Capit-All Desktop Instrumentation

The Challenge

To prevent cross-threading or over-tightening of caps, as well as the cross-contamination of samples during entry and removal. Also, to remove the need for disassembly for cleaning and maintenance and enable personnel at any level to operate instruments without the need for very high standards of training.

The Approach

Working as part of The Automation Partnership (TAP) team, the team made sure that the instrument’s robust design would deliver reliable, high throughput access and storage of samples. This was one of several projects completed over a period of more than 20 years.

The Outcome

This was one of the first desktop instruments developed by TAP. The design team needed to translate the look and feel created in much larger instruments into this smaller product and maintain high-quality usability and brand recognition.

The instrument enables increased laboratory throughput and improved ergonomics by capping or de-capping up to 96 tubes at once – approximately 10 seconds per rack. With the addition of spacers, it also enables its use with 500µl or 1.0ml tube racks on the same instrument and maintains seal integrity with pre-determined torque control. Safety features ensure that racks are loaded in the correct orientation.

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LEADseeker Multimodality Imaging System

The Challenge

Amersham Biosciences had a pressing need to convert a laboratory proof-of-principle prototype into a commercial imaging instrument, capable of fulfilling a number of functional roles. Their primary requirement was to increase the flexibility of the instrument to perform a wider range of modalities without compromising its performance. But equally important was a need to bring it to the market as rapidly as possible in order to meet many of the existing imaging challenges faced by the company.

Working in a multi-disciplinary team the key objective was to increase the flexibility of the instrument to perform a wider range of modalities without compromising performance. In addition, time to market was an important factor.

The Approach

The imager can function in three modes: as a manual system for assay development, in semi-automatic mode with a stacker workstation where microplates are delivered from a carousel to the imager, or as a fully automated system integrated with major robotics platforms for High-Throughput Screening (HTS) environments.

The team included microbiologists, physicists, software, mechanical and electronic engineers and a small product ion group that built and tested systems including three prototypes.

Early in the process a number of labs were visited, mainly in the USA, to gain an appreciation of what we call ‘care-abouts’ to understand the real needs of users. This bought a different perspective to the design team and enabled us to focus on creating real benefits which translated into much quicker setup times, greater efficiencies and thus improved overall performance.

The Outcome

The first multi-modality instrument on the market capable of imaging plates in seconds with automation allowing the processing of several hundred plates, or approximately 500 000 tests per day, using miniaturised screening formats. In addition, the build philosophy and construction had a significant influence on inventory, cash flow and QA as a result of innovative design thinking.

The role of industrial design played a significant role in working across the siloes of expertise by being the glue to bond these function together and to be the champion the user, laboratory technicians.

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  • soldier communications
    Technology Assessment of Digital Systems
    CASE STUDY
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    Electronics Manufacturing
    CASE STUDY
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    Sensor Monitoring of Manhole Infrastructures
    CASE STUDY
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    Project Cubert
    CASE STUDY
  • Millimetre-Wave Radar for Foreign Object Detection
    CASE STUDY

Could Radar Be a More Cost-Effective Security Screening Alternative to X-Rays?

By: Damien Clarke
Lead Consultant

10th October 2019

5 minute read

Home » Medical

A key task in the security market is the detection of concealed threats, such as guns, knives and explosives. While explosives can be detected by their chemical constituents the other threats are defined by their shape. A threat detection system must, therefore, be able to produce an image of an object behind an opaque barrier.

X-rays are probably the most commonly known technology for achieving this and they are widely used for both security and medical applications. However, while they produce high-quality images, x-ray machines are not cheap and there are health concerns with their frequent use on or in the vicinity of people.

An alternative to x-rays often used at airports for full-body screening are microwave imaging systems. These allow the detection of concealed objects through clothes though the spatial resolution is relatively low and objects are often indistinguishable (hence the requirement for a manual search). The ability to detect and identify concealed items can, therefore, be improved by using a high-frequency mm-wave (60 GHz) system.

Plextek has investigated this approach through the use of a Texas Instruments IWR6843 60 – 64 GHz mm-wave radar which is a relatively inexpensive consumer component that could be customised to suit many applications. However, a single radar measurement only contains range information and not angle information. It is, therefore, necessary to collect multiple measurements of an object from different viewpoints to form an image. This is achieved through the use of a custom 2D translation stage that enables the radar to be automatically moved to any point in space relative to the target object. In this example, radar data was collected across a regular grid of 2D locations with millimetre spacing between measurements.

