Semi-Automated Therapeutic Drug Monitoring as a Pillar toward Personalized Medicine for Tuberculosis Management

Abstract

Standard tuberculosis (TB) management has failed to control the growing number of drug-resistant TB cases worldwide. Therefore, innovative approaches are required to eradicate TB. Model-informed precision dosing and therapeutic drug monitoring (TDM) have become promising tools for adjusting anti-TB drug doses corresponding with individual pharmacokinetic profiles. These are crucial to improving the treatment outcome of the patients, particularly for those with complex comorbidity and a high risk of treatment failure. Despite the actual benefits of TDM at the bedside, conventional TDM encounters several hurdles related to laborious, time-consuming, and costly processes. Herein, we review the current practice of TDM and discuss the main obstacles that impede it from successful clinical implementation. Moreover, we propose a semi-automated TDM approach to further enhance precision medicine for TB management.

Advancing personalized medicine for tuberculosis through the application of immune profiling

“…Our recent review paper has proposed a novel strategy by incorporating semi-automated TDM using MIPD as a pillar of TB treatment (Jayanti et al, 2022). MIPD-based TDM has three approaches for its implementation, which incorporate a mechanistic approach, physiologically based pharmacokinetic modeling and simulation (PBPK), a data-driven approach (population PK), and a combination of both.…”

Push forward LC-MS-based therapeutic drug monitoring and pharmacometabolomics for anti-tuberculosis precision dosing and comprehensive clinical management

“…Jayanti et al. [ 134 ] proposed a straightforward, rapid, and affordable semi-automated TDM procedure associated with MIPD and the clinical setting. After sampling and data collection, the validated popPK and Bayesian forecasting methods were used to estimate PK parameters for the individual patient.…”

“…After sampling and data collection, the validated popPK and Bayesian forecasting methods were used to estimate PK parameters for the individual patient. This enables clinicians to simulate the PK profile of each drug for each patient in different scenarios, thereby promoting the administration and adjustment of dosage regimens corresponding to the results from the simulation and targeted therapy [ 134 ]. Incorporating immune profiling into MIPD-based TDM may also be beneficial [ 135 ].…”

“…This offers convenience and reduces the burden on patients, clinical practitioners, and laboratory staff. In addition, owing to the development of technological information and computational capability, MIPD platforms have been developed, implemented, validated, and refined to integrate all available insights into optimizing the dosage regimens of anti-TB drugs [ 108 , 134 ]. As a result, these “predictive” metabolites along with other covariates would enhance the feasibility of population-based doses and might predict the efficacy and unexpected ADRs for prospective patients.…”

Individualized antibiotic dosage regimens for patients with augmented renal clearance

“…As an approach to accurately determining the target concentration of drugs, TDM technologies show their advantages in drug dose adjustment. More rapid, convenient, and accurate technologies, such as point-of-care testing ( Irving and Gecse, 2022 ), and semi-automated TDM( Jayanti et al, 2022 ), are being vigorously developed. Finally, another limitation in this review was the English-language restriction.…”