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Looking into the Crystal-ball: Advances in technology for improving adherence

  • Current technological interventions focus either on reminding the patient or on tracking the pill removal from the packaging. However, they do not address the actual act of taking the medicine1.
  • The ingestible sensors or trackable pills have marked a technological revolution in the area of medication adherence. In addition, motion-sensor-based wearables are likely will mark their presence in the future2,4.
  • Predictive analytics can be quite useful in making timely and informed decisions to optimize health outcomes for patients3

Medication adherence is a global challenge for the healthcare community. However, accurately measuring and monitoring patient medication adherence is equally challenging. Patient self-reporting is the most commonly used measure of medication adherence. Pill counts, prescription refills, and directly observed therapy (DOT) are other conventional ways to measure adherence4. Recently, technology is being harnessed for tracking the medication-taking behavior of patients. From electronic reminders to an integrated medication event monitoring system (MEMS) and medication behavior monitoring system (MBMS) that reminds, dispenses, and records the medication-taking behavior,  technology has been continuously disrupting the conventional norms of healthcare and has offered many options to measure and improve medication adherence1,4,7.

Technology to improve medication adherence: Where we are?

There have been significant technological advances in medication adherence monitoring in recent years. A Medication Event Monitoring System (MEMS) makes use of electronic caps that record date-and-time stamps every time the patient opens the pill bottle4. Similar to these are electronic pill boxes that record and send a cellular signal to the web-based server when opened but have the capacity to store multiple medicines, making them a better option in case of complex multidrug regimens2. Electronic audiovisual reminder devices (AVRD) are pillboxes with lights that flash and alarm at specified times, reminding patients to take medications5.

Smart blister packaging, on the other hand, involves tracing the removal of the pill from the blister. Removing the pill from the blister creates a break in the label circuit, which is recorded by the microchip with a date-and-time stamp4. Another technology involves the use of radio frequency identification (RFID) sensor tag grids to the back of the package that records the date and time of the capsule or tablet pill dosing2.

Video-based monitoring involves the patients video-record their medication ingestion on their smartphones and sharing it with their practitioners2. Additionally, from sending time & dosage alerts to reminding patients to get their prescriptions refilled, AI-backed mobile applications aim to improve adherence via patients’ smartphones6. For more on this see our articles: Technological advancements and innovations to improve medication adherence and Measuring adherence – an “Achilles heel” in medication adherence.

Challenges with the existing technologies: Where do we lag?

There is no doubt that technology is transforming medication adherence monitoring and measurement. However, there are many challenges with it:

  1. Proxy measures: Opening the bottle or removal of the pill does not guarantee ingestion. The electronic devices cannot ensure that a pill was ingested, only that it was removed from the bottle, pill organizer, or blister pack1.
  2. Cost & privacy issues: The cost of technology is one of the potential limiting factors to its adoption by both patients and healthcare practitioners4. Privacy, security, provider reimbursement, integration & implementation are the additional challenges to its adoption5.
  3. Technical barriers: System accuracy and data fidelity are the major technical barriers associated with the adoption of technological interventions. Energy consumption and the lifetime of the devices are the additional challenges with technology4.

Moving beyond the challenges: The future of technology in medication adherence

1. Emerging smart technologies for medication adherence monitoring that hold substantial promise in the future:

  • Ingestible biosensor system: Also known as digital/electronic pill, or simply a digital medicine system, this novel technology offers the benefit of actual ingestion of the pill and therefore is likely to play an important role in the future. The system consists of a biosensor encapsulated with the drug, an adhesive external monitor worn on the abdomen, and a mobile app. Once the ingested pill reaches the stomach, the acid in the stomach activates the sensor. The sensor then sends a signal to a wearable sensor patch that in turn sends the information to the mobile device app. The information can also be stored in a cloud-based server. Patients and physicians can then view the medication intake information on the web-based portal2.
  • Wearable sensing systems or motion sensor technology: This includes wearable devices that contain motion-sensing gyro meters and accelerometers to detect user medication adherence. The motion-sensing elements identify and record the patient’s motions and match these with medication-taking movements such as skin motion during pill swallowing or hand movement during pill ingestion. This technology is currently in its nascent stages but is limited by the fact that many other activities such as drinking water or eating food are similar to the medication ingestion actions. Additionally, wearables can be inconvenient for certain patient groups4.
  • Medication behavior monitoring system (MBMS): This system utilizes technologies such as the Internet of things (IoT), deep learning, and artificial intelligence to map the medication behavior of the patient. First, the device reminds the patient to take the medicine with an alarm. When the patient comes closer to the device, the motion sensors detect the movement and send a signal to the device, which starts video recording the patient’s actions. The device then dispenses the medicine and confirms the intake of the medicine with the change in weight of the medicine container, and by matching the patient’s behavior with the action of drinking water. Finally, the device sends weekly adherence reports to the physicians7.
  • Capillary microfluidics-based diagnostic device: It is a miniaturized diagnostic device based on capillary microfluidics. Capillary microfluidics is a type of microfluidics, based on the principle of capillary action and helps to perform bio-analysis on bodily fluids rapidly. Think of it as a glucometer that analyses blood sugar levels. Similarly, this device can analyze a body fluid sample for the presence of medicine to confirm that the patient has taken it. This information can be shared with the physician and other stakeholders8.