This large set of radar measurements can then be processed to form an image. This is achieved by analysing the small variations in the signal caused by the change in viewpoint when the object is measured from different positions. The set of range only measurements is then extended to include azimuth and elevation as well. In effect, this process produces a 3D cube of intensity values defining the radar reflectivity at each point in space. A slice through this cube at a range corresponding to the position of the box allows an image to be formed of an object that is behind an (optically) opaque surface.

In this case, a cardboard box containing a fake gun was used as the target object. Clearly, a visual inspection of this box would not reveal the contents, however, 60 GHz mm-waves can penetrate cardboard and therefore an image of the concealed object can be produced. In this case, the resulting image of the contents of the box clearly shows the shape of the concealed gun.

This example simulates the detection of a gun being sent through the post and automatic image analysis algorithms would presumably be capable of flagging this box for further inspection. This would remove the need for human involvement in the screening process for each parcel.

A more mature sensor system using this approach could be produced that did not require the manual scanning process but used an array of antenna instead. It would also be possible to produce similar custom systems that were optimised for different target sets and applications.

 

Acknowledgement

This work was performed by Ivan Saunders during his time as a Summer student at Plextek before completing his MPhys at the University of Exeter.

A key task in the security market is the detection of concealed threats, such as guns, knives and explosives. While explosives can be detected by their chemical constituents the other threats are defined by their shape. A threat detection system must, therefore, be able to produce an image of an object behind an opaque barrier.

X-rays are probably the most commonly known technology for achieving this and they are widely used for both security and medical applications. However, while they produce high-quality images, x-ray machines are not cheap and there are health concerns with their frequent use on or in the vicinity of people.

An alternative to x-rays often used at airports for full-body screening are microwave imaging systems. These allow the detection of concealed objects through clothes though the spatial resolution is relatively low and objects are often indistinguishable (hence the requirement for a manual search). The ability to detect and identify concealed items can, therefore, be improved by using a high-frequency mm-wave (60 GHz) system.

Plextek has investigated this approach through the use of a Texas Instruments IWR6843 60 – 64 GHz mm-wave radar which is a relatively inexpensive consumer component that could be customised to suit many applications. However, a single radar measurement only contains range information and not angle information. It is, therefore, necessary to collect multiple measurements of an object from different viewpoints to form an image. This is achieved through the use of a custom 2D translation stage that enables the radar to be automatically moved to any point in space relative to the target object. In this example, radar data was collected across a regular grid of 2D locations with millimetre spacing between measurements.

This large set of radar measurements can then be processed to form an image. This is achieved by analysing the small variations in the signal caused by the change in viewpoint when the object is measured from different positions. The set of range only measurements is then extended to include azimuth and elevation as well. In effect, this process produces a 3D cube of intensity values defining the radar reflectivity at each point in space. A slice through this cube at a range corresponding to the position of the box allows an image to be formed of an object that is behind an (optically) opaque surface.

In this case, a cardboard box containing a fake gun was used as the target object. Clearly, a visual inspection of this box would not reveal the contents, however, 60 GHz mm-waves can penetrate cardboard and therefore an image of the concealed object can be produced. In this case, the resulting image of the contents of the box clearly shows the shape of the concealed gun.

This example simulates the detection of a gun being sent through the post and automatic image analysis algorithms would presumably be capable of flagging this box for further inspection. This would remove the need for human involvement in the screening process for each parcel.

A more mature sensor system using this approach could be produced that did not require the manual scanning process but used an array of antenna instead. It would also be possible to produce similar custom systems that were optimised for different target sets and applications.

Acknowledgement

This work was performed by Ivan Saunders during his time as a Summer student at Plextek before completing his MPhys at the University of Exeter.

Advanced Technologies in Healthcare

Nigel Whittle - Head of Medical & Healthcare

By: Nigel Whittle
Head of Medical & Healthcare

21st March 2019

4 minute read

Home » Medical

Some of the biggest changes in the practice of medicine and healthcare over the past 70 years have resulted from improvements in the way diseases and illnesses can be diagnosed and studied. Innovative technologies now allow doctors to discover increasing amounts of detailed information about both the progression and treatment of disease, allowing new treatment options and care pathways.

