Nucleic acid amplification is a crucial method in infectious disease diagnostic and identification of cancer mutations that allows for informed treatment. The CMOS-fabricated Ion-Sensitive Field-Effect Transistor (ISFET) can be exploited at the Point-of-Care as part of a handheld Lab-on-Chip (LoC) device thanks to its pH sensitivity to achieve real-time sensing of the hydrogen release during amplification. Current approaches involve off-chip processing of the sensor data, introducing challenges due to the amount of data to be transmitted and analysed, and to ensure patient privacy in a procedure that involves multiple data transfers. This paper proposes a pixel architecture for real-time in-pixel classification of the sensor data. A 4x4 ISFET array is shown, with a design that allows for full scalability to a much larger device. The system is developed in TSMC 65nm technology, resulting in a total pixel area of 51.4x49.54μm. Classification of positive and negative experiments is simulated with ideal and real experimental data.

BRAF p.V600E mutations are key biomarkers for colorectal cancer (CRC) which are associated with poor patient prognosis and response to EGFR treatment. This paper demonstrates a proof-of-concept study for a portable Lab-on-Chip (LoC) device integrated with Ion-Sensitive Field-Effect Transistor (ISFET) sensors in detecting BRAF p.V600E biomarkers with high accuracy and speed, for Point-of-Care (PoC) testing of CRC. Wild-type and mutant-type copies of the BRAF gene were successfully distinguished using chip-compatible loop-mediated isothermal amplification (LAMP) reactions. Optimisation of the LAMP assay targeting BRAF p.V600E was performed and tested using qPCR instrumentation as a gold standard and benchmark for the LoC, exhibiting improved limits of detection (LODs) at 102copies/µL in under 15 minutes. A bespoke signal processing methodology was also developed using the Convolutional Neural Network EEGNet to classify nucleic acid amplification experiments on ISFET arrays, achieving an accuracy of over 95% and designed to be easily transferable to novel DNA/RNA targets. The findings show evidence of the potential to employ ISFET sensing in PoC diagnostics for CRC, ultimately bridging the gap in accessibility in limited resource settings.

PIK3CA p.E545K mutation is a well-studied breast cancer biomarker with a clinical significance as a therapeutic target, particularly with the use of the small molecule inhibitor Alpelisib. An issue with detecting this mutation and other mutations in this exon is that 98% of its sequence homology is identical to a pseudogene, a non-functional non-coding gene found in chromosome 22. This paper aims to use ISFET enabled Lab-on-Chip (LoC) technology, coupled with a well-studied isothermal amplification method (LAMP), as a means to distinguish wild-type (WT), mutant (MT) and pseudogene (PG) copies of DNA. In an age where affordability and accessibility of diagnostic tests is of crucial importance, the use of CMOS technology offers a great potential as an alternative for regular near-patient molecular testing using liquid biopsies. Bespoke primer design is tested and optimised with synthetic DNA to achieve high specificity and low sensitivity (100 copies). The primer efficiencies were also tested on our in-house LoC system showing near identical results to those obtained from a qPCR instrument. Spiking experiments were also conducted, where mixed populations of WT and MT were tested to assess the primers' abilities to estimate the variant allele frequency (VAF) of p.E545K and to mimic clinical scenarios. The results continue to depict how LoC technology in partnership with LAMP detection can be used in a liquid biopsy setting to detect blood DNA biomarkers to assist better patient stratification.

This work presents a chemical readout system designed in TSMC 180 nm technology. The proposed design has an input range of 0-1.8 V, linearity (R2) of over 0.997, high sensitivity of 600 KHz/pH, a maximum frame rate of 1.4 μ$s$and a small chip area. The readout system includes an Ion-Sensitive Field Effect Transistor (ISFET) front-end that works in the saturation region, trans-linear circuits for linearity enhancement, and a CCO (Current Controlled Oscillator)-based ADC as an analogue to digital converter. This system was designed to provide a good balance between input range, linearity, and silicon area. The proposed architecture is capable of compensating for 400 mV of trapped charge by changing the biasing current of the lineariser as a universal quadratic equation solver.

