Hydrophilic polymers are the center of research emphasis in nanotechnology because of their perceived “intelligence”. They can be used as thin films, scaffolds, or nanoparticles in a wide range of biomedical and biological applications. Here we highlight recent developments in engineering uncrosslinked and crosslinked hydrophilic polymers for these applications. Natural, biohybrid, and synthetic hydrophilic polymers and hydrogels are analyzed and their thermodynamic responses are discussed. In addition, examples of the use of hydrogels for various therapeutic applications are given. We show how such systems’ intelligent behavior can be used in sensors, microarrays, and imaging. Finally, we outline challenges for the future in integrating hydrogels into biomedical applications.

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Hydrogels in Biology and Medicine: From Molecular Principles to Bionanotechnology†

Wearable sensor technologies are essential to the realization of personalized medicine through continuously monitoring an individual's state of health. Sampling human sweat, which is rich in physiological information, could enable non-invasive monitoring. Previously reported sweat-based and other non-invasive biosensors either can only monitor a single analyte at a time or lack on-site signal processing circuitry and sensor calibration mechanisms for accurate analysis of the physiological state. Given the complexity of sweat secretion, simultaneous and multiplexed screening of target biomarkers is critical and requires full system integration to ensure the accuracy of measurements. Here we present a mechanically flexible and fully integrated (that is, no external analysis is needed) sensor array for multiplexed in situ perspiration analysis, which simultaneously and selectively measures sweat metabolites (such as glucose and lactate) and electrolytes (such as sodium and potassium ions), as well as the skin temperature (to calibrate the response of the sensors). Our work bridges the technological gap between signal transduction, conditioning (amplification and filtering), processing and wireless transmission in wearable biosensors by merging plastic-based sensors that interface with the skin with silicon integrated circuits consolidated on a flexible circuit board for complex signal processing. This application could not have been realized using either of these technologies alone owing to their respective inherent limitations. The wearable system is used to measure the detailed sweat profile of human subjects engaged in prolonged indoor and outdoor physical activities, and to make a real-time assessment of the physiological state of the subjects. This platform enables a wide range of personalized diagnostic and physiological monitoring applications.

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Fully integrated wearable sensor arrays for multiplexed in situ perspiration analysis

An analyte monitor includes a sensor, a sensor control unit, and a display unit. The sensor has, for example, a substrate, a recessed channel formed in the substrate, and conductive material disposed in the recessed channel to form a working electrode. The sensor control unit typically has a housing adapted for placement on skin and is adapted to receive a portion of an electrochemical sensor. The sensor control unit also includes two or more conductive contacts disposed on the housing and configured for coupling to two or more contact pads on the sensor. A transmitter is disposed in the housing and coupled to the plurality of conductive contacts for transmitting data obtained using the sensor. The display unit has a receiver for receiving data transmitted by the transmitter of the sensor control unit and a display coupled to the receiver for displaying an indication of a level of an analyte. The analyte monitor may also be part of a drug delivery system to alter the level of the analyte based on the data obtained using the sensor.

Analyte Monitoring Device And Methods Of Use

A nonlinear model predictive controller has been developed to maintain normoglycemia in subjects with type 1 diabetes during fasting conditions such as during overnight fast. The controller employs a compartment model, which represents the glucoregulatory system and includes submodels representing absorption of subcutaneously administered short-acting insulin Lispro and gut absorption. The controller uses Bayesian parameter estimation to determine time-varying model parameters. Moving target trajectory facilitates slow, controlled normalization of elevated glucose levels and faster normalization of low glucose values. The predictive capabilities of the model have been evaluated using data from 15 clinical experiments in subjects with type 1 diabetes. The experiments employed intravenous glucose sampling (every 15 min) and subcutaneous infusion of insulin Lispro by insulin pump (modified also every 15 min). The model gave glucose predictions with a mean square error proportionally related to the prediction horizon with the value of 0.2 mmol L(-1) per 15 min. The assessment of clinical utility of model-based glucose predictions using Clarke error grid analysis gave 95% of values in zone A and the remaining 5% of values in zone B for glucose predictions up to 60 min (n = 1674). In conclusion, adaptive nonlinear model predictive control is promising for the control of glucose concentration during fasting conditions in subjects with type 1 diabetes.

