Lateral flow testing at CDP: A surprising result

May 27th 2021

Mike Worth

When we modelled the use of lateral flow testing at CDP we discovered something surprising: there was a high chance we could test everyone every day without preventing a single transmission of COVID-19. This application of mathematical modelling and bioscience gave us powerful evidence on which to base our response, allowing us to direct our efforts where they will have maximum impact: improved ventilation and new air filtration installations in our offices, labs, and workshops.

In common with all businesses, CDP has been closely watching developments in practises, and technology to keep our people and community safe from COVID-19 infections, while maintaining business operations. In the UK, lateral flow tests (LFTs) have been rolled out in a variety of settings over the last few months. These tests have major benefits in that they are low cost, give a result in half an hour, and require no medical expertise to administer. When the use of these LFTs became a possibility here at CDP, our COVID-19 team began drawing up plans for the roll out.

The two key questions were “who to test” and “how often to test”

As a multidisciplinary business with diverse capabilities and specialisms, our people work in a variety of locations and patterns. Most of these working patterns and risk profiles don’t match those of the early adopters of these tests, such as those in clinical and educational settings. As a result, we built a team to analyze the available data and tailor our use of the tests for maximum impact in our particular case. The team was led by myself, a simulation scientist, and my colleague Richard Owen, our Senior Consultant Bioscientist. The team identified the latest bioscience data available on the parameters of COVID-19 and the LFTs, then developed a bespoke Monte Carlo model – used to predict the probability of different outcomes – to model potential infections across the business. We used the popular Anaconda python platform for scientific computing.

What are the key inputs?

COVID-19 infection timeline

A viral infection typically progresses through several stages: when a person first catches the infection, the virus multiplies until they become infectious and often continues to multiply causing symptoms before the immune system is able to fight back and eliminate the virus. LFTs can provide an “early warning” when virus levels start to increase, but before symptoms start.

‘Effective R’ within CDP

We’ve changed our working environment in a variety of ways to reduce transmission potential. If this was 100% effective then LFTs wouldn’t offer any benefit, but we all understand that the measures are instead designed to reduce the risk to the lowest reasonable level. While we have no evidence for transmission on-site, we’re aware of some cases, unfortunately, brought in from the outside community and so we applied a “reasonable worst case” estimate of transmission.

Background population case rate

Clearly more cases of COVID-19 circulating outside CDP would result in more infected people coming onto our site and identification of each one could potentially prevent further infection. We recognized that this value has changed rapidly so we investigated the benefit of LFTs in a variety of scenarios.

Sensitivity: if a person with COVID-19 takes an LFT, what is the chance that it will give an accurate, positive result?

This property of the LFTs on the market is very important. While they can be more than 90% sensitive for symptomatic people, those people should already have isolated and obtained a “gold-standard” PCR (lab) test. When used in asymptomatic populations with well-functioning immune systems, the sensitivity can be as low as 3%. Considering the population demographic in this study compared to our own, our model took a less pessimistic view of LFT performance and erred on the side of higher sensitivity.

Specificity: if a person without COVID-19 takes a lateral flow test, what is the chance that it will give an accurate, negative result?

The LFTs on the market are thought to have a specificity of around 99.5%. While 0.5% might sound low, current estimates are that only 0.1% of the population has COVID-19; therefore the 0.5% false positives actually make up significantly more people than the number that are really infected. This is the source of some controversy as it can cause unnecessary isolation when the case rate is low; however, this risk was not considered a significant problem for us at CDP as we took a “better safe than sorry” approach.

What did we learn from the model?

There are multiple measures for the success of a testing program. In our analysis we simply looked at the number of people becoming infected, and how much this could be reduced by a variety of regimes. We ran the model many times with differing input values to evaluate the impact of testing regimes and understand the sensitivity of our results to the various inputs, which are either uncertain estimates or subject to change over time. In a result that surprised us all, we discovered that in our specific situation the benefit of LFTs is actually very small. Of course, the keywords here are “our specific situation” – by tailoring our model to CDP we gained maximum value for our own decision. However, this model is inherently not a generalized result and is not a valid evidence base for decisions in other contexts. There was a high chance that we could test everyone, every day (totaling thousands of tests) without preventing a single transmission of COVID-19.

