Dripping In Data; What Does 'Cloud Computing' Mean For Patients And...

Dripping In Data; What Does 'Cloud Computing' Mean For Patients And Pharma Collaboration In The Era Of Citizen Science?

By Emma Sutcliffe, Head, Patient Engagement and Innovation, NexGen Healthcare

Emma Sutcliffe, Head, Patient Engagement and Innovation, NexGen Healthcare

Harnessing data in the ‘Insight Economy’ is standard practice in most sectors. Research experts use ‘big data’ convincingly – smashing silos to combine data analytics, market research and behavioural neuroscience to create a personalised product. Big data is strategically engineered to enable continuous refinement, underpin new product development and also to enhance customer service, choice and experience. Accordingly, the pharmaceutical industry should embrace the ‘biological big data’ revolution. The science behind decision making is progressing through a plethora of data tracks including social, behavioural, cognitive, subconscious and artificial intelligence streams. It is time to amalgamate multiple data sources in pharma R&D to deliver unprecedented informational clarity about what kind of therapy will or won’t work to better manage health and create a framework for Citizen Science.

Cloud collaborations and confidence

Hospitals and governmental organisations have long outsourced data management and were pioneers to eschew confidence in health cloud-computing. This was a resourcing necessity because compliant outsourcing and analytics for sensitive health data liberate employees to focus on core competencies – care, research, medical support.

“The science behind decision making is progressing through a plethora of data tracks including social, behavioural, cognitive, subconscious and artificial intelligence streams.”

Indeed, the adoption of cloud computing to manage and facilitate health care innovation has encouraged national and international organisations to establish ‘mega-medical data’ investiture. In January 2019, the UK government launched ‘Health Data Research UK’, to create multiple public data hubs and expedite biometric data trawling. It takes up to five years to secure answers for simple diagnostic questions, which is unacceptable to people with a rare or life-threatening condition. Cloud computing alongside AI, where data scientists can tap-into a seamless data research service promises to truncate this diagnostic odyssey. As part of the HDRUK launch, public forums were held inviting patient leaders and patient groups to outline expectations. Their counsel was that inefficiency in creating storable, searchable, shareable health data would not be tolerated; public confidence in cloud computing of biometric data is undergirded. Patients perceive cloud computing to be a natural component of digital health care services and research. Even data security breaches have not deterred the Citizen Science movement. Clarion calls to use big data and socialised health advocacy continues.

Pharma companies need data-harvesting strategies

Daniel Thomas at BBC Newsweek said, “expectations are now sky-high as research tools evolveclients want faster, cheaper and more innovative research.” In medicine and in health, therefore, both for the individual and for governments tasked to address the major health care challenges of our times (chronic illness with ageing, obesity and cancer), a pharma or biotech company without a strategy and infrastructure to harvest big data is starting to look vulnerable. 

Fortunately, translational bioinformatics research has also been in place for over a decade with the ‘information explosion’ – the growth of publicly available molecular and clinical data combined with next-generation sequencing and genomic data. As data increases in size, health organisations have revolutionised their data infrastructure accordingly. The transition from pure biological and medical sciences to melded, data-driven sciences means that the challenge of data transfer, storage and analysis are ‘housekeeping’ basics. Innovative healthcare companies have already moved past questioning ‘what do we do with these data’ and/or ‘how do we keep these data safe?’; into progressive creation of models of data architecture in partnership with traditional R&D processes.

 Data is the symptom and the solution

‘Big data’ as a catch-all term represents an imperative method of integrating and researching health information at enormous volumes in a high-performance environment to deliver better health solutions, products or services. As such, ‘traditional’ pharmaceutical organisations must reconfigure laboratory-based research infrastructures into enterprise health care organizations where high computer algorithmic power is as ‘normal’ output as a health solution as a medicine, pill or therapeutic intervention. Data is now a symptom, a solution and a therapy.

 Accordingly, enterprise-level infrastructures of managing, storing, interpreting, sharing and securing large volumes of sensitive data are also needed. This is most readily achieved using cloud computing and platforms. However antediluvian approaches and outmoded belief that cloud computing is not secure remains prevalent in many pharmaceutical organisations. Despite innovative collaborations and notable R&D successes using cloud computing across multiple therapeutic areas, misconceptions about security of cloud computing prevail. The ‘cloud computing climate’ is changeable; opportunistic and innovative in start-ups but lagging in larger companies. This is because broad, elastic systems need to be purchased that have the ‘ABC triumvirate’ -- Accuracy, Biological transformation and Capacity at scale. The enormity of creating both a big data strategy and then integrating cloud computing in models that invite stakeholders across the entire health IT spectrum to collaborate is a Herculean endeavour.

Routine data analytics require innovative partnership models

Fortunately, academic, medical, public and governmental institutions are proficient in their use of cloud computing. In contrast, some pharmaceutical companies are unconvinced about their vital role in big data translation. Caution prevails about responsibility and regulatory repercussions in the event of a security or privacy outages. Migration of patient data to routine cloud storage is inevitable, however. Furthermore, public demand for expedited health solutions will continue as will the expectation of big data research collaborations by public and private health partnerships. Citizen Scientists want fast and accurate answers from big data that are both preventative and curative; they will pressure the more restrained companies into reconfiguring and integrating scalable R&D cloud computing systems into routine innovation for progress.

 Smart companies investing in smart data platforms

Competent systems, services and products from trusted companies such as Google enable confident adoption of cloud computing research tools by pharma. Pharma companies are becoming big data health care companies and the expedited health care solutions that result as a part of the ‘Citizen Health’ movement are the ‘industrial revolution’ of the big data age. Researchers have proved that IT services delivered via cloud computing paradigms – the provision of on-demand access to shared pools of resources – provide major benefits for health care. Recalcitrance is not an option.

The global spend on cloud computing by health care is predicted to reach $35 billion by 2022; this is driven by the clear need for pharma to reconfigure the product pipeline in a data pipeline. Compelling partnerships with companies like Google Health can cut the time to discover and develop a new medicine by a factor of 10. A robust data pipeline emboldens pharma by guiding decisions whilst broadening the search for potential solutions. Big data secured, analysed and used to further personalised medicine has big opportunities for pharma to be a true partner every day for people in the era of Citizen Health.

Weekly Brief

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