We often hear about the convergence of medtech, digital health and life sciences. What does this convergence look like in practice?
The convergence of medtech, digital health, and life sciences in practice is creating realtime, holistic, and personalised healthcare solutions. This transformation extends care beyond hospitals through IoT-enabled devices such as home dialysis systems, connected infusion pumps, remote monitoring platforms, and wearable sensors.
At the same time, advanced digital surgical platforms including robotics, image guided systems, and intraoperative analytics are transforming care within hospitals by enhancing precision, standardisation, and outcomes during procedures. Together, these innovations create a continuum of care across preoperative, intra-operative, and post-operative settings.
Data from these diverse sources, home-based devices, wearables, hospitals, and surgical platforms, are securely aggregated and stored in scalable cloud infrastructures. Cloud-based platforms enable seamless interoperability, longitudinal patient records, and real-time data access across stakeholders, allowing the integrated ecosystem to leverage advanced analytics, AI, and clinical insights for patient-specific outcomes, early risk detection, and personalised interventions. For instance, home-based therapies such as dialysis can be monitored remotely for safety and adherence, while digital platforms help surgical teams optimise techniques and recovery pathways.
In drug development and clinical research, this convergence enables faster, data-driven decisions through simulation, digital twins, and real-world evidence.
Overall, this integrated ecosystem is shifting healthcare from a reactive model to a more proactive, continuous, and patient-centric approach.
Which healthcare technologies are currently overhyped, and which are still underestimated?
In the broader healthcare technology landscape, certain areas receive significant attention, particularly advance solutions such as AI driven diagnostics and decision-making systems that are designed to augment and support clinicians in delivering more effective care. While promising, these technologies are still some distance from widespread, reliable adoption considering the challenges in terms of trust, regulation, and realworld validation need with so much variability.
This is especially critical given variations in patient populations, disease patterns, and healthcare practices across different regions, making it challenging for AI models to generalise consistently. This highlights the need for clinical evidence and localised validation before deployment at scale. Similarly, fragmented digital health apps often overstate their clinical impact without deep integration into care pathways.
In contrast, several technologies remain underestimated. Interoperability platforms that connect data across systems are critical to enabling data-driven real time, holistic, personalised solutions but still face challenges of adoption. Remote patient monitoring, when integrated into clinical workflows, can enable realtime patient tracking, reduce rehospitalisations, and lower healthcare costs. Additionally, simulation, digital twins, and model-based approaches in medtech can accelerate innovation and improve clinical outcomes. The true transformation lies in building integrated, ecosystem driven technologies, though progress is often hindered by fragmented data landscapes and limited information sharing across institutions.
Remote patient monitoring has moved from a niche concept to a mainstream healthcare strategy. What lessons have we learned so far?
Remote patient monitoring (RPM) has evolved into a mainstream healthcare strategy across specialties, offering several important lessons. First, its true value is realised only when it is tightly integrated into clinical workflows and delivers measurable clinical outcomes. Second, real time data is powerful, but without actionable insights and clinician engagement, it adds limited value RPM solutions are now enabling targeted, personalised diagnostics and treatments. Third, patient empowerment and engagement require technologies that are simple, reliable, and personalised to drive sustained use. Fourth, interoperability and data sharing remain key challenges, often limiting scalability. Finally, RPM has demonstrated clear benefits in reducing hospital readmissions, improving chronic disease management, and lowering healthcare costs.
Overall, the shift has highlighted that success lies not just in technology deployment, but in aligning people, processes, and data to deliver meaningful, patient-centric outcomes.
What are the biggest cybersecurity challenges facing connected healthcare ecosystems today?
The growing connectivity across medical devices, particularly as care expands into homes, ambulatory care, and remote clinics, creates a broader digital ecosystem, bringing with it an increased need for robust cybersecurity measures to safeguard against potential breaches and ransomware attacks. Many legacy systems lack built-in security controls and are difficult to update, making them easy targets. Data interoperability, while essential, introduces risks around secure data exchange, especially when institutions hesitate to adopt standardised protocols. Additionally, protecting sensitive patient data across cloud platforms and third-party vendors add complexity. Real-time data flows further amplify the need for continuous monitoring and rapid threat detection. Finally, balancing usability with strong security measures remains a challenge, as overly complex controls can hinder clinical efficiency. Addressing these issues requires a comprehensive approach that integrates robust security frameworks, regulatory compliance, and a culture of cybersecurity awareness across the healthcare ecosystem.
How do you see smart implants, wearables and implantable IoT devices reshaping patient care over the next decade?
Smart implants, wearables, and implantable IoT devices are set to transform patient care by enabling continuous, realtime, and personalised monitoring and intervention. For example, smart orthopedic implants like Zimmer Biomet’s connected knee provide data on mobility and recovery, allowing clinicians to adjust rehabilitation remotely and enable clinical insights for future surgeries. Capgemini has been instrumental in building the connected ecosystem around Advanced pacemakers and implantable cardioverter defibrillators (ICDs) which enable continuous monitoring of cardiac rhythms and alert the clinicians when devices detect abnormal arrhythmia or deliver necessary therapeutic shocks during critical arrhythmia event.