This paper presents an experimental characterisation of the pH dependence of drift on ISFET sensors. Experiments are run on an array of over 4000 sensors fabricated in commercial CMOS technology with pH buffer solutions of known pH. A mathematical model is built and the fitted coefficients are compared between experiments where the pH is constant and where pH changes. An exponential and a linear model are compared, as well as different metrics for coefficient comparison. It is shown that a dependence can be found between drift and pH variation when drift rate exceeds$15\mu V/s$. This serves as a first step towards the development of a new metric to aid classification of nucleic acid amplification experiments.

This paper presents a winner-take-all (WTA) approach for implementing background inhibition in neuromorphic Ion-Sensitive Field-Effect Transistor (ISFET) arrays. The integration of WTA, integrate and fire (I&F) and CMOS-based electrochemical readout paves the way for the next generation of Lab-on-chip (LoC) platforms to diagnose and classify infectious diseases using sensor learning. The integration of the WTA in individual pixels allows for spatial adaptive filtering which can help eliminate the dynamic background due to ion accumulation at the gate of the sensors. The readout is done through address-event representation (AER) to enable ultra-low power data acquisition. The cluster implementation makes the design scalable for implementation as part of a large-scale integrated sensor. The paper proposes a novel ultra-low powered approach where the pixel power consumption ranges from 171.6nW to 410.9nW with an expected sensitivity of 20.2 KHz/dpH to 29.1 KHz/dpH. The sensor array is implemented in TSMC 0.18$\mu\mathrm{m}$.

Data-driven approaches for molecular diagnostics are emerging as an alternative to perform an accurate and inexpensive multi-pathogen detection. A novel technique called Amplification Curve Analysis (ACA) has been recently developed by coupling machine learning and real-time Polymerase Chain Reaction (qPCR) to enable the simultaneous detection of multiple targets in a single reaction well. However, target classification purely relying on the amplification curve shapes currently faces several challenges, such as distribution discrepancies between different data sources of synthetic DNA and clinical samples (i.e., training vs testing). Optimisation of computational models is required to achieve higher performance of ACA classification in multiplex qPCR through the reduction of those discrepancies. Here, we proposed a novel transformer-based conditional domain adversarial network (T-CDAN) to eliminate data distribution differences between the source domain (synthetic DNA data) and the target domain (clinical isolate data). The labelled training data from the source domain and unlabelled testing data from the target domain are fed into the T-CDAN, which learns both domains' information simultaneously. After mapping the inputs into a domain-irrelevant space, T-CDAN removes the feature distribution differences and provides a clearer decision boundary for the classifier, resulting in a more accurate pathogen identification. Evaluation of 198 clinical isolates containing three types of carbapenem-resistant genes (blaNDM,blaIMPandblaOXA-48) illustrates a curve-level accuracy of 93.1% and a sample-level accuracy of 97.0% using T-CDAN, showing an accuracy improvement of 20.9% and 4.9% respectively, compared with previous methods. This research emphasises the importance of deep domain adaptation to enable high-level multiplexing in a single qPCR reaction, providing a solid approach to extend qPCR instruments' capabilities without hardware modification in real-world clinical applications.

This paper introduces a linear weighted integrate-and-fire (I&F) neuron architecture for Ion-Sensitive Field-Effect Transistors (ISFETs). It contributes to the next generation of neuromorphic lab-on-chip (LoC) platforms with the aim to integrate electrochemical sensors with neural networks on-silicon to compensate for sensor non-idealities. The neuron consists of a readout circuit, a linear voltage-controlled weighting circuit, and a robust I&F circuit with low power consumption. Notably, the readout in the neuron circuit achieves linear conversion of input voltage to output current at low power. This work also presents a cluster architecture for spatial correlation of trapped charge effects and process variations. The calibration system integrated in each cluster is realized using a current bit cell chain inspired from the current mode algorithmic ADC. The compensation range for each pixel ranges from −157.7 mV to 128.1 mV. The system is implemented as a $25\times 20$ cluster array, and the sensitivity of each cluster is 10.92 kHz/pH.

