RESUMEN

Target controlled infusion (TCI) is a clinically-available and widely-used computer-controlled method of drug administration, adjusting the drug titration towards user selected plasma- or effect-site concentrations, calculated according to pharmacokinetic-pharmacodynamic (PKPD) models. Although this technology is clinically available for several anaesthetic drugs, the contemporary commercialised PKPD models suffer from multiple limitations. First, PKPD models for anaesthetic drugs are developed using deliberately selected patient populations, often excluding the more challenging populations, such as children, obese or elderly patients, of whom the body composition or elimination mechanisms may be structurally different compared to the lean adult patient population. Separate PKPD models have been developed for some of these subcategories, but the availability of multiple PKPD models for a single drug increases the risk for invalid model selection by the user. Second, some models are restricted to the prediction of plasma-concentration without enabling effect-site controlled TCI or they identify the effect-site equilibration rate constant using methods other than PKPD modelling. Advances in computing and the emergence of globally collected databases has allowed the development of new "general purpose" PKPD models. These take on the challenging task of identifying the relationships between patient covariates (age, weight, sex, etc) and the volumes and clearances of multi-compartmental pharmacokinetic models applicable across broad populations from neonates to the elderly, from the underweight to the obese. These models address the issues of allometric scaling of body weight and size, body composition, sex differences, changes with advanced age, and for young children, changes with maturation and growth. General purpose models for propofol, remifentanil and dexmedetomidine have appeared and these greatly reduce the risk of invalid model selection. In this narrative review, we discuss the development, characteristics and validation of several described general purpose PKPD models for anaesthetic drugs.

RESUMEN

Providing the optimal dosing strategy of a drug for an individual patient is an important task in pharmaceutical sciences and daily clinical application. We developed and validated an optimal dosing algorithm (OptiDose) that computes the optimal individualized dosing regimen for pharmacokinetic-pharmacodynamic models in substantially different scenarios with various routes of administration by solving an optimal control problem. The aim is to compute a control that brings the underlying system as closely as possible to a desired reference function by minimizing a cost functional. In pharmacokinetic-pharmacodynamic modeling, the controls are the administered doses and the reference function can be the disease progression. Drug administration at certain time points provides a finite number of discrete controls, the drug doses, determining the drug concentration and its effect on the disease progression. Consequently, rewriting the cost functional gives a finite-dimensional optimal control problem depending only on the doses. Adjoint techniques allow to compute the gradient of the cost functional efficiently. This admits to solve the optimal control problem with robust algorithms such as quasi-Newton methods from finite-dimensional optimization. OptiDose is applied to three relevant but substantially different pharmacokinetic-pharmacodynamic examples.

RESUMEN

BACKGROUND: Oliceridine is a biased ligand at the µ-opioid receptor recently approved for the treatment of acute pain. In a thorough QT study, corrected QT (QTc) prolongation displayed peaks at 2.5 and 60 minutes after a supratherapeutic dose. The mean plasma concentration peaked at 5 minutes, declining rapidly thereafter. OBJECTIVE: The purpose of this study was to examine the basis for the delayed effect of oliceridine to prolong the QTc interval. METHODS: Repolarization parameters and tissue accumulation of oliceridine were evaluated in rabbit left ventricular wedge preparations over a period of 5 hours. The effects of oliceridine on ion channel currents were evaluated in human embryonic kidney and Chinese hamster ovary cells. Quinidine was used as a control. RESULTS: Oliceridine and quinidine produced a progressive prolongation of the QTc interval and action potential duration over a period of 5 hours, paralleling slow progressive tissue uptake of the drugs. Oliceridine caused modest prolongation of these parameters, whereas quinidine produced a prominent prolongation of action potential duration and QTc interval as well as development of early afterdepolarization (after 2 hours), resulting in a high torsades de pointes score. The 50% inhibitory concentration values for the oliceridine inhibition of the rapidly activating delayed rectifier current (human ether a-go-go current) and late sodium channel current were 2.2 and 3.45 µM when assessed after traditional acute exposure but much lower after 3 hours of drug exposure. CONCLUSION: Our findings suggest that a gradual increase of intracellular access of drugs to the hERG channels as a result of their intracellular uptake and accumulation can significantly delay effects on repolarization, thus confounding the assessment of QT interval prolongation and arrhythmic risk when studied acutely. The multi-ion channel effects of oliceridine, late sodium channel current inhibition in particular, point to a low risk of devloping torsades de pointes.

