title: Modeling for critically ill patients: An introduction for beginners.
abstract: Models are mathematical tools used to describe real-world features. Therapeutic interventions in the field of critical care medicine may easily be translated into such models. Indeed, numerous variables influencing drug pharmacokinetics and pharmacodynamics are systematically documented in the intensive care unit over time. Organ failure, fluid shifts, other drug administration, and renal replacement therapy may cause changes in physiological values, such as body weight and composition, temperature, serum protein levels, arterial pH, and renal or hepatic function. Trials assessing the efficacy and safety of novel drugs usually exclude critically ill patients, and guidelines regarding drug dosage rarely apply to such patients. Modeling in the critically ill may allow physicians to inform decisions related to therapeutic interventions, particularly relating to infectious diseases. However, few clinicians are familiar with these methods. Here, we present a current overview of population pharmacokinetic and pharmacodynamic models applicable in critically ill patients aimed at nonspecialists and then emphazize recent potential of modeling for optimizing treatments and care in the intensive care unit.
authors.affiliation: Medical Intensive Care Unit, Hôpital Européen Georges Pompidou, Assistance Publique-Hôpitaux de Paris, Université Paris Descartes Sorbonne Paris Cité, Paris, France.
authors.forename: Emmanuel
authors.initials: E
authors.lastname: Lafont
authors.affiliation: Centre d'Investigation Clinique-0991 INSERM, Université Paris Descartes Sorbonne Paris Cité, Paris, France.
authors.forename: Saik
authors.initials: S
authors.lastname: Urien
authors.affiliation: Centre d'Investigation Clinique-1166 INSERM, Hôpital La Pitié-Salpêtrière, Assistance Publique-Hôpitaux de Paris, Université Pierre et Marie Curie, Paris, France.
authors.forename: Joe-Elie
authors.initials: JE
authors.lastname: Salem
authors.affiliation: Medical Intensive Care Unit, Hôpital Raymond Poincarré, Assistance Publique-Hôpitaux de Paris, Université Versailles-Saint Quentin, Garches, France.
authors.forename: Nicholas
authors.initials: N
authors.lastname: Heming
authors.affiliation: Medical Intensive Care Unit, Hôpital Européen Georges Pompidou, Assistance Publique-Hôpitaux de Paris, Université Paris Descartes Sorbonne Paris Cité, Paris, France. Electronic address: christophe.faisy@egp.aphp.fr.
authors.forename: Christophe
authors.initials: C
authors.lastname: Faisy
mesh_terms: D001499:Bayes Theorem; D016638:Critical Illness / Q000628:therapy*; D004305:Dose-Response Relationship, Drug; D016903:Drug Monitoring / Q000379:methods; D006801:Humans; D008962:Models, Theoretical; D011237:Predictive Value of Tests; D055553:Prescription Drugs / Q000493:pharmacokinetics* / Q000494:pharmacology*
chemical_list: D055553:Prescription Drugs
keywords: Bayesian network; Critically ill patients; Multicompartmental model; Pharmacodynamics; Pharmacokinetics; Predictive model