We have developed a CMOS System-on-Chip capable of concurrent DNA detection and actuation towards ultrafast and accurate molecular diagnostics. The system relies on a sensor array to perform electrochemical imaging by combining potentiometric ion-sensitive field-effect transistor (ISFET) sensing with impedance spectroscopy to concurrently detect DNA molecules and protons generated during an amplification reaction at high resolution. The impedance sensing electrodes are also used to conduct DNA manipulation using dielectrophoresis (DEP), further improving performance. The system achieves a maximum electric field strength of 2.5MV/m, generated with an AC voltage input of 1.8V, which is suitable for a battery supplied portable device. The sensing system made of EIS and ISFET front-ends are implemented in 0.18 μm CMOS technology. The ISFET sensing system presents a readout sensitivity of up to 129 mV (with a gain of 15 dB) with programmable controlled gate voltage to compensate non-idealities. Lastly, the EIS system is able to detect an impedance up to 100 MO within a frequency range between 100Hz-100kHz, presenting a dynamic range of 84.1 dB. The integrated systems achieve dual sensing and actuation for electrochemical DNA sensing with improved performance.

This paper presents a method for detection of ESR1 p.E380Q, a common Breast Cancer (BC) mutation, using an ISFET (Ion-Sensitive Field-Effect Transistor) based Lab-on-Chip (LoC) platform. The LoC contains an ISFET array that can detect pH changes during DNA amplification, specifically Loop-Mediated Isothermal Amplification (LAMP). Synthetic ESR1 DNA was detected in a comparison pH-LAMP assay, carried out on the LoC platform as well as a conventional qPCR instrument. Positive detection of the allele arises due to bespoke allele-specific primers that target one base-pair difference between the wild-type and mutant alleles. The LoC and qPCR demonstrate comparable results detecting the mutant allele with mutant primers in around 25 minutes. The sensing microchip technology coupled with the molecular methods of isothermal chemistries and primer design allow this platform to be tested at a Point-of-Care setting for breast cancer patients, offering mutational tracking platform of circulating tumour DNA in liquid biopsies to assist patient stratification and allow tailored treatments.

A multi-sensor pixel is presented using ion-sensitive field-effect transistors (ISFETs) as ion sensors, photodiodes as optical sensors and MOSFETs as temperature sensors. The pixel is inspired from an Active Pixel Sensor (APS) topology previously reported as an ISFET front-end. Current mirrors and switches are used to multiplex sensors and encode the output in the time domain for in-pixel quantisation. A novel temperature compensation method, based on temperature coefficient cancellation, is implemented based on bandgap and translinear circuits. The non-idealities of ISFETs, such as drift and trapped charge, are compensated by source voltage modulation. The pixel is implemented using TSMC 0.18 μm CMOS technology and occupies a 38 μm × 36 μm area with an ultra-low power consumption of 33.96nW associated with weak inversion operation. The simulated results demonstrate a high pH sensitivity of 33.96 ns/pH and an ultra-stable temperature variation between 63 fA/°C and 2.3 pA/°C.

The ion-sensitive field-effect transistor (ISFET) has emerged as an ideal candidate to carry out point-of-care diagnosis through detection of hydrogen ions produced during amplification of pathogenic DNA. This group has previously hypothesised that ISFET-based DNA detection could be enhanced by positioning DNA close to the ISFET surface using electrodes that carry out low-power manipulation of DNA through dielectrophoresis (DEP). This paper provides a proof-of-concept for an ISFET-DEP system for DNA detection, combining information gathered from the literature and FEM electric field simulations to test the validity of the hypothesis and highlight key challenges in implementation. An electrode system was designed with sets of line and rectangular castellated interdigitated electrodes that produced simulated maximum electric field strengths between 2.58 - 7.70 × 105Vm-1and is capable of trapping DNA with applied voltages as low as (0.50 ± 0.05)V. Using this design, a 180nm CMOS prototype was developed for preliminary testing, containing three 5 × 2 arrays of 20μm × 20μm ISFETs as part of an 800μm × 400μm chip.

