A scalable method for parameter identification in kinetic models of metabolism using steady-state data.

Motivation: In kinetic models of metabolism, the parameter values determine the dynamic behaviour predicted by these models. Estimating parameters from in vivo experimental data require the parameters to be structurally identifiable, and the data to be informative enough to estimate these parameters. Existing methods to determine the structural identifiability of parameters in kinetic models of metabolism can only be applied to models of small metabolic networks due to their computational complexity.

Making Triage Decisions for the Acute Community Care Program: Paramedics Caring for Urgent Health Problems in Patients' Homes.

The Acute Community Care Program (ACCP) initiative sends specially trained paramedics to evaluate and treat patients with urgent care problems in their residences during evening hours. ACCP safety depends on making appropriate triage decisions from patients' reports during phone calls about whether paramedics could care for patients' urgent needs or whether they require emergency department (ED) services. Furthermore, after ACCP paramedics are on scene, patients may nonetheless need ED care if their urgent health problems are not adequately treated by the paramedic's interventions.

Early experiences with the Acute Community Care Program in eastern Massachusetts.

Objectives: Emergency departments (EDs) frequently provide care for nonemergent health conditions outside of usual physician office hours. A nonprofit, fully integrated health insurer/care delivery system that enrolls socioeconomically disadvantaged adults with complex health needs partnered with an ambulance service provider to offer after-hours urgent care by specially trained and equipped paramedics in patients' residences. The Massachusetts Department of Public Health gave this initiative, the Acute Community Care Program (ACCP), a Special Project Waiver.

Model-based design of bistable cell factories for metabolic engineering.

Motivation: Metabolism can exhibit dynamic phenomena like bistability due to the presence of regulatory motifs like the positive feedback loop. As cell factories, microorganisms with bistable metabolism can have a high and a low product flux at the two stable steady states, respectively. The exclusion of metabolic regulation and network dynamics limits the ability of pseudo-steady state stoichiometric models to detect the presence of bistability, and reliably assess the outcomes of design perturbations to metabolic networks.

Constructing kinetic models of metabolism at genome-scales: A review.

Constraint-based modeling of biological networks (metabolism, transcription and signal transduction), although used successfully in many applications, suffer from specific limitations such as the lack of representation of metabolite concentrations and enzymatic regulation, which are necessary for a complete physiologically relevant model. Kinetic models conversely overcome these shortcomings and enable dynamic analysis of biological systems for enhanced in silico hypothesis generation. Nonetheless, kinetic models also have limitations for modeling at genome-scales chiefly due to: (i) model non-linearity; (ii) computational tractability; (iii) parameter identifiability; (iv) estimability; and (v) uncertainty.