Asunto(s)

RESUMEN

Introduction:Safety and tolerability is a critical area where improvements are needed to decrease the attrition rates during development of new drug candidates. Modeling approaches, when smartly implemented, can contribute to this aim.Areas covered:The focus of this review was on modeling approaches applied to four kinds of drug-induced toxicities: hematological, immunological, cardiovascular (CV) and liver toxicity. Papers, mainly published in the last 10 years, reporting models in three main methodological categories - computational models (e.g., quantitative structure-property relationships, machine learning approaches, neural networks, etc.), pharmacokinetic-pharmacodynamic (PK-PD) models, and quantitative system pharmacology (QSP) models - have been considered.Expert opinion:The picture observed in the four examined toxicity areas appears heterogeneous. Computational models are typically used in all areas as screening tools in the early stages of development for hematological, cardiovascular and liver toxicity, with accuracies in the range of 70-90%. A limited number of computational models, based on the analysis of drug protein sequence, was instead proposed for immunotoxicity. In the later stages of development, toxicities are quantitatively predicted with reasonably good accuracy using either semi-mechanistic PK-PD models (hematological and cardiovascular toxicity), or fully exploited QSP models (immuno-toxicity and liver toxicity).

Asunto(s)

RESUMEN

Pharmacometric methods have hugely benefited from progress in analytical and computer sciences during the past decades, and play nowadays a central role in the clinical development of new medicinal drugs. It is time that these methods translate into patient care through therapeutic drug monitoring (TDM), due to become a mainstay of precision medicine no less than genomic approaches to control variability in drug response and improve the efficacy and safety of treatments. In this review, we make the case for structuring TDM development along five generic questions: 1) Is the concerned drug a candidate to TDM? 2) What is the normal range for the drug's concentration? 3) What is the therapeutic target for the drug's concentration? 4) How to adjust the dosage of the drug to drive concentrations close to target? 5) Does evidence support the usefulness of TDM for this drug? We exemplify this approach through an overview of our development of the TDM of imatinib, the very first targeted anticancer agent. We express our position that a similar story shall apply to other drugs in this class, as well as to a wide range of treatments critical for the control of various life-threatening conditions. Despite hurdles that still jeopardize progress in TDM, there is no doubt that upcoming technological advances will shape and foster many innovative therapeutic monitoring methods.

RESUMEN

Body-on-a-chip and human-on-a-chip systems are currently being used to augment and could eventually replace animal models in drug discovery and basic biological research. However, hydrophobic molecules, especially therapeutic compounds, tend to adsorb to the polymer materials used to create these microfluidic platforms, which may distort the dose-response curves that feed into pharmacokinetic/pharmacodynamic (PK/PD) models, which translate preclinical data into predictions of clinical outcomes. Inverse liquid-solid chromatography paired with a numerical optimization based on the Langmuir model of adsorption was used to characterize the adsorption isotherm parameters of drugs to polydimethylsiloxane (PDMS) and polymethylmethacrylate (PMMA), polymers commonly used in these platforms. The adsorption isotherms were then compared against concentration measurements of drugs recirculated in these platforms. This research further illustrates the point that by quantifying drug or drug candidate interactions before system dosing and including this data in the PK/PD models, then polymers used in these platforms need not be limited to "less-adsorbing" materials.