We design an Ion-Sensitive Field-Effect (ISFET) array leveraging on the two successful fields of neuromorphic electronics and chemical sensing to encode the signal in spikes and perform sensor processing between neighbouring pixels. The array is structured as clusters integrating 4 × 4 pixels with sensor compensation, taking advantage of spatial correlation of sensor non-idealities. The offset compensation is capable of calibrating in a range of 662 mV. The system shows a robust, scalable and power efficient architecture with a sensitivity ranging from 2.56 MHz/pH to 3.38 MHz/pH. The pixel occupies an area of 30μm × 24μm, and the cluster area is 205 μm × 205 μm. The layout of each pixel is spread out with digital blocks embedded in-between, which improves signal coupling by enlarging the chemical sensing area of each pixel. The system readout implements address event representation (AER) for triggering the outputs.

Widening the range of targets for ion-sensitive field-effect transistors (ISFETs) fabricated in unmodified CMOS technology has been enabled by the deposition of polymeric ionophore membranes at the surface, requiring specific sensor training. We present a novel ISFET array with on-chip multiplexing capabilities to perform offline training and real-time sensing on a single substrate, enabling analogue averaging for low noise sensing and reducing post-processing. The analogue front-end pixels rely on a modular current-mode spatial averaging (CMSA) circuit, producing an averaged sensor output per cluster based on a switching matrix integrated within the array. At the output stage, a weak inversion active resistor implements an ELIN system to guarantee linearity, reaching an expected sensitivity of 160 mV/pH with a gain of 3, when designed using a 0.18 μm standard CMOS technology. Based on calibration data for the ion targets, an on-chip training algorithm determines the sensitivity of each pixel to each ion, identifies sensing regions corresponding to polymeric membranes at the surface and sets the pixel connectivity through the switching matrix.

We present the next step of neuromorphic ISFET arrays with spike domain encoding and spatial device compensation. Each pixel provides a spiking signal with a frequency related to the pH in solution and expected sensitivity of 48.6 to 112.2 kHz/dpH. The array is arranged as clusters which use regulation to cancel undesirable sensor offset and then linear interpolation for temporal drift during the readout. The scheme relies on spatial correlation of ISFET behaviour which is demonstrated with a low standard deviation of 11.6 mV sensor offset, which is well in the pixel compensation range of ± 500 mV. On an array level, address-event representation is used for external signal handling, which enables low power and scalable throughput. The array chip is implemented in TSMC 0.18 μm CMOS technology.

We present a novel System-on-Chip (SoC) design for DNA amplification and detection with the ability to electrostatically manipulate DNA molecules. The chip integrates an array of ISFET sensors for pH monitoring with heaters for temperature regulation, which enables amplification methods requiring thermal cycling or constant temperature. The sensing array comprises 1129 pixels, with each pixel based on an ISFET front-end with a programmable gate and implemented in a unity gain buffer configuration. The pH readout achieves a sensitivity of 196.5mV/pH with a gain of 30 and a frame rate of 80.5 fps. A temperature characterisation demonstrates that the system is capable of raising the temperature of a 10μL chemical solution to 96.44° C. Lastly, the on-chip interdigitated electrodes use a dielectrophoresis (DEP) technique to generate an AC sinusoidal electric field over a frequency range of 100Hz-1MHz with a simulated amplitude of approximately 100kVm-1to orient and immobilise DNA molecules at the ISFET sensing interface.

A mobile diagnostic system is demonstrated for the early detection of infectious disease outbreaks in remote areas. The system comprises an ISFET-based platform, an AndroidOS application running on a smartphone, and a cloud server. Incorporation of microfluidics on the 78×56 ISFET array permits on-board isothermal DNA amplification and detection. Each die is mounted on single-use cartridges. The platform is controlled by the app, which collects relevant data via Bluetooth to process through algorithms stored on the smartphone. Upon a positive result, a data package containing disease type, geographical location, and timestamp is sent to the cloud. Real-time monitoring of outbreaks to pandemics can be visualized accordingly.

