Ingestible Sensor Research Articles

Ingestible electronic sensors to measure instantaneous medication adherence: A narrative review.

ObjectiveMedication nonadherence contributes to significant morbidity and mortality worldwide. While many techniques to measure adherence exist, digital pill systems represent a novel, direct method of measuring adherence and a means of providing instantaneous adherence supports. In this narrative review, we discuss digital pill system research based on clinical trials and qualitative investigations conducted to date and potential future applications of digital pill system in medication adherence measurement.MethodsWe conducted a literature search in PubMed of English language peer-reviewed articles describing the use of digital pill system for medication adherence measurement between 2000 and 2021. We included all articles that described the deployment of ingestible sensors and those involving qualitative investigations of digital pill system with human subjects.ResultsA total of 95 articles were found on initial search; 75 were removed based on exclusion criteria. Included articles were categorized as investigations that deployed an ingestible sensor in human populations (n = 18), or those that conducted qualitative work (n = 3). For pilot studies, the mean accuracy of the sensor to successfully detect a medication ingestion event ranged from 68% to 100%. When digital pill systems were deployed in real-world clinical settings, accuracy ranged from 68% to 90% with lower accuracy due to nonadherence to digital pill system technology. Qualitative studies demonstrated that providers and patients perceive the digital pill system as a facilitator for improving adherence and as a potential platform for delivering adherence interventions. Additionally, ingestion data from digital pill system was viewed as useful in facilitating adherence discussions between clinicians and patients.ConclusionsThis narrative review demonstrates that the use of digital pill system is broadly feasible across multiple disease states including human immunodeficiency virus, hepatitis C infection, solid organ transplants, tuberculosis, schizophrenia, cardiovascular disease, and acute fractures, where adherence is closely linked to significant morbidity and mortality. It also highlights key areas of research that are still needed prior to broad-scale clinical deployment of such systems.

The effectiveness of automated digital health solutions at successfully managing obesity and obesity-associated disorders: A PICO-structured investigation.

Most adults in the UK and USA are classified as overweight or obese. Recent studies suggest that the prevalence of obesity has further increased during the SARS-CoV-2 pandemic and associated lockdowns. Digital technologies may be effective at managing obesity and related comorbidities, a potential further justified by social isolation and distancing circumstances.This review of published literature employed a Patient-Intervention-Comparison-Outcome structured approach on the use of digital solutions to determine the effectiveness of their use in the management and treatment of obesity, hypertension, and type 2 diabetes and included commercially available, automated devices and applications that did not require intervention from a clinician. Our search covered studies published between January 2004 and February 2019, and 18 papers were included in the final analysis. The digital solutions reviewed were smartphone applications, wearable activity trackers, and ‘digital medicine offerings’ (DMO), including ingestible sensors and wearable patches.This study found that not all interventions were effective at encouraging the lifestyle changes required for the management of obesity. Smartphone applications requiring interaction from the patient appeared to be more effective at encouraging engagement with treatment interventions than more passive wearable activity trackers. Automated feedback from smartphone applications was effective at managing type 2 diabetes, while DMO were effective at reducing blood pressure.With the advancement of new technologies alongside a rapid increase in the prevalence of obesity and associated disorders, further studies comparing the various technologies available in larger sample populations for longer periods would help determine the most cost-effective preventive and therapeutic strategies.

The use of technology-based adherence monitoring in the treatment of hepatitis C virus.

