2.4: Renal Drug Dosing

Keyword(s):  
2021 ◽  
Vol 14 (5) ◽  
pp. 472
Author(s):  
Tyler C. Beck ◽  
Kyle R. Beck ◽  
Jordan Morningstar ◽  
Menny M. Benjamin ◽  
Russell A. Norris

Roughly 2.8% of annual hospitalizations are a result of adverse drug interactions in the United States, representing more than 245,000 hospitalizations. Drug–drug interactions commonly arise from major cytochrome P450 (CYP) inhibition. Various approaches are routinely employed in order to reduce the incidence of adverse interactions, such as altering drug dosing schemes and/or minimizing the number of drugs prescribed; however, often, a reduction in the number of medications cannot be achieved without impacting therapeutic outcomes. Nearly 80% of drugs fail in development due to pharmacokinetic issues, outlining the importance of examining cytochrome interactions during preclinical drug design. In this review, we examined the physiochemical and structural properties of small molecule inhibitors of CYPs 3A4, 2D6, 2C19, 2C9, and 1A2. Although CYP inhibitors tend to have distinct physiochemical properties and structural features, these descriptors alone are insufficient to predict major cytochrome inhibition probability and affinity. Machine learning based in silico approaches may be employed as a more robust and accurate way of predicting CYP inhibition. These various approaches are highlighted in the review.


2020 ◽  
Vol 12 ◽  
pp. 175883592097411
Author(s):  
Natalie Reizine ◽  
Everett E. Vokes ◽  
Ping Liu ◽  
Tien M. Truong ◽  
Rita Nanda ◽  
...  

Background: Many cancer patients who receive chemotherapy experience adverse drug effects. Pharmacogenomics (PGx) has promise to personalize chemotherapy drug dosing to maximize efficacy and safety. Fluoropyrimidines and irinotecan have well-known germline PGx associations. At our institution, we have delivered PGx clinical decision support (CDS) based on preemptively obtained genotyping results for a large number of non-oncology medications since 2012, but have not previously evaluated the utility of this strategy for patients initiating anti-cancer regimens. We hypothesize that providing oncologists with preemptive germline PGx information along with CDS will enable individualized dosing decisions and result in improved patient outcomes. Methods: Patients with oncologic malignancies for whom fluoropyrimidine and/or irinotecan-inclusive therapy is being planned will be enrolled and randomly assigned to PGx and control arms. Patients will be genotyped in a clinical laboratory across panels that include actionable variants in UGT1A1 and DPYD. For PGx arm patients, treating providers will be given access to the patient-specific PGx results with CDS prior to treatment initiation. In the control arm, genotyping will be deferred, and dosing will occur as per usual care. Co-primary endpoints are dose intensity deviation rate (the proportion of patients receiving dose modifications during the first treatment cycle), and grade ⩾3 treatment-related toxicities throughout the treatment course. Additional study endpoints will include cumulative drug dose intensity, progression-free survival, dosing of additional PGx supportive medications, and patient-reported quality of life and understanding of PGx. Discussion: Providing a platform of integrated germline PGx information may promote personalized chemotherapy dosing decisions and establish a new model of care to optimize oncology treatment planning.


2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Shota Ichikawa ◽  
Misaki Hamada ◽  
Hiroyuki Sugimori

AbstractBody weight is an indispensable parameter for determination of contrast medium dose, appropriate drug dosing, or management of radiation dose. However, we cannot always determine the accurate patient body weight at the time of computed tomography (CT) scanning, especially in emergency care. Time-efficient methods to estimate body weight with high accuracy before diagnostic CT scans currently do not exist. In this study, on the basis of 1831 chest and 519 abdominal CT scout images with the corresponding body weights, we developed and evaluated deep-learning models capable of automatically predicting body weight from CT scout images. In the model performance assessment, there were strong correlations between the actual and predicted body weights in both chest (ρ = 0.947, p < 0.001) and abdominal datasets (ρ = 0.869, p < 0.001). The mean absolute errors were 2.75 kg and 4.77 kg for the chest and abdominal datasets, respectively. Our proposed method with deep learning is useful for estimating body weights from CT scout images with clinically acceptable accuracy and potentially could be useful for determining the contrast medium dose and CT dose management in adult patients with unknown body weight.


