Toward in silico CMC: An industrial collaborative approach to model-based process development.

The Third Modeling Workshop focusing on bioprocess modeling was held in Kenilworth, NJ in May 2019. A summary of these Workshop proceedings is captured in this manuscript. Modeling is an active area of research within the biotechnology community, and there is a critical need to assess the current state and opportunities for continued investment to realize the full potential of models, including resource and time savings. Beyond individual presentations and topics of novel interest, a substantial portion of the Workshop was devoted toward group discussions of current states and future directions in modeling fields. All scales of modeling, from biophysical models at the molecular level and up through large scale facility and plant modeling, were considered in these discussions and are summarized in the manuscript. Model life cycle management from model development to implementation and sustainment are also considered for different stages of clinical development and commercial production. The manuscript provides a comprehensive overview of bioprocess modeling while suggesting an ideal future state with standardized approaches aligned across the industry.

Phase transitions in fluctuations and their role in two-step nucleation.

We consider the thermodynamic behavior of local fluctuations occurring in a stable or metastable bulk phase. For a system with three or more phases, we present a simple analysis based on classical nucleation theory that predicts thermodynamic conditions at which small fluctuations resemble the phase having the lowest surface tension with the surrounding bulk phase, even if this phase does not have a lower chemical potential. We also identify the conditions at which a fluctuation may convert to a different phase as its size increases, referred to here as a "fluctuation phase transition" (FPT). We demonstrate these phenomena in simulations of a two dimensional lattice model by evaluating the free energy surface that describes the thermodynamic properties of a fluctuation as a function of its size and phase composition. We show that a FPT can occur in the fluctuations of either a stable or metastable bulk phase and that the transition is first-order. We also find that the FPT is bracketed by well-defined spinodals, which place limits on the size of fluctuations of distinct phases. Furthermore, when the FPT occurs in a metastable bulk phase, we show that the superposition of the FPT on the nucleation process results in two-step nucleation (TSN). We identify distinct regimes of TSN based on the nucleation pathway in the free energy surface and correlate these regimes to the phase diagram of the bulk system. Our results clarify the origin of TSN and elucidate a wide variety of phenomena associated with TSN, including the Ostwald step rule.

Extended linear response for bioanalytical applications using multiple enzymes.

We develop a framework for optimizing a novel approach to extending the linear range of bioanalytical systems and biosensors by utilizing two enzymes with different kinetic responses to the input chemical as their substrate. Data for the flow injection amperometric system devised for detection of lysine based on the function of L-lysine-alpha-oxidase and lysine-2-monooxygenase are analyzed. Lysine is a homotropic substrate for the latter enzyme. We elucidate the mechanism for extending the linear response range and develop optimization techniques for future applications of such systems.

Morphology of nanoclusters and nanopillars formed in nonequilibrium surface growth for catalysis applications.

We consider growth of nanoclusters and nanopillars in a model of surface deposition and restructuring yielding morphologies of interest in designing catalysis applications. Kinetic Monte Carlo numerical modeling yields examples of the emergence of face centered cubic (fcc) symmetry surface features in Pt-type metal nanostructures, allowing evaluation of the fraction of the resulting active sites with desirable properties, such as (111)-like coordination, as well as suggesting the optimal growth regimes.

Mesoscale model of the assembly and cross-linking of HPV virus-like particles.

We present a novel kinetic Monte Carlo model to simulate the real process time-scale of the assembly of Human Papillomavirus (HPV) virus-like particles (VLPs) incorporating the formation of intercapsomeric disulfide bonds. The objective was to develop insights into the underlying mechanisms of HPV VLP assembly and cross-linking during in vitro production of the HPV vaccine. The model integrates actual experimental data and detailed information of VLP geometrical structure in microscopic mechanistic steps. The principal novelty of this model is in the concurrent simulation of VLP assembly and cross-linking including a variable for spatial angular arrangement of capsomeres during their assembly that affects the overall rates of VLP assembly and cross-linking. The cross-linking modeled by using the mechanistic probability rules between involved cysteine residues. The model was utilized to better understand the actual process data and check on the hypothesis related to factors affecting the rates of HPV growth and maturation.

Enzymatic filter for improved separation of output signals in enzyme logic systems towards 'sense and treat' medicine.