Asunto(s)

RESUMEN

With a long half-life, pharmacokinetic (PK) evaluation of monoclonal antibodies in rodents lasts multiple weeks during which the animals may grow significantly. We evaluated the impact of weight, age, and previous drug exposure on the PK of rituximab. Serum concentrations of rituximab were measured after intravenous and subcutaneous dosing in Sprague Dawley rats aged between 7 and 21 weeks and weighing between 200 and 600 g. The growth of rats during the study was incorporated into the model through the increase of the volumes of compartments in relation to the rats total body weight. The final model successfully captured all the data; and no difference was observed in the rituximab PK profiles between exposure naïve and redosed or young and older rats. Incorporating the rodent growth over the time course of the study into the PK model was shown to be important for providing a more physiological description of the disposition of rituximab, especially when young and rapidly growing animals are used. Redosing the same rats with monoclonal antibodies might be a viable strategy for reducing the use of laboratory animals in accordance with the 3R principles.

Asunto(s)

RESUMEN

Osteoporosis is a disorder of the bones in which they are weakened to the extent that they become more prone to fracture. There are various forms of osteoporosis: some of them are induced by drugs, and others occur as a chronic progressive disorder as an individual gets older. As the median age of the population rises across the world, the chronic form of the bone disease is drawing attention as an important worldwide health issue. Developing new treatments for osteoporosis and comparing them with existing treatments are complicated processes due to current acceptance by regulatory authorities of bone mineral density (BMD) and fracture risk as clinical end points, which require clinical trials to be large, prolonged, and expensive to determine clinically significant impacts in BMD and fracture risk. Moreover, changes in BMD and fracture risk are not always correlated, with some clinical trials showing BMD improvement without a reduction in fractures. More recently, bone turnover markers specific to bone formation and resorption have been recognized that reflect bone physiology at a cellular level. These bone turnover markers change faster than BMD and fracture risk, and mathematically linking the biomarkers via a computational model to BMD and/or fracture risk may help in predicting BMD and fracture risk changes over time during the progression of a disease or when under treatment. Here, we discuss important concepts of bone physiology, osteoporosis, treatment options, mathematical modeling of osteoporosis, and the use of these models by the pharmaceutical industry and the Food and Drug Administration.

Asunto(s)

RESUMEN

Modern model-based approaches to cardiac safety and efficacy assessment require accurate drug concentration-effect relationship establishment. Thus, knowledge of the active concentration of drugs in heart tissue is desirable along with inter-subject variability influence estimation. To that end, we developed a mechanistic physiologically based pharmacokinetic model of the heart. The models were described with literature-derived parameters and written in R, v.3.4.0. Five parameters were estimated. The model was fitted to amitriptyline and nortriptyline concentrations after an intravenous infusion of amitriptyline. The cardiac model consisted of 5 compartments representing the pericardial fluid, heart extracellular water, and epicardial intracellular, midmyocardial intracellular, and endocardial intracellular fluids. Drug cardiac metabolism, passive diffusion, active efflux, and uptake were included in the model as mechanisms involved in the drug disposition within the heart. The model accounted for inter-individual variability. The estimates of optimized parameters were within physiological ranges. The model performance was verified by simulating 5 clinical studies of amitriptyline intravenous infusion, and the simulated pharmacokinetic profiles agreed with clinical data. The results support the model feasibility. The proposed structure can be tested with the goal of improving the patient-specific model-based cardiac safety assessment and offers a framework for predicting cardiac concentrations of various xenobiotics.

