Using the PharmCAT tool for Pharmacogenetic clinical decision support.

Here, we will provide our insights into the usage of PharmCAT as part of a pharmacogenetic clinical decision support pipeline, which addresses the challenges in mapping clinical dosing guidelines to variants to be extracted from genetic datasets. After a general outline of pharmacogenetics, we describe some features of PharmCAT and how we integrated it into a pharmacogenetic clinical decision support system within a clinical information system. We conclude with promising developments regarding future PharmCAT releases.

Decentralized Digital Health Services Caught Between the Pressure for Innovation and the Burden of Regulations.

Multiple challenges await third-party digital health services when trying to enter the health market. Prominent examples of such services are clinical decision support systems provided as external software. Uncertainty about their challenges, technical as well as legal, pose serious hurdles for many innovations to be adopted early on.

Legal Challenges for IT Service Providers in Pharmacogenomics.

IT providers offering services based on genetic data face serious challenges in managing health data in compliance with the General Data Protection Regulation (GDPR). Based on a literature research and our experiences, an overview of GDPR compliant processing of sensitive data is given. The GDPR requirements for processing sensitive data were specified for a use case concerning a service provider of a pharmacogenomic decision support system.

Integrating Pharmacogenetic Decision Support into a Clinical Information System.

Pharmacogenetic testing can prevent adverse drug events but has rarely found its way into clinical routine. One reason is the lack of tools for smooth and automatable integration of pharmacogenetic knowledge into existing processes. Especially, electronic medical records (EMR) represent a suitable environment for such tools.