2. Predicting the patient group at the highest risk of non-adherence to provide tailored interventions and improve adherence:

  • Predictive analytics is an algorithm-based technique that utilizes artificial intelligence, machine learning, neural network, and other computational tools to identify, predict and improve medication non-adherence. The two essential components of predictive analytics are patient data and predictive models. Predictive analytics has the potential to improve adherence. The major predictors identified through multiple studies should be used to create generalizable models that can be easily adapted in the future. Upon careful evaluation of these prediction models, they should be able to guide the use of appropriate interventions to improve adherence3,9. For more on this see our article: Power of algorithm: identifying high-risk non-adherent patient groups.

3. Advances in drug delivery systems that aim to improve patient compliance & adherence with less frequent or tailored dosing:

  • Implantable microchips: These silicone-based chips offer a controlled release of drugs over a period in the body. A microchip consists of hundreds of tiny reservoirs of drugs fabricated on a silicon substrate that acts as the cathode. These drug reservoirs are sealed using wafer bonding and are layered by an anode membrane. An external wireless electrical potential dissolves the reservoir cover and releases a single dose of the drug10.
  • 3D printing: 3D printing is an additive manufacturing method that involves the deposition of materials in layers to create a digitally designed 3D solid model. This technique offers the advantage of designing tailored pharmaceutical doses, and combination tablets or polypills that aid in maximizing medication adherence, specifically in pediatrics and geriatric population11.
  • Remotely controlled nanochannel delivery system (nDS): This new drug delivery system in development could offer a controlled release of drugs. This system is a nanofluidic device that is implanted subcutaneously and can be controlled remotely via bluetooth technology. It can be used to provide customized doses of drug. This could turn out to be the future of an on-demand delivery platform for managing chronic diseases12.

Towards a better future:

Medication non-adherence is a multi-factorial challenge and technology has only been able to hit a few right chords. No single intervention is perfect and has its challenges and limitations. Although the new advancements are more objective and integrated with functionality, the cost of technology, data & privacy concerns, users’ comfort, and lack of appropriate criteria to assess the monitoring technology remains unsolved. Moreover, the clinical translation of these interventions is still questionable and requires a shred of strong real-world evidence4. Despite all these challenges, we can be hopeful that technology is going to find its way and reshape drug delivery and monitoring.

“I see trackable pills playing an important role in the future. People who are adherent with care don’t really need them, but there are always medications that are difficult to adhere to” – Tahir Rahman, MD, an associate professor of psychiatry at Washington University School of Medicine in St Louis, Missouri

References

1.    Stirratt MJ, Curtis JR, Danila MI, Hansen R, Miller MJ, Gakumo CA. Advancing the Science and Practice of Medication Adherence. J Gen Intern Med. Feb 2018;33(2):216-222. doi:10.1007/s11606-017-4198-4

2.    Adje YH, Brooks KM, Castillo-Mancilla JR, Wyles DL, Anderson PL, Kiser JJ. The use of technology-based adherence monitoring in the treatment of hepatitis C virus. Ther Adv Infect Dis. Jan-Dec 2022;9:20499361221095664. doi:10.1177/20499361221095664

3.    Koesmahargyo V, Abbas A, Zhang L, et al. Accuracy of machine learning-based prediction of medication adherence in clinical research. Psychiatry Res. Dec 2020;294:113558. doi:10.1016/j.psychres.2020.113558

4.    Mason M, Cho Y, Rayo J, Gong Y, Harris M, Jiang Y. Technologies for Medication Adherence Monitoring and Technology Assessment Criteria: Narrative Review. JMIR Mhealth Uhealth. Mar 10 2022;10(3):e35157. doi:10.2196/35157

5.    Mistry N, Keepanasseril A, Wilczynski NL, et al. Technology-mediated interventions for enhancing medication adherence. J Am Med Inform Assoc. Apr 2015;22(e1):e177-93. doi:10.1093/jamia/ocu047

6.    Babel A, Taneja R, Mondello Malvestiti F, Monaco A, Donde S. Artificial Intelligence Solutions to Increase Medication Adherence in Patients With Non-communicable Diseases. Front Digit Health. 2021;3:669869. doi:10.3389/fdgth.2021.669869

7.    Roh H, Shin S, Han J, Lim S. A deep learning-based medication behavior monitoring system. Math Biosci Eng. Jan 28 2021;18(2):1513-1528. doi:10.3934/mbe.2021078

8.    Delamarche E, Temiz Y, Lovchik RD, Christiansen MG, Schuerle S. Capillary Microfluidics for Monitoring Medication Adherence. Angew Chem Int Ed Engl. Aug 9 2021;60(33):17784-17796. doi:10.1002/anie.202101316

9.    A Bohlmann et al. Machine Learning and Medication Adherence: Scoping Review. JMIR Publications. 2021;2(4)doi:10.2196/26993

10.  Eltorai AE, Fox H, McGurrin E, Guang S. Microchips in Medicine: Current and Future Applications. Biomed Res Int. 2016;2016:1743472. doi:10.1155/2016/1743472

11. Vaz MV, Kumar L. 3D Printing as a Promising Tool in Personalized Medicine.AAPS PharmSciTech. 2021 Jan 17;22(1):49. doi: 10.1208/s12249-020-01905-8.

12. Trani DN, Silvestri A, Bruno G, et al. Remotely controlled nanofluidic implantable platform for tunable drug delivery. Lab on a Chip. 2019. http://dx.doi.org/10.1039/c9lc00394k