Asunto(s)

RESUMEN

The purpose of this study was to build regression models for the prediction of apparent oral clearance (CL/F) for small-molecule inhibitors in the pediatric population using data obtained from adults. Two approaches were taken; a simple allometric regression model which considers no interdrug or interindividual variability and an allometric regression model with mixed-effects modeling where some variability parameters are included in the model. Average CL/F values were obtained for 15 drugs at various dosages from 31 literatures (a total of 139 data sets) conducted in adults and for 15 drugs from 26 literatures (62 data sets) conducted in children. Data were randomly separated into the "modeling" or "validation" data set, and the 2 allometric regression models were applied to the modeling data set. The predictive ability of the models was examined by comparing the observed and model-predicted CL/F in children using the validation data set. The percentage root mean square error was 17.2% and 26.3% in the simple allometric regression model and the allometric regression model with mixed-effects modeling, respectively. The predictive ability of the 2 models seems acceptable, suggesting that they could be useful for predicting the CL/F of new small-molecule inhibitors and for determining adequate doses in clinical pharmacotherapy for children.

Asunto(s)

RESUMEN

The medical use of marijuana is increasing, yet little is known about the exposure-response relationship for its psychoactive effects. It is well known that the plasma concentrations of the principal psychoactive component of marijuana, Δ9-tetrahydrocannabinol (THC), do not directly correlate to the observed psychoactive effects. The purpose of this research was to use an effect-compartment modeling approach to predict and relate the concentrations of the psychoactive components (THC and its active metabolite) in the "hypothetical" effect-site compartment to the observed psychoactive effects. A "hypothetical" effect-compartment model was developed using literature data to characterize the observed delay in peak "highness" ratings compared with plasma concentrations of the psychoactive agents following intravenous administration of THC. A direct relationship was established between the reported psychoactive effects ("highness" or intoxication) and the predicted effect-site concentrations of THC. The differences between estimated equilibration half-lives for THC and THC-OH in the effect-compartment model indicated the differential equilibration of parent drug and the active metabolite between plasma and the effect-site. These models contribute to the understanding of the pharmacokinetic-pharmacodynamic relationships associated with marijuana use and are important steps in the prediction of pharmacodynamic effects related to the psychoactive components in marijuana.

Asunto(s)

RESUMEN

Physiologically based pharmacokinetic modeling is a commonly used strategy in the drug development and regulatory submissions. This commentary provides a critical overview of the current status of physiologically based pharmacokinetic methodologies to predict transporter-mediated pharmacokinetics, in addition to the impact of disease and genetics with respect to local and systemic concentration.

Asunto(s)

RESUMEN

Darbepoetin alfa (Darbe) is a hyperglycosylated analogue of recombinant human erythropoietin (Epo). The aim of this study was to develop a population pharmacokinetic model for Darbe following intravenous (i.v.) and subcutaneous (s.c.) administration to infants. Data from 2 infant clinical studies (a single i.v. dose study following a 4 µg/kg dose of Darbe, and a single s.c. dose study following 1 µg/kg or 4 µg/kg dose of Darbe) were combined and analyzed simultaneously using nonlinear mixed-effect modeling approach. Darbe population pharmacokinetics was well described by a 2-compartment model with first-order elimination. The covariate analysis identified significant impact of gender on clearance and bodyweight on volume of distribution. The clearance of Darbe was estimated to be 0.050 L/h/kg in male infants and 0.031 L/h/kg in female infants. The predicted population mean value of Vp is 0.84 L/kg, which is associated with the subject's bodyweight (p < 0.05). Following s.c. administration, the estimated absorption rate (i.e., ka) of Darbe was 0.062 L/h. The model provides a suitable starting point for the development of further pharmacokinetic-pharmacodynamic models in infants in a variety of disease settings. Because the covariate-pharmacokinetic parameter relationships were identified in only 22 infants, further investigation with larger sample size is warranted.

