Industry
Life Sciences
Patient-centered Care Models Taking Center Stage in Life Sciences
Highlights
- Chronic kidney disease (CKD), being a major health issue, with rising prevalence, needs reimagining dialysis and improving patients’ quality of life, which demands immediate attention.
- AI in dialysis enhances patient outcomes by personalising treatment, predicting Intradialytic Hypotension (IDH) and optimising treatment planning.
- The design and development of dialysis machines demand interdisciplinary collaboration among domain experts and ecosystem players.
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Need for dialysis
CKD is a major health issue, with rising prevalence and its importance as a cause of death. So, a better understanding of etiology, screening, and implementation programs is needed to translate advances in CKD treatment into improved patient outcomes.
Dialysis is a critical, life-supporting treatment for individuals with kidney failure, functioning as a substitute for the kidneys by filtering out waste, toxins, and excess fluids from the bloodstream. It maintains electrolyte balance, prevents fluid overload, and improves the quality of life for patients awaiting a transplant or managing severe kidney disease. There are two types of dialysis: Hemodialysis and peritoneal dialysis. Both types perform the essential functions of the damaged kidney by removing waste products and excess fluid from the bloodstream. Innovations in dialysis include portable and wearable devices for home use, such as miniaturised haemodialysis machines and wearable artificial kidneys, as well as advancements in membranes and AI-driven systems to improve efficiency and patient outcomes.
Market drivers
Increasing prevalence of kidney diseases
Ageing is a prominent factor. Additionally, the rise in the prevalence of obesity and diabetes can result in kidney disease. Genetics is another key factor that contributes to the rising prevalence of kidney disease. In addition to this, exposure to toxic substances, such as lead, cadmium, arsenic, as well as through contaminated water and air, poor nutrition and lifestyle choices such as smoking are also increasing kidney diseases.
Lack of kidney donors
Although the number of kidney transplantations is growing every year, there is an increasingly long waiting list. Transplant failure and a lack of adequate kidney donors can lead to increased use of dialysis treatment for patients with kidney failure. Hence, such factors are expected to drive the growth of the global renal dialysis market.
AI for dialysis
AI in dialysis enhances patient outcomes by personalising treatment, predicting Intradialytic Hypotension (IDH), and optimising treatment planning. By analysing large datasets derived from all dialysis sessions around the globe, AI can reduce hospitalisation and enhance vascular access monitoring, metamorphosing dialysis from reactive to proactive care, supporting nephrologists (human in loop) rather than replacing them. The objective of integrating AI into dialysis is to advance toward "precision dialysis," ensuring personalised treatment for individual patients. However, there may be regulatory compliance challenges that are to be conquered.
One of the global majors in dialysis machines has developed a machine learning model, which uses electronic health records comprising intradialytic blood pressure measurements and multiple treatment- and patient-level variables. The model was trained and validated using observational data from 42,656 hemodialysis sessions across 693 in-centre patients. Within the training cohort, it was refined to trigger an IDH alert 15 to 75 minutes ahead of a potential event. As part of this effort, data from the organisation’s global clinical systems were unified in the cloud, bringing together information from 40 countries across six continents and encompassing over 350 patient treatment parameters. It included information from more than 540,000 dialysis patients, more than 140 million dialysis treatments, and more than 34 million laboratory assessments.
Miniaturisation need
Dialysis machines are large, and haemodialysis usually takes three to four hours per session, conducted three times per week.
The total time can vary based on individual needs, with shorter, more frequent sessions possible for home haemodialysis or longer sessions for nocturnal, in-centre, or at-home treatments. This means the person undergoing dialysis must be tethered to the machine for longer periods. The restriction of life, which is one of the most unbearable side effects of long-term dialysis, has to be tackled.
To improve patient’s quality of life, dialysis must be transformed. Home dialysis, wearable technologies, and implantable artificial kidneys represent promising alternative options. Solutions that can offer deep miniaturisation, shrinking systems to micro- and nano-levels, are crucial for such improvements.
Wearable dialysis
One significant advantage of wearable technology in CKD management is its small size, portability, and non-invasive nature.
Wearable and portable dialysis devices can dramatically improve patients’ quality of life by allowing them to continue their daily activities while undergoing dialysis. Innovations in nanotechnology, advances in electronics, and miniaturisation have produced a new generation of wearable and portable dialysis devices, heralding a new dawn in dialysis machines.
Physicians can use data from these devices to identify changes in the patient's condition and provide early intervention before the disease progresses. Hence, such advancements in renal dialysis are expected to drive the growth of the market in focus.
AR/VR for dialysis
Dialysis is an exhausting experience, and considering the frequency of sessions, this can really take a toll on the human spirit. Augmented Reality (AR) and Virtual Reality (VR) technologies can be effectively used in dialysis to improve patient experience and training, and to reduce pain, anxiety, and boredom during treatments. VR offers immersive, soothing environments, while AR is utilised for technical training, such as virtual, on-demand training for dialysis machines and catheter procedures. Considering that over 10% of all patients undergoing dialysis, prefer peritoneal dialysis this is an interesting option in renal care.
Ecosystem advantage
Smart and connected medical devices leverage IoT, AI, ML, and bio-digital twin technologies. Traditionally, key challenges faced by the medical device industry are extended hours of equipment downtime and service expenses. With IoT, it is possible to monitor dialysis machines to ensure that the downtime is minimised. With an efficient condition-based monitoring of the dialysis machine, it is possible to enhance clinical workflow and patient experience by ensuring adherence to dialysis schedules.
The design and development of such smart, connected dialysis machines require interdisciplinary collaboration among domain experts. To achieve this, medical device manufacturers, pharmaceutical companies, and healthcare providers need to embrace ecosystem partnerships. Given the long development timelines and the necessity for absolute precision, these collaborations are essential in shaping the future success of medical device companies.
Dialysis is a complex procedure, and patients have to undergo this for many years, and it is important to use technology including AI as a powerful enabler for clinical teams and not a replacement. By ensuring data flows seamlessly across care settings, it is possible to support caregivers with decisive actionable insights helping patients engage more confidently in their own care. This is precisely the objective of the digital transformation of dialysis.