Computationally restoring the potency of a clinical antibody against Omicron.

The COVID-19 pandemic underscored the promise of monoclonal antibody-based prophylactic and therapeutic drugs and revealed how quickly viral escape can curtail effective options. When the SARS-CoV-2 Omicron variant emerged in 2021, many antibody drug products lost potency, including Evusheld and its constituent, cilgavimab. Cilgavimab, like its progenitor COV2-2130, is a class 3 antibody that is compatible with other antibodies in combination and is challenging to replace with existing approaches.

Perspectives for self-driving labs in synthetic biology.

Self-driving labs (SDLs) combine fully automated experiments with artificial intelligence (AI) that decides the next set of experiments. Taken to their ultimate expression, SDLs could usher a new paradigm of scientific research, where the world is probed, interpreted, and explained by machines for human benefit. While there are functioning SDLs in the fields of chemistry and materials science, we contend that synthetic biology provides a unique opportunity since the genome provides a single target for affecting the incredibly wide repertoire of biological cell behavior.

Computationally restoring the potency of a clinical antibody against SARS-CoV-2 Omicron subvariants.

The COVID-19 pandemic underscored the promise of monoclonal antibody-based prophylactic and therapeutic drugs, but also revealed how quickly viral escape can curtail effective options. With the emergence of the SARS-CoV-2 Omicron variant in late 2021, many clinically used antibody drug products lost potency, including Evusheld and its constituent, cilgavimab. Cilgavimab, like its progenitor COV2-2130, is a class 3 antibody that is compatible with other antibodies in combination and is challenging to replace with existing approaches.

Mixture Model Framework for Traumatic Brain Injury Prognosis Using Heterogeneous Clinical and Outcome Data.

Prognoses of Traumatic Brain Injury (TBI) outcomes are neither easily nor accurately determined from clinical indicators. This is due in part to the heterogeneity of damage inflicted to the brain, ultimately resulting in diverse and complex outcomes. Using a data-driven approach on many distinct data elements may be necessary to describe this large set of outcomes and thereby robustly depict the nuanced differences among TBI patients' recovery.

A modular approach to create a neurovascular unit-on-a-chip.

In this work, we describe the fabrication and working of a modular microsystem that recapitulates the functions of the "Neurovascular Unit". The microdevice comprised a vertical stack of a poly(dimethylsiloxane) (PDMS) neural parenchymal chamber separated by a vascular channel via a microporous polycarbonate (PC) membrane. The neural chamber housed a mixture of neurons (~4%), astrocytes (~95%), and microglia (~1%).

Bifurcations: focal points of particle adhesion in microvascular networks.

Objective: Particle adhesion in vivo is dependent on the microcirculation environment, which features unique anatomical (bifurcations, tortuosity, cross-sectional changes) and physiological (complex hemodynamics) characteristics. The mechanisms behind these complex phenomena are not well understood. In this study, we used a recently developed in vitro model of microvascular networks, called SMN, for characterizing particle adhesion patterns in the microcirculation.

Flow and adhesion of drug carriers in blood vessels depend on their shape: a study using model synthetic microvascular networks.

Development of novel carriers and optimization of their design parameters has led to significant advances in the field of targeted drug delivery. Since carrier shape has recently been recognized as an important design parameter for drug delivery, we sought to investigate how carrier shape influences their flow in the vasculature and their ability to target the diseased site. Idealized synthetic microvascular networks (SMNs) were used for this purpose since they closely mimic key physical aspects of real vasculature and at the same time offer practical advantages in terms of ease of use and direct observation of particle flow.

A physiologically realistic in vitro model of microvascular networks.

Existing microfluidic devices, e.g. parallel plate flow chambers, do not accurately depict the geometry of microvascular networks in vivo.

Synthetic microvascular networks for quantitative analysis of particle adhesion.

We have developed a methodology to study particle adhesion in the microvascular environment using microfluidic, image-derived microvascular networks on a chip accompanied by Computational Fluid Dynamics (CFD) analysis of fluid flow and particle adhesion. Microfluidic networks, obtained from digitization of in vivo microvascular topology were prototyped using soft-lithography techniques to obtain semicircular cross sectional microvascular networks in polydimethylsiloxane (PDMS). Dye perfusion studies indicated the presence of well-perfused as well as stagnant regions in a given network.

Simulation-based analysis of fluid flow and electrokinetic phenomena in microfluidic devices.

Recent advances in microfabrication techniques, sensing methods, and miniaturization have enabled automated analysis of samples using microfluidic systems. Each unique application requires successful custom development of integrated lab-on-a-chip devices. This involves design, analysis and characterization of individual components, (pumps, valves, mixers, separators, sensors) and the integrated system.