Direct-acting antivirals (DAAs) achieve high hepatitis C virus (HCV) cure rates and are forgiving to missed doses, but adherence–efficacy relationships have not been well defined. Traditional adherence measures (e.g. pill counts, self-report and pharmacy refills) over-estimate medication adherence. Newer technology-based tools have been used to provide more objective adherence data. Herein, electronic medication diaries (e-diaries), medication events monitoring system (MEMS®) caps, electronic blister packs, electronic pill boxes, video-based directly observed therapy (vDOT), artificial intelligence platforms (AIPs), and ingestible sensor systems are described, and compared based on existing studies using DAA. Percent adherence, predictors of adherence, and HCV cure rates utilizing these technologies are included. DAA adherence with e-diaries was 95–96%, MEMS® caps and ingestible biosensors were between 95% and 97%, blister pack weekly dosing ranged 73–98%, and daily dosing 73–94%, whereas electronic pill boxes ranged between 39% and 89%, vDOT was 98% and AIP 91–96%. Despite a wide range of adherence, high sustained virologic response (SVR) rates (86–100%) were observed across all studies utilizing these different technology-based tools. Current data support the forgiveness of DAA therapies to missed doses using tools that provide more quantitative adherence measures compared with self-report and provide insight on adherence–efficacy relationships for contemporary DAA.

The Case for Digital Pill Use in Clinical Trials

Medication adherence in clinical trials is significantly overestimated through every phase of drug development. This can cause a reduction in statistical power, potentially resulting in incorrect conclusions regarding efficacy, safety, tolerability, and dose-response relationships, in addition to major cost overruns. Digital pill systems enable adherence measurement through an embedded ingestible sensor paired with an external receiver. An oral pharmaceutical product is over-encapsulated by a pharmaceutical-grade shell containing a biocompatible sensor. Upon exposure to gastrointestinal fluid, the shell dissolves and the sensor is activated. Medication ingestion data is transmitted via a digital signal. Clinicians and researchers use this data to track, in real time, when and if a medication was taken. These systems have demonstrated a 99.4% rate of accuracy, and have over 15-years of supporting experience and safety data. Spurred by the accelerated adoption of technology in healthcare and in everyday life, patients have become tech-savvy. They quickly adapt to these devices, and are able to use them safely and effectively. Digital pills can be implemented in most types of studies. In early-stage trials such as pharmacokinetic and pharmacodynamic studies, or dose-finding studies, accurate information on maximum-tolerated dose levels is essential and cannot be established unless study participants are highly adherent. In later-stage pivotal trials, effective medication adherence tracking can strengthen the dataset and confidence in the study results. Significant nonadherence may generate results that do not meet statistical or clinical significance for the critical endpoints, resulting in at worst, a failed trial, or at best, the need to enroll additional patients at substantial additional cost. Most clinical trials fail to achieve statistical significance, and poor medication adherence is often an important contributor. A digital pill system can ensure the quality and integrity of adherence data, increase confidence in the overall study data, and improve clinical trial efficiency

O43 INTRA-ABDOMINAL PRESSURE VARIATIONS IN HUMANS DURING PHYSICAL EXERCISES AND DAILY LIFE BY INTRAGASTRIC WIRELESS SENSOR

Abstract Aim The conflict between the intra-abdominal pressure (IAP) applied to the abdominal wall and its resistance determines the occurrence of ventral hernia. Knowledge about IAP variation in everyday life is limited and mainly obtained by invasive methods. The objective of the study is to propose a comprehensive evaluation of IAP based on a limited risk and discomfort method. Material and Methods A prospective study was carried out in 20 healthy volunteers. The intragastric pressure, validated for estimating IAP, was assessed by an ingestible pressure sensor*. Volunteers realized a set of supervised exercises, including breathing, apnea after calm exhalation and seven muscle contraction stereotyped exercises in three different positions (supine, sitting, standing). Then the volunteers resumed their daily activities with the pressure continuously recorded until gastric emptying. Pressure variations and rates were computed. Results The highest IAP levels were reached during coughing and jumping. Maximum peaks were respectively 65 ± 35 and 67 ± 31 mmHg with pressure rates of 121 and 114 mmHg.s−1 for these two exercises. The position did not affect the IAP variation. Men had significantly higher pressure values for pushing against a wall (P < 0.01), Valsalva maneuver and legs raising (P < 0.05) exercises. During daily life, peaks greater than 50, 100, and 150 mmHg occurred on average five times, twice, and once per hour, respectively. Conclusions This study provides a real-life characterization of IAP allowing the quantification of mechanical solicitation applied to the abdominal wall and the identification of risk situations for the occurrence of ventral hernias. * (SmartPill™, Medtronic, Minneapolis, MN, U.S.A)

