Clinical Decision Support for Precision Dosing: Opportunities for Enhanced Equity and Inclusion in Health Care

Abstract

Precision dosing aims to tailor doses to individual patients with the goal of improving treatment efficacy and avoiding toxicity. Clinical decision support software (CDSS) plays a crucial role in mediating this process, translating knowledge derived from clinical trials and real-world data (RWD) into actionable insights for clinicians to use at the point of care. However, not all patient populations are proportionally represented in clinical trials and other data sources that inform CDSS tools, limiting the applicability of these tools for underrepresented populations. Here, we review some of the limitations of existing CDSS tools and discuss methods for overcoming these gaps. We discuss considerations for study design and modeling to create more inclusive CDSS, particularly with an eye toward better incorporation of biological indicators in place of race, ethnicity, or sex. We also review inclusive practices for collection of these demographic data, during both study design and in software user interface design. Because of the role CDSS plays in both recording routine clinical care data and disseminating knowledge derived from data, CDSS presents a promising opportunity to continuously improve precision dosing algorithms using RWD to better reflect the diversity of patient populations.

Best Practice for Therapeutic Drug Monitoring of Infliximab: Position Statement from the International Association of Therapeutic Drug Monitoring and Clinical Toxicology

“…184 However, it remains unclear how applicable, enforceable, and beneficial these articles are for MIPD, given that MIPD only provides dose recommendations, potentially checked and authorized by a clinical pharmacist, with the final decision on adjusting the dosing generally left at the discretion of the treating physician. 185 In addition, with the impact of the new European Union Medical Device Regulation, MIPD software is considered a class II medical device and is subject to strict risk compliance. 186…”

“…First, seamless integration with the EHR system is necessary to automate the extraction of diverse patient data types directly from the EHR, enhancing the clinical utility of MIPD. 74,185 Second, POC testing can be combined with MIPD to reduce the turnaround time of concentration measurement and allow dose recommendations based on "realtime" PK of the patient.…”

Diversity, Equity, and Inclusion: Translating Clinical Pharmacology for All

“…With the exponential increase in our ability to harness multi‐modal data and digital technologies, translation of our understanding of population sources of variability to precision dosing solutions for all patients is an opportunity for intelligent clinical decision support systems, as reviewed by Hughes et al 14 . We are witnessing substantial progress in the science and technology required to develop intelligent, continuously learning precision dosing systems driven by population pharmacology models built from clinical trial and real‐world data in diverse populations 14–16 . Translating scientific and medical advances to equity in health care will, however, need to consider and address the critically important extrinsic factor of Social Determinants of Health through innovative health system, public health, and policy‐level interventions, as eloquently discussed by Golden 17 —reflecting her compelling State of the Art lecture at the ASCPT 2022 Annual Meeting.…”

“…12 The authors offer a call to action for the teaching community to be cognizant of the nuanced and incomplete overlaps between self-assigned labels of race and the true biological drivers of variation in disease biology and pharmacologic response to therapeutics, cautioning against the use of clinical case vignettes containing oversimplification and stereotyping. Equally important to appreciate for successful personalization of therapeutics and dosing across diverse populations is the multiplicity of intrinsic and extrinsic determinants of benefit/risk of drugs and our often incomplete understanding of the role of these factors, particularly in under-represented racial groups, as reviewed for direct oral anticoagulants by Thompson et al 13 With the exponential increase in our ability to harness multi-modal data and digital technologies, translation of our understanding of population sources of variability to precision dosing solutions for all patients is an opportunity for intelligent clinical decision support systems, as reviewed by Hughes et al 14 We are witnessing substantial progress in the science and technology required to develop EDITORIAL intelligent, continuously learning precision dosing systems driven by population pharmacology models built from clinical trial and real-world data in diverse populations. [14][15][16] Translating scientific and medical advances to equity in health care will, however, need to consider and address the critically important extrinsic factor of Social Determinants of Health through innovative health system, public health, and policylevel interventions, as eloquently discussed by Golden 17 -reflecting her compelling State of the Art lecture at the ASCPT 2022 Annual Meeting.…”

“…Equally important to appreciate for successful personalization of therapeutics and dosing across diverse populations is the multiplicity of intrinsic and extrinsic determinants of benefit/risk of drugs and our often incomplete understanding of the role of these factors, particularly in under-represented racial groups, as reviewed for direct oral anticoagulants by Thompson et al 13 With the exponential increase in our ability to harness multi-modal data and digital technologies, translation of our understanding of population sources of variability to precision dosing solutions for all patients is an opportunity for intelligent clinical decision support systems, as reviewed by Hughes et al 14 We are witnessing substantial progress in the science and technology required to develop EDITORIAL intelligent, continuously learning precision dosing systems driven by population pharmacology models built from clinical trial and real-world data in diverse populations. [14][15][16] Translating scientific and medical advances to equity in health care will, however, need to consider and address the critically important extrinsic factor of Social Determinants of Health through innovative health system, public health, and policylevel interventions, as eloquently discussed by Golden 17 -reflecting her compelling State of the Art lecture at the ASCPT 2022 Annual Meeting.…”