The most significant developments which are likely to change the face of medicine over the next few decades include:

  • Enhanced self-management for patients and the elderly through technology support systems to empower understanding and control of conditions.
  • Improved patient access to health service infrastructure through utilisation of remote care and monitoring systems.
  • Further developments in medical imaging and the application of Artificial Intelligence systems to effectively analyse and diagnose conditions.
  • Precision medicine that can target medical interventions to specific sub-groups of patients based on genomic data.
  • Robotic surgical systems that can conduct exquisitely precise operations in difficult-to-reach anatomical areas without flagging or losing concentration.

Self-Management for Patients

Day-to-day physiological monitoring technology, driven particularly by the spread of a variety of consumer wearable devices with communication capabilities, has the ability to collect and integrate health information from a variety of sources, both medical and consumer-based. The next generation of wearables is likely to significantly blur the division between technology lifestyle accessory and medical device, as reliable non-invasive sensors for the measurement of blood pressure, blood sugar, body temperature, pulse rate, hydration level and many more become increasingly implemented within these devices. The provision and integration of these derived complex sets of data has the potential to provide valuable information, that enabling a holistic approach to healthcare. The US FDA is currently working closely with industry to facilitate the introduction and effective use of these more advanced devices.

Enhanced Patient Access

In the UK, the NHS has brought high-quality medical services to every citizen, but often at the cost of long waits for visits to the doctor when a patient is concerned about his health. The introduction of improved access systems, including video-conferencing facilities, electronic health records and AI-powered chatbots, promises to be a powerful and game-changing move. In particular, chatbots systems such as Babylon Health or Ada can provide a highly accessible medical triage procedure, which can alleviate the pressure on over-worked doctors in GP surgeries, and allow those doctors to focus on patients with more serious conditions. With increasing sophistication, these chatbots can potentially provide accurate diagnostic advice on common ailments without any human interaction or involvement. The key concern is, of course, ensuring that the algorithms operate with patient safety foremost, which requires fine tuning to balance between over-caution and under diagnosis.

Medical Imaging and Artificial Intelligence

Following admission to a hospital, a key element of modern medicine is the use of imaging systems for clinical diagnosis, and the main challenge for doctors is to interpret the complexity and dynamic changes of these images. Currently, most interpretations are performed by human experts, which can be time-consuming, expensive and suffer from human error due to visual fatigue. Recent advances in machine learning systems have demonstrated that computers can extract richer information from images, with a corresponding increase in reliability and accuracy. Eventually, Artificial Intelligence will be able to identify and extract novel features that are not discernible to human viewers, allowing enhanced capabilities for medical intervention. This will allow doctors to re-focus on their interaction with patients, which is often cited as the most valued aspect of medical intervention.

Precision Medicine

The current paradigm for medical treatment is changing through the development of powerful new tools for genome sequencing which allows scientists to understand how genes affect human health. Medical decisions can now take account of genetic information, allowing doctors to tailor specific treatments and prevention strategies for individual patients.

In essence, precision medicine is able to classify patients into sub-populations that are likely to differ in their response to a specific treatment. Therapeutic interventions can then be concentrated on those who will benefit, sparing expense and often unpleasant side effects for those who will not.

Robotic Surgery

Currently, robotic surgical devices are simply instruments that can translate actions outside the patient to inside the patient, often working through incisions as small as 8mm. The benefits of this are clear in terms of minimally invasive surgery, and by allowing surgeons to conduct the operations in a relaxed and stress-free environment. At the moment the robot does not do anything without direct input, but with the increasing development of AI systems, it is likely that in 10 or 15 years, certain parts of an operation such as suturing may be performed automatically by a robot, albeit under close supervision.

What will new technology mean for healthcare?

It is fiendishly difficult to predict the impact of innovative technological advances on medical practice and patient care. However, the overall message is clear – improvements in front end technology will allow patients to have a greater responsibility for their own personal health and well-being. Increased access to medical practice through innovative and efficient mechanisms will allow doctors to focus their time on the patients identified as suffering from more serious illnesses. Highly trained AI systems can then complement the doctors’ prowess in identifying and diagnosing particular diseases. Finally, treatment options will be highly tailored to individual patients and their conditions, increasing the cost-effectiveness of treatment.