Asunto(s)

RESUMEN

Precision medicine approach has a potential to ensure optimum efficacy and safety of drugs at individual patient level. Physiologically based pharmacokinetic and pharmacodynamic (PBPK/PD) models could play a significant role in precision medicine by predicting interindividual variability in drug disposition and response. In order to develop robust PBPK/PD models, it is imperative that the critical physiological parameters affecting drug disposition and response and their variability are precisely characterized. Currently used PBPK/PD modeling software, for example, Simcyp and Gastroplus, encompass information such as organ volumes, blood flows to organs, body fat composition, glomerular filtration rate, etc. However, the information on the interindividual variability of the majority of the proteins associated with PK and PD, for example, drug metabolizing enzymes, transporters, and receptors, are not fully incorporated into these PBPK modeling platforms. Such information is significant because the population factors such as age, genotype, disease, and gender can affect abundance or activity of these proteins. To fill this critical knowledge gap, mass spectrometry-based quantitative proteomics has emerged as an important technique to characterize interindividual variability in the protein abundance of drug metabolizing enzymes, transporters, and receptors. Integration of these quantitative proteomics data into in silico PBPK/PD modeling tools will be crucial toward precision medicine.

Asunto(s)

RESUMEN

To reveal unknown and potentially important mechanisms of drug action, multi-biomarker discovery approaches are increasingly used. Time-course relationships between drug action and multi-biomarker profiles, however, are typically missing, while such relationships will provide increased insight in the underlying body processes. The aim of this study was to investigate the effect of the dopamine D2 antagonist remoxipride on the neuroendocrine system. Different doses of remoxipride (0, 0.7, 5.2, or 14 mg/kg) were administered to rats by intravenous infusion. Serial brain extracellular fluid (brainECF) and plasma samples were collected and analyzed for remoxipride pharmacokinetics (PK). Plasma samples were analyzed for concentrations of the eight pituitary-related hormones as a function of time. A Mann-Whitney test was used to identify the responding hormones, which were further analyzed by pharmacokinetic/pharmacodynamic (PK/PD) modeling. A three-compartment PK model adequately described remoxipride PK in plasma and brainECF. Not only plasma PRL, but also adrenocorticotrophic hormone (ACTH) concentrations were increased, the latter especially at higher concentrations of remoxipride. Brain-derived neurotropic factor (BDNF), follicle stimulating hormone (FSH), growth hormone (GH), luteinizing hormone (LH), and thyroid stimulating hormones (TSH) did not respond to remoxipride at the tested doses, while oxytocin (OXT) measurements were below limit of quantification. Precursor pool models were linked to brainECF remoxipride PK by Emax drug effect models, which could accurately describe the PRL and ACTH responses. To conclude, this study shows how a multi-biomarker identification approach combined with PK/PD modeling can reveal and quantify a neuroendocrine multi-biomarker response for single drug action.

Asunto(s)

RESUMEN

In vitro-in vivo extrapolation techniques combined with physiologically based pharmacokinetic models represent a feasible approach to establishing links between critical quality attributes and the time course of drug concentrations in vivo. By further integrating the results with pharmacodynamic (PD) models, scientists can also explore the time course of drug effect. The aim of this study was to assess whether differences in dissolution rates would affect the onset, magnitude, and duration of the time course of ibuprofen-mediating pain relief. An integrated in vitro-in vivo extrapolation-physiologically based pharmacokinetic/PD model was used to simulate pharmacokinetic and PD profiles for ibuprofen free acid (IBU-H) and its salts. Two elements of the pharmacokinetic profile, the peak of exposure (Cmax) and the time to peak concentration (Tmax), were sensitive to dissolution rate, whereas only 1 element of the pharmacodynamic profile was affected, namely the onset of drug action. The Cmax differences between IBU-H and its salts seem to be mitigated in the (hypothetical) effect compartment because of the concurrent distribution and elimination processes. Furthermore, the predicted maximum concentration in the effect compartment exceeded the EC80 value, which marks the plateau phase of the PD concentration-response curve, regardless of whether IBU-H or its salts were administered. Understanding the target site distribution kinetics and the potential nonlinearities between exposure and response will assist in setting criteria that are more scientifically based for the demonstration of therapeutic equivalence.

