Dynamic global sensitivity analysis in bioreactor networks for bioethanol production

The Use of Global Sensitivity Analysis to Assess the Oral Absorption of Weakly Basic Compounds: A Case Example of Dipyridamole

OBJECTIVE

To utilize the global system analysis (GSA) in oral absorption modeling to gain a deeper understanding of system behavior, improve model accuracy, and make informed decisions during drug development.

METHODS

GSA was utilized to give insight into which drug substance (DS), drug product (DP), and/or physiological parameter would have an impact on peak plasma concentration (Cmax) and area under the curve (AUC) of dipyridamole as a model weakly basic compound. GSA guided the design of in vitro experiments and oral absorption risk assessment using FormulatedProducts v2202.1.0. The solubility and precipitation profiles of dipyridamole in different bile salt concentrations were measured. The results were then used to build a mechanistic oral absorption model.

RESULTS

GSA warranted further investigation into the precipitation kinetics and its link to the levels of bile salt concentrations. Mechanistic modeling studies demonstrated that a precipitation-integrated modeling approach appropriately predicted the mean plasma profiles, Cmax, and AUC from the clinical studies.

CONCLUSIONS

This work shows the value of GSA utilization in early development to guide in vitro experimentation and build more confidence in identifying the critical parameters for the mathematical models.

A Non-Probabilistic Solution for Uncertainty and Sensitivity Analysis on Techno-Economic Assessments of Biodiesel Production with Interval Uncertainties

Techno-economic assessments (TEA) of biodiesel production may comply with various economic and technical uncertainties during the lifespan of the project, resulting in the variation of many parameters associated with biodiesel production, including price of biodiesel, feedstock price, and rate of interest. Engineers may only collect very limited information on these uncertain parameters such as their variation intervals with lower and upper bound. This paper proposes a novel non-probabilistic strategy for uncertainty analysis (UA) in the TEA of biodiesel production with interval parameters, and non-probabilistic reliability index (NPRI) is employed to measure the economically feasible extent of biodiesel production. A sensitivity analysis (SA) indicator is proposed to assess the sensitivity of NPRI with regard to an individual uncertain interval parameter. The optimization method is utilized to solve NPRI and SA. Results show that NPRI in the focused biodiesel production of interest is 0.1211, and price of biodiesel, price of feedstock, and cost of operating can considerably affect TEA of biodiesel production.

State Estimation Based on Nonlinear Observer for Hydrogen Production in a Photocatalytic Anaerobic Bioreactor

Hydrogen concentration in a photocatalytic continuous bioreactor was estimated. For the above system, a novel kinetic model of the sulfate-reducing process for hydrogen production was proposed and experimentally confirmed. In addition, we present the design of an estimator based on nonlinear observer, which is robust against modeling errors, to estimate the observable states of the bioreactor. Sulfate, biomass, sulfide, carbon dioxide, cadmium in liquid, cadmium sulfide, and hydrogen concentrations were estimated in spite of errors in the evaluation of the parameters using sulfate concentration as measurable output. The convergence of the proposed observer was analyzed using Lyapunov stability theory. Finally, maximum hydrogen production was 225 mL and 175 mL for batch and continuous processes, respectively.