What was the outcome?

We both verified that each small “cog in the machine” was behaving as expected and validated that the results of the whole model matched reality (we already had a historic dataset for what COVID-19 transmission looked like without lateral flow testing). We also further explored uncertainty in the driving factors, to assure ourselves that the remaining uncertainly in the inputs would not substantially change the outputs. Following this process, the non-intuitive result allowed us to confidently redeploy our efforts onto alternative COVID-fighting initiatives. Following the evolving scientific knowledge, we’ve improved the ventilation of our offices, labs and workshops and installed air filtration to reduce the potential for airborne viruses to move between people.

We inevitably enter investigations with preconceptions, but by applying science to the big decisions we’re able to confidently manage our choices and prioritize our resources to keep ourselves and others safe in this weird world. By combining our expertise in both mathematical modelling and bioscience, we created a team that is more powerful than the sum of its parts, demonstrating the power of mathematical modelling in making decisions.

What next for events in the world of COVID-19?

February 11th 2021

Ana Romero

The impact of the pandemic has dramatically shaken up the world of conferences and events. Ana Romero, Digital Marketer and Events Coordinator at Cambridge Design Partnership, looks back over a tumultuous year and asks, “what next”?

Here we are, almost exactly a year ago. This is Pharmapack, in Paris. The two-day event was attended by 5,500 delegates and more than 400 exhibitors, and just look at the optimism on our faces! We don’t know it yet, but this is the last physical event we’ll attend before the pandemic descends, forcing us into our spare rooms and at the mercy of Teams, Zoom, and an emerging world of digital-only events.

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CDP team at Pharmapack in Paris, February 2020. Left to right; Jon Powell, Senior Consultant, Ana Romero, Digital Marketer and Events Coordinator, Martha Hodgson, Market and Design Insights Research Consultant, and Uri Baruch, Partner and Head of Drug Delivery

Welcome to chaos

A month later, in March 2020, the events world was in chaos and turmoil. I was busy contacting the organizers of each event we were planning to attend, checking their websites for updates, following the news and, arranging refunds for cancelled conferences.

Many conference organizers simply announced that they would be cancelling their 2020 offering and would be back in 2021. But others tried to offer a virtual experience. The idea of going online came as a relief to us here at CDP – as we were just as keen as before to share our expertise, to network with our peers, and meet tomorrow’s clients.

However, the transition to digital has been challenging, especially for event organizers dramatically adapting their business model and event delivery in a matter of weeks.

Forget the plan; it’s time to adapt.

So what have we learned? The most immediate learning for us at CDP has been that a good virtual conference is made by enabling the sort of interactions which make a physical conference so valuable. Can you get talking with someone who is visiting the event, develop them into a contact and then, hopefully, a client?

The first virtual conference we attended didn’t work at all. We couldn’t network with other companies, to reach the people we wanted or to strike up any sort of rapport with other attendees. A low bar had been set.

However, in only a few months, I’ve seen many improvements in the different platforms used and some real successes so far. Several virtual conferences we’ve attended during the pandemic have offered far better ways to connect and market to delegates. For example, some platforms allowed us to see and filter the delegate list (by name, role, and company name) and to request a one-to-one meeting with that person. In addition, the ability to watch presentations on demand made it easier to book a video conference during a session slot and later go and watch what we missed, something that wouldn’t have been possible in a real-life event.

Virtual conferences have crystallized how important it is to have your material in a digital and interactive format. We’ve learned to have just enough collateral in the digital booth to initiate a conversation. In a virtual exhibition, it’s easier to visit a virtual booth and fill your virtual goodie bag with all of the marketing collateral with just a click. This also has the risk of someone (including competitors) downloading your collateral and leaving the booth without saying a word. While this wouldn’t normally happen in a physical event it’s not hugely problematic: our materials can be seen by anyone.

One downside is that international events may not be particularly international: if an event is taking place on UK time and you want people from around the globe to virtually attend, you’ll find it’s tricky to enable conversations between members that are located in the US or Asia, due to the time differences. We’ve noticed this effect in the events we’ve taken part in.