New approaches to antipsychotic medication adherence – safety, tolerability and acceptability

ABSTRACT Introduction Antipsychotic pharmacotherapy is considered a first-line treatment in schizophrenia-related disorders and is associated with favorable prognosis and lower mortality rates. However, low adherence rates present a major clinical challenge. In this paper, we will review contemporary approaches to improve adherence to antipsychotic treatment, considering their mechanism of action, safety, tolerability and acceptability. Areas covered Novel pharmacological delivery methods included different routes of administration of registered medications (such as intramuscular clozapine preparation and transdermal asenapine), modifications of existing compounds (such as 3-monthly injectable formulation of paliperidone palmitate), and increased interest in oral long-acting medication formulations (such as with penfluridol). In addition, we reviewed innovative technology to monitor adherence, based on the use of electronic digital medicine systems and ingestible sensors. Expert opinion All of these diverse approaches were clinically relevant in enhancing treatment adherence and found to be safe and tolerable. The place of each approach is predicated on a personalized approach in each patient, and future research could usefully use large comparative studies to establish robust treatment guidelines. The implementation of new and varied approaches to antipsychotic treatment adherence is welcomed and have the potential to make a significant impact on morbidity in this often difficult-to-treat population.

Microbiome–Gut Dissociation: Investigating the Origins of Obesity

The reduction of excessive weight remains a major public health challenge, with control currently limited to a calorie reduction strategy. Currently, attempts are being made at revisiting the fibre hypothesis based on the African studies of Denis Burkitt, that the lack of dietary fibre in the modern diet was responsible for the occurrence of obesity and many of the other non-communicable diseases of what he called “Western civilization”. However, the dilemma is that Burkitt himself stressed that other peoples of his day, such as the Maasai, remained healthy without consuming such high fibre diets. Equally, the present obesity epidemic is accompanied by diseases of a malfunctioning immune system and of poor mental health that do not seem to be adequately explained simply by a deficiency of dietary fibre. Though unknown in Burkitt’s day, an increasing degradation of a mutualistic intestinal microbiome would offer a better fit to the observed epidemiology, especially if the microbiome is not effectively passed on from mother to child at birth. Taking the broader view, in this article we posit a view of the microbiome as a cofactor of mammalian evolution, in which a maternal microbial inheritance complements the parental genetic inheritance of the animal, both engaging epigenetic processes. As this would require the microbiome to be fully integrated with the animal as it develops into an adult, so we have a meaningful evolutionary role for the microbiome–gut–brain axis. By a failure to correctly establish a microbiome–gut interface, the inhibition of maternal microbial inheritance sets the scene for the future development of non-communicable disease: compromised immune system function on the one hand and dysfunctional gut–brain communication on the other. The basic principle is that the fully functioning, diverse, microbiome achieves interkingdom communication by the generation of messenger chemicals, semiochemicals. It is envisaged that the in situ detection of these as yet ill-defined chemical entities by means of an ingestible sensor would indicate the severity of disease and provide a guide as to its amelioration.

Ingestible devices for studying the gastrointestinal physiology and their application in oral biopharmaceutics.

Ingestible sensor systems are unique tools for obtaining physiological data from an undisturbed gastrointestinal tract. Since their dimensions correspond to monolithic oral dosage forms, such as enteric coated tablets or hydrogel matrix tablets, they also allow insights into the physiological conditions experienced by non-disintegrating dosage forms on their way through the gastrointestinal tract. In this work, the different ingestible sensor systems which can be used for this purpose are described and their potential applications as well as difficulties and pitfalls with respect to their use are presented. It is also highlighted how the data on transit times, pH, temperature and pressure as well as the data from different animal models commonly used in drug product development such as dogs and pigs have contributed to a deeper mechanistic understanding of oral drug delivery.

