Tag: Diagnostics

COVID-19 quarantine - How we are keeping our innovation projects moving
By Jez Clements and Mike Cane
March 13th 2020
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Jez Clements

Partner

Mike Cane

Partner

COVID-19 quarantine – How we are keeping our innovation projects moving

Mitigating infection means more and more people are working away from the office. At Cambridge Design Partnership we have geared up to work remotely, both internally with our project teams and externally with our customers. In this special blog, Jez shares some of the communication approaches we are using.

Here at Cambridge Design Partnership, we have a wealth of experience in remote working and conferencing. Our move to create the best possible virtual comms was initially sparked by our clients all over the world, with whom we seek to work closely in a collaborative and creative atmosphere from our HQ in Cambridge, UK and our East Coast engineering hub in Raleigh, North Carolina in the US.

We were mindful of the findings of Professor Albert Mehrabian, who back in the 1970s first mooted the concept of non-verbal communication. He found that in a test where people were asked to convey their feelings, 7% of communication was conveyed by the speaker’s words, 38% by their tone of voice and 55% by their body language.

In a vibrant meeting atmosphere like a brainstorm or creative discussion we naturally prefer the face to face experience, we find we talk a lot with our hands, technical props or mocks ups. So the trusty teleconference is lacking. Low cost video conferencing has been around for a while, but we have found that with a careful choice of hardware, software and etiquette, it’s a game changing tool.

The basics

We need teams to feel as though multiple locations have merged together, with everyone feeling relaxed and engaged so that they can fully contribute to the discussion. It’s crucial that everyone can see and hear each another, as well as look at what’s being presented or created, such as sketches, models, prototypes, videos and other simulations.

Choose the right platform

We use the Zoom videoconference platform; it integrates with Office and is easy to use. We simply email a link to join a meeting and with one click, the participant is in. Having said that we can easily add a password if needed.

But the software is only part of the equation, the camera and audio on many laptops leave much to be desired, and there are lots of relatively low cost add-ons that make all the difference.

Get plenty of cameras

You need high-definition video so participants can clearly see each other’s facial expressions and body language. This is surprisingly important – remember Professor Mehrabian’s findings! We use the Logitech range of high definition video conferencing cameras. We use ‘Connect’ for personal use and ‘Meet Up’ in larger conference rooms, they plug into your laptop and are transformational. They can be placed in your room to give a feeling of space, so the camera is not looking up your nose like many laptops do and the images are much more lifelike and expressive.

For groups you need enough cameras and screens for all team members to see and be seen. This makes everyone feel connected, rather than just having one camera focused on a whiteboard or a ‘talking head’. We link these cameras and screens into the meeting using the Zoom platform.

Clear audio

Having clear audio is essential, especially in larger rooms when people move about. Meet up offers great audio, but those who have to use laptops on their own need headsets or a Jabra table-top speaker/microphone, they are omni-directional and work really well with groups in larger rooms. It’s so important not to have to strain to make out what is being said, it makes the meeting much more relaxed and natural.

The role of the smart phone

Another key tool is the humble smartphone. This provides the flexibility for individual members to communicate very quickly. For instance, if there is a sketch or prototype someone wants to show, they can grab their smartphone, activate the Zoom app (use the joining code) and immediately share their camera. Of course, people can also join the meeting just with a smartphone.

Preparation is key

We always set up our meeting rooms in advance. No matter how good your kit is, there is often a technology ‘moment’ that needs resolution. You don’t want to lose that creative vibe as your team waits for IT issues. Also, don’t forget the conventional best practices for meetings apply as normal. Make sure you have a facilitator who issues briefing documents well ahead of the meeting and takes charge of the session with a clear plan.

Reap the benefits

With many virtual meetings and brainstorming sessions now under our belt, we’ve found that the remote working technology can actually enhance the communication experience. For instance, instead of all huddling around the same whiteboard or drawing, our use of smartphone cameras means that a drawing or virtual model can immediately be shared with everyone, regardless of their location. We have also found that a virtual meeting is usually much easier and quicker to organize, with more chance of all key players being able to attend and less time wasted while we wait for everyone to be available. It’s also hugely helpful that sessions can be easily recorded. This can be useful in unpicking exactly what was said and decided during a session.

Also, it’s remarkable to see how we are able to screen-share in our virtual meetings and work on complex Computer Aided Design (CAD), zooming in and highlighting areas, with the whole meeting able to follow and contribute.