Author(s):  
Jurjen S. Kingma ◽  
Desirée M. T. Burgers ◽  
Valerie M. Monpellier ◽  
Marinus J. Wiezer ◽  
Heleen J. Blussé van Oud‐Alblas ◽  
...  

2020 ◽  
Vol 11 ◽  
pp. 204209862095891
Author(s):  
Aisling R. Caffrey ◽  
Eric P. Borrelli

A “one-size-fits-all” approach has been the standard for drug dosing, in particular for agents with a wide therapeutic index. The scientific principles of drug titration, most commonly used for medications with a narrow therapeutic index, are to give the patient adequate and effective treatment, at the lowest dose possible, with the aim of minimizing unnecessary medication use and side effects. The art of drug titration involves the interplay of scientific drug titration principles with the clinical expertise of the healthcare provider, and an individualized, patient-centered partnership between the provider and the patient to review the delicate balance of perceived benefits and risks from both perspectives. Drug titration may occur as up-, down-, or cross-titration depending on whether the goal is to reach or maintain a therapeutic outcome, decrease the risk of adverse effects, or prevent withdrawal/discontinuation syndromes or recurrence of disease. Drug titration introduces additional complexities surrounding the conduct of clinical trials and real-world studies, confounding our understanding of the true effect of medications. In clinical practice, wide variations in titration schedules may exist due to a lack of evidence and consensus on titration approaches that achieve an optimal benefit-harm profile. Further, drug titration may be challenging for patients to follow, resulting in suboptimal adherence and may require increased healthcare-related visits and coordination of care amongst providers. Despite the challenges associated with drug titration, it is a personalized approach to drug dosing that blends science with art, and with supportive real-world outcomes-based evidence, can be effective for optimizing pharmacotherapeutic outcomes and improving drug safety.


2021 ◽  
pp. 106002802110102
Author(s):  
Janine Miller ◽  
John P. Knorr

Background The appropriateness of including the race coefficient in glomerular filtration rate (GFR) equations in Black patients is debated, and the impact on drug dosing is unknown. Objective This study explored the impact of removing the race coefficient on drug dosing in Black patients in comparison to conventional methods. Methods This was a retrospective study of hospitalized patients who self-identified as Black/African American and were prescribed an antimicrobial that includes renal dosage recommendations in the product labeling. The primary end point was the discordance between drug dosing recommendations derived by body surface area deindexed GFR estimated by the CKD-EPI equation (Chronic Kidney Disease Epidemiology study) with and without race versus recommendations derived from Cockcroft-Gault (CG). Results A total of 210 Black patients were included. There was an 18% rate of discordance when GFR was estimated with the race coefficient (GFR w/Race) versus without the race coefficient (GFR w/out Race). GFR w/out Race had a higher level of agreement with dosing by creatinine clearance (CrCl; κ = 0.779) than GFR w/Race versus CrCl (κ = 0.651). GFR w/out Race had less within-patient difference than GFR w/Race in comparison to CrCl (mean difference: −6.3 vs −18.0 mL/min). Conclusions and Relevance This represents the first report to examine the removal of the race coefficient and its implication on drug dose discordance. GFR w/out Race had a higher level of agreement and less drug dose discordance than GFR w/Race, in comparison to CrCl estimates. If GFR equations are considered comparable to CrCl for the purposes of guiding drug dosing, GFR w/out Race should be considered.


1993 ◽  
Vol 94 (8) ◽  
pp. 153-164 ◽  
Author(s):  
George L. Bakris ◽  
Robert Talbert

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