This paper introduces the use of a diode-connected MOSFET as a temperature controlled switch for trapped charge cancellation of ISFET sensors. The current flowing through the reverse-biased diodes of 2.7 aA is negligible at low temperature but reaches 23 fA when heated to 100°C, which allows for low temperature readout and high temperature compensation of trapped charge. The diode-connected device is tied to the floating gate of the ISFET which is integrated as part of a source-follower readout. The in-pixel feedback loop uses a comparator to turn off the polysilicon heaters once the offset has been cancelled, triggering the readout by switching the op amp into a buffer configuration. Simulations show that the system is calibrated in 35s and the output sensitivity reaches 27.74 mV/pH. The pixel output then tracks any ionic change at its surface without sensor offset.

We demonstrate a CMOS-based lab-on-chip platform which is capable of ion imaging to detect a variation in hydrogen, potassium and sodium ions. An ISFET array is used to detect a change in ion concentration with a calibration scheme to cancel the offset due to trapped charge. The Si3N4passivation layer confers an inherent sensitivity to the sensors, and additional polymer membranes are pipetted containing a potassium and sodium ionophore. An initial algorithm identifies the sensitivity of each pixel towards the target ions. The user can inject a solution with a given concentration of ions and observe the real-time output change of the array on a MATLAB interface. The display then provides an estimate of the target ion concentration.

We demonstrate a diagnostics platform which integrates an ISFET array and a temperature control loop for isothermal DNA detection. The controller maintains a temperature of 63°C to perform nucleic acid amplification which is detected by the on-chip sensors. The 32×32 ISFET array is first calibrated to cancel trapped charge and then measures the change in the pH of the reaction. The sensor data is sent to a microcontroller and the reaction is monitored in real-time using a MATLAB interface. Experiments confirm a change of 0.9 pH when tested for the presence of RNA associated with the Zika virus.

In this paper, we present a novel bio-inspired CMOS-based hexagonal ISFET sensor which, compared to traditional devices, exhibit a more compact arrangement as part of large arrays and provides benefits in terms of capacitive attenuation. We classify these novel sensors as Enclosed Gate Transistors (EGTs) and provide a layout in standard AMS 0.35 μm technology. Electrical characteristics are derived theoretically for the device, including an effective W/L, and simulations for both AMS 0.18 and 0.35 μm CMOS processes are provided. The results indicate a decrease in parasitic gate capacitance between 20 % and 40%, highlighting the advantages in attenuation of respectively 0.36 dB and 0.71 dB for the smallest lengths of devices. The noise performance is also improved, with the input referred noise reduced by 1 or 2 % for each process. The devices were fabricated in standard 0.35 μm CMOS technology for future characterisation.

In this paper, we present a novel approach to ISFET arrays which allows the conception of ion imaging Lab-on-CMOS platforms. K+ and Na+ selective polymer membranes are deposited on the surface of the array so that each pixel is selective to a particular ionic species. An initial calibration produces an accurate mapping of the array in terms of ion-selective regions and determines the sensitivity of the membrane. The system exhibits K+ and Na+ sensitivities of respectively 51.2 mV/dec and 46.8 mV/dec, and demonstrates good discrimination of Potassium and Sodium ions for a common solution exposed to the chip, with a reported error lower than 1%. This ISFET-based tri-ion imaging array constitutes the basis for a portable integrated multi-ion platform.

A novel pixel architecture is presented to be part of a pH-based DNA microarray using ISFETs as chemical sensors. The design, based on APS architectures, performs pulse width modulation to encode the pH in time. It allows compensation for a major ISFET nonideality, offset in the threshold voltage, which is caused by trapped charge on the floating gate and the passivation layer of the ISFET. Also, the drop in sensitivity due to the passivation capacitance inherent to CMOS processes is attenuated. The system is implemented using a 0.35 fim standard CMOS technology. The pixel is shown to achieve a high and tunable accuracy of between 0.55 μs/dpH and 2.9 μs/dpH. Along with an estimation of the noise and the incidence of calibration, this leads to a resolution of approximately 20 mpH on a 1 pH-range. Trapped charge compensation proves to be effective up to an offset voltage of 1.25 V. The pixel is compact and reaches a total area of 16.5 μm × 16.25 μm.