Ingestible, Biofriendly, and Flexible Flour-Based Humidity Sensors with a Wide Sensing Range

Ecofriendly and biofriendly materials are highly appealing in electronic devices with the booming development of the Internet of Things. Humidity sensors perform an indispensable role in various fields such as monitoring industry processes and living systems. In this contribution, for the first time, edible and abundant material-flour has been introduced to the sensing layers for humidity detection. The ionic conductive K2CO3 and hygroscopic glycerol (Gly) with biosafety were introduced to the sensing layer to promote a humidity sensing capability and long-time stability. The ingestible Gly-K2CO3 flour-based humidity sensor using PLA as substrates displays an excellent sensing performance and wide humidity detecting range. Good linearity between capacitance and relative humidity (RH) has been achieved for the RH range from 6% to 94%. According to a wireless monitoring system, even at 250 kHz, the sensor can still monitor the nuance of the humidity difference between 40% and 43% and exhibited an ultrafast response time (0.3 s) and recovery time (0.7 s). Furthermore, the consistent and stable sensing performance after long-time measurements for 100 days and bending tests for 500 cycles also demonstrated a long-time humidity detecting stability and mechanical flexibility for the Gly-K2CO3 flour-based humidity sensor. Humidity sensing mechanisms were thoroughly investigated through SEM-EDX, FTIR, XPS, and complex impedance spectroscopies. The enhanced sensing performance, wide humidity detecting range, and long-time stability are attributed to the ionic conductivity from K2CO3 and the hydrogen-bond interaction between H2O and enormous hydrophilic groups, such as hydroxyl and amino groups in the flour-based networks and binary solvent.

PMH34 Digital Health Tools to Monitor Medication Adherence Among Bipolar Disorder, Major Depressive Disorder and Schizophrenia

Among patients diagnosed with bipolar disorder (BPD), major depressive disorder (MDD) and schizophrenia (SCZ), poor adherence to psychopharmacologic therapy is common and results in increased health care utilization and costs. Emergence of digital tools that track medication adherence along with general health is useful, but evidence on caregiver valuations of such tools is limited. This study assessed caregivers’ preferences and willingness to pay (WTP) for digital (ingestible sensor pill, medication containers with electronic monitoring, mobile apps, smart pill dispensers) and non-digital (medication dairy, simple pill organizer) tools for caring BPD, MDD and SCZ patients.

Genetically optimized Fuzzy C-means data clustering of IoMT-based biomarkers for fast affective state recognition in intelligent edge analytics

IoMT sensors such as wearables, moodables, ingestible sensors and trackers have the potential to provide a proactive approach to healthcare. But grouping, traversing and selectively tapping the IoMT data traffic and its immediacy makes data management & decision analysis a pressing issue. Evidently, the selection process for real-world, time-constrained health problems involves looking at multivariate time-series data generated simultaneously from various wearables resulting in data overload and accuracy issues. Computational intelligence of edge analytics can extend predictive capability by quickly turning digital biomarker data into actions for remote monitoring and trigger alarm during emergency incidents without relying on backend servers. But the pervasive generation of data streams from IoMT levies significant issues in data visualization and exploratory data analysis. This paper presents a genetically optimized Fuzzy C-means data clustering technique for affective state recognition on the edge. Clustering segregates the biomarker data in chunks and generates a summarized data for each subject which is then genetically optimized to avoid stagnation in local optima. A multi-level convolution neural network is finally used to classify the affective states into the baseline, stress and amusement categories. The model is evaluated on the publicly available WESAD dataset and compares favorably to state-of-the-art with less time complexity. It demonstrates the use of data clustering technique for numerosity reduction of real-time data streams in intelligent edge analytics which facilitates fast analysis of affective state of the user.

