Implementation of Pharmacogenomics and Artificial Intelligence Tools for Chronic Disease Management in Primary Care Setting

Abstract

Chronic disease management often requires use of multiple drug regimens that lead to polypharmacy challenges and suboptimal utilization of healthcare services. While the rising costs and healthcare utilization associated with polypharmacy and drug interactions have been well documented, effective tools to address these challenges remain elusive. Emerging evidence that proactive medication management, combined with pharmacogenomic testing, can lead to improved health outcomes and reduced cost burdens may help to address such gaps. In this report, we describe informatic and bioanalytic methodologies that integrate weak signals in symptoms and chief complaints with pharmacogenomic analysis of ~90 single nucleotide polymorphic variants, CYP2D6 copy number, and clinical pharmacokinetic profiles to monitor drug–gene pairs and drug–drug interactions for medications with significant pharmacogenomic profiles. The utility of the approach was validated in a virtual patient case showing detection of significant drug–gene and drug–drug interactions of clinical significance. This effort is being used to establish proof-of-concept for the creation of a regional database to track clinical outcomes in patients enrolled in a bioanalytically-informed medication management program. Our integrated informatic and bioanalytic platform can provide facile clinical decision support to inform and augment medication management in the primary care setting.

MedMetaverse: Medical Care of Chronic Disease Patients and Managing Data Using Artificial Intelligence, Blockchain, and Wearable Devices State-of-the-Art Methodology

“…Robots in healthcare have the most promising future for older people. The health of many seniors is in danger because they live alone in the community without the help of family or a carer [145]. Older people can benefit significantly from robotic aid in the form of reminders of routine tasks and directions in new environments [40], [144].…”

External control arms: COVID-19 reveals the merits of using real world evidence in real-time for clinical and public health investigations

“…The population paradox is defined as understanding the clinical relevance of molecular differences within a population. The population paradox enables the use of clinicogenomics databases for therapeutic development, clinical trials design, and therapeutic decision making for individualized medical care (49)(50)(51)(52). Evidence gaps, however, remain for the use of NGS with RWE in health insurance coverage decision-making with the exception of pharmacogenomics testing, suspected pediatric genetic disorders, and oncology (48).…”

An Idealized Clinicogenomic Registry to Engage Underrepresented Populations Using Innovative Technology

“…The term “clinicogenomic” refers to datasets combining the genetic (and often other -omic bioanalyte) characteristics of disease, coupled with the phenotypic annotation of clinical outcomes. In pharmacogenomics, documenting the linkages between genotypes, practice guidelines, and population health remains challenging [ 14 ]. The nexus of oncology and pharmacogenomics is thus: chemotherapeutic toxicities and long-term clinical outcomes have been observed to differ substantially among populations [ 15 ].…”