In conclusion…

Now that we are used to virtual meetings, here at CDP we feel comfortable and confident with the technologies involved. It’s remarkable how people who are hundreds or even thousands of miles apart can work together really effectively, if the technology infrastructure is set up correctly.

The current outbreak of corona virus is worrying on every level, to which there are not many easy answers. However, there is a lot that we can do to ensure our economic activity is not hit too hard by the situation. We are happy to advise our clients how to make our virtual communication as effective as possible, and keep our innovation projects moving.

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January 31st 2020
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Brexit and the Implications for the Medical Device Industry

It’s been 42 months since the United Kingdom EU membership referendum took place, and with the date for ‘Brexit’ upon us it is time to reflect on upcoming changes.

What is known? At 11pm on Brexit day, Friday January 31st 2020 the UK formally leaves the EU and becomes a ‘third country’ (which means the UK will have the same status as countries like the USA and China), although EU law will continue to apply during the transition period as the UK and EU negotiate a trade deal. This transition period is planned to run until the end of December 2020. The outcome of negotiations is uncertain, it could be a deal that maintains the free flow of medical devices and diagnostics between UK and Europe, or the UK may remain a ‘third country’ and EU law ceases to apply.

So at the end of December there is a possibility that manufacturers who currently sell CE approved medical devices will fall into one of three categories; UK manufacturers selling into the UK, UK manufacturers selling into the EU, and EU manufacturers selling into the UK.

The first category is easy as UK manufacturers will have their product’s CE status transferred into UK law, so there will be no issues.

However, for UK manufacturers wishing to sell to the EU it might be more complex.

  • UK Manufacturers or importers may no longer be considered economic operators in the EU after the end of the transition period. So, in order to place Medical Devices on the EU market, Manufacturers would need to be based in the EU, or contract with an Authorized Representative, Person Responsible for Regulatory Compliance (PRRC) and an importer based in the EU.
  • Then moving forward, new CE certificates would only be issued by Notified Bodies based within the EU.
  • Finally, in the event of a no-deal situation in December 2020, all certificates issued by UK-based Notified Bodies would become void in the EU.

In the event of no deal in December 2020 there would also be an impact on European Manufacturers wishing to sell into the UK after the transition period.

  • EU manufacturers would need a ‘UK Responsible Person’ to take responsibility for their product in the UK, and register their product with the MHRA.
  • The UK will mirror the key elements contained within Regulation 2017/745 (MDR) and 2017/746 (In Vitro Diagnostic Device Regulation, IVDR), via the Medical Devices (Amendment etc.) (EU Exit) Regulations 2019 when each is applied, the MDR on 26th May 2020 and the IVDR on 26 May 2022.
  • After the transitional period, all medical devices (including active, implantable medical devices), In Vitro Diagnostic devices and custom-made devices will need to be registered with the MHRA prior to being placed on the UK market. The timelines for this are in line with the risk classification of the device and range from 4 months for high risk devices to 12 months for low risk ones.

With the implementation status of the Medical Devices Regulation in Europe not where anyone in the Industry would wish it to be, and only nine, or potentially eight (if there is no deal in December 2020) Notified Bodies designated against the MDR currently, it is clear that the industry as a whole is struggling to cope with the extent of the regulatory change.

The good news is it looks like the MHRA will take a pragmatic approach to the ‘worst-case’ no-deal scenario at the end of December 2020, whereby the European Regulations are transposed into UK Regulation so existing products do not immediately lose approval status; this goes a long way to maintaining access to vital products on the UK market and provides a clear pathway forward.

In the EU, UK manufacturers would be eligible to apply at national level for time-limited derogation for ‘protection of health’, but this is only likely to be granted for those devices with no alternative product for use in life threatening conditions, and is likely to be subjected to additional restrictions.

Here at Cambridge Design Partnership we’ll be keeping a close eye on the details of Brexit implementation and the impact on the healthcare sector. Next month we’ll be focusing on the implications of the changes to the Medical Device Regulation as the Date of Application approaches and how to be best prepared.

To find out how CDP can help you with the details of Brexit implementation and your MDR and IVDR transitions, please get in touch.

AI in healthcare
By James Baker
November 27th 2019
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James Baker

Partner

AI in healthcare, separating facts from fiction

James Baker, partner at Cambridge Design Partnership, considers the future for AI in the real world with help from a sideways look at its portrayal on the big screen.