Field validation of The Heat Strain Decision Aid during military load carriage

ObjectivesWe aimed to determine the agreement between actual and predicted core body temperature, using the Heat Strain Decision Aid (HSDA), in non-Ground Close Combat (GCC) personnel wearing multi terrain pattern clothing during two stages of load carriage in temperate conditions. DesignCross-sectional. MethodsSixty participants (men = 49, women = 11, age 31 ± 8 years; height 171.1 ± 9.0 cm; body mass 78.1 ± 11.5 kg) completed two stages of load carriage, of increasing metabolic rate, as part of the development of new British Army physical employment standards (PES). An ingestible gastrointestinal sensor was used to measure core temperature. Testing was completed in wet bulb globe temperature conditions; 1.2–12.6 °C.Predictive accuracy and precision were analysed using individual and group mean inputs. Assessments were evaluated by bias, limits of agreement (LoA), mean absolute error (MAE), and root mean square error (RMSE). Accuracy was evaluated using a prediction bias of ±0.27 °C and by comparing predictions to the standard deviation of the actual core temperature. ResultsModelling individual predictions provided an acceptable level of accuracy based on bias criterion; where the total of all trials bias ± LoA was 0.08 ± 0.82 °C. Predicted values were in close agreement with the actual data: MAE 0.37 °C and RMSE 0.46 °C for the collective data. Modelling using group mean inputs were less accurate than using individual inputs, but within the mean observed. ConclusionThe HSDA acceptably predicts core temperature during load carriage to the new British Army non-GCC PES, in temperate conditions.

Risk Factors and Predictors of Hypothermia and Dropouts During Open-Water Swimming Competitions

To measure core temperature (Tcore) in open-water (OW) swimmers during a 25-km competition and identify the predictors of Tcore drop and hypothermia-related dropouts. Twenty-four national- and international-level OW swimmers participated in the study. Participants completed a personal questionnaire and a body fat/muscle mass assessment before the race. The average speed was calculated on each lap over a 2500-m course. Tcore was continuously recorded via an ingestible temperature sensor (e-Celsius, BodyCap). Hypothermia-related dropouts (H group) were compared with finishers (nH group). Average prerace Tcore was 37.5°C (0.3°C) (N = 21). 7 participants dropped out due to hypothermia (H, n = 7) with a mean Tcore at dropout of 35.3°C (1.5°C). Multiple logistic regression analysis found that body fat percentage and initial Tcore were associated with hypothermia (G2 = 17.26, P < .001). Early Tcore drop ≤37.1°C at 2500 m was associated with a greater rate of hypothermia-related dropouts (71.4% vs 14.3%, P = .017). Multiple linear regression found that body fat percentage and previous participation were associated with Tcore drop (F = 4.95, P = .019). There was a positive correlation between the decrease in speed and Tcore drop (r = .462, P < .001). During an OW 25-km competition at 20°C to 21°C, lower initial Tcore and lower body fat, as well as premature Tcore drop, were associated with an increased risk of hypothermia-related dropout. Lower body fat and no previous participation, as well as decrease in swimming speed, were associated with Tcore drop.

A Brief Training Program to Support the Use of a Digital Pill System for Medication Adherence: Pilot Descriptive Study.

BackgroundDigital pill systems (DPSs), which comprise ingestible radiofrequency sensors integrated into a gelatin capsule that overencapsulates a medication, can directly measure ingestion events.ObjectiveTeaching users to operate a DPS is vital to ensure the collection of actionable ingestion and adherence data. In this study, we aim to develop and pilot a training program, grounded in the Technology Acceptance Model, to instruct individuals on DPS operation.MethodsA two-part training program, comprising in-person and text message–based components, was used with HIV-negative men who have sex with men with nonalcohol substance use, who had enrolled in a 90-day pilot demonstration study using the DPS to measure adherence to pre-exposure prophylaxis. We assessed the number of responses to text check-ins, the number and types of episodes where technical support was requested, the resolutions of such issues, and engagement with the program over the study period. Participant feedback on the program was evaluated through qualitative user experience interviews.ResultsA total of 15 participants were enrolled in and completed the program. Seven technical challenges related to DPS operations were reported across 5 participants. Most commonly, participants requested support connecting the wearable Reader device with their smartphone, charging the Reader, and operating the mobile app. A total of 6 issues were resolved asynchronously or in real time via phone; 1 required in-person evaluation and resolution. Preliminary qualitative findings indicate that both the in-person and remote follow-up components of the training program were perceived as acceptable. Suggested improvements included repeated DPS refresher sessions at in-person follow-up visits and enhanced written materials for the independent resolution of technological issues.ConclusionsA brief two-part DPS training program, drawing from individuals’ experiences and from the Technology Acceptance Model, can provide valuable insights for users. The program also identifies and addresses several areas of actual or potential challenges related to operating a DPS and allows for the resolution of such issues within the first week of DPS use.

