| 主权项 |
1. A method of using the Simcyp Simulator to identify a Virtual Twin to a real patient to identify drug treatment parameters and possible drug interactions comprising the following steps:
entering a chosen dosage, dosage interval, route of administration, and dosage form (where relevant) for the drug of interest (the primary drug). The name of the drug is matched with the compound libraries within the Simulator to determine if a file for that drug has been established. If so, the next step will be initiated; b) entering age, sex, weight, race of the patient and relevant genotypes (for enzymes and transporters, receptors), smoking habit (number of cigarettes smoked per day), and relevant biomarker data (e.g. markers of specific drug metabolizing enzyme activity—such as salivary caffeine level for CYP1A2, plasma 6 beta-hydroxycortisol level for CYP3A4). The prescriber is also requested to enter the names of any other drugs (and their dosage) that the patient is already taking or that the doctor wishes them to take simultaneously with the primary drug. The names of these drugs are matched with compound libraries within the Simcyp Simulator® to determine if files for those drugs have been established. If so, the degree of any interaction with the primary drug will subsequently be determined; c) determining on the patient's demographics and relevant information on disease state, the Simcyp Simulator® defines his or her tissue volumes and blood flows, renal function, and gut characteristics (gastric emptying rate, segmental volumes and transit times, lumen pH and flows etc) with reference to population data embedded within the system; d) defining the patient's relevant hepatic and intestinal metabolizing enzyme activities and organ uptake and efflux transporter activities based on individual demographics, genotypes, biomarker data, interacting medication, and the likely abundances of enzymes and transporters, together with values of specific scaling factors (e.g. hepatocellularity, milligrams of microsomal protein per gram of liver etc). Enzyme/transporter activities in the individual will have associated variances inasmuch as not every determinant parameter will have values specific to that patient's demographics and other input characteristics and will, therefore, be provided as a range based on population data embedded in the Simulator; e) using the pre-defined compound file for the drug of interest and those available for any interacting drugs, the Simulator predicts and plots the individual plasma drug concentration-time profile and its confidence limits for the chosen dosage regimen; f) linking the predicted drug exposure profile to drug response with an appropriate pharmacodynamic model chosen from the suite of such models available in the Simulator. The simplest of such models is a threshold model based on the prior definition of a ‘therapeutic range’ of plasma concentrations of the drug of interest, This range defines a lower limit below which the majority of patients would be expected to have no response and an upper limit above which most patients would be expected to experience a degree of toxicity. Such ranges are documented in the literature for many commonly used drugs (e.g. the ‘therapeutic range’ of theophylline, an anti-asthmatic drug, is 5-10 micrograms per ml plasma). Specific to the drug, more sophisticated pharmacodynamics models can be implemented, including linear, log linear, Emax, sigmoid Emax models, indirect and turnover models and complex stimulus-response models. (Gahrielsson & Weiner, 2006) These models require further specific system and drug-related parameter values derived from literature sources. In addition, disease progression models can be linked to the PKPD models to assess, in conjunction with information on disease severity, likely longer-term clinical outcomes in the individual patient; g) calculating and outputting any dosage adjustment necessary to maintain systemic drug exposure within the ‘therapeutic range’ or to reproduce systemic exposure in the absence of the interacting drugs; and h) outputting the individual plasma drug concentration-time profile and its confidence limits predicted for the new dosage regime in relation to the ‘therapeutic range’ or consistent with systemic exposure in the absence of the interacting drugs. |