We don’t expect face-to-face events to return properly in 2021. While many events companies are talking a confident game that plans for face-to-face before the year is out, most are adding other options to their virtual offerings. Think here of webinars, roundtables, and other additions that tend to suggest the new world is becoming “baked in”.

The post-COVID future

With all this virtual activity and conferencing ability we might ask, will the world ever go back to face-to-face conferences?

My feeling is that the leap to digital is a permanent one, but that physical conferences are far from finished. There are some significant downsides to virtual interaction that cannot easily be overcome. The first is the nature of the experience itself. If you travel to a conference and attend for two or three days, you are committed. You have spent time and money to get there, and as a result, you give it all your attention and energy, which makes the whole process more immersive. By contrast, a digital conference that you attend from your office or your home will struggle to capture your focus in the same way. You are so much more likely to be reading emails, on the phone, or being interrupted by your kids.

The very fact that it is so effortless to attend a digital conference can make it a less valued experience. If you “bump into” a delegate virtually, by messaging them through the conference’s contact system, it is far easier for them to ignore you. However, if you meet them at a real-life event, your chances of striking up a fruitful conversation are far stronger. Perhaps this is a good thing, forcing us to be on top of our game, offering nothing but compelling content and conversations. Although the process of tracking down attendees at a virtual conference is now quite slick, there’s nothing quite like meeting someone face-to-face and all of the non-verbal communication that goes into those meetings. It’s much harder to entertain clients and to build up goodwill online.

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Ben Strutt, Partner and Head of Design and Front-end Innovation, speaking with Max Angelov from the CDP offices in Cambridge ahead of presenting at last year’s virtual Global Innovation Forum, November 2020.

A crucial part of why we here at CDP value the opportunities offered by real-life conferences is that they give us the chance to develop and share our thought leadership. The events themselves are part of our learning, and giving presentations or taking part in discussions help to raise our profile in our key markets. The fact that a virtual conference presentation will often remain online for several months extends our reach significantly. We can also access information which shows who has been watching and, where it’s relevant and data protection allows, we can reach out to them afterwards to continue the conversation. This is a definite advantage of virtual events.

But when it comes to displaying our physical work, we want to show off what we create and allow booth visitors to interact with a connected inhaler, an innovative food packaging concept or any other product development. It’s hard to replicate the tactile experience of a real-life display of products that can be picked up and examined and where a visitor can ask questions of the development team.

All of this suggests that we’re headed for a future of hybrid physical and digital events. There will be real-life events, but some digital tools, such as one-to-one video meetings, digital roundtables, and others currently being explored will stay. Physical and remote attendees will be offered far more connectivity and interaction with other attendees than ever before.

In the meantime, as we press through the pandemic and emerge on the other side, it’s crucial to be creative and make use of the technology that allows us to connect virtually. It’s fair to say that virtual events are not yet providing the full benefits of a real-life gathering. But we are where we are and it’s in all our interests to work with digital alternatives so that we can keep doing business, one way or another. Whether it’s physical or digital, I’ll see you there.

CDP completes pilot manufacture of Point of Care diagnostic readers for rapid COVID-19 testing

February 9th 2021

A team at UK product and innovation company Cambridge Design Partnership (CDP) has produced highly deployable devices for COVID-19 testing. CDP has been collaborating with diagnostics tech firm QuantuMDx to refine their Q-POC™ device and produce the first batch of readers to detect COVID-19 within approximately 30 minutes. QuantuMDx is now investing over £11 million to scale up production and introduce this rapid diagnostic solution to benefit patients and frontline health workers across the globe.

QuantuMDx is developing molecular diagnostic devices for a range of diseases and has developed and launched a highly accurate lab-based SARS-CoV-2 assay. Prior to the COVID-19 outbreak, the firm had commissioned CDP to produce prototype devices for CE marking. CDP worked through the first UK lockdown to improve the design of the reader and the first units are deployed at UK hospitals for COVID-19 testing studies.

“After beginning our partnership with QuantuMDx during 2019, we were delighted to be asked to collaborate with this innovative company once again, at a critical time. The team has been highly motivated by this crucial project and proud to contribute to the national effort,” says Dan Haworth, CDP’s Head of Diagnostics.