Emerging wearable technology applications in gastroenterology: A review of the literature.

The field of gastroenterology has recently seen a surge in wearable technology to monitor physical activity, sleep quality, pain, and even gut activity. The past decade has seen the emergence of wearable devices including Fitbit, Apple Watch, AbStats, and ingestible sensors. In this review, we discuss current and future devices designed to measure sweat biomarkers, steps taken, sleep efficiency, gastric electrical activity, stomach pH, and intestinal contents. We also summarize several clinical studies to better understand wearable devices so that we may assess their potential benefit in improving healthcare while also weighing the challenges that must be addressed.

16.8 nW Ultra-Low-Power Energy Harvester IC for Tiny Ingestible Sensors Sustained by Bio-Galvanic Energy Source.

Herein, we present a 16.8 nW ultra-low-power (ULP) energy harvester integrated circuit (IC) for ingestible biomedical sensors. The energy harvester can be powered from the electro-galvanic operation inside a human body, which provides a sustainable and long-term energy source. The challenge of dealing with relatively high input impedance (∼kΩ) of the bio-galvanic energy source is addressed by introducing two design techniques. The first technique is an adaptive VMPP-controlled algorithm (AVCA) for a maximum power point tracking (MPPT) controller, and the second technique is a ULP delay-line-based zero current switching (ZCS) controller. Different from the conventional fractional open-circuit voltage (FOCV) method for MPPT, the proposed AVCA allows continuous source tracking without detachment of the harvester from the source. The ZCS operation is achieved using a delay-line controller without using either a comparator or an opamp. The proposed AVCA is realized using a 12.1 nW MPPT controller. Successful ZCS operation is achieved using a 2.1 nW delay controller. Overall power consumption of the IC is 16.8 nW. The converter has been fabricated in a 0.18μm CMOS process with 2μm thick top-metal option. The measured result shows that the converter achieves a peak efficiency of 72.1% to generate 507 nW output power. The ULP operation allows a significant reduction in electrode size down to the submillimeter scale (∼0.4mm2), demonstrating the good potential of the proposed energy harvester IC.

Long-Term Stability of the Electronic Sensor Component of a Digital Pill System in Real-World Storage Settings.

Background: Digital pill systems comprise an ingestible sensor integrated into a gelatin capsule that overencapsulates medication allowing real-time measures of medication ingestion. These systems may improve the manner in which medication adherence can be assessed and supported. Objective: In this investigation, we tested the durability of the ingestible sensor as part of a clinical trial to measure the feasibility and acceptability of the system to measure adherence to once daily tenofovir disoproxil fumarate/emtricitabine (NCT03842436). Methods: Digital pills not dispensed during the study were stored in a pharmacy. Seventeen sensors were selected from digital pills stored for at least 12 months and activated in a simulated gastric environment. A radiofrequency spectrum analyzer and the reader device used in the clinical trial to capture ingestion events were used to measure activation of emitters. A passing evaluation was defined as an energized emitter within 30 minutes of immersion, ability to broadcast a signal for 10 minutes, and successful acquisition by the reader. Results: All ingestible sensors passed the stability test. Mean activation time in simulated gastric fluid was 3.33 minutes (SD = 1.47); emitters remained active for a mean of 47.72 minutes (SD = 1.78). These parameters matched guidelines defined in the ID-Cap system requirements for use in patients. Conclusions: Ingestible sensor components of the ID-Cap system were therefore stable after long-term storage.

