{"id":147,"date":"2019-04-24T12:52:02","date_gmt":"2019-04-24T12:52:02","guid":{"rendered":"https:\/\/sepia2.unil.ch\/pharmacology\/?page_id=147"},"modified":"2020-09-04T03:45:40","modified_gmt":"2020-09-04T03:45:40","slug":"repeated-administration","status":"publish","type":"page","link":"https:\/\/sepia2.unil.ch\/pharmacology\/profiles\/repeated-administration\/","title":{"rendered":"Repeated Administration"},"content":{"rendered":"\n<h2 class=\"wp-block-heading\"> &#8220;Drug administration of a fixed dose at a regular time interval, through a given route&#8221;<\/h2>\n\n\n\n<h3 class=\"wp-block-heading\">Description<\/h3>\n\n\n\n<p>The most common approach to the maintenance of drug therapy is the repeated administration regimen. \n<\/p>\n\n\n\n<p>In repeated administration, accumulation occurs when\n the drug is administered before the previous dose is completely \neliminated. The amount of drug in the body will then progressively rise.\n In the most common case of first-order kinetics, the rate of drug \nelimination will increase proportionally. When the rate of drug \nelimination compensates the rate of drug administration, the average \ndrug concentration reaches steady state or plateau. At steady state, the\n amount of drug lost in each interval equals the amount gained, that is \nthe dose multiplied by the bioavailability. Therefore, the plasma \nconcentration fluctuates between doses similarly from one dosing \ninterval to another.\n<\/p>\n\n\n\n<p>The factors affecting the average steady state concentration are:<\/p>\n\n\n\n<ol class=\"wp-block-list\"><li>Rate\n of dose administration (unit dose divided by dosing interval), which \naffects proportionally the steady state plasma concentration.<\/li><li>Bioavailability, which modulates rate of dose administration.<\/li><li>Clearance:\n Reduced clearance will lead to higher steady state concentration, and \nvice-versa, making clearance inversely related to steady state \nconcentration.<\/li><\/ol>\n\n\n\n<p>During the dosing interval, the factors affecting the fluctuation of plasma concentration around the average concentration are:<\/p>\n\n\n\n<ol class=\"wp-block-list\"><li>Frequency\n of drug administration: For a similar dosing rate, the greater the \nrelative frequency of administration, the smaller the plasma \nfluctuation.<\/li><li>Elimination half-life: The longer the half-life, the smaller the plasma fluctuation<\/li><li>Rate of absorption: slower rate of absorption leads to a decrease in plasma fluctuation.<\/li><\/ol>\n\n\n\n<figure class=\"wp-block-video aligncenter\"><video height=\"336\" style=\"aspect-ratio: 334 \/ 336;\" width=\"334\" autoplay controls loop src=\"https:\/\/sepia2.unil.ch\/pharmacology\/wp-content\/uploads\/2019\/07\/repeatedadministration_Trim.mp4\"><\/video><\/figure>\n\n\n\n<p>The\n time required to reach steady state is determined by the drug&#8217;s \nhalf-life, as is the time it takes to reach a new plateau after a change\n in regimen.<\/p>\n\n\n\n<h3 class=\"wp-block-heading\">Clinical implications<\/h3>\n\n\n\n<p>As a result of accumulation, plasma \nconcentrations reach higher levels during repeated regimen than after \nadministration of a single dose. This is especially important for drugs \nwith long half-lives.\n<\/p>\n\n\n\n<p>The repeated administration regimen is used to \nensure an exposure to the drug within the therapeutic range over a \nprolonged time. Drugs with a narrow therapeutic window need a more \naccurate selection of dosage regimen, which must be adapted to the \npatient&#8217;s clearance and bioavailability.