Colin Toombs, VP Research & Development at QuantuMDx, said: “We’ve worked in partnership with CDP since April last year, to undertake accelerated pilot manufacture of our Q-POC™ device, which is a portable DNA/RNA analyser offering rapid, sample-to-answer, molecular diagnostic testing at the point of care. The QuantuMDx and CDP teams have worked in close partnership to optimise our product development and manufacture devices to deliver testing for COVID-19. They are being released initially for research use, but we are rapidly moving towards CE-IVD of Q-POC™ for SARS-CoV-2 detection. Working together with CDP, we’ve established an ongoing partnership for the future.”

The device works by processing a swab sample, amplifying the target sequence specific to SARS-CoV-2, which causes COVID-19, and then detecting whether the virus is present. This all happens within a sealed cartridge that is controlled by the reader with minimal user involvement.

“Within approximately 30 minutes from sample collection, the device will give an accurate answer to whether the patient has COVID-19” says Dan.

These first new readers have been designed and built at CDP’s HQ in Cambridgeshire, where the company has short-run manufacture capability alongside its R&D facilities.

CDP’s team working to develop the QuantuMDx device includes mechanical and electronics engineers, software engineers, regulatory experts and manufacturing engineers.

“We worked at speed to design, build and test these important devices as quickly as possible. We are all thrilled to play our part in beating COVID-19 and we congratulate QuantuMDx on moving to mass manufacture,” added Dan.

For further information and media enquiries, please contact: media@cambridge-design.com or call 01223 264428

Dreaming big during COVID-19

November 16th 2020

Laura Sierra

Product designer Laura Sierra is working with Cambridge Design Partnership as part of the marketing team. Here, she reflects on what she learnt during an international design competition, the Dream Big Challenge.

Laura says: I’m an industrial product designer from Colombia, now specialising in marketing and communications for the design world. I’ve studied for a Masters degree in Science and Marketing at Anglia Ruskin University. This led to me working on a project here at CDP, communicating all the amazing and innovative work the company does to the wider world.

In 2015, I had a wonderful opportunity to join a team competing in the Dream Big Challenge. It’s an international design competition for youth teams and to my surprise and delight, our team won. The whole experience was life-changing. Usually, the challenge takes place in a vast hall in Barcelona, where teams have just three hours to come up with disruptive and exciting solutions to design challenges.

This year, I was scheduled to get involved again. But, of course, Covid-19 meant that the plan for hundreds of young international designers getting together was never going to happen. The contest is sponsored by the likes of Santander and Nike. Cancellation would have been a major disappointment to all concerned.

But instead of giving up on the competition altogether, the organisers moved it online. So we competed anyway, using communications technology such as Zoom, working against the clock. This year’s online event attracted 900 competitors from all over the world. More than 350 projects were submitted, making this last-minute switch online a huge success.

My team chose to focus on the field of Education, as several of us had a keen interest in this area. In our home country of Colombia, a substantial percentage of children are not able to go to school and are also unable to reach the internet. So they miss out on education entirely. Could we think of a way to reach them?

To our delight, our project, called Ekko, scooped the third prize in the Education category. Our project was based on the idea of reaching children in remote areas via SMS messaging and radio. We aimed the project at pupils from 12-18 upwards, who could follow a class on the radio and interact with teachers via SMS. Many families have access to phones and radios in Colombia but do not have computers or access to the internet. And, of course, this model has potential in so many countries around the world. In Colombia, 47.7% of the population (23 million people) do not have internet access in their homes.

I learned a lot from the hectic three-hour webinar in which our team designed this education programme. Much of what I learned is proving very useful in my other online collaborative work during the Covid-19 crisis. Here is what I discovered about teamwork when you’re all working remotely under lots of pressure:

1. Have the right tools

I soon realised that it is important to have the tools which allow you to migrate between online and offline with ease. Make sure you have digital tools, creative materials and can do (and share) fast sketching so that you can share ideas as seamlessly as possible. In the competition, colleagues were connected from other places, even in different time zones. Working remotely using tools like Zoom, Google Meetings and WhatsApp was possible but also very intense. There is no doubt that online events change human interaction and experience. It is essential to have the proper tools to hand, allowing creatives and entrepreneurs to develop their projects remotely in a flexible and stress-free way.