However, each of these technology developments comes with associated costs and challenges. Not least, new technology could fundamentally change the way that medical staff work, requiring new skills and mindsets to effectively transform medical care into a radically new approach.

For an informative chat on how Plextek can assist with your Healthcare technology project, please contact Nigel at healthcare@plextek.com

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Some of the biggest changes in the practice of medicine and healthcare over the past 70 years have resulted from improvements in the way diseases and illnesses can be diagnosed and studied. Innovative technologies now allow doctors to discover increasing amounts of detailed information about both the progression and treatment of disease, allowing new treatment options and care pathways.

The most significant developments which are likely to change the face of medicine over the next few decades include:

  • Enhanced self-management for patients and the elderly through technology support systems to empower understanding and control of conditions.
  • Improved patient access to health service infrastructure through utilisation of remote care and monitoring systems.
  • Further developments in medical imaging and the application of Artificial Intelligence systems to effectively analyse and diagnose conditions.
  • Precision medicine that can target medical interventions to specific sub-groups of patients based on genomic data.
  • Robotic surgical systems that can conduct exquisitely precise operations in difficult-to-reach anatomical areas without flagging or losing concentration.

Self-Management for Patients

Day-to-day physiological monitoring technology, driven particularly by the spread of a variety of consumer wearable devices with communication capabilities, has the ability to collect and integrate health information from a variety of sources, both medical and consumer-based. The next generation of wearables is likely to significantly blur the division between technology lifestyle accessory and medical device, as reliable non-invasive sensors for the measurement of blood pressure, blood sugar, body temperature, pulse rate, hydration level and many more become increasingly implemented within these devices. The provision and integration of these derived complex sets of data has the potential to provide valuable information, that enabling a holistic approach to healthcare. The US FDA is currently working closely with industry to facilitate the introduction and effective use of these more advanced devices.

Enhanced Patient Access

In the UK, the NHS has brought high-quality medical services to every citizen, but often at the cost of long waits for visits to the doctor when a patient is concerned about his health. The introduction of improved access systems, including video-conferencing facilities, electronic health records and AI-powered chatbots, promises to be a powerful and game-changing move. In particular, chatbots systems such as Babylon Health or Ada can provide a highly accessible medical triage procedure, which can alleviate the pressure on over-worked doctors in GP surgeries, and allow those doctors to focus on patients with more serious conditions. With increasing sophistication, these chatbots can potentially provide accurate diagnostic advice on common ailments without any human interaction or involvement. The key concern is, of course, ensuring that the algorithms operate with patient safety foremost, which requires fine tuning to balance between over-caution and under diagnosis.

Medical Imaging and Artificial Intelligence

Following admission to a hospital, a key element of modern medicine is the use of imaging systems for clinical diagnosis, and the main challenge for doctors is to interpret the complexity and dynamic changes of these images. Currently, most interpretations are performed by human experts, which can be time-consuming, expensive and suffer from human error due to visual fatigue. Recent advances in machine learning systems have demonstrated that computers can extract richer information from images, with a corresponding increase in reliability and accuracy. Eventually, Artificial Intelligence will be able to identify and extract novel features that are not discernible to human viewers, allowing enhanced capabilities for medical intervention. This will allow doctors to re-focus on their interaction with patients, which is often cited as the most valued aspect of medical intervention.

Precision Medicine

The current paradigm for medical treatment is changing through the development of powerful new tools for genome sequencing which allows scientists to understand how genes affect human health. Medical decisions can now take account of genetic information, allowing doctors to tailor specific treatments and prevention strategies for individual patients.
In essence, precision medicine is able to classify patients into sub-populations that are likely to differ in their response to a specific treatment. Therapeutic interventions can then be concentrated on those who will benefit, sparing expense and often unpleasant side effects for those who will not.

Robotic Surgery

Currently, robotic surgical devices are simply instruments that can translate actions outside the patient to inside the patient, often working through incisions as small as 8mm. The benefits of this are clear in terms of minimally invasive surgery, and by allowing surgeons to conduct the operations in a relaxed and stress-free environment. At the moment the robot does not do anything without direct input, but with the increasing development of AI systems, it is likely that in 10 or 15 years, certain parts of an operation such as suturing may be performed automatically by a robot, albeit under close supervision.

What will new technology mean for healthcare?

