An official website of the United States government
Abstract Intranasal diamorphine (IND), approved for managing breakthrough pain in the UK, has been identified as an acceptable alternative offering effective, expedient, and less traumatic analgesia for children. However, the current dose regimen in pediatric populations relies on clinical expertise while the pharmacokinetics properties are poorly understood. This study aimed to develop diamorphine population pharmacokinetics (pop‐PK) models and simulate the IND dosing in virtual pediatric subjects. An integrated four‐compartment pop‐PK model with first‐order absorption and elimination provided an appropriate fit and characterized publicly available 385 concentration measurements of diamorphine, 6‐monoacetylmorphine, and morphine collected from adults. Body weight allometry and renal function maturation (age) were incorporated into the final model, serving as two covariates. The estimated IND relative bioavailability was around 52% compared with intramuscularly injected diamorphine. Using this final model, the morphine plasma concentrations, as the active metabolite for pain relief, were simulated in virtual subjects. The utility of model extrapolation was supported by external verification with acceptable average fold errors of 1.06 ± 0.30 and 0.83 ± 0.07 for morphine maximum concentration and exposures. Meanwhile, the simulated morphine concentration–time profiles could recover the PK profiles observed in children after a single dose of IND. The model‐based dosing simulations were therefore assessed in four children age groups to match the therapeutic window of morphine concentrations in steady state (10–20 μg/L). Our study demonstrates that the dose regimen of 0.3 mg/kg loading dose plus 0.1 mg/kg hourly maintenance dose is generally appropriate for multiple pediatric populations with breakthrough pain, in the view of PK.
more »
« less
Physiologically-Based Pharmacokinetics Modeling for Hydroxychloroquine as a Treatment for Malaria and Optimized Dosing Regimens for Different Populations
Malaria is a severe parasite infectious disease with high fatality. As one of the approved treatments of this disease, hydroxychloroquine (HCQ) lacks clinical administration guidelines for patients with special health conditions and co-morbidities. This may result in improper dosing for different populations and lead them to suffer from severe side effects. One of the most important toxicities of HCQ overdose is cardiotoxicity. In this study, we built and validated a physiologically based pharmacokinetic modeling (PBPK) model for HCQ. With the full-PBPK model, we predicted the pharmacokinetic (PK) profile for malaria patients without other co-morbidities under the HCQ dosing regimen suggested by Food and Drug Administration (FDA) guidance. The PK profiles for different special populations were also predicted and compared to the normal population. Moreover, we proposed a series of adjusted dosing regimens for different populations with special health conditions and predicted the concentration-time (C-T) curve of the drug plasma concentration in these populations which include the pregnant population, elderly population, RA patients, and renal impairment populations. The recommended special population-dependent dosage regimens can maintain the similar drug levels observed in the virtual healthy population under the original dosing regimen provided by FDA. Last, we developed mathematic formulas for predicting dosage based on a patient’s body measurements and two indexes of renal function (glomerular filtration rate and serum creatine level) for the pediatric and morbidly obese populations. Those formulas can facilitate personalized treatment of this disease. We hope to provide some advice to clinical practice when taking HCQ as a treatment for malaria patients with special health conditions or co-morbidities so that they will not suffer from severe side effects due to higher drug plasma concentration, especially cardiotoxicity.
more »
« less
- Award ID(s):
- 1955260
- PAR ID:
- 10432629
- Date Published:
- Journal Name:
- Journal of Personalized Medicine
- Volume:
- 12
- Issue:
- 5
- ISSN:
- 2075-4426
- Page Range / eLocation ID:
- 796
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
More Like this
-
-
Abstract AimsTo discover alternative dosing regimens of incretin mimetics that simultaneously reduce costs and maintain weight loss efficacy. As a secondary objective, we used our results to explore how allocating a limited incretin mimetics budget could affect public health on a national scale. Materials and MethodsWe used mathematical modelling and simulation of semaglutide and tirzepatide to investigate dosing regimens which have not yet been studied clinically. For semaglutide, we used a recent pharmacokinetic (PK) and pharmacodynamic (PD) model. For tirzepatide, we used a recent PK model and modelled PD by reparameterizing the semaglutide PD model to fit tirzepatide clinical data. ResultsReducing dose frequency does not commensurately reduce weight loss. For example, merely switching from one dose per week (q1wk) to one dose every 2 weeks (q2wk) maintains roughly 75% of the weight loss. Furthermore, if the decrease in dose frequency involves an appropriate increase in dose size, then approximately 100% of the weight loss is maintained. In addition, we compared offering incretin mimetics to (1) a fraction of obese US adults with q1wk dosing versus (2) twice as many obese US adults with q2wk dosing. Though scenarios (1) and (2) require the same budget, our analysis suggests that (2) reduces national obesity and mortality to a much greater degree. ConclusionOur study highlights the potential utility of alternative dosing regimens of incretin mimetics. Compared with standard once‐weekly dosing, costs can be halved and weight loss maintained. These cost‐saving results have implications for patients, physicians, insurers, and governments.more » « less