2. Find your common purpose

A common aim really helps an online project. If you have a clear reason why you’re undertaking the work, things will be much easier. In our competition there was a choice of five different sectors: Health, Sport, Education, Work and Sustainability. I worked with university professors Andres Rubiano and John Higuera. All of us are passionate about social innovation and wanted to change education, making it fun, free and interactive. This really helped our motivation when things didn’t go smoothly.

3. Creativity is key

Using your imagination in challenging times is more important than ever. An open mindset allows us to manage challenges. I truly think that each day is an opportunity to learn and design a better world. The key is to let our imagination fly, allowing it to create and to not panic about failing. This competition taught me that, even during a lockdown, working remotely, it was possible to connect online, study other projects, explore new ideas and connect with new people.

In conclusion: I’m delighted to say that our project, Ekko, is now in the throes of becoming a reality in Colombia. It looks as though those tumultuous three hours of intense activity could end up changing the lives of thousands of children for years ahead. That really is a good result, isn’t it?

COVID-19 Modelling

April 3rd 2020

Dr Karla Sanchez

Head of Biomedical Engineering

Alison Hart

Maria Fernandez-Martos Balson

Models are everywhere – anyone who has played a computer game has encountered a model, but in a pandemic, mathematical models are vital for understanding the dynamics of transmission, disease progression, healthcare needs and the overall outcome on the population.

Recent real world events have shown that critical decisions are being taken based on model data. Many people are still uncertain of how models work which can lead to them being met either with undue suspicion or absolute faith. In reality models are incredibly powerful, as you can test different courses of action quickly so an optimised response can be formulated, but their limitations need to be understood.

What is modelling?

Here we try and explain the basic principles of models, how mathematical models can help and what their limitations are.

Mathematical modelling involves making a mathematical representation of a system where the expected outcome of changing various parameters can be calculated. This means you can examine the outcomes of many scenarios using the same model. For example, the models reported on recently look at the spread of Covid-19 with different levels of social distancing and other interventions such as school closures. A model of a complex system is usually a collection of many separate models, each a breakdown of a different part of the system. For example, the first thing to consider when modelling the spread of disease is infection. You need to know certain things such as;

how likely is the infection to spread person to person with each contact?
how often do people come into contact with each other?

These values are called parameters and can be changed depending on the situation. The equations behind epidemiological models for the spread of infection are well established, but the parameters will vary between countries depending on things like the breakdown of age and population density. Crucially, epidemiological models rely on data. Sourcing these parameters is all part of modelling and assumptions have to be made.

For recent UK modelling this data came from a number of diverse sources. Census data could give a good indication of the age and distribution of households, data on social connections broken down by type (work, school, home) and age came from a BBC citizen science project. Even knowing this, data on class sizes, commute distance and company size were then needed to create a virtual population to simulate the spread of the disease.

Models can also show where collected data may be inaccurate. Recent models monitoring the situation in Spain found that the number of COVID-19 deaths reported appears to be significantly underestimated, given existing data on the expected seasonal number of deaths in a normal year and data on the total number of deaths recorded in the past few weeks (by any cause).

Simple demo of infection model.

This is a very simple model purely looking at infection. When ‘infected’ balls come into contact with others susceptible to the disease there is a probability that the other balls will become infected. There is no death rate, everybody recovers and is then immune. The speed of the balls represents the number of social contacts. The probability of infection, the proximity for infection, the length of the infection all need to be set. Even in this toy model many assumptions have been made.

What changed with the recent modelling?

Having modelled infection and the population, the outcome needs to be considered. What proportion will recover and develop immunity? What proportion of people will become hospitalised? Of them, crucially, how many will need intensive care and specialist equipment like ventilators. All these parameters depend on the disease itself. Unfortunately, Covid-19 is practically unknown, researchers have had only a few months to study it. That means there has been a degree of uncertainty with the parameters fed into the models.

One widely reported model that looked at the impact on the UK population was led by Imperial College London. Having updated their models with better information from Italy on the proportion of patients requiring intensive care beds, it found that the UK’s National Health Service would not be able to cope without further action, which led to the recent dramatic change in government policy.