<\/p>\n\n\n\n<p><p class=\"hiddenTitle\">Chart Pharmacokinetics<\/p>\n<div>\n\n    <div id=\"chartContainer\">\n        <canvas id=\"chart\"><\/canvas>\n        <div class=\"\" id=\"divSliderContainer\"><\/div>\n    <\/div>\n\n    <script>\n\n        let chart;\n        let baseDataChartValues = [];\n        let dataChart = [];\n        let dataChartStoredValues = [];\n        let labelsChart = [];\n\n        let dose = 1000;\n        let baseDose = 1000;\n\n        let mDose = 1000;\n        let baseMDose = 1000;\n\n        let tau = 8;\n        let baseTau = 8;\n\n        let vd = 50;\n        let baseVd = 50;\n\n        let cl = 10;\n        let baseCl = 10;\n\n        let f = 0.7;\n        let baseF = 0.7;\n\n        let ka = 2;\n        let tH;\n\n        const maxTime = 150;\n\n        function getPlasmaConcentration(h) {\n            let formulaPlasmaConcentration = (dose*f*ka\/(vd*(ka-cl\/vd))*(Math.exp(-cl\/vd*h)-Math.exp(-ka*h))+(mDose*f*ka\/(vd*(ka-cl\/vd))*((1-Math.exp(-Math.floor((h)\/tau)*cl\/vd*tau))\/(1-Math.exp(-cl\/vd*tau))*Math.exp(-cl\/vd*(h-Math.floor(h\/tau)*tau))-(1-Math.exp(-Math.floor((h)\/tau)*ka*tau))\/(1-Math.exp(-ka*tau))*Math.exp(-ka*(h-Math.floor(h\/tau)*tau)))));\n\n            return formulaPlasmaConcentration;\n        }\n\n        \/*\n         *\n         * t1\/2 = ln(2) * (volume of distribution \/ clearance)\n         *\n         *\/\n        function getHalfLife() {\n            tH = Math.log(2)*(vd\/cl);\n            return (Math.round(tH * 100) \/ 100);\n        }\n\n        function updateSlider(updateStored = false) {\n            dataChart = [];\n            if(updateStored) dataChartStoredValues = [];\n\n            for(let i = 0; i <= maxTime; i++) {\n                let concentration = getPlasmaConcentration(i);\n                dataChart.push(concentration);\n                if(updateStored) dataChartStoredValues.push(concentration);\n            }\n\n            chart.data.datasets[0].data = dataChart;\n            chart.data.datasets[1].data = dataChartStoredValues;\n\n            $( \"#slider-tau\" ).slider( \"option\", \"value\", tau);\n            chart.update();\n        }\n\n        let sliderTau = '<div id=\"slider-tau\" class=\"sliderRange\">' +\n                            '<span id=\"custom-handle-tau\" class=\"ui-slider-handle customHandle\"><\/span>' +\n                            '<span class=\"spanUnit\" id=\"\">Tau<\/span>' +\n                        '<\/div>';\n\n        $('#divSliderContainer').append(sliderTau);\n\n\n   \n\n        $(function() {\n\n            let handleTau = $('#custom-handle-tau');\n\n            $( \"#slider-tau\" ).slider({\n                orientation: \"vertical\",\n                range: \"true\",\n                min: 1,\n                max: 24,\n                step: 1,\n                value: tau,\n                create: function() {\n                    handleTau.text( $( this ).slider( \"value\" ) );\n                },\n                slide: function( event, ui ) {\n                    tau = ui.value;\n                    handleTau.text( ui.value );\n                    updateSlider();\n                }\n            });\n\n        });\n\n        Chart.pluginService.register({\n            beforeInit: function(chart) {\n\n                for(let i = 0; i <= maxTime; i++) {\n                    labelsChart.push(i);\n                    dataChart.push(getPlasmaConcentration(i));\n\n                    dataChartStoredValues = dataChart;\n                    baseDataChartValues = dataChart;\n                }\n\n            }\n        });\n\n        chart = new Chart(document.getElementById(\"chart\"), {\n            type: 'line',\n            data: {\n                labels: labelsChart,\n                datasets: [{\n                    label: \"Plasma Concentration\",\n                    data: dataChart,\n                    borderColor: colorDatasetMain.borderColor,\n                    fillColor: colorDatasetMain.fillColor,\n                    strokeColor: colorDatasetMain.strokeColor,\n                    highlightFill: colorDatasetMain.highlightFill,\n                    highlightStroke: colorDatasetMain.highlightStroke,\n                    borderWidth: \"1\",\n                    pointRadius: 0,\n                    fill: false\n                }, {\n                    label: \"Plasma Concentration\",\n                    data: dataChartStoredValues,\n                    borderColor: colorDatasetStored.borderColor,\n                    fillColor: colorDatasetStored.fillColor,\n                    strokeColor: colorDatasetStored.strokeColor,\n                    highlightFill: colorDatasetStored.highlightFill,\n                    highlightStroke: colorDatasetStored.highlightStroke,\n                    borderWidth: \"1\",\n                    pointRadius: 0,\n                    fill: false\n                }]\n            },\n            options: {\n                scales: {\n                    xAxes: [{\n                        scaleLabel: {\n                            display: true,\n                            labelString: 'H [hour]'\n                        }\n                    }],\n                    yAxes: [{\n                        scaleLabel: {\n                            display: true,\n                            labelString: 'C [mg\/l]'\n                        }\n                    }]\n                },\n                responsive: true,\n                maintainAspectRatio: false\n            }\n        });\n\n    <\/script>\n\n<\/div><\/p>\n\n\n\n<h3 class=\"wp-block-heading\">Related terms<\/h3>\n\n\n\n<p> <strong>\u03c4<\/strong> : dosing interval, h. <\/p>\n\n\n\n<p>Loading dose: In some situations, the steady state \nplasma concentration must be reached more rapidly. A higher dose can \nthen be administered on treatment initiation, to compensate for \naccumulation.\n<\/p>\n\n\n\n<p>Accumulation index (RAC): Index reflecting the \nextent of drug accumulation and determined by the ratio of plasma \nconcentration at plateau over plasma concentration after the first dose.\n It depends only on the dosing interval with regard to the half-life of \nthe drug.<\/p>\n\n\n\n<h3 class=\"wp-block-heading\">Assessment<\/h3>\n\n\n\n<p>The average steady state concentration can be assessed using the equation:\n<\/p>\n\n\n\n<div class=\"wp-block-blocks-latex-block-latex\"><script type=\"text\/x-mathjax-config\">   MathJax.Hub.Config({tex2jax: {inlineMath: [['$','$'], ['\\\\(','\\\\)']]}}); <\/script> <p class=\"formula\">$$C_{ssav}=F*Dose \\over CL*\\tau$$<\/p><p class=\"formula\"><\/div>\n\n\n\n<p> <strong>\u03c4<\/strong>  = dosing interval, h <\/p>\n\n\n\n<p><strong>F<\/strong> = <a href=\"\/pharmacology\/bioavailability\">Bioavailability<\/a> <\/p>\n\n\n\n<p><strong>CL<\/strong> = <a href=\"\/pharmacology\/clearance\">Clearance<\/a><\/p>\n\n\n\n<p>The accumulation index (RAC) can be calculated by the following equation:\n<\/p>\n\n\n\n<div class=\"wp-block-blocks-latex-block-latex\"><script type=\"text\/x-mathjax-config\">   MathJax.Hub.Config({tex2jax: {inlineMath: [['$','$'], ['\\\\(','\\\\)']]}}); <\/script> <p class=\"formula\">$$RAC= {1 \\over 1 - e^{- \\lambda * \\tau}}$$<\/p><p class=\"formula\"><\/div>\n\n\n\n<p> <strong>\u03bb<\/strong>  = <a href=\"\/pharmacology\/halflife\">elimination constant rate<\/a> = CL\/Vd<\/p>\n\n\n\n<p>Using the accumulation index the steady state concentration can be estimated by the equation:\n<\/p>\n\n\n\n<div class=\"wp-block-blocks-latex-block-latex\"><script type=\"text\/x-mathjax-config\">   MathJax.Hub.Config({tex2jax: {inlineMath: [['$','$'], ['\\\\(','\\\\)']]}}); <\/script> <p class=\"formula\">$$C_{ssav} \\approx RAC*C_{\\text{single dose}}$$<\/p><p class=\"formula\"><\/div>\n\n\n\n<p>Rate of accumulation to plateau:\n<\/p>\n\n\n\n<p>The amount of drug in the body rises on multiple dosing just as it does following a constant-rate IV infusion (see <a href=\"\/pharmacology\/intravenous-infusion\">intravenous infusion<\/a>).