Digital Pills: Impact of Rising Technology

Digital Pills (DP) are an innovative drug-device technology that permits to combine traditional medications with a monitoring system to record data about medication adherence as well as patients’ physiological data without human intervention. The Digital Medicine System (DMS), a drug–device combination developed for patients with serious mental illness, together combines adherence measurement with pharmacologic action by placing an ingestible sensor in a pill, allowing for information sharing among patients, Health Care Providers (HCPs), and caregivers via a mobile interface. Non-adherence to medication compromises the helpfulness of psychiatric treatments in patients with Serious Mental Illness (SMI). The combination of wearable technology with a “Digital Ingestion Tracking Program” (DITP) embedded within a pain pill may allow patients, caregivers as well as healthcare providers to track ingestion of pills through the web or a Smartphone app. Digital adherence technology could be promising patient-centered strategies for monitoring adherence. In November 2017, the Food and Drug Administration (FDA) approved a version of a second-generation antipsychotic, aripiprazole; embedded with a sensor (Abilify MyCite). The paper highlights the impact of DMS and provides detailed review about it.

Design and Delivery of Real-Time Adherence Data to Men Who Have Sex with Men Using Antiretroviral Pre-exposure Prophylaxis via an Ingestible Electronic Sensor.

Once daily tenofovir/emtricitabine when used for pre-exposure prophylaxis (PrEP) is effective in preventing HIV acquisition but requires consistent medication adherence. The use of ingestible technologies to monitor PrEP adherence can assist in understanding the impact of behavioral interventions. Digital pill systems (DPS) utilize an ingestible radiofrequency emitter integrated onto a gelatin capsule, which permits direct, real-time measurement of medication adherence. DPS monitoring may lead to discovery of nascent episodes of PrEP nonadherence and allow delivery of interventions that prevent the onset of sustained nonadherence. Yet, the acceptance and potential use of DPS in high-risk men who have sex with men (MSM; i.e., those who engage in condomless sex and use substances) is unknown. In this investigation, we conducted individual, semi-structured qualitative interviews with 30 MSM with self-reported non-alcohol substance use to understand their responses to the DPS, willingness and perceived barriers to its use, and their perceptions of its potential utility. We also sought to describe how MSM would potentially interact with a messaging system integrated into the DPS. We identified major themes around improved confidence of PrEP adherence patterns, safety of ingestible radiofrequency sensors, and design optimization of the DPS. They also expressed willingness to interact with messaging contingent on DPS recorded ingestion patterns. These data demonstrate that MSM who use substances find the DPS to be an acceptable method to measure and record PrEP adherence.

Is there any Hope for Monitoring Adherence in an Efficient and Feasible Way for Resistant Hypertension Diagnosis and Follow-Up?

Non-adherence to antihypertensive treatment is highly prevalent and represents a major factor affecting their effectiveness in hypertensive patients, thus contributing to apparent treatment resistance. It is however often overlooked because the methods to assess non-adherence are mainly subjective, limiting their usefulness in clinical practice. Non-adherence to treatment affects daily patient management, resulting in inappropriate, costly, and potentially harmful treatments and loss of the expected benefits from antihypertensive drugs. Specialized centers now use a combination of objective screening tools. Firstly, snapshots of adherence levels can be provided by analytical drug detection in various biological matrixes using liquid chromatography-tandem mass spectrometry (LC-MS/MS) and secondly electronic monitoring systems of drug delivery which provide longitudinal data on adherence. Routine utilization of those tools allows the detection of non-adherence in patients with resistant hypertension, thus enabling implementation of appropriate interventions to improve drug adherence and avoid unnecessary treatment intensification. Other complementary techniques, such as digital health feedback system with ingestible sensors, are currently evaluated. In the context of an increasing burden of uncontrolled and apparent treatment-resistant hypertension, detecting non-adherence to antihypertensive therapy is, as acknowledged by the latest guidelines, a top priority to implement in clinical practice but still faces medical conservatism and disbelief.