Suchergebnisse

Model-informed precision dosing (MIPD) has become synonymous with modern approaches forindividualizing drug therapy, in which the characteristics of each patient are considered as opposedto applying a one-size-fits-all alternative. This review provides a brief account of the currentknowledge, practices, and opinions on MIPD while defining an achievable vision for MIPDin clinical care based on available evidence.We begin with a historical perspective on variabilityin dose requirements and then discuss technical aspects of MIPD, including the need for clinicaldecision support tools, practical validation, and implementation of MIPD in health care.Wealso discuss novel ways to characterize patient variability beyond the common perceptions of geneticcontrol. Finally, we address current debates on MIPD from the perspectives of the new drugdevelopment, health-care economics, and drug regulations. ; QC 20201012

Introduction: Technical and logical breakthroughs have provided new opportunities in medicine to use knowledge bases and large-scale clinical data (real-world) at point-of-care as part of a learning healthcare system to diminish the knowledge-practice gap. Areas covered: The article is based on presentations, discussions and recommendations from an international scientific workshop. Value, research needs and funding avenues of knowledge bases and access to real-world data as well as transparency and incorporation of patient perspectives are discussed. Expert opinion: Evidence-based, publicly funded, well-structured and curated knowledge bases are of global importance. They ought to be considered as a public responsibility requiring transparency and handling of conflicts of interest. Information has to be made accessible for clinical decision support systems (CDSS) for healthcare staff and patients. Access to rich and real-world data is essential for a learning health care ecosystem and can be augmented by data on patient-reported outcomes and preferences. This field can progress by the establishment of an international policy group for developing a best practice guideline on the development, maintenance, governance, evaluation principles and financing of open-source knowledge bases and handling of real-world data.

Introduction Technical and logical breakthroughs have provided new opportunities in medicine to use knowledge bases and large-scale clinical data (real-world) at point-of-care as part of a learning healthcare system to diminish the knowledge-practice gap. Areas covered The article is based on presentations, discussions and recommendations from an international scientific workshop. Value, research needs and funding avenues of knowledge bases and access to real-world data as well as transparency and incorporation of patient perspectives are discussed. Expert opinion Evidence-based, publicly funded, well-structured and curated knowledge bases are of global importance. They ought to be considered as a public responsibility requiring transparency and handling of conflicts of interest. Information has to be made accessible for clinical decision support systems (CDSS) for healthcare staff and patients. Access to rich and real-world data is essential for a learning health care ecosystem and can be augmented by data on patient-reported outcomes and preferences. This field can progress by the establishment of an international policy group for developing a best practice guideline on the development, maintenance, governance, evaluation principles and financing of open-source knowledge bases and handling of real-world data. ; Funding Agencies|Swedish Research CouncilSwedish Research Council [2018-00747_3]; NEPI Foundation; Swedish Institute for Drug Informatics (SIDI); Swedish Society for Clinical Pharmacology and Pharmacotherapy