The successful implementation of pharmacogenetics (PGx) into clinical practice requires patient genomic data to be shared between stakeholders in multiple settings. This creates a number of barriers to widespread adoption of PGx, including privacy concerns related to the storage and movement of identifiable genomic data. Informatic solutions that support secure and equitable data access for genomic data are therefore important to PGx. Here we propose a methodology that uses smart contracts implemented on a blockchain-based framework, PGxChain, to address this issue. The design requirements for PGxChain were identified through a systematic literature review, identifying technical challenges and barriers impeding the clinical implementation of pharmacogenomics. These requirements included security and privacy, accessibility, interoperability, traceability and legal compliance. A proof-of-concept implementation based on Ethereum was then developed that met the design requirements. PGxChain's performance was examined using Hyperledger Caliper for latency, throughput, and transaction success rate. The findings clearly indicate that blockchain technology offers considerable potential to advance pharmacogenetic data sharing, particularly with regard to PGx data security and privacy, large-scale accessibility of PGx data, PGx data interoperability between multiple health care providers and compliance with data-sharing laws and regulations. 

/pdf/a-blockchain-based-framework-to-support-pharmacogenetic-data-1y2aaujj.pdf

A blockchain-based framework to support pharmacogenetic data sharing

Simple Summary Next-generation sequencing (NGS) is a cutting-edge technology that enables rapid, high-throughput sequencing of DNA and RNA. Researchers and clinicians can identify genetic mutations, gene fusions, and other alterations that may drive cancer growth. This is particularly important in precision oncology as it is applied in the context of Molecular Tumor Boards (MTBs). The latter are multidisciplinary teams of experts who use NGS and bioinformatics tools to analyze patients’ genetic profiles and develop personalized treatment recommendations for cancer patients. Thus, a crucial process for MTB decision-making is the analysis, compilation, and presentation of high-dimensional sequencing data, which are used for both preparation of and case presentation to all stakeholders. MIRACUM-Pipe precisely addresses these requirements and offers an easy-to-use, one-prompt standardized solution to analyze NGS data, including quality control, variant calling, copy number estimation, annotation, visualization, and report generation. Abstract (1) Background: Next-generation sequencing (NGS) of patients with advanced tumors is becoming an established method in Molecular Tumor Boards. However, somatic variant detection, interpretation, and report generation, require in-depth knowledge of both bioinformatics and oncology. (2) Methods: MIRACUM-Pipe combines many individual tools into a seamless workflow for comprehensive analyses and annotation of NGS data including quality control, alignment, variant calling, copy number variation estimation, evaluation of complex biomarkers, and RNA fusion detection. (3) Results: MIRACUM-Pipe offers an easy-to-use, one-prompt standardized solution to analyze NGS data, including quality control, variant calling, copy number estimation, annotation, visualization, and report generation. (4) Conclusions: MIRACUM-Pipe, a versatile pipeline for NGS, can be customized according to bioinformatics and clinical needs and to support clinical decision-making with visual processing and interactive reporting.

/pdf/miracum-pipe-an-adaptable-pipeline-for-next-generation-v438mz0w.pdf

MIRACUM-Pipe: An Adaptable Pipeline for Next-Generation Sequencing Analysis, Reporting, and Visualization for Clinical Decision Making

Our objective was to build a mock pharmacogenomic (PGx) patient portal and assess its ability to disseminate test results and information to patients. The YourPGx Portal delivered four sample PGx results (omeprazole, simvastatin, clopidogrel, and codeine). We hosted two study groups to assess patient knowledge and perceptions of PGx before and after accessing the portal. Ten PGx-tested and 10 traditional care participants were included (average 61 years, 60% women, 50% African American, and 55% had a bachelor's/advanced degree). Participants scored significantly higher on the post-test compared with the pre-test, with no significant differences between baseline scores or score change between the groups. Patient perceptions also improved after accessing the portal-more patients wanted their providers to have access to test results, and more patients would encourage family/friends to get PGx testing. Patients would share their test results with their healthcare providers, spouse/partner, and family; none would share results with their friends or social media. Almost all patients (95%) said the portal was easy to use and 65% said it was easy to understand. In this pilot study, patients' knowledge and perceptions of PGx improved after accessing the YourPGx Portal.

https://ascpt.onlinelibrary.wiley.com/doi/epdf/10.1111/cts.12681

Assessment of Patient Knowledge and Perceptions of Pharmacogenomics Before and After Using a Mock Results Patient Web Portal

Digital health, an emerging scientific domain, attracts increasing attention as artificial intelligence and relevant software proliferate. Pharmacogenomics (PGx) is a core component of precision/personalized medicine driven by the overarching motto "the right drug, for the right patient, at the right dose, and the right time." PGx takes into consideration patients' genomic variations influencing drug efficacy and side effects. Despite its potentials for individually tailored therapeutics and improved clinical outcomes, adoption of PGx in clinical practice remains slow. We suggest that e-health tools such as clinical decision support systems (CDSSs) can help accelerate the PGx, precision/personalized medicine, and digital health emergence in everyday clinical practice worldwide. Herein, we present a systematic review that examines and maps the PGx-CDSSs used in clinical practice, including their salient features in both technical and clinical dimensions. Using Preferred Reporting Items for Systematic Reviews and Meta-Analysis guidelines and research of the literature, 29 relevant journal articles were included in total, and 19 PGx-CDSSs were identified. In addition, we observed 10 technical components developed mostly as part of research initiatives, 7 of which could potentially facilitate future PGx-CDSSs implementation worldwide. Most of these initiatives are deployed in the United States, indicating a noticeable lack of, and the veritable need for, similar efforts globally, including Europe. 

Will Precision Medicine Meet Digital Health? A Systematic Review of Pharmacogenomics Clinical Decision Support Systems Used in Clinical Practice

Expanded sources for precision medicine

BACKGROUND Pharmacogenomic Clinical Decision Support Systems (CDSS) are considered to be the most feasible tool for adopting pharmacogenomic testing into clinical routine. OBJECTIVE To discuss important factors for implementing pharmacogenomic CDSS into German hospitals. METHODS We analyzed two relevant studies. Furthermore, we interviewed data privacy officers of three German university hospitals and examined relevant legal regulations in literature. RESULTS There are three major barriers for implementing pharmacogenomic CDSS into German hospitals: (i) the legal uncertainty; (ii) the lack of machine-readable data; (iii) the remaining knowledge gap of both genetics and pharmacogenomics among physicians. CONCLUSION The implementation of passive clinical decision support (CDS) for somatic mutations in the form of structured pharmacogenomic reports might be the most feasible CDS feature for clinicians in German hospitals.

Implementing Pharmacogenomic Clinical Decision Support into German Hospitals.

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Implementing Pharmacogenomic Clinical Decision Support into German Hospitals.