Pantelis Georgiou

Simultaneous DNA amplification and detection using a pH-sensing semiconductor system

We developed an integrated chip for real-time amplification and detection of nucleic acid using pH-sensing complementary metal-oxide semiconductor (CMOS) technology. Here we show an amplification-coupled detection method for directly measuring released hydrogen ions during nucleotide incorporation rather than relying on indirect measurements such as fluorescent dyes. This is a label-free, non-optical, real-time method for detecting and quantifying target sequences by monitoring pH signatures of native amplification chemistries. The chip has ion-sensitive field effect transistor (ISFET) sensors, temperature sensors, resistive heating, signal processing and control circuitry all integrated to create a full system-on-chip platform. We evaluated the platform using two amplification strategies: PCR and isothermal amplification. Using this platform, we genotyped and discriminated unique single-nucleotide polymorphism (SNP) variants of the cytochrome P450 family from crude human saliva. We anticipate this semiconductor technology will enable the creation of devices for cost-effective, portable and scalable real-time nucleic acid analysis.

A novel voltage-clamped CMOS ISFET sensor interface

This paper presents a novel interface for ion-sensitive field effect transistors (ISFET) in which operation at a fixed electrical bias is achieved by voltage clamping. The chosen topology provides pH-dependent current and voltage output signals to drive an appropriate output stage. The circuit can be operated in either strong or weak inversion, depending on the requirements of the application with a pseudo-differential ISFET-REFET topology to allow use of an on-chip reference electrode. Simulation results are shown herein for single-ended and differential implementations. For a single-ended front-end with 1nA bias current, the strong inversion implementation at 2.5V supply has a power consumption of 0.185mW at pH 7 and the weak inversion implementation at 1.5V supply has a power consumption of 13nW at pH 7. The circuit and ISFET-REFET pair have been fabricated in the UMC 0.25mum CMOS technology.

A multichannel DNA SoC for rapid point-of-care gene detection

Point-of-care diagnostics for detection of genetic sequences require biosensing platforms that are sensitive to the target sequence, and are also fast, mass-manufacturable, and - ideally - disposable. Conventional lab-based methods of detecting DNA sequences rely on optical methods, typically by the addition of fluorescent tags to the target DNA that in turn latches onto a DNA probe sequence only if there is a match between the two. These techniques are cumbersome as they require upfront tagging of the DNA with expensive reagents and laboratory equipment to detect the optical signals. Recently, developments have been made in transferring these optical methods to inexpensive CMOS ICs [1], although the requirement for tagging remains. Magnetic beads offer an alternative means of tagging the DNA and their presence can be detected by the shift in resonant frequency of an on-chip LC tank [2]. There have also been attempts based on “label-free” electrochemical detection using FETs [3,4], but none of these have been implemented in unmodified standard CMOS.

A Silicon Pancreatic Beta Cell for Diabetes

The paper will consider how silicon devices such as ion-sensitive field effect transistors can be used to model metabolic functions in biology. In a first example, a biologically inspired silicon beta cell is presented to serve as the main building block of an artificial pancreas. This is to be used for real-time glucose sensing and insulin release for diabetics. This system presents the first silicon implementation of a metabolic cell capable of exhibiting variable bursting behavior upon glucose stimulation. Based on the Hodgkin and Huxley formalism, this approach achieves dynamics similar to that of biological beta cells by using devices biased in the subthreshold regime. In addition to mimicking the physiological behavior of the beta cell, the circuit achieves good power efficiency, measured to be 4.5 muW

Robust Fault Detection System for Insulin Pump Therapy Using Continuous Glucose Monitoring

Background: The popularity of continuous subcutaneous insulin infusion (CSII), or insulin pump therapy, as a way to deliver insulin more physiologically and achieve better glycemic control in diabetes patients has increased. Despite the substantiated therapeutic advantages of using CSII, its use has also been associated with an increased risk of technical malfunctioning of the device, which leads to an increased risk of acute metabolic complications, such as diabetic ketoacidosis. Current insulin pumps already incorporate systems to detect some types of faults, such as obstructions in the infusion set, but are not able to detect other types of fault such as the disconnection or leakage of the infusion set. Methods: In this article, we propose utilizing a validated robust model-based fault detection technique, based on interval analysis, for detecting disconnections of the insulin infusion set. For this purpose, a previously validated metabolic model of glucose regulation in type 1 diabetes mellitus (T1DM) and a continuous glucose monitoring device were used. As a first step to assess the performance of the presented fault detection system, a Food and Drug Administration-accepted T1DM simulator was employed. Results: Of the 100 in silico tests (10 scenarios on 10 subjects), only two false negatives and one false positive occurred. All faults were detected before plasma glucose concentration reached 300 mg/dl, with a mean plasma glucose detection value of 163 mg/dl and a mean detection time of 200 min. Conclusions: Interval model-based fault detection has been proven (in silico) to be an effective tool for detecting disconnection faults in sensor-augmented CSII systems. Proper quantification of the uncertainty associated with the employed model has been observed to be crucial for the good performance of the proposed approach.

A bio-inspired glucose controller based on pancreatic β-cell physiology.

