Hitting the market: Anaesthesia system for less pain in childbirth
From left: Ms Ng, Dr Ma and Mr Leng with uSINE, their AI-based image processing software and needle-based drug injection system
When NUS Electrical and Computer Engineering Research Fellow Dr Ma Jun heard about the launch of the NUS Industry Liaison Office’s Graduate Research Innovation Programme (GRIP), he knew it would be the ideal platform to take a research project he had worked on with others to the masses.
With it, he hoped to reduce the pain and complication risks for women worldwide during childbirth.
The project, uSINE, combines Artificial Intelligence (AI)-based image processing software and a needle-based drug injection system to enable clinicians to be guided by ultrasound images to administer spinal anaesthesia to the right location.
Current methods for anaesthesia injections
Currently, epidural injections offering pain relief to patients during childbirth are administered using palpation-based “blind” procedures or ultrasound scans, which have a first time needle insertion success rate of 40 per cent or 68 per cent respectively.
This increases the risk of complications for patients, which can include nerve injury and paralysis. Other drawbacks of the current methods are the inability to cater to obese patients and the need for anaesthetists to be aided by a radiologist and additional nurses for the ultrasound-guided procedures.
Clinical studies involving 100 patients conducted by the KK Women’s and Children’s Hospital (KKH) between 2016 and 2017 were promising, achieving a high level of accuracy — 92 per cent.
uSINE’s targeted approach reduces the risk of complications. Additionally, women experiencing excruciating birth pangs get more effective pain relief.
The system enables clinicians and anaesthetists to administer epidurals at the right location to a high level of accuracy
Seeing the potential for scalability and commercialisation of the technology, Dr Ma invited NUS Graduate School for Integrative Sciences and Engineering PhD students Ms Ng Cailin and Mr Leng Yusong to form HiCura Medical.
The start-up was among the more than 90 applications seeking to join the inaugural cohort of GRIP, and was shortlisted along with 14 others to receive an initial tranche of $50,000 each in seed funding from NUS.
“GRIP gave us a lot of help, because all three of us are engineers. We didn’t have any marketing or pitching experience, or anything of that sort,” said Ms Ng.
“So we took the three-day GRIP workshop over three weekends, and it was a long three-month period where we had to think about how we’re going to sell this, where our stakeholders are, where our customers are coming from, and what kind of business model we are going to take.”
Under GRIP, the team was also matched with a dedicated mentor, Dr Kate Lazarenko, a digital health consultant and adjunct lecturer at the NUS Institute of Systems Science’s Smart Health Leadership Centre. Ms Ng credits Dr Lazarenko as well as Dr Bipin Bhola Sewakram and Dr Christina Tong from the NUS Industry Liaison Office for dispensing invaluable advice and support that helped HiCura move forward.
Next steps
Currently the start-up is raising capital as well as fine-tuning the software. It is also looking to set up its quality management system, as well as user interface and experience design (UI/UX).
With further research and clinical studies, HiCura’s AI technology could be expanded for other procedures that involve inserting a needle into the epidural space of the spine, such as spinal anaesthesia for hip replacement operations, lumbar punctures and drug delivery.
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