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Nonlinear model predictive control of glucose concentration in subjects with type 1 diabetes

The present invention relates generally to systems and methods for measuring an analyte in a host. More particularly, the present invention relates to systems and methods for transcutaneous measurement of glucose in a host.

Transcutaneous analyte sensor

A miniaturized device for simultaneous measurement of glucose and lactate levels was produced by means of photopatterning of enzyme-containing photosensitive membrane precursors. This device shows no cross-talk and a lifetime for both the glucose and the lactate sensors of more than 2 weeks when continuously operated in undiluted bovine serum. Linear response ranges of up to 40 mM for glucose and 25 mM for l-lactate, in combination with 95% response times of 0.98 with respect to laboratory techniques. Subcutaneous measurements of glucose levels in pigs were close to the corresponding blood levels obtained without in vivo calibration.

Thin-film microbiosensors for glucose-lactate monitoring

A neural predictive controller for closed-loop control of glucose using subcutaneous (s.c.) tissue glucose measurement and s.c. infusion of monomeric insulin analogs was developed and evaluated in a simulation study. The proposed control strategy is based on off-line system identification using neural networks (NNs) and nonlinear model predictive controller design. The system identification framework combines the concept of nonlinear autoregressive model with exogenous inputs (NARX) system representation, regularization approach for constructing radial basis function NNs, and validation methods for nonlinear systems. Numerical studies on system identification and closed-loop control of glucose were carried out using a comprehensive model of glucose regulation and a pharmacokinetic model for the absorption of monomeric insulin analogs from the s.c. depot. The system identification procedure enabled construction of a parsimonious network from the simulated data, and consequently, design of a controller using multiple-step-ahead predictions of the previously identified model. According to the simulation results, stable control is achievable in the presence of large noise levels, for unknown or variable time delays as well as for slow time variations of the controlled process. However, the control limitations due to the s.c. insulin administration makes additional action from the patient at meal time necessary.

Neural predictive controller for insulin delivery using the subcutaneous route

We studied the kinetics of glucose exchange between plasma and interstitial fluid (ISF) in human skeletal muscle and adipose tissue under fasting conditions. Five normal human subjects received an intravenous [6,6- 2 H 2 ]glucose infusion in a prime-continuous fashion. During the tracer infusion, the open-flow micropeffusion technique was employed to frequently sample ISF from quadriceps muscle and subcutaneous adipose tissue. The tracer glucose kinetics observed in muscle and adipose tissue ISF were found to be well described by a capillary-tissue exchange model. As a measure of transcapillary glucose exchange efficiency, the 95%. equilibrium time was calculated from the identified model parameters. This time constant was similar for skeletal muscle and adipose tissue (28.6 ± 3.2 vs. 26.8 ± 3.6 min; P = 0.60). Furthermore., we found that the (total) interstitial glucose concentration was significantly lower (P < 0.01) in muscle (3.32 ± 0.46 mmol/l) and adipose tissue (3.51 ± 0.17 mmol/l) compared with arterialized plasma levels (5.56 ± 0.13 mmol/l). Thus the observed gradients and dynamic relationships between plasma and ISF glucose in muscle and adipose tissue provide evidence that transcapillary exchange of glucose is limited in these two tissues under fasting conditions.

Assessment of transcapillary glucose exchange in human skeletal muscle and adipose tissue

We studied the kinetics of glucose exchange between plasma and interstitial fluid (ISF) in human skeletal muscle and adipose tissue under fasting conditions. Five normal human subjects received an ...

Paul Wach

Papers

Thin-film microbiosensors for glucose-lactate monitoring

Neural predictive controller for insulin delivery using the subcutaneous route

Assessment of transcapillary glucose exchange in human skeletal muscle and adipose tissue

Assessment of transcapillary glucose exchange in human skeletal muscle and adipose tissue.

Process improvement in diabetes care via benchmarking