In the report, the team presents a pandemic curve for different degrees of potential government intervention. The different measures that they considered the impacts of were: no intervention, household isolation, social distancing, and school closures. With no intervention, the model predicted a need for hospitalisation thirty times what the current UK healthcare system can manage. Only by combining all of the measures would the healthcare system not be overwhelmed.

This is one of the graphs from the Imperial paper [1]. The vertical axis shows the number of critical care beds needed through time in each scenario. The blue region shows the time period on the horizontal axis where various social distancing is applied. The horizontal red lines show the maximum number of NHS critical care beds available. The various lines, explained in the key, show the difference between doing nothing, applying some social distancing and with full school and university closures. This graph shows that without all measures being taken the number of available beds would be exceeded.

What happens next? What about the large peak when the measures are withdrawn?

We need time. Time to get better testing, time to find new treatments and more ventilators. The current model suggests the current restrictions should keep the number of cases at a manageable level for the next few months.

The Imperial model makes important assumptions. Firstly, it assumes that measures put in place to control the spread of the virus are all lifted at the same time, which is neither realistic nor advisable. Secondly, it assumes that recurrences of the outbreak after the initial lift of restrictions continue for an indefinite period. In reality, this may not happen due to people acquiring immunity or the availability of a vaccine. Finally, it doesn’t account for infected cases that have gone undetected or for tools such as contact tracing, which can help break the chain of transmission. All of this will affect the number of people who become infected once the measures are lifted.

A competing model by Oxford University followed the publication of Imperial’s model. This model stated that under-detection of cases could be high, indicating that a significant part of the UK population could have already contracted the virus. This caused a big media response, however, given the data available it seems an unexpected conclusion to draw, as epidemiologist Adam Kucharski pointed out.

The Imperial model has since been refined and other competing models have been published, but the consensus remains.

It’s important to remember that the model is only based on what we know now. Models are continuously updated. Research teams are now focusing on measuring the impact and preparedness of healthcare systems by predicting the number of hospital beds, ventilators and testing kits needed based on what the models are telling us. They are also looking at the big question of the length of time needed before lifting restrictions and how to prevent a second wave of the outbreak, and models will help us to understand this better.

So in a few months the situation will have changed, the model will be updated with more information and the curve may look very different. Data should start to emerge to confirm level of immunity gained from recovering from the disease. More hospitals are currently being built and there is a national effort to produce more ventilators. Doctors have already identified the response that causes some patients to develop severe symptoms while most have a mild version, which may make it possible to screen people to detect who is most vulnerable or identify better treatments.

Given the rate of learning in the last 3 months the picture may be very different when more accurate assumptions are fed into the models.

Once a vaccine has been developed, we may require modelling for rolling it out to best effect, as well as monitoring changes in the virus. This will feed into the ongoing body of research for this pandemic and will help us prepare for future pandemics.

While models are not always accurate, they help build a consensus of understanding that informs policy and helps save lives. Taking the right measures at the right time is key in the fight against Covid-19 and through modelling we can make the best-informed decisions possible from the data available.

References

[1] https://www.imperial.ac.uk/media/imperial-college/medicine/sph/ide/gida-fellowships/Imperial-College-COVID19-NPI-modelling-16-03-2020.pdf
[2] https://www.gov.uk/government/groups/scientific-advisory-group-for-emergencies-sage-coronavirus-covid-19-response

Scaling up for COVID-19 diagnostic testing

March 16th 2020

Dan Haworth

Head of Diagnostics

The coronavirus is putting massive demand on test labs globally and the UK, along with many other countries, do not have enough capacity or test kits to keep up with demand. Intensive testing is not being carried out and the number of people with the virus is unknown. It will therefore be unclear if someone has the virus, whether they have immunity, or if they are still at risk of contracting it.

There needs to be increased capacity of central lab testing but also mass deployment of Point of Care (PoC) systems for near patient and home testing. PoC devices can provide accurate results within minutes and are intuitive for use by minimally trained users. Test results need to be reported in real time for epidemiological monitoring and Smartphone apps could play an important role in tracking cases.

What is currently being done and what devices are needed?

