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Vol 22, No. 03, March 2018   |   Issue PDF view/purchase
Women in Science
Changing the way we see

Dr Anjali Jaiprakash
Advance Queensland research fellow at Queensland University of Technology (QUT)

Develop medical devices that translate robotic vision into affordable systems that can be used to improve healthcare outcomes. (Light field retinal diagnostic system to decrease preventable blindness globally)

Winner of MIT Technology Review - Innovators Under 35 Asia Pacific 2018

Featured on 2017 Robohub’s annual Ada Lovelace Day “25 women in robotics you need to know about” list

You have a PhD in biology, how was the switch over to robotics?

Robotics and AI is challenging the way we interact and live in this world and biology is all about understanding life itself. I work a lot in the clinical setting, allowing me to understand some of the challenges face in hospitals and I think solutions to some of the greatest challenges in life is at the intersection of many fields.

What is it like working at the intersection of medicine, engineering and design to develop medical devices?

It's fun. Everybody has different personalities and come from different strong technical background. Our team is very respectful of each other's learning.

You developed this new light field retinal diagnostic system to replace expensive and complex cameras currently used to detect eye conditions, tell us more about the device and your motivation in developing it.

80% of eye diseases leading to blindness are preventable if monitored regularly and treated on time. Eye diseases such as glaucoma or macular degeneration, which are preventable, affect an estimated 285 million people worldwide.

Although modern retinal imaging equipment can provide good quality diagnostic images, something is wrong. Many people who suffer sight threatening diseases live outside of major centres and high quality portable, reliable, imaging equipment must be made available to provide treatment. Currently, taking a high quality image of the retina suitable for accurate diagnosis requires precision equipment that is bulky, expensive, difficult to transport and requires sophisticated technical training to operate.

So, we have developed a new class of retinal imaging device using the platform state-of-the-art light field technology or plenoptic technology. The device is called retinal plenoptoscope.

Light field technology captures both the intensity and the direction of the light rays in a scene. This contrasts with a conventional camera, which only records light intensity. This device will significantly improve the affordability, reliability and portability of retinal imaging while also delivering new diagnostic features; the ability to create 3D views, metric measurement of retinal features and post-acquisition refocussing that no other retinal imaging device can offer.

We want to give vision to robots, which changes the way we can see the world, or in this case, the human eyes.

What would you say to aspiring females who want to take up science as a career?

I have been very fortunate to have great mentors and a supporting family. I would say, be bold, have fun, and have the attitude of getting things done.

You do a fair bit of voluntary work at QUT to promote diversity and equal opportunities. Can you share some projects you have done?

I am touched by the stories I hear from people who are less fortunate than I am. For example, QUT offers equity services to students who are differently abled and gave me an opportunity to take notes and be an assigned writer for students who were challenged with dyslexia or a broken wrist….

What do you wish to see in this world, in terms of healthcare?

I see humans and robots working together for a better future. Healthcare is a human right and technology has the potential give this basic right to everyone of us.

Using engineering to solve biological problems

Dr Bee Luan KHOO
Senior post-doctoral research associate from the

Singapore-MIT Alliance for Research and Technology (SMART)

Circulating Tumor Cell (CTC) cluster assay for treatment evaluation and patient prognosis

Winner of MIT Technology Review - Innovators Under 35 Asia Pacific 2018

What brought you into science?

I have a genuine interest in nature from a very young age. That led to my involvement in science and research, with the encouragement from my educators in Singapore. I took on plenty of internships before stepping into doctoral studies and working at SMART.

I am a biomedical scientist by training, but I enjoy bioengineering approaches for translation applications. Integrating different disciplines of research excites me as it helps me in problem-solving. I find that when you look at a problem in a different way, you can find new solutions to the problem. I like to use engineering approaches to solve biological problems, because biological problems can sometimes be very complex, and technology can help break these problems down.

Currently, the gold standard for cancer monitoring is through tissue biopsies which can be painful, invasive and sometimes difficult to obtain. This may also not reflect the disease condition throughout the course of disease and treatment. You and your SMART team have developed the CTC assay, a liquid biopsy to monitor disease status. Tell us more about this assay.

Doctors use bioimaging scans and tumour biopsies to monitor disease status. But these methods may not always be sensitive enough for detection. We, at SMART, developed a new technology that could potentially tell doctors in real-time, how well patients are responding to treatment.

This assay utilises a microfluidic device for cancer management and evaluation, dubbed the circulating tumour cell (CTC) Cluster Assay. The assay aims to mimic parts of the tumour microenvironment in vitro by integrating a confined fluidic niche using microwells with hypoxia and tumour-associated immune cells, so that there is interaction between cells (https://www.nature.com/articles/nprot.2017.125). We can generate clusters of cancer and immune cells from the patient directly. The ability to form clusters reflect how the patients are responding to treatment, which means that when the patient is responding well to the treatment, cluster forming potential decreases with time. We have also found that if the patient has a longer overall survival rate in the future, the cluster forming potential is also reduced.

This new assay can provide information in two weeks, enabling doctors to quickly intervene and improve therapeutic strategies. The test may also be used to guide the choice of anti-cancer therapy in patients.

Which types of cancer can be monitored using the assay?

This project is managed by a team of scientists at the Singapore-MIT Alliance for Research and Technology (SMART) and Mechanobiology Institute at the National University of Singapore (NUS). In the beginning, we have done this in metastatic types of cancer in breast, lung, head and neck cancers. Since then, we have moved on to even earlier stages of cancer as we want to demonstrate that the assay has the sensitivity to even pick up presence of CTC at a low count.

We are not trying to isolate any specific sub populations of the CTC assay. We are not aiming a certain biomarker. Potentially, we could work with any kind of cancer if we pick the optimal environment to allow their proliferation. We are working closely with clinicians from the Cancer Science Institute (CSI) and National Cancer Centre of Singapore (NCCS) to foster these aims.

We work with patient samples and healthy samples, those with cancer and those without cancer. We did not generate any clusters from healthy samples (thankfully!). There are however some patients subtypes that are not able to generate clusters. This could be because they could be undergoing treatment which is effective. We are tweaking this procedure for every subtype, but in general, it is flexible, and we hope to demonstrate the assay utility with multiple cancer types.

As the lead researcher in your current study, in a bioengineering environment, what advice would you give young female students wishing to take up science as a career?

Simple: Don’t differentiate yourself by gender or even age. It does not mean that with age or with a specific gender, you have more experience. As an individual, we should aim to see the best in ourselves as what we are and try to do our best. When you try your best, people will see it and they will recognise it for who you are.

What do you think is the most significant barrier to female leadership?

As a Singaporean, I think we are still pretty open to gender diversity. We should then try to be the best that we can and overcome any stereotypical thinking. It boils down to every individual at the end and to look for opportunities in places that promote development. In SMART BioSyM, I have had the support to seek independent grants, which granted me the Young Investigator Grant Award by NMRC and to drive this research independently with my team.

What will be the biggest challenge for the generation of women behind you?

The biggest challenge is to believe in yourself, prove yourself and redefine current possible stereotypes.

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