HT World explores the latest research developments in the world of health technology
World’s most comprehensive AI-powered tool for neuroscience unveiled
The new Brain Knowledge Platform (BKP) has been unveiled by Allen Institute researchers and engineers.
This first-of-its-kind database and research tool has just launched with data from over 34 million brain cells.
It compiles and standardises the world’s neuroscience data into a common format and language allowing deep, seamless collaboration between international teams all united in the common goal of finding cures for brain disease.
The Allen Institute partnered with technology leaders like Amazon Web Services, which built the core computing infrastructure powering Brain Knowledge Platform, and Google to develop AI models for neuroscience.
The collaboration and innovation have created the tool that is designed to transform how treatments for diseases like Alzheimer’s and Parkinson’s are discovered.
For decades, brain researchers have faced a major communications challenge: Labs around the world have relied on a variety of methods and technology to study the brain and classify its diverse cell populations.
These labs have adopted their own terminology and classification systems for their findings and cell types – a diversity that has meant neuroscience lacks a standardised, comprehensive vocabulary to describe and understand the brain and its incredible complexity.
This lack of alignment has slowed the pace of discovery because it’s as though research teams are speaking different languages, hindering seamless collaboration
The Allen Institute is now creating a universal translator for brain science.
The new platform takes all the different ways scientists describe brain cells and organises them into one giant, searchable map that everyone can use.
Brain Knowledge Platform uses AI to help scientists find patterns and connections they might miss on their own.
For example, a scientist studying a brain cell that seems important in Parkinson’s disease can search the platform and instantly see how that same cell behaves in healthy brains, in Alzheimer’s patients, and in people with other conditions.
AI helps them spot similarities and differences that could lead to new treatments.
The Platform also includes a catalogue of genetic tools allowing researchers to immediately begin probing scientific questions that surface.
If a researcher finds an interesting brain cell, they can immediately obtain the tools they need to study that cell in their own lab—going from inquiry to action in a single step, with the ultimate goal of discovery.
The platform also connects basic brain research to actual medical treatments and includes data from both healthy and diseased brains, so researchers can see what goes wrong in conditions like Alzheimer’s and Parkinson’s. They can identify which brain cells are affected and then test potential treatments on those specific cells.
The Institute says that the platform reveals connections between different brain diseases, and may speed up collaboration and big scientific discovery.
Pancreatic cancer research project attacks ‘seeds of metastasis’
A team of surgeons, anesthesiologists and engineers at the University of Illinois Chicago is studying how lidocaine, a common local anesthetic, affects pancreatic cancer cells released into the bloodstream during surgery.
Their latest advancement evaluates a method for capturing these rogue cells and is published in the journal Lab on a Chip.
Circulating tumour cells are cancerous cells that break away from the tumor, often during tumor-removal surgery, and escape into the bloodstream.
Patients with more aggressive circulating tumor cells in their blood have poorer prognoses and higher recurrence rates.
Votta-Velis said patients must recover from surgery before starting chemotherapy. In that window of time, circulating tumor cells, or CTCs, can travel throughout the body and spawn new tumors.
But preliminary in-vitro studies have shown that lidocaine may hamper cells from bursting back out of the bloodstream, instead trapping them to be naturally cleaned out by our immune systems.
Because circulating tumor cells are rare, isolating them could mean pulling 30 to 40 cells out of the billions in our bloodstream — just like pulling a needle from a haystack.
That’s why Votta-Velis teamed up with fellow University of Illinois Cancer Center affiliate Ian Papautsky, the UIC Richard and Loan Hill Professor of Biomedical Engineering in the College of Engineering.
He specialises in microfluidics: how small amounts of fluids, like blood, flow through minute channels.
His contribution to the project is a small microfluidic device, fabricated from glass and plastic, measuring just a couple of inches long and containing channels just wider than a strand of hair.
The device isolates cancer cells from a patient’s blood sample based on their size, a process referred to as a liquid biopsy.
In 2019, the team demonstrated that this method picks out cancer cells with 93 per cent accuracy.
This time, the researchers compared Papautsky’s method to a commercially available tool called EasySep, which pulls cells apart magnetically.
They said magnetic separation can be harsh and sometimes destroy the cells it’s attempting to catch.
The researchers tested both systems, EasySep and their original method, with blood samples from pancreatic cancer patients.
They found that Papautsky’s method recovered eight times as many cancer cells and processed blood samples faster, in as little as 20 minutes.
Dr. Pier Giulianotti, a co-investigator and the division chief of general, minimally invasive and robotic surgery in the College of Medicine, said this discovery opens the door to the next generation of personalised medical treatment.
New biosensor technology maps enzyme mystery inside cells
Cornell researchers have developed a powerful new biosensor that reveals, in unprecedented detail, how and where kinases – enzymes that control nearly all cellular processes – turn on and off inside living cells.