Central lab testing is being scaled up. Several hospitals in the UK are installing new high-throughput analysers and additional staff shifts to increase capacity from 1500 tests/day to 10,000 tests/day. Emergency funding is being provided by government agencies such as BARDA in the US for new Covid-19 (SARS-CoV-2) testing. These new tests are being authorised for emergency use, on systems such as Roche’s Cobas 6800 and 8800 systems as well as Hologic’s Panther Fusion analyser. However, due to the potential remoteness of sample collection, the time taken to transport and process an individual sample may still take several hours.

Point of Care devices have the ability to provide high performance sample-to-answer nucleic acid testing in at little as 15 minutes. A disposable cartridge controlled by a portable table-top instrument carries out complex sample processing steps including sample preparation, RT-PCR or isothermal amplification of viral RNA, followed by detection to provide a lab-quality result. Many systems already on the market have proven performance and are cleared for use by minimally trained operators. These systems are ideal for mobile clinics and remote settings.

Although some of these systems already provide a menu of respiratory tests (such as Flu A and B) they cannot detect the specific strain of SARS-CoV-2. Emergency government funding is also being provided to R&D teams across the world to implement the SARS-CoV-2 assay on their systems as fast as possible. Last week Qiagen was given $598k for implementation of SARS-CoV-2 on their QiaStat-Dx point of care platform.

Lateral flow immunoassays, similar to pregnancy testers, may also provide an ideal format for testing for SARS-CoV-2 as they are very low-cost, highly deployable and rapid so most people will be able to use them in their own home. Several companies are developing lateral flow tests for viral detection from swab samples, but also for detecting antibodies (IgG and IgM) in blood samples to indicate if a person has had the virus, and therefore immunity. Lateral flow tests can, however, suffer from false negatives (low specificity) and their ability to accurately diagnose early stages of covid-19 is currently unclear.

Fast-Track Regulation

In normal circumstances, it can take 6 months for regulatory bodies such as the FDA to approve a new in-vitro diagnostic test. This is typically after a clinical trial is performed to demonstrate the test is effective and this alone can take 12 – 18 months. Since Covid-19 is similar to other SARS respiratory virus, this process may take much less time and several companies are claiming to be able to validate new covid-19 assays in several weeks/months.

The FDA is already authorising some companies such as Roche to deploy their tests under “emergency use” conditions. Companies such as Roche has a proven system and track record or high integrity results, whereas there is a risk that less known companies who claim to have a PoC or rapid test do not meet the safety and efficacy requirements – the consequences of which could be much more significant than not testing at all. The FDA and other regulatory bodies need to carefully weigh up the risks of authorising use of potentially poorly performing devices.

Connectivity and mobile apps

Real-time result reporting is a critical aspect to monitor and track the spread of disease. Lab analysers and many PoC systems have in place connectivity infrastructure to send results to healthcare systems and onto authorities, but this is not easily achieved for remote testing and especially lateral flow tests which are ‘instrument-free’.

SmartPhone apps may be able to help in these cases by transmitting photos of test results, such as the test and control line on a lateral flow strip along with patient data. This technology is also capable of knowing location to identify new outbreaks and hotspots.

China made use of a SmartPhone app which provided the owner with a ‘risk profile’ and was used widely to control their epidemic. By location sharing, it was able to contract trace and determine whether the user had likely come into contact with a person who had tested positive.

Conclusion

Scale-up of central lab testing is already underway but we also need mass deployment of point of care systems – nucleic acid testing and immunoassay lateral flow tests. Healthcare workers and the general public need to be able to operate these so anyone anywhere can get tested quickly, reliably and accurately.

Regulatory authorities need to act responsibly to authorise for emergency use tests and devices that are likely to provide high quality results. These need fast-tracking so companies can rapidly scale up their manufacture – in a similar way to what companies are currently doing for ventilators and other PPE. In addition, remote deployment of devices into clinics and homes need to make use of SmartPhone apps to communicate the results for real-time tracking of cases.

CDP is a design and development partner certified to ISO 13485. We can help with device development, manufacturing scale-up, verification and regulatory approvals. For more information contact Dan Haworth at +44 (0)1223 264428 or hello@cambridge-design.com

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