Adherence to antiretroviral (ARV) therapy is critical for achieving HIV RNA suppression in HIV-infected patients and for preventing HIV acquisition in uninfected individuals using pre-exposure prophylaxis (PrEP). Yet a high level of adherence is challenging for HIV-infected individuals on life-long ARVs, and for HIV-negative individuals using daily PrEP who are not at daily risk for HIV acquisition. Poor adherence was primarily responsible for a lack of drug effectiveness in multiple recent double-blind, placebo-controlled PrEP studies. These studies found that counting product returns and using patient self-report significantly over predicted adherence as measured by ARV concentrations in blood plasma or cells. Since the consequences of poor or intermittent adherence are significant, valid measures of adherence are critical for optimizing the effectiveness of both HIV treatment and prevention, in both the clinic and research settings. Blood plasma or intracellular concentration monitoring have been considered the gold standard for determining if an ARV has been ingested, and is a common marker for therapeutic drug monitoring or clinical trial adherence monitoring. However, this approach has its own set of limitations, including being invasive, requiring advanced processing or storage (e.g. intracellular measures), being a short-term measure of drug taking behavior (depending on the half-life of the analyte), and requiring long turn-around times or substantial sample processing prior to analysis. We propose the use of infra-red (IR) matrix-assisted laser desorption electrospray ionization (MALDESI) technology for mass spectrometry imaging (MSI) to visualize and quantify ARV concentrations in hair. Our hypothesis is that IR-MALDESI MSI can rapidly quantify ARV concentrations, provide evidence of drug ingestion non-invasively and longitudinally, and allow for clinician/researcher and patient/study participant feedback on adherence performance.
Three specific aims are proposed: 1) Develop IR-MALDESI MSI hair protocols for high sensitivity and accuracy to quantify 11 ARVs in 5 therapeutic drug classes, 2) Conduct 3 structured dose proportionality studies to develop mathematical benchmarks for real-time IR-MALDESI hair adherence monitoring in both PrEP and HIV treatment applications, and validate the benchmarks with a Phase 2 PrEP study, and 3) In the setting of REAL TIME clinical monitoring, investigate the acceptability, appropriateness, and feasibility of using hair IR-MALDESI MSI to provide HIV+ patients with feedback regarding longitudinal patterns of medication adherence. The goal of this work is to develop a simple, noninvasive, longitudinal depiction of ARV adherence that will provide high clarity feedback for both clinicians and patients.

Public Health Relevance

It is important to identify if someone is taking a medication regularly and as prescribed to optimize their health and wellbeing. Sometimes, patients have trouble remembering if and when they miss doses; other times, even though patients are taking their medication, it is not getting into the body in the right amount. Quickly monitoring medications in 5-10 hair strands using our novel imaging technology called IR-MALDESI will allow patients and their doctors to see how much medication they are exposed to over 1 or more months, and help identify challenges to taking medication in both research and clinical settings. This proposal will optimize and explore the acceptability and feasibility of using IR-MALDESI for monitoring medications in hair.

Agency
National Institute of Health (NIH)
Institute
National Institute of Allergy and Infectious Diseases (NIAID)
Type
Research Project (R01)
Project #
5R01AI122319-02
Application #
9198479
Study Section
Special Emphasis Panel (ZAI1)
Program Officer
Zhang, Hao
Project Start
2016-01-01
Project End
2020-12-31
Budget Start
2017-01-01
Budget End
2017-12-31
Support Year
2
Fiscal Year
2017
Total Cost
Indirect Cost
Name
University of North Carolina Chapel Hill
Department
Pharmacology
Type
Schools of Pharmacy
DUNS #
608195277
City
Chapel Hill
State
NC
Country
United States
Zip Code
27599
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Gonzalez, Daniel; Rao, Gauri G; Bailey, Stacy C et al. (2017) Precision Dosing: Public Health Need, Proposed Framework, and Anticipated Impact. Clin Transl Sci 10:443-454