The major challenge for the application of autonomous medical sensing systems is the noise produced by non-zero physiological concentrations of the sensed target. If the level of noise is high, then a real signal indicating abnormal changes in the physiological levels of the analytes might be hindered. Inevitably, this could lead to wrong diagnostics and treatment, and would have a negative impact on human health. Here, we report the realization of a filter system implemented to improve both the fidelity of sensing and the accuracy of consequent drug release. A new filtering method was tested in the sensing system for the diagnosis of liver injury. This sensing system used the enzymes alanine transaminase (ALT) and aspartate transaminase (AST) as the inputs. Furthermore, the output of the sensing system was designed to trigger drug release, and therefore, the role of the filter in drug release was also investigated. The drug release system consists of beads with an iron-cross-linked alginate core coated with different numbers of layers of poly-l-lysine. Dissolution of the beads by the output signals of the sensing system in the presence and absence of the filter was monitored by the release of rhodamine-6G dye encapsulated in the beads, mimicking the release of a real drug. The obtained results offer a new view of the problem of noise reduction for systems intended to be part of sense and treat medical devices.

Modularity of biochemical filtering for inducing sigmoid response in both inputs in an enzymatic AND gate.

We report the first systematic study of designed two-input biochemical systems as information processing gates with favorable noise transmission properties accomplished by modifying the gate's response from a convex shape to sigmoid in both inputs. This is realized by an added chemical "filter" process, which recycles some of the output back into one of the inputs. We study a system involving the biocatalytic function of the enzyme horseradish peroxidase, functioning as an AND gate. We consider modularity properties, such as the use of three different input chromogens that when oxidized yield signal detection outputs for various ranges of the primary input, hydrogen peroxide. We also examine possible uses of different filter effect chemicals (reducing agents) to induce the sigmoid response. A modeling approach is developed and applied to our data, allowing us to describe the enzymatic kinetics in the framework of a formulation suitable for evaluating the noise-handling properties of the studied systems as logic gates for information processing steps.

Enzymatic AND logic gate with sigmoid response induced by photochemically controlled oxidation of the output.

We report a study of a system which involves an enzymatic cascade realizing an AND logic gate, with an added photochemical processing of the output, allowing the gate's response to be made sigmoid in both inputs. New functional forms are developed for quantifying the kinetics of such systems, specifically designed to model their response in terms of signal and information processing. These theoretical expressions are tested for the studied system, which also allows us to consider aspects of biochemical information processing such as noise transmission properties and control of timing of the chemical and physical steps.

Networked enzymatic logic gates with filtering: new theoretical modeling expressions and their experimental application.

We report the first study of a network of connected enzyme-catalyzed reactions, with added chemical and enzymatic processes that incorporate the recently developed biochemical filtering steps into the functioning of this biocatalytic cascade. New theoretical expressions are derived to allow simple, few-parameter modeling of network components concatenated in such cascades, both with and without filtering. The derived expressions are tested against experimental data obtained for the realized network's responses, measured optically, to variations of its input chemicals' concentrations with and without filtering processes. We also describe how the present modeling approach captures and explains several observations and features identified in earlier studies of enzymatic processes when they were considered as potential network components for multistep information/signal processing systems.

Enzyme-based logic: OR gate with double-sigmoid filter response.

The first realization of a biomolecular OR gate function with double-sigmoid response (sigmoid in both inputs) is reported. Two chemical inputs activate the enzymatic gate processes, resulting in the output signal: chromogen oxidation, which occurs when either one of the inputs or both are present (corresponding to the OR binary function), and can be optically detected. High-quality gate functioning in handling of sources of noise is enabled by "filtering" involving pH control with an added buffer. The resulting gate response is sigmoid in both inputs when proper system parameters are chosen, and the gate properties are theoretically analyzed within a model devised to evaluate its noise-handling properties.

Enzyme-based logic analysis of biomarkers at physiological concentrations: and gate with double-sigmoid "filter" response.

We report the first realization of a biomolecular AND gate function with double-sigmoid response (sigmoid in both inputs). Two enzyme biomarker inputs activate the gate output signal, which can then be used as indicating liver injury, but only when both of these inputs have elevated pathophysiological concentrations, effectively corresponding to logic-1 of the binary gate functioning. At lower, normal physiological concentrations, defined as logic-0 inputs, the liver-injury output levels are not obtained. High-quality gate functioning in handling of various sources of noise, on time scales of relevance to potential applications, is enabled by utilizing "filtering" effected by a simple added biocatalytic process. The resulting gate response is sigmoid in both inputs when proper system parameters are chosen, and the gate properties are theoretically analyzed within a model devised to evaluate its noise-handling properties.