Furthermore, Capgemini collaborated on development of a wearable continuous glucose monitoring device, which enables efficient, ongoing management of glucose levels. Together, these advancements represent a shift from reactive to a more continuous, proactive care model. In neurology, implantable devices supporting remote programming for neurostimulation allow clinicians to fine tune therapy without requiring hospital visits, which is another area where Capgemini has closely worked with customers to deliver solutions. Wearables further extend this ecosystem by capturing daily health data and supporting early intervention. Together, these technologies help reduce hospitalisations, support data driven treatment, advance more value-based, patient-centered care.
How is GenAI changing the way medical devices are designed, tested, and approved?
GenAI is reshaping medical device development across the entire lifecycle, from concept to approval, by enabling faster, more intelligent, and simulation-driven processes. In early stages, it supports ideation through virtual design exploration and realistic simulations, helping engineers evaluate multiple design options efficiently. During development, GenAI assists in code generation, model refinement, and automated documentation aligned with standards. In verification and validation, it enables rapid test case creation including test suites, synthetic test data generation, and intelligent test automation, significantly improving coverage and speed. For regulatory approval, GenAI is being leveraged to streamline documentation, automate traceability, and generate evidence aligned with regulatory standards requirements, improving submission quality and speed.
However, despite these advances, a human in the loop remains critical to ensure clinical relevance, validate outputs, address edge cases, and maintain accountability, especially given patient variability, safety requirements, and stringent regulatory expectations.
How can India become a global hub for healthcare innovation? What advantages do Global Capability Centres (GCCs) in India offer to healthcare and MedTech companies today?
India can emerge as a global hub for healthcare innovation by combining its clinical depth, strong engineering talent, and an evolving ecosystem that supports rapid prototyping and scalable manufacturing. The country has a vast pool of highly skilled doctors and clinicians who bring strong diagnostic expertise and exposure to diverse disease profiles, enabling robust real-world validation. Increasing collaboration between clinicians, academia, industry, and government could further accelerate innovation through applied research and policy support.
Global Capability Centres (GCCs) in India play a strategic role by bringing together medtech engineering, digital health, AI, and regulatory expertise under one roof. Alongside a rapidly growing startup ecosystem, they are fostering an integrated innovation environment. Government initiatives and digital health infrastructure are strengthening interoperability and access. Together, these elements are creating a vibrant ecosystem that supports scalable, costeffective, and globally relevant healthcare solutions.
Looking ahead to 2030, what will be the defining characteristics of a truly intelligent healthcare ecosystem?
By 2030, a truly intelligent healthcare ecosystem will be connected, predictive, and patient centric, delivering real-time, holistic, and personalised care from the comfort of homes. Seamless interoperability will enable secure data flow across devices, providers, and platforms, overcoming today’s data silos. GenAI, combined with clinical intelligence, will enable a shift from reactive to preventive care by predicting risks, enabling early interventions, and supporting targeted therapies, strengthened by breakthroughs in genomics and proteomics.
Smart implants, wearables, and remote monitoring systems will generate actionable insights, while digital twins and simulation models will guide precision treatment. Humans in the loop frameworks will remain critical to ensure trust, safety, and ethical decision making.
Additionally, strong collaboration across clinicians, academia, industry, and regulators will drive innovation and faster adoption. Ultimately, the ecosystem will be outcome driven, leveraging integrated technologies to improve care quality, reduce costs, and enhance patient engagement at scale.
If you had to place one bet on a technology that will fundamentally change healthcare outcomes over the next five years, what would it be and why?
AI-driven drug discovery and development platforms could fundamentally transform healthcare outcomes over the next five years. By combining AI/GenAI with biological data, genomics, and proteomics, these platforms can rapidly identify drug targets, design molecules, and predict efficacy, significantly reducing the time and cost of bringing new therapies to market.
This will be particularly impactful for complex and challenging diseases such as specific cancer solutions, Alzheimer’s disease, Parkinson’s disease, rare genetic disorders, and autoimmune conditions, where traditional approaches have been struggling. AIdriven approaches can uncover hidden biological patterns and enable more targeted, personalised therapies.
While clinical validation remains a bottleneck, the acceleration in early-stage discovery and precision targeting makes this a high impact, near term transformation area with the potential to address unmet medical needs at scale.
Healthcare leaders today are dealing with rising costs, workforce shortages, regulatory complexity, and growing patient expectations. What would be your advice to CEOs trying to future-proof their organisations in this environment?
Healthcare leaders across MedTech and BioPharma must adopt an ecosystem-driven mindset to navigate rising costs, workforce shortages, regulatory complexity, and evolving patient expectations. The focus should shift from standalone innovations to integrated, data driven platforms that connect devices, therapies, and patient data, enabling real-time, holistic, personalised care.
Leaders need to invest in AI and automation to accelerate drug discovery, enhance clinical decisionmaking, augment workforce productivity, and drive manufacturing optimisation through improved efficiency, quality, and supply chain resilience. Embedding quality, safety, and regulatory compliance by design across both device and drug lifecycles is essential to manage growing complexity.
Co-innovation across clinicians, academia, industry, and government will be essential to ensure healthcare innovations remain relevant, scalable, and impactful. Finally, aligning strategies toward value-based, outcome-driven care models will be key. Organisations that integrate therapeutic innovation, technology, and manufacturing excellence will be best positioned for sustainable, patient-centric growth.
lakshmipriya.nair@expressindia.com
lakshmipriyanair@gmail.com