\n That is, the approach to the plateau depends solely on the drug\u2019s \nelimination half-life. The simulation for the antiepileptic drug \nphenobarbital in the the figure below illustrates this point. This drug \nhas a half-life of 4 days (? 100 h) and is given at a dose of 100 mg \nonce daily. The figure plots the plasma concentration of phenobarbital \nas a function of time for the application scheme 100 mg per day, and for\n comparison for 50 mg twice per day. The figure shows that the approach \nto the plateau is the same for the two application schemes, and the \naverage plasma concentration follows an exponential time course with the\n half-life corresponding to that of drug elimination. Therefore, after \nthree elimination half-lives 88%, and after four half-lives 94 % of the \nsteady state concentration is reached. <\/p>\n\n\n\n<div class=\"wp-block-image\"><figure class=\"aligncenter\"><img loading=\"lazy\" decoding=\"async\" width=\"452\" height=\"372\" src=\"https:\/\/sepia2.unil.ch\/pharmacology\/wp-content\/uploads\/2020\/09\/FigRateToSS.jpg\" alt=\"\" class=\"wp-image-1322\" srcset=\"https:\/\/sepia2.unil.ch\/pharmacology\/wp-content\/uploads\/2020\/09\/FigRateToSS.jpg 452w, https:\/\/sepia2.unil.ch\/pharmacology\/wp-content\/uploads\/2020\/09\/FigRateToSS-300x247.jpg 300w\" sizes=\"auto, (max-width: 452px) 100vw, 452px\" \/><\/figure><\/div>\n\n\n\n<p>Simulation\n of Phenobarbital plasma concentration during repeated oral \nadministration for the application schemes indicated. Based on Vd = 38 \nL, CL = 0.26 L\/h (t1\/2 = 100 h), F = 1. \n\n<\/p>\n","protected":false},"excerpt":{"rendered":"<p>&#8220;Drug administration of a fixed dose at a regular time interval, through a given route&#8221; Description The most common approach to the maintenance of drug therapy is the repeated administration regimen. In repeated administration, accumulation occurs when the drug is administered before the previous dose is completely eliminated. The amount of drug in the body &hellip; <\/p>\n<p class=\"link-more\"><a href=\"https:\/\/sepia2.unil.ch\/pharmacology\/profiles\/repeated-administration\/\" class=\"more-link\">Continue reading<span class=\"screen-reader-text\"> &#8220;Repeated Administration&#8221;<\/span><\/a><\/p>\n","protected":false},"author":1,"featured_media":0,"parent":8,"menu_order":0,"comment_status":"closed","ping_status":"closed","template":"","meta":{"footnotes":""},"class_list":["post-147","page","type-page","status-publish","hentry"],"_links":{"self":[{"href":"https:\/\/sepia2.unil.ch\/pharmacology\/wp-json\/wp\/v2\/pages\/147","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/sepia2.unil.ch\/pharmacology\/wp-json\/wp\/v2\/pages"}],"about":[{"href":"https:\/\/sepia2.unil.ch\/pharmacology\/wp-json\/wp\/v2\/types\/page"}],"author":[{"embeddable":true,"href":"https:\/\/sepia2.unil.ch\/pharmacology\/wp-json\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"https:\/\/sepia2.unil.ch\/pharmacology\/wp-json\/wp\/v2\/comments?post=147"}],"version-history":[{"count":20,"href":"https:\/\/sepia2.unil.ch\/pharmacology\/wp-json\/wp\/v2\/pages\/147\/revisions"}],"predecessor-version":[{"id":1324,"href":"https:\/\/sepia2.unil.ch\/pharmacology\/wp-json\/wp\/v2\/pages\/147\/revisions\/1324"}],"up":[{"embeddable":true,"href":"https:\/\/sepia2.unil.ch\/pharmacology\/wp-json\/wp\/v2\/pages\/8"}],"wp:attachment":[{"href":"https:\/\/sepia2.unil.ch\/pharmacology\/wp-json\/wp\/v2\/media?parent=147"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}