-
The antiviral remdesivir has been approved by regulatory bodies such as the European Medicines Agency (EMA) and the US Food and Drug administration (FDA) for the treatment of COVID-19. However, its efficacy is debated and toxicity concerns might limit the therapeutic range of this drug. Computational models that aid in balancing efficacy and toxicity would be of great help. Parametrizing models is difficult because the prodrug remdesivir is metabolized to its active form (RDV-TP) upon cell entry, which complicates dose–activity relationships. Here, we employ a computational model that allows drug efficacy predictions based on the binding affinity of RDV-TP for its target polymerase in SARS-CoV-2. We identify an optimal infusion rate to maximize remdesivir efficacy. We also assess drug efficacy in suppressing both wild-type and resistant strains, and thereby describe a drug regimen that may select for resistance. Our results differ from predictions using prodrug dose–response curves (pseudo-EC50s). We expect that reaching 90% inhibition (EC90) is insufficient to suppress SARS-CoV-2 in the lungs. While standard dosing mildly inhibits viral polymerase and therefore likely reduces morbidity, we also expect selection for resistant mutants for most realistic parameter ranges. To increase efficacy and safeguard against resistance, we recommend more clinical trials with dosing regimens that substantially increase the levels of RDV-TP and/or pair remdesivir with companion antivirals.more » « less
-
Population pharmacokinetic (PK) modeling has become a cornerstone of drug development and optimal patient dosing. This approach offers great benefits for datasets with sparse sampling, such as in pediatric patients, and can describe between-patient variability. While most current algorithms assume normal or log-normal distributions for PK parameters, we present a mathematically consistent nonparametric maximum likelihood (NPML) method for estimating multivariate mixing distributions without any assumption about the shape of the distribution. This approach can handle distributions with any shape for all PK parameters. It is shown in convexity theory that the NPML estimator is discrete, meaning that it has finite number of points with nonzero probability. In fact, there are at most N points where N is the number of observed subjects. The original infinite NPML problem then becomes the finite dimensional problem of finding the location and probability of the support points. In the simplest case, each point essentially represents the set of PK parameters for one patient. The probability of the points is found by a primal-dual interior-point method; the location of the support points is found by an adaptive grid method. Our method is able to handle high-dimensional and complex multivariate mixture models. An important application is discussed for the problem of population pharmacokinetics and a nontrivial example is treated. Our algorithm has been successfully applied in hundreds of published pharmacometric studies. In addition to population pharmacokinetics, this research also applies to empirical Bayes estimation and many other areas of applied mathematics. Thereby, this approach presents an important addition to the pharmacometric toolbox for drug development and optimal patient dosing.more » « less
-
BackgroundDoxorubicin and other anthracyclines are crucial cancer treatment drugs. However, they are associated with significant cardiotoxicity, severely affecting patient care and limiting dosage and usage. Previous studies have shown that low carbon monoxide (CO) concentrations protect against doxorubicin toxicity. However, traditional methods of CO delivery pose complex challenges for daily administration, such as dosing and toxicity. To address these challenges, we developed a novel oral liquid drug product containing CO (HBI‐002) that can be easily self‐administered by patients with cancer undergoing doxorubicin treatment, resulting in CO being delivered through the upper gastrointestinal tract. Methods and ResultsHBI‐002 was tested in a murine model of doxorubicin cardiotoxicity in the presence and absence of lung or breast cancer. The mice received HBI‐002 twice daily before doxorubicin administration and experienced increased carboxyhemoglobin levels from a baseline of ≈1% to 7%. Heart tissue from mice treated with HBI‐002 had a 6.3‐fold increase in CO concentrations and higher expression of the cytoprotective enzyme heme oxygenase‐1 compared with placebo control. In both acute and chronic doxorubicin toxicity scenarios, HBI‐002 protected the heart from cardiotoxic effects, including limiting tissue damage and cardiac dysfunction and improving survival. In addition, HBI‐002 did not compromise the efficacy of doxorubicin in reducing tumor volume, but rather enhanced the sensitivity of breast 4T1 cancer cells to doxorubicin while simultaneously protecting cardiac function. ConclusionsThese findings strongly support using HBI‐002 as a cardioprotective agent that maintains the therapeutic benefits of doxorubicin cancer treatment while mitigating cardiac damage.more » « less
- Free Publicly Accessible Full Text
-
Accepted Manuscript1.0
- Journal Article:
- https://doi.org/10.3390/jpm12050796