In the movies, we often see big tech and deep data combine to challenge humankind in new and ever more fiendish ways. Indeed, at the cinema, human interaction with Artificial Intelligence (AI) is a rich seam of storytelling, which rarely ends well, for the human!

Meanwhile, back in the real world, we are now in an era where digital data, and more importantly the insights that can be drawn from it, can be as important – and as valuable – as physical objects. At Cambridge Design Partnership (CDP), one of our specialisms is the design of medical devices, often using information and machine learning to provide utility and value beyond the physical device alone.

So, in the spirit of fun, here is what the silver screen tells us about the big questions surrounding machine learning in healthcare, and we ask how these ideas relate to the reality of what the technology can achieve today?

What price genetic data? (Gattaca)

In the 1997 film Gattaca, only genetically perfect humans are eligible for better jobs and lifestyles. We cheer on Ethan Hawke’s ‘genetically inferior’ character as he assumes the identity of a superior being in order to become an astronaut.

In today’s world, less than 20 years since Gattaca was filmed, genetic profiling and statistical prediction is gathering speed. Mapping of genomic sequences to traits is a rich area of study and just this week, Matt Hancock the UK Health secretary announced that all babies could receive a complete genome sequencing at birth. Crucially, this technology has the potential to predict an individual’s likelihood to suffer illness in the future. But should the way you are treated as a patient, or indeed a person, be determined by an assessment of your genetic makeup? Already insurers are asking for access to medical records and premiums are affected by the presence of certain diseases, so should they also be able to consider the likelihood of future illness as well?

Diagnosis – how far should you go? (Minority Report)

The film Minority Report envisages a world in which arrest and incarceration is based on a prediction of the likelihood to commit a crime before it has occurred.

Already today’s healthcare and wellness technologies create significant amounts of data about individuals.  New processing methods and machine learning can analyse these multiple sources and draw conclusions.

Yet many clinicians don’t want every possible analysis to be given to them. For example, who is responsible if systems predict the probability of an illness, but the medical practitioner can’t confirm this conclusively? Does informing the patient provide any utility?

There are recent moves to define what can and can’t be done with personal data, such as the European Union’s General Data Protection Regulation (GDPR). These seek to control access to and ownership of data, but as yet, there are no similar frameworks to control the conclusions drawn from it.

What if AI overtakes human intelligence? (Ex Machina)

In the film Ex Machina a humanoid robot is created and given ‘intelligence’ built using a record of billions of human internet searches. But then (surprise!) the robot uses its knowledge of human interactions and desires to achieve its own freedom, deliberately misleading its human masters to do so.

Machine learning using huge amounts of information is an approach we see increasingly used in real life. In the field of diagnostics, AI is already showing great promise in diagnosing conditions such as Alzheimer’s and in facilitating cancer diagnoses. AI predictions are compared with a gold standard diagnostic to determine the most significant automated metrics to detect the condition.

This approach is already being used in cancer screening, enabling earlier detection through far more extensive analysis than is possible manually.

But what if AI doesn’t react like we expect? (2001)

An all time classic, 2001 cleverly hides a story of unintended consequences within a ground breaking and spectacular space opera. The HAL character appears to have a sinister agenda and behaves malevolently, attempting to kill off the human crew – but ultimately is understood to have been driven by conflicting orders.

In the real world, AI can deliver responses that are not what we expect. Large data sets may still contain insufficient information, erroneous or poor-quality data, which by chance may create patterns that have no meaning.

A good example of where AI can deliver unanticipated (and unwanted) behaviour is the late, unlamented Microsoft Tay chatbot. Its premise was that, by listening to and learning from posts on Twitter, it could generate useful tweets and help manage commercial Twitter accounts. But within hours of its release in 2016, Tay began posting inflammatory and offensive tweets and had to be taken down.

So, before we make AI systems independent, how can we be sure how they will behave and who takes responsibility for their actions?

Sometimes, AI can really help us (Wall-E)

The 2008 story of a good-natured planetary janitor-bot left to clean up our human mess shows how AI can really benefit humankind, turning its hand to automating work that would otherwise be onerous and low value. See also, C-3PO and R2-D2 in the Star Wars movies. It’s surely no coincidence that the two loveable droids are the only characters to appear in every single film in the Star Wars franchise.

