Medical research is shaping up to be an interdisciplinary endeavour, with researchers drawing from a wider suite of technologies and tools to improve patient outcome.

A forthcoming research programme on brain cancer treatment will see a multi-disciplinary team from the National Neuroscience Institute (NNI), Duke-NUS Medical School and National University of Singapore enlisting the help of genomics, artificial intelligence (AI), bioengineering and nanotechnology to improve the odds of finding new drug targets. In a nod to their innovative approach, the study was awarded $9.88 million in research grants.

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Precision medicine – the way forward in brain cancer treatment

The core of the research centres around using precision medicine to differentiate treatment. This stems from the fact that cancer tumours differ in their molecular structure, even though they may look the same under the microscope.

“With better profiling and categorisation, we aim to find and repurpose existing chemotherapy drugs to match them to specific patients, instead of using a one-size-fits-all approach,” said Associate Professor Ang Beng Ti, Head and Senior Consultant, Department of Neurosurgery, NNI @Singapore General Hospital campus and Associate Professor, Duke-NUS Medical School.

The research holds promise for glioblastoma patients. Glioblastoma is a highly aggressive brain cancer with limited treatment options. The current standard of care involves surgery, radiotherapy and chemotherapy. However, due to the location of the tumour, its structure and high tumour recurrence, the outlook for patients is grim. About one in two patients die within 15 months of diagnosis.

NNI sees  60 to 80 new glioblastoma patients each year. To develop faster and safer treatment options for these patients, the team plans to use and develop new technologies and processes in this study:


To get a better handle on the nature of glioblastoma, the team will be tapping on the glioma repository housed within the NNI Tissue Bank. The intention is to create a comprehensive dataset termed "Glioportal", linking the clinical characteristics and genomic data to each of the patient-derived tumor specimens. So far, about 150 tumour specimens have been collected from patients. These are used to grow cells with the same molecular fingerprint providing  a safe way to study the tumour pathways, and experiment with existing or new drug combinations at no risk to patients. 

The benefits extend beyond the current research, as Professor Patrick Tan, Programme in Cancer and Stem Cell Biology, Duke-NUS Medical School explained, “The data generated from these models are captured in a database which investigators worldwide can use to generate new hypotheses. This forms an important resource and contribution to global brain cancer research.”

Artificial intelligence

To increase the chances of finding new insights and good matches for drug targets, the team will be utilising artificial intelligence (AI) to trawl through huge datasets. First, researchers will use AI and data-mining to study how glioblastoma cells behave and change, so as to form a fuller picture of each tumour subtype. Next, the team will collaborate with BenevolentAI (BAI), an AI drug discovery company in London to identify drug targets.

“Using AI to sieve through existing drugs to find and prioritise those with the highest potential for testing helps to speed up the drug discovery process,” said Adjunct Associate Professor Carol Tang, Neuro-oncology Programme, NNI; Adjunct Associate Professor, School of Biological Sciences, Nanyang Technological University.

Bioengineering and nanotechnology

Currently the only way to identify the tumour sub-type is through studying tissue samples resected during surgery. However, this comes with the risk of brain injury and repeat surgery is often not possible when the tumour recurs. To overcome these challenges, a team from NUS is devising a solution using bioengineering and nanotechnology.

The team discovered that patients’ blood samples contain important tumour biomarkers. These are tiny particles about one-tenth the thickness of hair. Therefore, it is building a nanosensor platform, suited to the size of these particles, to analyse the molecular profile of tumours.

Collecting blood samples is safe and minimally invasive, allowing for repeated tests to track the progression of the disease, stratify patients for clinical trials, and monitor the treatment efficacy of individual patients.

Adaptive clinical trials

Finally, the separate strands of the research will culminate in a clinical trial. Patients identified through their blood samples will be matched to identified drug targets for trials. The trials will be conducted as part of a larger international study called GBM AGILE and will adopt an adaptive clinical trial format. 

“Compared to traditional clinical trials where results are analysed only at the end of the trial, an adaptive trial allows us to review the effectiveness of drugs and their side effects on patients throughout the trial. This means effective drugs can graduate faster from trials to clinical use and benefit more patients,” explained Dr Lin Xuling, Senior Consultant, Department of Neurology, NNI.

The research is slated to stretch over five years, with clinical trials expected to start in late 2022. The news brings cheer to patients and caregivers who journey with them. One of them is Mr Declan MacFadden, who lost his wife to the disease in 2018. Recalling how glioblastoma affected his wife’s eyesight, movement and memory, and her rapid decline,  Mr MacFadden said is hopeful that the research will result in much needed new treatments to improve patients’ quality of life and help them live longer.

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