The well-being model: a new drug interaction model for positive and negative effects.

BACKGROUND: Drugs are routinely combined in anesthesia and pain management to obtain an enhancement of the desired effects. However, a parallel enhancement of the undesired effects might take place as well, resulting in a limited therapeutic usefulness. Therefore, when addressing the question of optimal drug combinations, side effects must be taken into account. METHODS: By extension of a previously published interaction model, the authors propose a method to study drug interactions considering also their side effects. A general outcome parameter identified as patient's well-being is defined by superposition of positive and negative effects. Well-being response surfaces are computed and analyzed for varying drugs pharmacodynamics and interaction types. In particular, the existence of multiple maxima and of optimal drug combinations is investigated for the combination of two drugs. RESULTS: Both drug pharmacodynamics and interaction type affect the well-being surface and the deriving optimal combinations. The effect of the interaction parameters can be explained in terms of synergy and antagonism and remains unchanged for varying pharmacodynamics. For all simulations performed for the combination of two drugs, the presence of more than one maximum was never observed. CONCLUSIONS: The model is consistent with clinical knowledge and supports previously published experimental results on optimal drug combinations. This new framework improves understanding of the characteristics of drug combinations used in clinical practice and can be used in clinical research to identify optimal drug dosing.

Pharmacodynamic modelling of drug-induced ventilatory depression and automatic drug dosing in conscious sedation.

In conscious sedation (CS) procedures, the patient is sedated but retains the ability to breathe spontaneously. Drug-induced ventilatory depression represents a dangerous side effect of CS, possibly leading to hypoventilation and subsequent hypoxia. In this work, we propose a new pharmacodynamic model for drug-induced ventilatory depression. The model presents a parsimonious structure and shows good agreement with experimental data for different drugs. In addition, we explore the innovative idea of regulating drug infusion during CS by means of a feedback control system based on measurements of transcutaneous partial pressure of CO(2). In simulations, the controller proves able to maintain a predefined target of CO(2) despite pain, external disturbances and inter-patient variability in the sensibility to the drug. The implementation of the controller during CS procedures would improve clinical practice minimizing the occurrence of drug-induced ventilatory depression by tailoring drug infusion to patient's needs.

A new model for drug interactions and optimal drug dosing.

Drugs are routinely combined in anesthesia and pain management to obtain an enhancement of the desired effects. However, a parallel enhancement of the undesired effects might take place as well, resulting in a limited therapeutic usefulness. Therefore, when addressing the question of optimal drug combinations, side effects must be taken into account. We propose a new method to study drug interactions considering also their side effects and to identify optimal drug dosing. The model is consistent with clinical knowledge and can explain previously published experimental results, improving our understanding of the characteristics of drug combinations used in clinical practice.

Optimal infusion policy of intravenous morphine and ketamine - A Mixed-Integer Linear Programming application.

Recently, a model for drug interactions considering also side effects has been proposed. According to this model, the effect compartment concentration range maximizing the global well-being of the patient can be identified. This optimal range represents the set which should be targeted by drug infusion. In this work, we apply this novel model to the clinically relevant combination of intravenous morphine and ketamine. The optimal range is identified and its center used as the reference value for controller design. The control problem can be formulated as consisting of mixed continuous and discrete parts. By solving the optimal control problem, the optimal infusion policy is identified minimizing the drug consumption.

Combinations of bupivacaine, fentanyl, and clonidine for lumbar epidural postoperative analgesia: a novel optimization procedure.

BACKGROUND: The authors developed and applied a method to optimize the combination of bupivacaine, fentanyl, and clonidine for continuous postoperative lumbar epidural analgesia. METHODS: One hundred eighteen patients undergoing knee or hip surgery participated in the study. Postoperative epidural analgesia during 48 h after surgery was optimized under restrictions dictated by side effects. Initially, eight combinations of bupivacaine, fentanyl, and clonidine (expressed as drug concentration in the solution administered) were empirically chosen and investigated. To determine subsequent combinations, an optimization model was applied until three consecutive steps showed no decrease in pain score. For the first time in a clinical investigation, a regression model was applied when the optimization procedure led to combinations associated with unacceptable side effects. RESULTS: The authors analyzed 12 combinations with an allowed bupivacaine concentration range of 0-2.5 mg/ml, a fentanyl concentration range of 0-5 microg/ml, and a clonidine concentration range of 0-5 microg/ml. The best combinations of bupivacaine, fentanyl, and clonidine concentrations were 1.0 mg/ml-1.4 microg/ml-0.5 microg/ml, 0.9 mg/ml-3.0 microg/ml-0.3 microg/ml, 0.6 mg/ml-2.5 microg/ml-0.8 microg/ml, and 1.0 mg/ml-2.4 microg/ml-1.0 microg/ml, respectively, all producing a similarly low pain score. The incidence of side effects was low. The application of the regression model to combinations associated with high incidence of motor block successfully directed the optimization procedure to combinations within the therapeutic range. CONCLUSIONS: The results support further study of the combinations of bupivacaine, fentanyl, and clonidine mentioned above for postoperative analgesia after knee and hip surgery. This novel optimization method may be useful in clinical research.