Applications and challenges in therapeutic drug monitoring of cancer treatment: A review

2020 ◽  
pp. 107815522097904
Author(s):  
Bushra Salman ◽  
Murtadha Al-Khabori
Keyword(s):  
Therapeutic Drug Monitoring ◽  
Anticancer Agents ◽  
Drug Monitoring ◽  
Cancer Therapeutics ◽  
Therapeutic Index ◽  
Therapeutic Drug ◽  
Narrow Therapeutic Index ◽  
Dose Individualization ◽  
Therapeutic Outcomes ◽  
Wide Variability

Most anticancer agents show wide variability in pharmacokinetics (PK) and have a narrow therapeutic index which makes fixed dosing suboptimal. To achieve the best therapeutic outcomes with these agents, many studies have postulated using PK or therapeutic drug monitoring (TDM)-guided dosing. However, multiple factors contribute to the variability in PKs making the application of TDM in practice challenging. Also, despite the known association with clinical outcomes, standard guidelines on PK-guided dosing are lacking for most agents. Understanding the factors that contribute to PK variability and their impact is essential for dose individualization. The purpose of this review is to discuss the factors that contribute to the PK variability of anticancer agents and the challenges faced in practice when individualizing doses for certain widely used agents. Searching the literature has identified several gaps and efforts are needed to ensure better targeting of cancer therapeutics.

scholarly journals Validasi Metode Bioanalisis Vankomisin HCl dalam Spiked-plasma Manusia Menggunakan KCKT-UV untuk Aplikasi PKOD

2019 ◽  
Vol 19 (1) ◽  
pp. 57-70
Author(s):  
Ari Wibowo ◽  
Damas Inggil Maulidina ◽  
Wahyuni Shalatan Fitri ◽  
Vitarani Ningrum
Keyword(s):  
Staphylococcus Aureus ◽  
Therapeutic Drug Monitoring ◽  
Drug Monitoring ◽  
Methicillin Resistant Staphylococcus Aureus ◽  
Therapeutic Index ◽  
Therapeutic Drug ◽  
Pharmacokinetic Variability ◽  
First Line ◽  
Narrow Therapeutic Index ◽  
Spiked Plasma

As the first-line antibiotic for the treatment of infections caused by methicillin-resistant Staphylococcus aureus  (MRSA), vancomycin has  a narrow therapeutic index with high pharmacokinetic   variability. Therefore, it is deemed necessary to examine its concentration in the blood as a strategy to monitor the fulfillment of therapeutic levels  in patients receiving vancomycin. This study aimed to validate vancomycin bioanalysis  in  spiked-human  plasma  for  the  applications  of  therapeutic  drug  monitoring  (TDM).

scholarly journals Therapeutic Drug Monitoring of Cytotoxic Drugs

2020 ◽  
Vol 10 (02) ◽  
pp. 284-291
Author(s):  
Qutaiba Ahmad Al Khames Aga ◽  
Yazan A. Bataineh ◽  
Hala Mousa Sbaih
Keyword(s):  
Therapeutic Drug Monitoring ◽  
Drug Monitoring ◽  
Malignant Tumors ◽  
Therapeutic Index ◽  
Review Article ◽  
Cytotoxic Drugs ◽  
Therapeutic Drug ◽  
Narrow Therapeutic Index ◽  
Time Curve ◽  
The Common

The majority of anticancer drugs are recognized with a narrow therapeutic index, the area under the plasma levels vs. time curve (AUC) is the common pharmacokinetic (PK) parameter, which utilizes specifically for cytotoxic drugs. Therapeutic drug monitoring (TDM) approach in these drugs has never been completely applied due to different reasons, for example, the use of combination chemotherapies for different malignant tumors, and the behavior of intracellular compounds; it is possible to eliminate these limitations by using specific concentrations of cytotoxic drugs and measure AUC after certain conditions. In this review article, we discussed the common TDM parameters, methods of analysis, and some of drug interactions for a group of cytotoxic drugs.

Therapeutic drug monitoring in cancer management

1993 ◽  
Vol 39 (11) ◽  
pp. 2419-2430 ◽  
Author(s):  
A J Galpin ◽  
W E Evans
Keyword(s):  
Therapeutic Drug Monitoring ◽  
Anticancer Drugs ◽  
Drug Monitoring ◽  
Therapeutic Index ◽  
Concentration Effect ◽  
Therapeutic Drug ◽  
Pharmacokinetic Studies ◽  
Narrow Therapeutic Index ◽  
Cancer Management ◽  
Definition Of