Back in 1950, computing pioneer Alan Turing predicted that by the year 2000 computers would be able to trick us into believing they were human 30% of the time. He was not far wrong, in 2014 a chatbot called Eugene Goostman convinced 33% of judges that “he” was a 13-year-old from Ukraine, thus officially passing the Turing Test. We see these kinds of natural language interaction technologies being used increasingly in consumer goods, but also finding utility in medical applications such as triage with patients seeking care. This enables faster access and a better “customer experience” whilst also allowing healthcare practitioners to focus on provision.

In conclusion, at CDP our focus is on how to realise value for our clients, and machine learning is one of the tools we can bring to bear.  With the ongoing bombardment of new technologies, it is important to understand when it can provide effective solution, and when more traditional methods will provide the best results.  It’s no longer a question of what can we do with AI?

We need to ask: What should we do?

Developing guidance for regulatory submissions
By Helen Simons
September 12th 2019
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Helen Simons

Quality Specialist

Developing guidance for regulatory submissions

RAPS (Regulatory Affairs Professionals Society) publish a set of excellent “Fundamentals” books, each covering a different regulatory context: US, EU, Canadian and International (which covers other markets). These books detail the key aspects of the regulations for pharmaceuticals, medical devices and IVDs (In vitro diagnostics) with considerations about how they should be followed and implemented.  These are essential for healthcare companies looking to make submissions outside of the jurisdictions they are familiar with.

These books need to be regularly updated as regulations evolve to ensure they are current, and I have been chosen as a subject matter expert for the US fundamentals book that looks at the requirements of the FDA (Food & Drug Administration).  I have recently updated the chapter “supply chain and traceability”, along with a second author, Jyoti Chauhan.

This chapter was initially introduced in the last edition (10th) and so was relatively new to the book. Upon reading, I was most surprised that it did not cover any elements of supply chain or traceability for medical devices, only focusing on pharmaceutical requirements, specifically the Drug Quality and Security Act. I felt the chapter was lacking in detail on medical devices because traceability is a key topic at the moment with the introduction of UDIs (Unique device identifiers) in the last few years, so this was a big gap to be missing.

My first task was to pull together all the existing guidance on the topic of UDIs which the FDA have published as well as the key aspects of the CFR (code of Federal Regulations) in relation to supply chain and traceability. It was interesting to compare them at the same time as different pieces of information are emphasised in different guidance, so I wanted to summarise these in a cohesive overview.

Adapting to the formal writing style of these publications was a practical challenge, but I hope my description and analysis will help other regulatory professionals navigate the tricky waters involved in submitting their products to the FDA for approval.

If you want to know more about these subjects or how CDP can help you with your quality and regulatory activities, then please do get in touch with us at hello@cambridge-design.com.

Dr Pari Datta|||Dr Pari Datta
May 14th 2019
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6 steps to build winning biosimilar defence strategies through user and technology mapping

WEBINAR
With Pari Datta
14 MAY 2019

The market for biosimilars is growing rapidly at over 30% per annum, as increasingly more biological drugs are going off-patent and the rate of regulatory approvals increases. The major high-value mono-clonal antibodies are considered as the big opportunities by companies in the bio-similar space, including for example the TNF-alpha inhibitors. Although bio-similar development and regulatory hurdles have been more challenging than expected, developing a robust biosimilar defence strategy is still a vital and difficult process. Solutions within a strategy can range from relatively simple, such as powerful new counter-biosimilar messaging to more complex, value-added propositions which include novel delivery devices, diagnostics and even digital elements. Questions range from how to discover new underlying opportunities from which to build a defence strategy and how to deliver technology-enabled propositions which can make them really possible.

In this webinar, Dr Pari Datta (Senior Innovation & Research Consultant) demonstrates how simple user experience mapping methods can reveal truly-original opportunities throughout the journeys of the patient, HCP and even the product during the process of treatment. From these opportunities, technology mapping will be used to show how the latest technologies, from digital to formulation, can be identified or even conceived to create innovative value-added propositions. The key elements which need further development within each proposition will be considered – from satisfying multiple stakeholders, business model development to building the evidence required to generate confidence in its future commercial success.

