildung soll den zeitlichen Verlauf der Wirkung in Abhängigkeit von den Blutspiegeln in ihrem nichtlinearen Zusammenhang bei verschiedenen Dosierungsstrategien beschreiben. Ziel der Untersuchung ist es, mit diesem Konzept die Grundlage für eine optimierte Anwendung von Propofol im Rahmen der totalen intravenösen Anästhesie zu schaffen. Gleichzeitig erfolgt damit die klinische Erprobung eines neuen Pharmakons, anders als sonst vielfach üblich, von Anfang an auf rationaler Ebene, die durch pharmakokinetische Modelle und pharmadynamische Daten gebildet wird. Somit wird ein auf Empirie beruhendes "trial and error"- Verfahren bei der Entwicklung von klinischen Dosierungsvorstellungen vermieden.

Abstract: Introduction: This article is part of the Focus Theme of Methods of Information in Medicine on the German Medical Informatics Initiative. Similar to other large international data sharing networks (e.g. OHDSI, PCORnet, eMerge, RD-Connect) MIRACUM is a consortium of academic and hospital partners as well as one industrial partner in eight German cities which have joined forces to create interoperable data integration centres (DIC) and make data within those DIC available for innovative new IT solutions in patient care and medical research. Objectives: Sharing data shall be supported by common interoperable tools and services, in order to leverage the power of such data for biomedical discovery and moving towards a learning health system. This paper aims at illustrating the major building blocks and concepts which MIRACUM will apply to achieve this goal. Governance and Policies: Besides establishing an efficient governance structure within the MIRACUM consortium (based on the steering board, a central administrative office, the general MIRACUM assembly, six working groups and the international scientific advisory board), defining DIC governance rules and data sharing policies, as well as establishing (at each MIRACUM DIC site, but also for MIRACUM in total) use and access committees are major building blocks for the success of such an endeavor. Architectural Framework and Methodology: The MIRACUM DIC architecture builds on a comprehensive ecosystem of reusable open source tools (MIRACOLIX), which are linkable and interoperable amongst each other, but also with the existing software environment of the MIRACUM hospitals. Efficient data protection measures, considering patient consent, data harmonization and a MIRACUM metadata repository as well as a common data model are major pillars of this framework. The methodological approach for shared data usage relies on a federated querying and analysis concept. Use Cases: MIRACUM aims at proving the value of their DIC with three use cases: IT support for patient recruitment into clinical trials, the development and routine care implementation of a clinico-molecular predictive knowledge tool, and molecular-guided therapy recommendations in molecular tumor boards. Results: Based on the MIRACUM DIC release in the nine months conceptual phase first large scale analysis for stroke and colorectal cancer cohorts have been pursued. Discussion: Beyond all technological challenges successfully applying the MIRACUM tools for the enrichment of our knowledge about diagnostic and therapeutic concepts, thus supporting the concept of a Learning Health System will be crucial for the acceptance and sustainability in the medical community and the MIRACUM university hospitals