When Theresa May was UK Prime Minister, she pledged to revolutionise the health service by deploying artificial intelligence in the NHS, aiming to prevent over 20,000 cancer-related deaths each year by 2033. The Prime Minister wanted industry and charities to work with the NHS to develop algorithms that can use patient data and lifestyle information to warn GPs when a patient should be referred to an oncologist or another specialist.
This announcement highlighted the increasing focus on the role of artificial intelligence and big data in diagnostics. The interaction of diagnostic tests and big data has positive implications not only for human health but also in animal, agri-tech and environmental applications. In this blog, we look at the implications for the lateral flow market.
What is big data?
According to Wikipedia: “Big data is data sets that are so voluminous and complex that traditional data-processing application software is inadequate to deal with them”. Martin-Sanchez and Verspoor, 2014 noted that the distinguishing characteristics of big data are;
- Volume (hugeness of data availability),
- Velocity (arrival of data as a flood of fashion),
- Variety (existence of data from multiple sources with diversified formats).
BIS Research’s 2018 Global Big Data In Healthcare Market report states that big data in healthcare was estimated to be worth $14 billion in 2017, and is anticipated to grow to over $68 billion by the end of 2025. Being driven by unprecedented growth in healthcare data, organisations are employing analytical tools, artificial intelligence, and machine learning techniques to derive data-driven insights in order to reduce health care costs, enhance revenue streams, develop personalized medicine, and manage proactive patient care. The key to leveraging big data effectively will be Artificial Intelligence (“AI”): technology that will allow machines to analyse a range of data sources, detect patterns and generate algorithms which can be refined as more data is gathered.
How will this impact lateral flow diagnostics?
In numerous ways. A couple of examples are highlighted below:
First, the specification of a lateral flow device may incorporate big data findings. The ability to quantify lateral flow tests results on a reader platform, such as a desktop reader or Abingdon’s Smartphone reader, AppDx, and combining this data with additional data sources, should allow improved diagnosis. For example, combining the sex, age, location, co-morbidities of patients and lifestyle aspects may generate a more effective diagnostic algorithm to stratify the patient population more effectively. Current reader technology can easily handle these algorithms and connected (WiFi, Bluetooth) readers mean that as datasets grow, these algorithms can be further optimised.
Secondly, lateral flow test results can be captured in the field and this information communicated via the cloud to a central source, alongside other data sources, and analysed by AI. One area of increasing interest here is the connected farm. Smart sensing and monitoring and cloud-based data management can allow for example the real-time monitoring of plant disease outbreaks. This can allow farms in the vicinity of the outbreak to be offered preventative treatments thus restricting the extent of the outbreak. In addition, AI-driven analysis of the data alongside other factors such as humidity and temperature could provide an early early-warning mechanism that could eventually prevent outbreaks in the future. Google Ventures is the leading investor in a $15 million round of funding for the Farmers Business Network, a company that is using big data to show farms large and small how to make the most of their business.
In many ways, lateral flow diagnostic results have the potential to be used less as stand-alone devices and more as part of data capture solution together with other data sources. This has applicability across the diagnostics market from the connected farm, for both plant and animal health, through environmental testing and the clinical market, and onwards into the home testing market.
Lateral Flow Quantification
By 2022, reports have suggested the quantitative lateral flow assay market will be valued at $1.2bn, which is a CAGR of 8.5% from 2017. The trend towards decentralised testing; increased demand for multiplex testing, and as evidence above the potential requirement for data analysis and algorithms are all driving this growth. In addition, technological change is improving the performance of both lateral flow readers and assays increasing the number of biomarkers that can be tested and also the sensitivity of these assays.
Things to consider:
- Do you have a “big data strategy” for your developed or to be developed lateral flow assay?
- Does your qualitative lateral flow assay need quantifying now or in the future? If so, consider this as part of your choice of lateral flow contract service provider now
- If your lateral flow assay needs quantifying, an integrated contract service provider can offer a seamless development service across both assay and reader?
- Does the lateral flow reader technology you are considering have sufficient capability and flexibility? Can it handle algorithms? Is it connected?
Artificial Intelligence and Big Data are set to transform a number of markets and are likely to have a dramatic impact on diagnostics. The $5 billion lateral flow market will be impacted in numerous ways and much of the growth in the LFD (Lateral Flow Device) market will be driven by the increased use of quantitative lateral flow assays and their integration into an overall diagnostic solution. The impact of this will be seen across agri-tech, animal health, environmental and clinical markets.
Abingdon Health’s role in the growing lateral flow market
Abingdon Health has a long track record of developing and manufacturing single target and multiplex lateral flow assays, both qualitative and quantitative, within regulated and non-regulated markets. Watch one of our videos or contact us to learn more about our capabilities.