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Personalised medicine brings a healthcare revolution - CDP||
By Dan Haworth
October 23rd 2017
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Dan Haworth

Dan Haworth

Head of Diagnostics

Drugs that work – personalised medicine brings a healthcare revolution

It took 13 years and £2 billion to sequence the human genome back in 2003. Fast forward 15 years to today and next-generation sequencing (NGS) can do it for less than $1,000 in a matter of days. High-throughput sequencing technologies, computational power and data-mining techniques have opened up a whole new era in medical treatment – and our approach to product development.

Genetic differences in DNA allow scientists to determine how a patient will respond to certain drugs, enabling doctors to target their treatment. For example, the Sanger Institute recently discovered that the aggressive blood cancer acute myeloid leukaemia could be classified as 11 distinct disease groups, based on specific constellations of genetic mutations. This explains why some patients will be cured and others will not if they receive exactly the same treatment.

This ‘personalised’ approach promises to improve patient outcomes as the right treatment can be given from the start – time is not wasted by finding what works by trial and error – and unpleasant side effects can be minimised. Treatment is more efficient – and less money is wasted on ineffective drugs.

Diagram-01

New targeted approaches based on genetic information are gaining particular attention from pharma companies, as they can dramatically reduce drug development costs and timescales. Whereas traditional drug discovery often leads to high failure rates in phase 2 or 3 trials, targeted treatment allows smaller trials and shorter regulatory review times because the drugs are safer and more effective.

Although the market size is smaller, lower side effects mean an increased price can be charged for the drug. An example of this is the Food and Drug Administration’s (FDA’s) approval in 2012 of a new cystic fibrosis (CF) therapy for patients with a rare genetic mutation (G551D mutation). This particular gene is responsible for only 4% of CF cases in the US – around 1,200 people.

The UK government has also recognised the value of the personalised treatment approach. The NHS is undertaking the ‘100,000 Genomes Project’ – 100,000 whole human genomes from 70,000 patients are being sequenced to identify potentially new diagnostics and drive the development of new drugs.

But the race is on. Genomics and biotechnology company 23andMe – which originally provided ancestry information from a saliva sample sent through the post (direct-to-consumer genetic testing) for £125 – has recently been approved by the FDA to provide risk information for 10 genetic diseases, such as Parkinson’s disease and late-onset Alzheimer’s disease. It is estimated that the company has accumulated valuable genetic information about more than two million people.

From this vast library of genomic information becoming available, new products will emerge that target the underlying cause specific to an individual patient. This will likely involve at least two medical products – a diagnostic test and the therapeutic product itself, working together as a so-called companion diagnostic (a diagnostic that is essential for the safe and effective use of a corresponding drug).

Pharma and device companies will need to collaborate more closely to ‘co-develop’ these products to ensure the drug is safe and effective, and the performance of the diagnostic is acceptable. And, since the barriers to drug development are significantly reduced with targeted treatment, smaller innovative companies will get involved. With its access to hugely valuable genomic data, 23andMe is one such company – which is presumably why it has just raised $250 million from private investors.

I predict that NGS and data analytics will be the powerful research tools that provide the understanding. But although NGS is starting to move out of the research lab and into the clinical environment, the data it provides is unnecessarily detailed for routine testing. It will be the lower-cost, more accessible diagnostic devices that will be used to test specific genetic sequences – leading to a proliferation of companion diagnostics.

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We are just scratching the surface of personalised medicine, which is why Cambridge Design Partnership is working with both drug delivery and diagnostics clients to help them navigate this rapidly developing market. If you’d like to know more, get in touch.

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August 1st 2017
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Point of care diagnostics: navigating systems architectures

Diagnostic testing is rapidly moving out of the lab and into the hands of untrained users. But developing the system architecture for a high-performance test that is also easy to use is a complex challenge.

A great example of advancements in point-of-care (PoC) testing is the pregnancy test. In the 1970s, Wampole’s 10-step test took two hours by a trained lab technician. Today it is carried out in minutes in the privacy of your own home using an off-the-shelf disposable device.

PoC diagnostic tests should be quick and simple – and ideally not rely on the user’s skill to generate a reliable result. But, unlike pregnancy tests, molecular-based tests currently need more complex steps. For example, sample preparation may be needed to lyse cells, remove inhibitors or increase titre and this can be extremely challenging to implement at the point of care at acceptable cost and device complexity.

Wampole’s test could be categorised as a ‘chemistry set’ where the skill of the operator is critical to generate an accurate result – there might be several critical timing steps, mixing and resuspension steps performed using a manual pipette, metering and sub-sampling precise volumes followed by vortexing and ‘gentle’ heating before looking for a subtle colour change. Lots to go wrong and not at all user friendly.