It is fiendishly difficult to predict the impact of innovative technological advances on medical practice and patient care. However, the overall message is clear – improvements in front end technology will allow patients to have a greater responsibility for their own personal health and well-being. Increased access to medical practice through innovative and efficient mechanisms will allow doctors to focus their time on the patients identified as suffering from more serious illnesses. Highly trained AI systems can then complement the doctors’ prowess in identifying and diagnosing particular diseases. Finally, treatment options will be highly tailored to individual patients and their conditions, increasing the cost-effectiveness of treatment.
However, each of these technology developments comes with associated costs and challenges. Not least, new technology could fundamentally change the way that medical staff work, requiring new skills and mindsets to effectively transform medical care into a radically new approach.

For an informative chat on how Plextek can assist with your Healthcare technology project, please contact Nigel at healthcare@plextek.com

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The New Science of Genetic Medicine

Nigel Whittle - Head of Medical & Healthcare

By: Nigel Whittle
Head of Medical & Healthcare

9th January 2019

Home » Medical

With surprisingly little fanfare, in October 2018 NHS England became the first health service in the world to routinely offer genetic medicine in the fight to treat cancer.

From that date, hospitals across England have been linked to specialist centres that can read, analyse and interpret DNA isolated from patients with cancer. Through this service, cancer patients can be screened for the existence of key mutations within their tumours that can indicate the best drugs for treatment or to point towards clinical trials of experimental therapies that may be beneficial.

The move marks a big step towardprecision medicine, which offers more effective therapies that are tailored to individual patients.

What is the science underpinning this move?

Firstly, a quick crash course in cancer biology:

  • Cells are the building blocks of every living organism.The instructions (or genes) that tell a cell how to develop and what to do are encoded in long linear molecules of DNA found in the nucleus of the cell.
  • These DNA molecules can be damaged over time or through exposure to chemicals or environmental changes. Cells become cancerous when specific changes in the DNA, called ‘driver mutations’, tell cells to grow faster and behave abnormally.
  • Many cancers form solid tumours, which are masses of tissue, while cancers of the blood, such as leukaemia, generally do not form solid tumours.
  • As these cancer cells multiply to form a tumour, selective pressure increases the number and type of harmful mutations found within the DNA.
  • The cells may acquire additional properties through mutation, such as malignancy which means that they can spread into, or invade nearby tissues. In addition, as these tumours grow, some cancer cells break off and travel to distant parts of the body and form new tumours far from the original site.

Accordingly, although every cell of a particular cancer is related to the same original “parent” cell, the mixture of cells within a tumour becomes increasingly complex. The idea that different kinds of cells make up one cancer is called “tumour heterogeneity”, and in practice means that every cancer is unique. So two people with, say, lung cancer who are the same age, height, weight, and ethnicity, and who have similar medical histories, will almost certainly have two very different cancers.

By the time a cancer tumour is 1cm in diameter, the millions of cells within it are very different from each other, and each cancer has its own genetic identity created by the DNA in its cells.

This, of course, makes the treatment of cancer incredibly difficult and explains why scientific breakthroughs in the understanding of cancer biology do not always lead to significant improvements in overall survival rates.

How will cancer treatment change?

Precision medicine is an approach to patient care that allows doctors to select the best treatments for patients based on a genetic understanding of their disease. The idea of precision medicine is not new, but recent advances in science and technology have allowed the ideas to be brought more fully into clinical use.

Normally, when a patient is diagnosed with cancer, he or she receives a standard treatment based on previous experience of treating that disease. But typically, different people respond to treatments differently, and until recently doctors didn’t know why. But now the understanding that the genetic changes within one person’s cancer may not occur in others with the same type of cancer has led to a better understanding of which treatments will be most effective.

At the simplest level, this understanding allows targeted therapy against cancer, in which drugs (quite often complex biological molecules) are used to target very specific genetic changes in cancer cells. For example, around 15–20% of malignant breast cancers contain cells with a higher than normal level of a protein called HER2 on their surface, which stimulates them to grow. When combined with a suitable test, it means that not only can the drug be given to those patients most likely to benefit, but also the drug, with its associated side effects, need not be given to patients who will not benefit from its use.

So genetic medicine has already transformed the treatment of some cancer patients. The advent of widespread genetic medicine within the NHS is likely to lead to significant benefits for cancer patients, including:

• The identification of patients who are most likely to benefit from particular cancer therapy.