Introduction: Control algorithms for closed-loop insulin delivery in type 1 diabetes have been mainly based on control engineering or artificial intelligence techniques. These, however, are not based on the physiology of the pancreas but seek to implement engineering solutions to biology. Developments in mathematical models of the β-cell physiology of the pancreas have described the glucose-induced insulin release from pancreatic β cells at a molecular level. This has facilitated development of a new class of bio-inspired glucose control algorithms that replicate the functionality of the biological pancreas. However, technologies for sensing glucose levels and delivering insulin use the subcutaneous route, which is nonphysiological and introduces some challenges. In this article, a novel glucose controller is presented as part of a bio-inspired artificial pancreas. Methods: A mathematical model of β-cell physiology was used as the core of the proposed controller. In order to deal with delays and lack of accuracy introduced by the subcutaneous route, insulin feedback and a gain scheduling strategy were employed. A United States Food and Drug Administration-accepted type 1 diabetes mellitus virtual population was used to validate the presented controller. Results: Premeal and postmeal mean ± standard deviation blood glucose levels for the adult and adolescent populations were well within the target range set for the controller [(70, 180) mg/dl], with a percent time in range of 92.8 ± 7.3% for the adults and 83.5 ± 14% for the adolescents. Conclusions: This article shows for the first time very good glucose control in a virtual population with type 1 diabetes mellitus using a controller based on a subcellular β-cell model.

A Composite Model of Glucagon-Glucose Dynamics for In Silico Testing of Bihormonal Glucose Controllers

Background: The utility of simulation environments in the development of an artificial pancreas for type 1 diabetes mellitus (T1DM) management is well established. The availability of a simulator that incorporates glucagon as a counterregulatory hormone to insulin would allow more efficient design of bihormonal glucose controllers. Existing models of the glucose regulatory system that incorporates glucagon action are difficult to identify without using tracer data. In this article, we present a novel model of glucagon-glucose dynamics that can be easily identified with standard clinical research data. Methods: The minimal model of plasma glucose and insulin kinetics was extended to account for the action of glucagon on net endogenous glucose production by incorporating a new compartment. An existing subcutaneous insulin absorption model was used to account for subcutaneous insulin delivery. The same model of insulin pharmacokinetics was employed to model the pharmacokinetics of subcutaneous glucagon absorption. Finally, we incorporated an existing gastrointestinal absorption model to account for meal intake. Data from a closed-loop artificial pancreas study using a bihormonal controller on T1DM subjects were employed to identify the composite model. To test the validity of the proposed model, a bihormonal controller was designed using the identified model. Results: Model parameters were identified with good precision, and an excellent fitting of the model with the experimental data was achieved. The proposed model allowed the design of a bihormonal controller and demonstrated its ability to improve glycemic control over a single-hormone controller. Conclusions: A novel composite model, which can be easily identified with standard clinical data, is able to account for the effect of exogenous insulin and glucagon infusion on glucose dynamics. This model represents another step toward the development of a bihormonal artificial pancreas.

Advanced Insulin Bolus Advisor Based on Run-To-Run Control and Case-Based Reasoning

This paper presents an advanced insulin bolus advisor for people with diabetes on multiple daily injections or insulin pump therapy. The proposed system, which runs on a smartphone, keeps the simplicity of a standard bolus calculator while enhancing its performance by providing more adaptability and flexibility. This is achieved by means of applying a retrospective optimization of the insulin bolus therapy using a novel combination of run-to-run (R2R) that uses intermittent continuous glucose monitoring data, and case-based reasoning (CBR). The validity of the proposed approach has been proven by in-silico studies using the FDA-accepted UVa-Padova type 1 diabetes simulator. Tests under more realistic in-silico scenarios are achieved by updating the simulator to emulate intrasubject insulin sensitivity variations and uncertainty in the capillarity measurements and carbohydrate intake. The CBR(R2R) algorithm performed well in simulations by significantly reducing the mean blood glucose, increasing the time in euglycemia and completely eliminating hypoglycaemia. Finally, compared to an R2R stand-alone version of the algorithm, the CBR(R2R) algorithm performed better in both adults and adolescent populations, proving the benefit of the utilization of CBR. In particular, the mean blood glucose improved from 166 ± 39 to 150 ± 16 in the adult populations (p = 0.03) and from 167 ± 25 to 162 ± 23 in the adolescent population (p = 0.06). In addition, CBR(R2R) was able to completely eliminate hypoglycaemia, while the R2R alone was not able to do it in the adolescent population.

A Robust ISFET pH-Measuring Front-End for Chemical Reaction Monitoring

This paper presents a robust, low-power and compact ion-sensitive field-effect transistor (ISFET) sensing front-end for pH reaction monitoring using unmodified CMOS. Robustness is achieved by overcoming problems of DC offset due to trapped charge and transcoductance reduction due to capacitive division, which commonly exist with implementation of ISFETs in CMOS. Through direct feedback to the floating gate and a low-leakage switching scheme, all the unwanted factors are eliminated while the output is capable of tracking a pH reaction which occurs at the sensing surface. This is confirmed through measured results of multiple devices of different sensing areas, achieving a mean amplification of 1.28 over all fabricated devices and pH sensitivity of 42.1 mV/pH. The front-end is also capable of compensating for accumulated drift using the designed switching scheme by resetting the floating gate voltage. The circuit has been implemented in a commercially-available 0.35 μm CMOS technology achieving a combined chemical and electrical output RMS noise of 3.1 mV at a power consumption of 848.1 nW which is capable of detecting pH changes as small as 0.06 pH.

A CMOS-Based ISFET Chemical Imager With Auto-Calibration Capability

This paper presents a novel auto-calibration technique for eliminating sensor mismatch in CMOS-based chemical imagers. Designed using an 8 × 8 array comprising of pH-sensitive ion-sensitive field-effect transistors (ISFETs), the chemical imager is capable of implementing a gradient-based calibration algorithm by biasing programmable-gate (PG) ISFETs at a common operating point when exposed to a solution of homogenous pH. The system was fabricated in a typical 0.35-μm CMOS technology and demonstrated a fast rate of convergence (500 ms per iteration) while a convergence accuracy of 45 mV on a gain of 10 (0.5% relative standard error and 2% pixel-to-pixel variation) was achieved. A maximum pH sensitivity of 57 mV/pH is also reported.