Abstract Several anticancer drugs display characteristics that make them suitable candidates for therapeutic drug monitoring (TDM), including substantial pharmacokinetic variability and a narrow therapeutic index. However, concentration-effect relationships (pharmacodynamics) of most antineoplastic agents have not been well defined, thus limiting the widespread clinical application of TDM for cancer chemotherapy. Strategic incorporation of pharmacokinetic studies during phase I-III clinical trials should facilitate the identification of concentration-effect relationships and the definition of clinically useful levels of treatment intensity. We review representative clinical studies that have defined pharmacodynamic relationships for methotrexate, teniposide, etoposide, carboplatin, and mercaptopurine. Given that TDM has impacted positively on the clinical use of many drugs belonging to other therapeutic classes, and that pharmacodynamic correlations have been identified in several recent studies of anticancer drugs, we consider implementation of TDM a rational strategy for optimizing the use of selected antineoplastics.

scholarly journals Model-Optimized Fluconazole Dose Selection for Critically Ill Patients Improves Early Pharmacodynamic Target Attainment without the Need for Therapeutic Drug Monitoring

2020 ◽  
Vol 65 (3) ◽  
Author(s):  
Indy Sandaradura ◽  
Jessica Wojciechowski ◽  
Deborah J. E. Marriott ◽  
Richard O. Day ◽  
Sophie Stocker ◽  
...  
Keyword(s):  
Therapeutic Drug Monitoring ◽  
Critically Ill ◽  
Drug Monitoring ◽  
Critically Ill Patients ◽  
Drug Exposure ◽  
Fungal Infections ◽  
Therapeutic Drug ◽  
Target Attainment ◽  
Dose Selection ◽  
Dose Individualization

ABSTRACT Fluconazole has been associated with higher mortality compared with the echinocandins in patients treated for invasive candida infections. Underexposure from current fluconazole dosing regimens may contribute to these worse outcomes, so alternative dosing strategies require study. The objective of this study was to evaluate fluconazole drug exposure in critically ill patients comparing a novel model-optimized dose selection method with established approaches over a standard 14-day (336-h) treatment course. Target attainment was evaluated in a representative population of 1,000 critically ill adult patients for (i) guideline dosing (800-mg loading and 400-mg maintenance dosing adjusted to renal function), (ii) guideline dosing followed by therapeutic drug monitoring (TDM)-guided dose adjustment, and (iii) model-optimized dose selection based on patient factors (without TDM). Assuming a MIC of 2 mg/liter, free fluconazole 24-h area under the curve (fAUC24) targets of ≥200 mg · h/liter and <800 mg · h/liter were used for assessment of target attainment. Guideline dosing resulted in underexposure in 21% of patients at 48 h and in 23% of patients at 336 h. The TDM-guided strategy did not influence 0- to 48-h target attainment due to inherent procedural delays but resulted in 37% of patients being underexposed at 336 h. Model-optimized dosing resulted in ≥98% of patients meeting efficacy targets throughout the treatment course, while resulting in less overexposure compared with guideline dosing (7% versus 14%) at 336 h. Model-optimized dose selection enables fluconazole dose individualization in critical illness from the outset of therapy and should enable reevaluation of the comparative effectiveness of this drug in patients with severe fungal infections.

scholarly journals 1101. Implementing a Beta-Lactam Therapeutic Drug Monitoring Program: Experience from a Large Academic Medical Center

2021 ◽  
Vol 8 (Supplement_1) ◽  
pp. S642-S642
Author(s):  
Venugopalan Veena ◽  
Malva Hamza ◽  
Barbara A Santevecchi ◽  
Kathryn DeSear ◽  
Kartikeya Cherabuddi ◽  
...  
Keyword(s):  
Therapeutic Drug Monitoring ◽  
Drug Monitoring ◽  
Dosage Adjustment ◽  
Total Serum ◽  
Therapeutic Drug ◽  
Beta Lactam ◽  
Dose Individualization ◽  
Material Support ◽  
Drug Concentrations ◽  
Drug Registry

Abstract Background Beta-lactams (BL) are the cornerstone of antimicrobial treatment for infections. Beta-lactam therapeutic drug monitoring (BL-TDM) optimizes drug concentrations to ensure maximal efficacy and minimal toxicity. The goals of this study were to describe the implementation process of a BL-TDM program and to further describe our experience using BL-TDM in clinical practice. Methods This was a retrospective review of adult patients with available BL-TDM between January 2016 and November 2019 at the University of Florida (UF) Health Shands Hospital. Total serum concentrations of BL were measured in the Infectious Diseases Pharmacokinetics Lab (IDPL) at UF, using a validated ultrahigh pressure liquid chromatography assay with triple quadrupole mass spectroscopy (LC-MS-MS). At our institution, TDM is available for 11 BLs and in-house assays are performed from Mon-Fri for most BLs. Results A total of 3,030 BL concentrations were obtained. An analysis was performed on the first BL-TDM encounter in 1,438 patients. The median age was 57 years (IQR, 41-69) and the median BMI was 27.5 kg/m2 (IQR, 22.5-34.5). On the day of BL-TDM, the median serum creatinine was 0.83 (IQR, 0.59-1.30). Fifty-one percent of patients (n=735) were in an ICU at the time of BL-TDM with a median SOFA score of 6 (IQR, 3-9). BL-TDM was most frequently performed on cefepime (61%, n=882), piperacillin (15%, n=218), and meropenem (11%, n=151). The BL was administered as a continuous infusion in 211 (15%) patients. An interim analysis of 548 patients showed that BL-TDM was performed a median of 2 days (IQR, 1-4) from the start of BL therapy and resulted in a dosage adjustment in 26% (n=145). Conclusion BL-TDM was performed in older, non-obese patients with normal renal function. Over half of the evaluated patients were in an ICU at the time of TDM. This finding emphasizes the value of BL-TDM in the ICU setting because altered pharmacokinetics during critical illness has been linked to enhanced BL clearance. Interestingly, BL-TDM resulted in dosage adjustment in 1 in 4 patients who were receiving licensed BL dosing regimens, thus highlighting the role of TDM in dose individualization. BL-TDM was performed most commonly within the 72-hours of therapy initiation. Early BL-TDM has been shown to improve patient outcomes and should be promoted. Disclosures Venugopalan Veena, PharmD, Melinta (Other Financial or Material Support, Received a stipend for participation in a drug registry)Merck (Other Financial or Material Support, Received a stipend for participation in a drug registry) Charles A. Peloquin, Pharm.D., Nothing to disclose