The Clinical Laboratory Improvement Amendment (CLIA) from the Food and Drug Administration (FDA) regulates laboratory testing for human diagnostics in the US and has categorised the complexity of a diagnostic test as either: waived, moderate complexity or high complexity. The level of complexity is determined by adding up the scores from seven criteria. A CLIA waived test means it is ‘simple to use, and there is little chance the test will provide wrong information or cause harm if it is done incorrectly’.

The simplest test for the user is to ‘add sample and walk away’ and the device carries out the necessary assay functions. This convenience typically generates significant market share over more labour-intensive competitor devices but there are trade-offs with device complexity and development risk. For complicated assays, ‘reader’ and ‘consumable’ system architectures are frequently used. However, consumables tend to be bulky and expensive, and the readers even more so.

Below I outline some high-level considerations when developing system architectures for a PoC diagnostic device, and how to navigate between the ‘chemistry set’ and ‘fully integrated product’.

Assay robustness

It all starts with the foundation of any diagnostic test – the assay. A correctly implemented assay is fundamental to providing high-performance, reliable and repeatable results in the intended use environment.

Identifying sensitive parts of the assay that require careful controls, and functions that are more tolerant to variability, provides the first insights into the required architecture. For example, flow-rate variations may have a significant impact on test performance, which necessitates the use of an automated pump – or the detection method may require special optics. An untrained operator may not be capable of performing these steps with the appropriate control, so reader hardware may be needed.

Ideally the assay is well characterised in the lab before the system architecture is developed – but this is seldom the case. Another issue is that lab processes can be difficult or costly to implement in a ‘highly useable’, low-cost PoC test. So designing a system architecture that is capable of accommodating the necessary functions based on preliminary lab results is a tricky challenge. Capturing risks and uncertainties, and carrying out feasibility testing of the high-risk aspects during early stages of the project, will better inform the system architecture and can avoid unpleasant discoveries later on.

User burden

Although CLIA waive is highly desirable, many PoC devices are categorised as ‘moderately complex’ – it may be a good option for the user to carry out certain functions if they are tolerant to sources of variability (i.e. by understanding assay robustness and assessing operation against CLIA scoring criteria).

User involvement can significantly reduce device complexity but operators are busy people and can easily get distracted in a PoC setting. Failure alerts and fail-safe features help reduce the risk of generating an erroneous result. Mechanical guides and ‘poka yoke’ mistake-proofing features, as well as electronic timeouts and sensing (e.g. QR code read by the reader), can notify the operator that an incorrect or expired component is used. In the event of inactivity, the reader may invalidate the test altogether.

Device complexity

Every project is constrained by time and money and, if the development team has done its job properly, the device will be just complex enough to satisfy user convenience and assay needs. Of course, it’s not as simple as that – other crucial factors such as cost of goods and ‘platform’ requirements also need consideration.

Estimating device cost early on – and continuously updating the estimates – informs the viability of the architecture and ultimate success of the product. If cost estimates are high, it may be necessary to re-examine the assay and explore alternative, lower-cost technical solutions or implement more of a ‘chemistry set’ approach (but understand the impact to the user and viability of the product). Directing functionality (and cost) away from the consumable and onto the reader is generally a good option as non-disposable parts are less cost sensitive.

When designing system architectures intended to be a ‘platform’, it is important to consider the requirements of future assays and, if necessary, build in redundant capability to minimise the effort to accommodate new tests. This is easier said than done under tight timescales. But modular system architectures and components that allow modification – for example, volume expansion or increased flow rate – allow potential flexibility.

Navigating the trade-offs to develop a system architecture that addresses all the considerations is a difficult challenge – and one that is often rushed as businesses are keen to meet their next milestone.

At Cambridge Design Partnership we use a holistic development approach involving close collaboration between our in-house human factors, mechanical, electronic, software and manufacturing engineers, as well as assay scientists. In the early phases of a project we identify the technical and market uncertainties – and thoroughly explore different architectures whilst characterising the assay and understanding user involvement, regulatory issues, manufacturing processes and ultimate device cost. This manages project risk and sets the course for a high-performance system delivered quickly to market. Get in touch for help with your next diagnostic challenge.

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For more on navigating the trade-offs in point-of-care diagnostic system development, contact Cambridge Design Partnership.

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