Necessity is regarded as the mother of invention, and the healthcare landscape aptly justifies this adage. Our country is witnessing an ongoing socio-demographic transformation, with increasing life-expectancy, lifestyle-transitions, resource-availability and healthcare access. A natural corollary is the surge in non-communicable diseases, which accounts for substantial morbidity in our population today. Apart from these aspects, the South-Asian ethnicity is also recognised to carry greater risk of premature cardio-metabolic diseases. It is unsurprising that cardiovascular diseases are the leading causes of death in our population, accounting for over one in four deaths in India. The stigma and/or denial associated with health-related issues, like diabetes, hypertension, or a psychiatric disorder, carries immense burden on the intent and efforts towards optimum care.
The interventions to promote good health-related quality of life, are possible at multiple levels across the continuum of chronic diseases. This continuum includes occurrence of risk-factors, diseases, clinical-events, long-term complications and untimely death. The interventions across this continuum, include primordial, primary, secondary and tertiary levels of prevention; a complex framework with good health at its heart.
The complexity engendered by a holistic healthcare landscape, duly calls for the hand-in-glove support of technology. Right from visualising the burden and impact of a health-problem in community, to facilitating timely risk-assessment and diagnosis, setting priorities and defining goals of care, identifying opportune targets for intervention, providing healthcare access and delivery, sustenance of health in long-term, defining clinical approaches based on precision-medicine and personalised-care, technology has an integral role to play in medical science.
R&D made more cost- and time-effective
Drug discovery, in particular, is an expensive and time-intensive process with a high risk of failure. With the ever-increasing unmet needs in an inherently complex healthcare scenario, medical science carries responsibility to yield appropriate therapeutic solutions. Innovative technologies can help clinical-research immensely, by reducing research expenditure and the time required to bring out effective medication to the masses. Artificial Intelligence (AI) can help companies reconfigure business models, streamline operations, and enhance everything from research and data analysis to supply chain and product monitoring.
As a result, many leading companies in the industry have announced partnerships, and in-house initiatives to harness the use of AI. For instance, Boehringer Ingelheim, in particular, has collaborated with Click Therapeutics, to develop and commercialise CT-155, a novel prescription digital therapeutic to aid in the treatment of schizophrenia. The company is also using AI to pursue deeper insights in areas like cardio-renal-metabolic conditions, a group of interconnected disorders that affect more than a billion people globally and are a leading cause of death.
Technology leading the charge in genomics
Technologies such as AI/ML, cloud computing, data analytics and High-Performance Computing (HPC) have enabled significant breakthroughs in the field of genomics. These advancements are now enabling researchers and medical professionals to process terabytes worth of a patient’s genetic data from the DNA in mere hours now. It is now also making genomics research at a population level possible, as these advanced technologies now equip researchers and healthcare professionals with tools earlier unavailable to them.
This vast genetic data can now be used to understand the impact of a specific genetic trait on a patient’s health or how a particular drug can treat a health condition differently in specific parts of populations.
The Human Genome Project (1990-2003), for instance, transformed the field of biology and brought the importance of genome sequencing to the forefront of lifesciences. The project led to a greater understanding of the genetic makeup of organisms. Consequently, knowledge of DNA increased and research activities for gene-based treatment have sped up.
The advent of ‘precision medicine’
Precision medicine refers to a tailored approach to medical care where the needs of a specific group of patients are prioritised over a one-size-fits-all approach. It relies on the use of biological indicators called biomarkers to characterise the group of patients by their risk for certain diseases and response to treatments. It can also be used to characterise patient genotypes and phenotypes in detail.
With advances in digital diagnostics and easy availability of patient data, now, care has been ‘digitised,’ and more importantly, personalised. The availability of advanced DNA sequencing technology has also enabled researchers to know more about human genetics and thus, conduct a detailed analysis of genotypes.
The advent of new technologies and mobile medical apps has allowed companies to actively track a patient’s physiology in real-time. With more access to patient data than ever, companies and researchers are now better equipped to respond to newer healthcare challenges.
It would be an understatement that technology is revolutionising the pharma and healthcare sector, in multiple ways. To be in a position to address the healthcare burden, save lives, and improve patient-outcomes, a technology-driven R&D machinery is going to be the key for the pharma and healthcare foundation of the society.