scholarly journals Personalized drug concentration predictions with machine learning: an exploratory study

2020 ◽  
Vol 9 (6) ◽  
pp. 980
Author(s):  
Danish Shakeel ◽  
Shakeel Ahmad Mir
Keyword(s):  
Machine Learning ◽  
Therapeutic Drug Monitoring ◽  
Regression Model ◽  
Drug Monitoring ◽  
Drug Level ◽  
Therapeutic Drug ◽  
Reference Ranges ◽  
Dose Individualization ◽  
Out Of Sample ◽  
Blood Drug Level

Background: The dose individualization by therapeutic drug monitoring (TDM) can be improved if population-based reference ranges are available, as there is large inter- and intrapatient variability. If these ranges are not available, dose individualization may not be optimal. Machine learning can help achieve accurate drug dose settings and predict the resultant levels.Methods: Two random forest models, a multi-class classifier to predict dose and a regression model to predict blood drug level were trained on 320 patients’ data, consisting of their age, sex, dose and blood drug level. The classifier consisted of 1000 estimators (decision trees) and the regression model consisted of 1300 estimators. The model was evaluated on randomly split test set having 10% of the total dataset size. The regression model was compared against k-Nearest neighbor and linear regression models. The classifier was evaluated using accuracy, precision, and F1 Score; the regression model was evaluated using R2, Root mean squared error, and mean absolute error.Results: The classifier had an out-of-sample accuracy of 68.75%, average precision of 0.7567, and an average F1 score of 0.6907. The regression model had an out-of-sample R2 value of 0.2183, root mean squared value of 3.7359, and a mean absolute error of 2.5156. These values signify an average classification performance, and a below-average regression performance due to small dataset.Conclusions: It is possible for machine learning algorithms to be used in therapeutic drug monitoring. With a well-structured, rich, and large dataset, a very accurate model can be built.

scholarly journals Advances in Therapeutic Drug Monitoring in Biologic Therapies for Pediatric Inflammatory Bowel Disease

2021 ◽  
Vol 9 ◽  
Author(s):  
Akshay Kapoor ◽  
Eileen Crowley
Keyword(s):  
Inflammatory Bowel Disease ◽  
Therapeutic Drug Monitoring ◽  
Bowel Disease ◽  
Drug Monitoring ◽  
Drug Exposure ◽  
Therapeutic Drug ◽  
Dose Individualization ◽  
Loss Of Response ◽  
Fixed Weight ◽  
Inflammatory Bowel

In the current era of treat-to-target strategies, therapeutic drug monitoring (TDM) has emerged as a potential tool in optimizing the efficacy of biologics for children diagnosed with inflammatory bowel disease (IBD). The incorporation of TDM into treatment algorithms, however, has proven to be complex. “Proactive” TDM is emerging as a therapeutic strategy due to a recently published pediatric RCT showing a clear benefit of “proactive” TDM in anti-TNF therapy. However, target therapeutic values for different biologics for different disease states [ulcerative colitis (UC) vs. Crohn's disease (CD)] and different periods of disease activity (induction vs. remission) require further definition. This is especially true in pediatrics where the therapeutic armamentarium is limited, and fixed weight-based dosing may predispose to increased clearance leading to decreased drug exposure and subsequent loss of response (pharmacokinetic and/or immunogenic). Model-based dosing for biologics offers an exciting insight into dose individualization thereby minimizing the chances of losing response. Similarly, point-of-care testing promises real-time assessment of drug levels and individualized decision-making. In the current clinical realm, TDM is being used to prolong drug durability and efficacy and prevent loss of response. Ongoing innovations may transform it into a personalized tool to achieve optimal therapeutic endpoints.

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