• The avoidance of unnecessary treatments that are less likely to work for specific groups of patients.

• The development of novel therapies targeted at specific tumour cells or cellular pathways.

Not only will precision medicine allow the development of precise and effective treatment strategies for cancer patients whilst improving the overall quality of life, but it will also finally destroy the myth of ‘one size fits all’ cancer therapy.

For an informative chat on how Plextek can assist with your Healthcare technology project, please contact Nigel at healthcare@plextek.com

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With surprisingly little fanfare, in October 2018 NHS England became the first health service in the world to routinely offer genetic medicine in the fight to treat cancer.

From that date, hospitals across England have been linked to specialist centres that can read, analyse and interpret DNA isolated from patients with cancer. Through this service, cancer patients can be screened for the existence of key mutations within their tumours that can indicate the best drugs for treatment or to point towards clinical trials of experimental therapies that may be beneficial.

The move marks a big step towardprecision medicine, which offers more effective therapies that are tailored to individual patients.

What is the science underpinning this move?


Firstly, a quick crash course in cancer biology:

  • Cells are the building blocks of every living organism. The instructions (or genes) that tell a cell how to develop and what to do are encoded in long linear molecules of DNA found in the nucleus of the cell.
  • These DNA molecules can be damaged over time or through exposure to chemicals or environmental changes. Cells become cancerous when specific changes in the DNA, called ‘driver mutations’, tell cells to grow faster and behave abnormally.
  • Many cancers form solid tumours, which are masses of tissue, while cancers of the blood, such as leukaemia, generally do not form solid tumours.
  • As these cancer cells multiply to form a tumour, selective pressure increases the number and type of harmful mutations found within the DNA.
  • The cells may acquire additional properties through mutation, such as malignancy which means that they can spread into, or invade nearby tissues. In addition, as these tumours grow, some cancer cells break off and travel to distant parts of the body and form new tumours far from the original site.


Accordingly, although every cell of a particular cancer is related to the same original “parent” cell, the mixture of cells within a tumour becomes increasingly complex. The idea that different kinds of cells make up one cancer is called “tumour heterogeneity”, and in practice means that every cancer is unique. So two people with, say, lung cancer who are the same age, height, weight, and ethnicity, and who have similar medical histories, will almost certainly have two very different cancers.

By the time a cancer tumour is 1cm in diameter, the millions of cells within it are very different from each other, and each cancer has its own genetic identity created by the DNA in its cells.


This, of course, makes the treatment of cancer incredibly difficult and explains why scientific breakthroughs in the understanding of cancer biology do not always lead to significant improvements in overall survival rates.

How will cancer treatment change?

Precision medicine is an approach to patient care that allows doctors to select the best treatments for patients based on a genetic understanding of their disease. The idea of precision medicine is not new, but recent advances in science and technology have allowed the ideas to be brought more fully into clinical use.

Normally, when a patient is diagnosed with cancer, he or she receives a standard treatment based on previous experience of treating that disease. But typically, different people respond to treatments differently, and until recently doctors didn’t know why. But now the understanding that the genetic changes within one person’s cancer may not occur in others with the same type of cancer has led to a better understanding of which treatments will be most effective.

At the simplest level, this understanding allows targeted therapy against cancer, in which drugs (quite often complex biological molecules) are used to target very specific genetic changes in cancer cells. For example, around 15–20% of malignant breast cancers contain cells with a higher than normal level of a protein called HER2 on their surface, which stimulates them to grow. When combined with a suitable test, it means that not only can the drug be given to those patients most likely to benefit, but also the drug, with its associated side effects, need not be given to patients who will not benefit from its use.

So genetic medicine has already transformed the treatment of some cancer patients. The advent of widespread genetic medicine within the NHS is likely to lead to significant benefits for cancer patients, including:

• The identification of patients who are most likely to benefit from particular cancer therapy.

• The avoidance of unnecessary treatments that are less likely to work for specific groups of patients.

• The development of novel therapies targeted at specific tumour cells or cellular pathways.


Not only will precision medicine allow the development of precise and effective treatment strategies for cancer patients whilst improving the overall quality of life, but it will also finally destroy the myth of ‘one size fits all’ cancer therapy.

For an informative chat on how Plextek can assist with your Healthcare technology project, please contact Nigel at healthcare@plextek.com

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