Defining trends in life sciences & healthcare in 2022
Sensyne Health’s Vice President of Clinical, Ray Valencia M.D., has some thoughts on trends that will be present in the life sciences and healthcare industries across 2022.
2021 was a significant year for the advancement of healthcare, perhaps even more so than when the pandemic first hit the entire global population in 2020. Since the first SARS-CoV-2 vaccination programme started, over half of the globe is now fully vaccinated, with the extra protection of a third ‘booster’ jab currently being rolled out.
There is no doubt that the pandemic is still causing suffering, but it has also triggered a shift within the entire health system and exposed the urgent need for innovation in how treatments are discovered, and care is provided. Over the last year, we’ve seen huge strides taken, for example, the need to remotely interact with healthcare providers; the use of advanced predictive algorithms to predict disease deterioration, and the acceleration of vaccine and drug development.
As we start to look ahead to what 2022 holds for the sector, it’s clear technology will continue to be pivotal in accelerating change. In an industry that was slower than other industries to embrace new ways of working, the digital transformation that has occurred across the last two years has been exceptional.
Embracing AI/ ML technology to identify tailored treatments for individuals
Improving patient care has always been a key priority for the healthcare industry, but with a deluge of data now available for clinicians, the opportunity to deliver personalised medicine and treatments has increased, as long as we also give clinicians the tools to rapidly synthesise all this data.
Through the use of personalised medicines, clinicians will potentially be able to better treat and even prevent disease with greater efficiency and precision, reducing certain risks such as side effects, utilisation of ineffective treatments, time to treatment and cost. There is no one size fits all approach to healthcare.
This is where technologies such as Artificial Intelligence (AI) and machine learning can make a real impact. By using an intelligent system, more accurate patient-specific predictions and recommendations can be made that help to inform clinicians with the aim to improve patient outcomes.
Clinical trials are set to become more uniform
The use of technology throughout the life sciences industry is becoming widely accepted, and the benefits that accompany this adoption of tech are starting to be recognised. One key area is the use of data analytics platforms. This coupled with the increase in deidentified real-world patient data becoming more available has revolutionised the work of researchers and academics.
By utilising anonymised real-world patient data in data analytics platforms, research can become more efficient. These platforms aim to significantly speed up, for example, drug discovery and development ensuring the time from ‘bench to bedside’ is drastically reduced.
Alongside speeding up the process, by using both large datasets and next generation analytics, researchers can now work in different ways and refine the patient cohorts involved in clinical trials. Through analysing real-world data, researchers can identify patients with the right characteristics for the treatment and build control arms around this, reducing the need for mass participation and significantly speeding up the recruitment process. This targeted, analytical approach to clinical trials can also provide a better understanding of specific treatment outcomes.
As data analytics platforms and the use of ethically sourced patient data becomes more mainstream over the next few years, clinicians and researchers will, ultimately, have the opportunity to use these platforms to develop tools aimed at improving their patient care as well as continue to develop more personalised treatments or treatment regimes.
Synthetic control arms will be deployed more than ever before
While synthetic control arms (SCAs) are not a new technique, the true potential of SCA technology is just starting to be recognised and embraced more widely. SCAs have the potential to transform clinical development, reducing recruitment challenges within clinical trials and avoiding the unnecessary exposure of patients to placebos that could deny them disease treatments.
Despite the very clear benefits of using SCA technology, challenges remain around accessing viable, usable data, and particularly for rare or unusual diseases. As we look to the future, conducting clinical trials through a multidisciplinary, collaborative, and innovative approach will help speed up and improve the development of vaccines, drugs, and other treatments. The greater efficiency (time, cost and reducing failure rates) offered by synthetic control arms will see them continue to grow in popularity across the sector.
Sharing data on a larger scale will become the norm
There is no doubt that competition across the sector is only going to increase. More companies are leaning on technology to give them the competitive edge. But it is the collaboration between traditional pharma organisations and more innovative life sciences companies, that will be key to bringing drugs and treatments to market faster.
Data is soon to become the most critical tool for the industry. Without it, the development of new treatments and medication will become increasingly more difficult to discover. Data sharing will be paramount to this success.
This last year has seen huge growth in the sector, with an increasing number of health tech and life sciences organisations coming to the market. We now need to ensure these organisations are working together, utilising technology to allow, where appropriate, sharing and pooling of anonymised data, ethically.
For the disruptive digital transformation that has occurred during the pandemic to continue to benefit individuals across the globe, life science and healthcare organisations must work together in order to fully realise the benefits for all.
However, with increasing amounts of patient data now being collected, increasing amounts of patient data now being collected, and technology truly being integrated into health systems, researchers are going to be able to develop drugs and treatments with far more targeted, cost and time effective results.