'MacDope': a simulation of drug disposition in the human body: applications in clinical pharmacokinetics.

Abstract

1 We have described a novel approach to absorption, distribution, metabolism and elimination of drugs in which the patient is described using 23 Patient Factors and drugs by up to 50 Drug Factors. Kinetic behaviour of a drug results from the interaction of patient and drug factors according to equations describing an eight compartment model. In this model non-linear processes (protein binding, hepatic drug metabolism and renal tubular transport) are handled by derivations of the law of mass action which have been generalised to permit the consequences of multiple drugs interacting at single macromolecular sites to be correctly calculated. 2 The mathematical description of this model is provided in a companion paper and solution of the equations is only possible using a digital computer. The computer programme is provided with an interactional format which makes operation independent of mathematical skills. Patients are defined by age, sex, height and weight with, or without, organ dysfunction; the programme then generates appropriate factors. Drug enters the system when a prescription is typed on the keyboard and required Drug Factors are then retrieved from the disc files. Drug concentrations in plaVma or body fluids are given as simple graphs as a function of time, or in tabular form. 3 Any of the Patient or Drug Factors may be altered before, or during a run and up to three drugs may be simulated at one time thus permitting certain kinetic interactions to be examined. The scope of the simulator is illustrated using aspirin: pH dependent gastric absorption, first-order conversion of aspirin to salicylate, partly first order and partly saturable hepatic metabolism of salicylate, and the complex renal handling of this drug are all represented. Interaction of phenytoin with salicylate has been examined quantitatively to suggest limited clinical relevance for the observed displacement of phenytoin from serum albumin. The use of the simulator in a short course of pharmacokinetics is briefly described.

Diverse Data Sets Can Yield Reliable Information through Mechanistic Modeling: Salicylic Acid Clearance

“…The intracellular localization means that a slow k on1 becomes understandable in the light of the time required for convection-permeation-diffusion processes to enter the cells and to permeate the mitochondrial membrane, and for the time to take the same route in reverse for the reaction product, salicylurate to enter the blood and to be cleared into the urine by glomerular filtration. Bloch et al [ 17 ] also model aspirin clearance, reporting similar results with a different modeling system. To assuage our guilt feelings for not accounting for these retarding processes, we developed a crude but more general model that does that.…”

Application of a frame-based computer-aided learning system in clinical chemistry

“…Computer‐aided learning (CAL) has been successfully introduced in medicine as part of the undergraduate teaching course in general practice (Murray et al 1976a, b) and has been applied to renal function (Dickinson & Shepherd 1972), principles of haemodynamics (Dickinson et al 1973), oral anticoagulants and diabetic ketoacidosis (Hoffer 1973), and clinical pharmacokinetics (Bloch et al 1980).…”

Computing Science and Statistics: Proceedings of the Symposium on Interface, 21-24 Apr 1991, Seattle, WA

“…They inconcentration-time curves on a configurable graph. The data elude utilization: 1) of a fixed model simulator where the files can be exported to other graphics and statistics number and/or types of tissues are fixed (Bloch et al, 1980; packages. The pictorial flow diagram, a table of all tissue Gabrielsson and Hakman, 1986; Menzel el al., 1987); 2) of parameter values, the steady-state solution set, and the a general simulation system (Blau and Neely, 1987); and graphic plots can be printed..…”