Asunto(s)

RESUMEN

Nephrotoxicity is the major dose-limiting toxicity of cisplatin (CDDP). The aim of this study was to develop a pharmacokinetic (PK)/toxicodynamic (TD) model of CDDP-induced acute renal injury in rats and to simulate nephrotoxicity at various dosing rates. CDDP was administered to rats by a 30-s bolus or a 2-h infusion (1.0, 2.5, 5.0, and 7.5 mg/kg). Unbound CDDP concentrations in plasma and urine were determined up to 2 h after administration in the PK study, and plasma creatinine (Cr) levels were monitored for up to 7 days as an index of nephrotoxicity in the TD study. The PK was linear and was fitted with a traditional 2-compartment model. The TD was nonlinear and differed between dosing rates. The creatinine concentration profiles were fitted with a signal transduction-indirect response model. Population analysis using a nonlinear mixed-effect model was adapted to the developed PK/TD model and was well-validated. Dosing simulations from the developed population PK/TD model indicated that CDDP-induced nephrotoxicity was due to not only Cmax but also the time above the toxic concentration of CDDP. Prolongation of infusion time will not necessarily attenuate acute nephrotoxicity. This study demonstrated the potential utility of PK/TD modeling for preventing nephrotoxicity.

Asunto(s)

RESUMEN

Our study aimed at the investigation of in vivo anticancer effect of the combination use of dexamethasone (DEX) and gemcitabine (GM) as well as the development of pharmacokinetic/pharmacodynamic (PK/PD) models in MCF-7 xenograft model. Further, simulations were conducted to optimize doses and administration schedules. The inhibitory effect of different doses and administration schedules were investigated in MCF-7 xenograft model. Semi-mechanism-based PK/PD models were established based on the preclinical data to characterize the relationship between plasma concentration and the time course of the drug response quantitatively. The PK/PD models were further applied to predict and optimize doses and administration schedules, which would lead to tumor stasis by the end of the treatment. Synergistic effect was observed in the PD study in vivo and further confirmed by the estimated combination index ψ obtained from PK/PD models. The optimum dose regimen was selected as DEX 2 mg/kg, qd and GM 10 mg/kg, q2d based on the simulation results. In summary, the PD interaction between DEX and GM was demonstrated as synergism by both experimental results and modeling approach. Dosage regimens were optimized as predicted by modeling and simulations, which would provide reference for preclinical study and translational research as well.

Asunto(s)

RESUMEN

"All animals are equal, but some are more equal than others" was the illustrious quote derived from British writer George Orwell's famed work, Animal Farm. Extending beyond the remit of political allegory, however, this statement would appear to hold true for the selection of appropriate animal models to simulate human physiology in preclinical studies. There remain definite gaps in our current knowledge with respect to animal physiology, notably those of intra- and inter-species differences in gastrointestinal (GI) function, which may affect oral drug delivery and absorption. Factors such as cost and availability have often influenced the choice of animal species without clear justification for their similarity to humans, and lack of standardization in techniques employed in past studies using various animals may also have contributed to the generation of contradictory results. As it stands, attempts to identify a single animal species as appropriately representative of human physiology and which may able to adequately simulate human in vivo conditions are limited. In this review, we have compiled and critically reviewed data from numerous studies of GI anatomy and physiology of various animal species commonly used in drug delivery modeling, commenting on the appropriateness of these animals for in vivo comparison and extrapolation to humans.

Asunto(s)

RESUMEN

Cannulation of the thoracic lymph duct in experimental animals allows direct measurement of the lymphatic exposure of lymph-targeted drugs. When coupled with recent advances in genetically modified and diseased mouse models, this presents further opportunities to define changes in biological processes and disease in response to drug treatment. Although cannulation of the thoracic lymph duct in mice is inherently challenging because of the small size and delicate nature of the duct, it can be further confounded by anatomical variations between animals. In this communication, we present our observations on the anatomical features of the thoracic lymph duct between mice of different strains and genders, and discuss the impact of these features on the "cannulatability" of the duct. We also provide some technical tips to help guide other investigators to deliver higher experimental success rates.

Asunto(s)