The advance provides scientists with a new way to study the molecular switches that regulate cellular processes, including cell growth and DNA repair, as well as cellular responses to chemotherapy drugs and pathological conditions such as cancer.
Cells rely on kinases to control processes from cellular metabolism and growth to stress responses. Unraveling how the more than 500 kinases in human cells all work together is one of biology’s biggest puzzles.
Until now, researchers lacked robust tools to see exactly where and how these enzymes act inside cells. Understanding those precise signaling patterns is key to learning how cells respond to drugs – and to designing more effective therapies.
The new technique is called ProKAS (Proteomic Kinase Activity Sensors).
ProKAS works by using chains of amino acids, known as peptides, engineered to imitate the natural proteins kinases act on. Each peptide carries a unique amino acid “barcode” that marks its location within the cell.
When a kinase acts on the peptide, mass spectrometry detects both the action and its corresponding barcode, revealing the kinase’s activity, location and timing.
This allows scientists to monitor many kinases at once, across multiple regions of a cell, with high precision and speed, creating a spatial map of enzyme activity.
For this study, Smolka’s team used the barcoded peptides to monitor kinase activity during cells’ response to a range of anti-cancer drugs that induce DNA damage.
Using ProKAS, the researchers were able to track the action of kinases that respond to DNA damage, to see exactly where and when they became active inside cells, including in specific parts of the nucleus.
They observed how key DNA damage response kinases, such as ATR, ATM, and CHK1, reacted over time, revealing differences in activity across regions that could not be measured before.
The system also handled many samples quickly, showing that it could be scaled up for larger studies.
The team can already analyse 36 samples in a single 30-minute mass spectrometry run.
ProKAS’s design also makes it adaptable for studying other human kinases.
In the future, the technology could help scientists explore poorly studied kinases and help pharmaceutical researchers identify new drugs that affect kinase activity in disease processes.
Looking ahead, the team plans to integrate ProKAS with computational design tools, expanded peptide libraries and other approaches to deepen understanding of how kinases shape cell behaviour.
New ‘heart percentile’ calculator helps young adults grasp their long-term risk
A first-of-its-kind online calculator that uses percentiles to help younger adults forecast and understand their risk of a heart event over the next 30 years has been developed.
With rates of obesity, diabetes and hypertension rising among younger Americans, the study authors say identifying long-term risk earlier could help bend the curve on future heart disease, the leading cause of death in the US and worldwide.
The free tool, designed for adults aged 30 to 59, calculates a person’s 30-year risk of developing heart disease using common health measures, such as blood pressure, cholesterol, smoking status, diabetes history and kidney function.
After a person enters their information, the calculator displays their percentile rank among 100 peers of the same age and sex, along with a simple visual. (See an illustration of how the tool displays results.)
The research team stresses that the tool, based on the American Heart Association’s PREVENT equations, is designed to encourage discussions between patients and clinicians and is not a substitute for clinical care.
For many people in their 30s and 40s, cardiovascular issues may seem like a distant problem. But a 35-year-old with a low risk of a heart attack, stroke or heart failure in the next 10 years could still face a high risk over 30 years.
Earlier analyses by the team found that about one in seven young US adults who are low risk in the short-term over 10 years are actually at high risk over 30 years.
The team say that predicting long-term risk at a younger age could help clinicians prioritise preventive efforts for younger adults, such as behavioural modifications or earlier initiation of antihypertensive and lipid-lowering therapies.
Precision therapy could stop breast cancer at the source
Researchers have identified a promising new therapy for triple-negative breast cancer (TNBC), which is among the most aggressive and difficult-to-treat forms of the disease.
Their approach employs an antibody-drug conjugate – a delivery system that uses an antibody to identify cancer cells and deliver a highly potent chemotherapy directly into those cells without harming surrounding healthy tissue.
Antibody-drug conjugates make it possible to use chemotherapy drugs that are too toxic to deliver on their own, offering a promising avenue for treating the most difficult cancers.
In 2025, an estimated 316,950 women and 2,800 men will be diagnosed with invasive breast cancer.
TNBC accounts for about 10 to 15 per cent of all breast cancer cases, and it is widely considered the most difficult breast cancer subtype to treat.
This is because TNBC tends to grow and spread more quickly than other forms of breast cancer, and it typically fails to respond to therapies that work in other subtypes, such as hormonal therapies.
As a result, survival rates for TNBC tend to be lower than for other breast cancers. Additionally, TNBC disproportionately affects younger women, Black women and those with certain genetic mutations.
The research team believes this strategy may pave the way for more precise, effective treatments for TNBC, and the approach could also one day be leveraged against other cancers with similar biology.
