Dynamic Measurement of Nanoflows: Analysis and Theory of an Optofluidic Flowmeter

Scientists must overcome fundamental measurement problems if microfluidic devices are to become reliable and commercially viable. In particular, microfluidic devices require precise control over operating conditions such as flow-rate, υυ , which is difficult to measure continuously and in situ. Given the small scales involved, state-of-the-art approaches generally require accurate models to infer υυ on the basis of indirect measurements. However, such methods necessarily introduce model-form errors that dominate at the nL/min scale being targeted by the community. To address these problems, we develop a robust and largely assumption-free scaling method that relates the fluorescence efficiency I of fluorophores to υυ through a dosage parameter ξ, which depends on the flow rate and laser power. Notably, we show that this scaling relationship emerges as a universal feature from a general class of partial differential equations (PDEs) describing the experimental setup, which consists of an excitation beam and fluorescence detector. As a result, our approach avoids uncertainties associated with most modeling assumptions, e.g. the exact system geometry, the flow profile, the physics of fluorescence, etc. Moreover, the corresponding measurements remain valid down to the scale of 10 nL/min, with some devices potentially capable of reaching 1 nL/min. As an added benefit, the measurement procedure is mathematically simple, requiring a few trivial computations, as opposed to the full solution of a PDE. To support these claims, we discuss and quantify uncertainties associated with our method and present experimental results that confirm its validity.

Enabling adoption of 2D-NMR for the higher order structure assessment of monoclonal antibody therapeutics

The increased interest in using monoclonal antibodies (mAbs) as a platform for biopharmaceuticals has led to the need for new analytical techniques that can precisely assess physicochemical properties of these large and very complex drugs for the purpose of correctly identifying quality attributes (QA). One QA, higher order structure (HOS), is unique to biopharmaceuticals and essential for establishing consistency in biopharmaceutical manufacturing, detecting process-related variations from manufacturing changes and establishing comparability between biologic products. To address this measurement challenge, two-dimensional nuclear magnetic resonance spectroscopy (2D-NMR) methods were introduced that allow for the precise atomic-level comparison of the HOS between two proteins, including mAbs. Here, an inter-laboratory comparison involving 26 industrial, government and academic laboratories worldwide was performed as a benchmark using the NISTmAb, from the National Institute of Standards and Technology (NIST), to facilitate the translation of the 2D-NMR method into routine use for biopharmaceutical product development. Two-dimensional ¹H,¹⁵N and ¹H,¹³C NMR spectra were acquired with harmonized experimental protocols on the unlabeled Fab domain and a uniformly enriched-¹⁵N, 20%-¹³C-enriched system suitability sample derived from the NISTmAb. Chemometric analyses from over 400 spectral maps acquired on 39 different NMR spectrometers ranging from 500 MHz to 900 MHz demonstrate spectral fingerprints that are fit-for-purpose for the assessment of HOS. The 2D-NMR method is shown to provide the measurement reliability needed to move the technique from an emerging technology to a harmonized, routine measurement that can be generally applied with great confidence to high precision assessments of the HOS of mAb-based biotherapeutics.

Efficient and Robust Optimization for Building Energy Simulation

Efficiently, robustly and accurately solving large sets of structured, non-linear algebraic and differential equations is one of the most computationally expensive steps in the dynamic simulation of building energy systems. Here, the efficiency, robustness and accuracy of two commonly employed solution methods are compared. The comparison is conducted using the HVACSIM+ software package, a component based building system simulation tool. The HVACSIM+ software presently employs Powell's Hybrid method to solve systems of nonlinear algebraic equations that model the dynamics of energy states and interactions within buildings. It is shown here that the Powell's method does not always converge to a solution. Since a myriad of other numerical methods are available, the question arises as to which method is most appropriate for building energy simulation. This paper finds considerable computational benefits result from replacing the Powell's Hybrid method solver in HVACSIM+ with a solver more appropriate for the challenges particular to numerical simulations of buildings. Evidence is provided that a variant of the Levenberg-Marquardt solver has superior accuracy and robustness compared to the Powell's Hybrid method presently used in HVACSIM+.